ALBERT

Description: This paper explores temperature variability over southern South America. Four states of temperature variability are revealed in both winter and summer seasons. Synoptic‐scale meteorological patterns help diagnose the temperature variability states with low‐level temperature and moisture advection are closely related to patterns of temperature variability. Large‐scale modes of climate variability show some connection to temperature variability states, no single mode appears to be a primary driver. Abstract Key spatiotemporal patterns of monthly scale temperature variability are characterized over southern South America using k‐means clustering. The resulting clusters reveal patterns of temperature variability, referred to as temperature variability states. Analysis is performed over summer and winter months separately using data covering the period 1980–2015. Results for both seasons show four primary temperature variability states. In both seasons, one state is primarily characterized by warm temperature anomalies across the domain while another is characterized by cold anomalies. The other two patterns tend to be characterized by a warm north–cold south and cold north–warm south feature. This suggests two primary modes of temperature variability over the region. Composites of synoptic‐scale meteorological patterns (wind, geopotential height, and moisture fields) are computed for months assigned to each cluster to diagnose the driving meteorology associated with these variability states. Results suggest that low‐level temperature advection promoted by anomalies in atmospheric circulation patterns is a key process for driving these variability states. Moisture‐related processes also are shown to play a role, especially in summer. The El Niño–Southern Oscillation and the Southern Annular Mode exhibit some relationship with temperature variability state frequency, with some states more common during amplified phases of these two modes than others. However, the climate modes are not a primary driver of the temperature variability states.

Description: Abstract Abrupt swings in temperature can exert negative impacts, ranging from human health to agricultural production. Here, we focus on a global assessment of the extremes in the temperature swings at sub‐daily scales using Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2) data. Overall, the regions with extremely large swings in hourly temperature (i.e., 99th percentile) are located in desert or arid regions, and the land masses exhibit larger temperature swings than the oceans. In contrast, the first percentile of the hourly temperature swings exhibits a different spatial pattern, with the lowest values (i.e., largest negative swings) located in the Rocky Mountain, South Australia, South and North Africa and some regions in Northwestern China. We identify a significant downward/upward trend in the 99th/1st percentile of sub‐daily (i.e., hourly and 12 hr) temperature changes in the midlatitudes in the Northern Hemisphere, particularly during boreal summer. Overall, the regions with significant trends in the Northern Hemisphere are collocated with the paths of the jet streams and storm tracks. The significant downward/upward trends in the 99th/1st percentile of the sub‐daily temperature swings over the Northern Hemisphere can be explained by a weakening in the Northern Hemisphere's summer circulation, as suggested by the downward trend in the eddy kinetic energy. These results indicate that a weak/strong persistence in the circulation may lead to less/more abrupt temperature swings (i.e., increase or decrease) caused by horizontal temperature advection.

Description: Abstract The presence of a seasonal snowpack determines the hydrology, geomorphology and ecology of wide parts of the Iberian Peninsula, with strong implications for the economy, transport and risk management. Thus, reliable information on snow is necessary from a scientific and operational point of view. This is the case of the Iberian Peninsula where, lack of observation has impeded proper analysis of snowpack duration, magnitude and interannual variability. In this study we present the first snow climatology of the entire Iberian Peninsula. The scarcity of in situ observations has been overcome, using a newly developed remote sensing snow database from MODIS satellite sensors for the period 2000 ‐ 2014 and a physically based snow model (Factorial Snow Model‐ FSM), driven by a regional atmospheric model (Weather Research and Forecast model‐ WRF) over the Iberian Peninsula for the period 1980 ‐ 2014. The snowpack of the main mountain areas (Pyrenees, Cantabrian, Central, Iberian range and Sierra Nevada) are described, estimated from the generated databases. The information has been processed using a k‐means cluster algorithm, looking for similarities in snow indices at different elevation bands. Results show four different types of snowpack in terms of depth, duration and interannual variability, lying over different elevation bands in the different ranges, proving the variability of the snowpack over Iberia. Analyses reveal areas characterised by ephemeral snowpacks, while in some sectors snowpack lasts, on average, 198 days per year with 3.02 meters of peak snow depth. The coefficient of variation of interannual peak snow depth oscillated between 35.2% and 162.4%. All the analysed indices show that at common elevations the Cantabrian range and the Pyrenees host the deepest and longest lasting snowpacks, followed by the Central and Iberian ranges. The Sierra Nevada exhibits the shortest, shallowest snowpack and more year‐to‐year variability. This article is protected by copyright. All rights reserved.

Description: ABSTRACT The understanding of past millennium climate change is very important. Due to the lack of continuously annual resolution records, the temperature characteristics in the low‐latitude regions of East Asia (LLREA) during past several centuries are still unknown. Using tree‐ring width chronology from Taiwan, an island located in the western Pacific region and in southeastern China, February–October mean temperature from 1380 to 2007 AD was reconstructed. Spatial correlation analysis indicated that the reconstructed temperature could represent the sea‐land temperature change in LLREA. During the past six centuries, both the warmest intervals and the largest variability of temperature appeared in the twentieth century. This is probably related to human activities. Temperature in LLREA provided good contrast with temperature changes in the Tibet Plateau and elsewhere in the Northern Hemisphere. The LLREA entered into the Little Ice Age around the year of 1450, approximately 100 years earlier than the Tibet Plateau. The 10‐year cycle contained in the reconstructed temperature is close to the 11‐year period of solar activity, which revealed there was a certain relationship between them. The temperature in LLREA significantly correlated with solar activity at the decadal to centennial scales. The strong/weak solar irradiance corresponded to the great/small temperature variability. This article is protected by copyright. All rights reserved.

Description: Abstract The Catskill Mountains and surrounding counties in south‐central New York State are home to almost 400,000 residents, and supply drinking water to over 9 million people in New York City and other municipalities. In this study, we identify a set of stations in this region that are appropriate for climatological analysis, and examine variations in precipitation, streamflow, and temperature between 1900 and 2016, extending the time domain of previous studies of the climatology of this region during both the early and recent portions of the record. Temperatures have increased since the mid‐20th century, in particular daily minimum temperatures, at rates that vary with season and elevation. As a result, diurnal temperature ranges have tended to decrease, particularly during the warm season at lower elevations. The most significant hydrological events include the cold drought of the 1960s (a year‐round phenomenon), and the wet period beginning in the late 1990s (primarily a warm season phenomenon). We also find evidence of a particularly wet period at the start of the 20th century. Cyclic behavior is found in both hydrological and temperature records, with the most prominent cycle in cold season precipitation and streamflow peaking at 28 years. This article is protected by copyright. All rights reserved.

Description: Abstract The monthly and seasonal variability and distribution of dust events over northern Saudi Arabia were studied using ground‐based measurements from 11 surface stations for the period of 1978‐2010. Additionally, to study the synoptic climatology of the dust variability, the aerosol index (AI) data from the Total Ozone Mapping Spectrometer (TOMS) satellite and meteorological data from the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis datasets were used. The dust types observed at the surface stations are classified into two categories: weak dust and dust storms. A statistical study of the ground measurements demonstrated that weak dust category events are prevalent in the cold months, whereas storm category events are prevalent in the hot months. Additionally, the annual distribution distinguishes two periods for dust observations, before and after 1989, where the number of events in the first period is lower than the annual average but increases during the second period. The synoptic climate study indicated that two main atmospheric wind patterns, anticyclonic and northerly (shamal) patterns, accompany the dust events in the study area. The dust in winter and autumn is mainly affected by the anticyclonic pattern, while that in spring and summer is mainly affected by the shamal pattern. In addition, a synoptic study of selected cases confirmed the climate results and demonstrated the existence of two atmospheric patterns corresponding to winter and summer. Both patterns include troughs over the Red Sea and Arabian Gulf and a ridge or high‐pressure cell over the eastern Mediterranean region during the summer atmospheric pattern and over the mid‐Arabian Peninsula during the winter atmospheric pattern. The characteristic of non‐dust storm composition demonstrated that the storms exhibit pronounced synoptic systems (winter and summer) with the highest pressure/geopotential gradient near the Arabian Peninsula. This article is protected by copyright. All rights reserved.

Description: Abstract The impact of the Pacific multidecadal oscillation (PMO) on precipitation in April during the sowing season in Northeast China (NEC) was analyzed. According to the results, there was a significant interdecadal change in the relationship between the PMO in December of the previous year and the precipitation in NEC in April of the following year during different PMO phases. Before 1980, when the PMO was in a negative phase, there was no significant correlation between the PMO and NEC April precipitation. After 1980, when the PMO changed to a positive phase, the relationship between the two variables became significant. Based on further analysis, the main reason for this relationship is that as the PMO changes from a negative phase to a positive phase, the northern North Pacific warms, and the north–south temperature gradient in the mid‐ to high latitudes of the North Pacific decreases, which weakens the mid‐ to high‐level westerlies, thus increasing the impact of North Pacific water vapor transport on the April precipitation in NEC. When the PMO changes from a negative phase to a positive phase, the increased sea surface temperature (SST) significantly strengthens the Aleutian low (AL), which can enhance the Alaska warm current and further increase the sea temperature in the PMO region. This air‐sea interaction forms a positive feedback that maintains the SST signal from December of the previous year to April of the following year, which affects the circulation and water vapor conditions of NEC and ultimately affects NEC April precipitation. This positive feedback mechanism was further verified in the ECHAM5 model. When the positive anomalous SST appeared in the PMO region, as in the observations after 1980, the AL was significantly enhanced, which in turn affected the SST enhancement. This article is protected by copyright. All rights reserved.

Description: Abstract Statistical downscaling methods are extensively used to refine future climate change projections produced by physical models. Distributional methods, which are among the simplest to implement, are also among the most widely used, either by themselves or in conjunction with more complex approaches. Here, building off of earlier work we evaluate the performance of seven methods in this class that range widely in their degree of complexity. We employ daily maximum temperature over the Continental U. S. in a "Perfect Model" approach in which the output from a large‐scale dynamical model is used as a proxy for both observations and model output. Importantly, this experimental design allows one to estimate expected performance under a future high‐emissions climate‐change scenario. We examine skill over the full distribution as well in the tails, seasonal variations in skill, and the ability to reproduce the climate change signal. Viewed broadly, there generally are modest overall differences in performance across the majority of the methods. However, the choice of philosophical paradigms used to define the downscaling algorithms divides the seven methods into two classes, of better vs. poorer overall performance. In particular, the bias‐correction plus change‐factor approach performs better overall than the bias‐correction only approach. Finally, we examine the performance of some special tail treatments that we introduced in earlier work which were based on extensions of a widely used existing scheme. We find that our tail treatments provide a further enhancement in downscaling extremes. This article is protected by copyright. All rights reserved.

Description: Western Africa with three rainfall zones of the Guinea Coast (0°–10°N, 25°W–15°E), the Western Sudano Sahel (10°–20°N, 25°–5°W) and the Eastern Sudano Sahel (10°–20°N, 5°W–15°E). Abstract The interannual variability and trends of atmospheric moisture flux convergence (MFC) and the flux transport and their roles in wet season rainfall variability during the West Africa monsoon season have been investigated using the Climate Research Unit observational datasets and the National Center for Environmental Prediction reanalysis 2 from 1979 to 2016 and the Coordinated Regional Downscaling Experiment (CORDEX)‐Africa model outputs. Particular emphasis has been placed on the three rainfall zones: the Western Sudano Sahel, the Eastern Sudano Sahel and the Guinea Coast. The MFC shows largest variability and impact on rainfall in the Western Sudano Sahel, followed by the Guinea Coast, but there is no significant impact in the Eastern Sudano Sahel. Furthermore, the MFC shows significant positive trends at the Sahelian locations but not at the Guinea Coast. The CORDEX‐Africa models adequately simulate the climatology and spatial patterns of the mean June to September atmospheric moisture; however, differences exist in the magnitude and signs of the temporal trend. The model ensemble mean is presented, which better represents the atmospheric moisture during the monsoon rainfall variability. A mean bias‐corrected projection of the atmospheric moisture shows enhanced rainfall variability of the Guinea Coast in the representative concentration pathway (RCP) 4.5 and RCP 8.5 at the end of the 21st century.

Description: Both ERA‐20C and NOAA‐20CR with only the observed surface signal assimilated, could reproduce the observed MJO characteristics very well, with the former superior to the latter, regardless of MJO intensity. Abstract The Madden–Julian Oscillation (MJO), as a dominant mode of tropical intraseasonal oscillation, plays an important role in the variability of global weather and climate. However, current state‐of‐the‐art atmospheric circulation models have difficulty in reproducing observed MJO characteristics when forced by observed daily sea surface temperature alone. An important practical question is how much data a model needs in assimilation to reproduce real MJO events? By analysing ERA‐20C and NOAA‐20CR reanalysis data, the authors tried to figure out whether a model could reproduce observed MJO events by assimilating the observed surface signal alone. The phase propagation and vertical structure associated with MJO were compared between the reanalysis data and observations during 1979–2010. A total skill score considering both temporal correlation and spatial standard deviation were defined. The result showed that both ERA‐20C and NOAA‐20CR could reproduce the observed MJO characteristics very well, with the former superior to the latter, regardless of MJO intensity. Thus, a minimum requirement for an operational atmospheric model for MJO prediction is the assimilation of the observed surface signals.

Description: The temperature inversions are a common phenomenon occurring in the lower troposphere. Their temporal and spatial variability is, however, determined by the inversion type. Surface‐based inversions (SBI) indicate a clear diurnal cycle, while the day–night variability of elevated inversions (EI) is far less pronounced. The analysis conducted revealed that anticyclonic circulation is both an important factor supporting the subsidence leading to EI occurrence and a good precursor of the nocturnal radiation favourable for the development of deep SBI. Abstract Tropospheric temperature inversions are thought to be an important feature of climate as well as a significant factor affecting air quality and low‐level cloud formation. The aim of this study is to investigate the temporal and spatial variability of the tropospheric temperature inversions, in particular so‐called elevated inversions, over Europe. The analysis is based on data gained from ERA‐Interim reanalysis for the period 1981–2015. The data consist of air temperature, and geopotential height from the entire vertical cross‐section of the troposphere, that is, from 1,000 to 100 hPa. The study examines the temporal (intra‐ and inter‐annual) variability of the temperature inversions based on their frequency, base height, depth, and strength. The analysis conducted revealed that the temperature inversions are a common phenomenon occurring in the lower troposphere. Their temporal and spatial variability is, however, determined by the inversion type. Surface‐based inversions (SBI) indicate a clear diurnal cycle, while the day–night variability of elevated inversions (EI) is far less pronounced. Two main regions of the most frequent EI occurrence may be distinguished. These are: (a) a marine area west of the Iberian Peninsula and (b) Eastern Europe. Both of them are located in areas which are under the influence of extensive high‐pressure systems—the permanent Azores High and semipermanent Siberian High, respectively. The development of EI should be therefore attributed to the large‐scale subsidence and adiabatic heating of air parcels. EI are also quite common over the other parts of the Atlantic Ocean, which is closely linked to the development of marine inversions. SBI tend to be stronger than EI—the mean seasonal inversion strength is usually substantially higher for SBI. In turn, EI reach higher values of the mean seasonal inversion depth as compared with SBI.

Description: It is found that the climatology, interannual variation, spatial modes and characteristic indices of the winter North Pacific storm track (WNPST) are extremely sensitive to the choice of cumulus convection scheme (CCS). The Kuo scheme has a stronger ability to simulate the WNPST. We find that energy conversion from the eddy available potential energy to eddy kinetic energy among these CCSs may be one of the key reasons affecting the simulation results of the WNPST. Abstract Based on the regional climate model RegCM4.5 driven by National Centers for Environmental Prediction (NCEP) reanalysis, the influence of cumulus convection schemes (CCSs) on the winter North Pacific storm track (WNPST) is investigated. It is found that the climatology, interannual variation, spatial modes and characteristic indices of the WNPST are extremely sensitive to the choice of CCS. Among the selected CCSs, WNPST climatology and interannual variation in the Kuo scheme are better than in other CCSs, with a smaller root mean square error. The WNPST spatial modes and strength indices in the Kuo and Grell schemes are more consistent with NCEP reanalysis. The Kuo scheme has a stronger ability to simulate the WNPST latitude index and the interannual variation of winter characteristic indices. In addition, we attempt to reveal the possible reasons for the different performances of CCSs from the viewpoint of baroclinic energy conversion (BCEC). It is found that the energy conversion from the mean available potential energy to the eddy available potential energy (BCEC1) has no significant difference among the Kuo, Grell and Emanuel schemes, while energy conversion from the eddy available potential energy to eddy kinetic energy (BCEC2) in the Kuo scheme is obviously better than other CCSs, which means that the differences in BCEC2 among these CCSs may be one of the key reasons affecting the simulation results of the WNPST.

Description: 118‐year urban climate and extreme weather events of Metropolitan Manila, the capital of the Philippines. Observed temperature and precipitation are rising in this megacity. Temperature is driven by large and small scale forcing (i.e., ENSO, urbanization) while precipitation is heavily influenced by landfalling and distant tropical cyclones. Abstract Metropolitan Manila, the Philippines, is a megacity with a population of 12.9 million people. Unabated urbanization and disorganized infrastructure build‐up, coupled with a large urban poor population have made many of its population vulnerable to climate change. This study presents the 118‐year urban climate and extreme weather events of Metropolitan Manila. Daily average and minimum temperature are on the rise comparable to countrywide trends. Consequently, there are more warm and less cold nights. Total annual precipitation is also increasing at a rate of 77.99 mm/decade. Decreasing simple daily intensity index implies that higher observed precipitation is due to the increase in wet days count rather than intensity. Tropical cyclones (TCs) are critical in producing most extreme rainfall events in the metropolis. Extreme precipitation is induced either by a TC's immediate rainbands or remote precipitation effects by enhancing the prevailing summer monsoon flow. TC‐induced rain modulates annual rainfall variability and is estimated to contribute 45.2% to Metropolitan Manila mean total rainfall.

Description: Abstract Precipitation during the Ethiopian Kiremt (June–September) season has exhibited significant interannual and multidecadal variability over the 20th and early 21st century. We investigated the temporal variability in the strength of the teleconnections between sea‐surface temperatures in key global oceanic regions, including the Tropical Pacific, Indian Ocean, and Tropical Atlantic, and Kiremt season precipitation at subseasonal, interannual and multi‐decadal time scales. We also investigate the influence of the Madden‐Julian Oscillation (MJO). We performed a systematic analysis of 112‐year long (1901–2012) precipitation in the northern region of East Africa including the southern and central regions of Ethiopia and uncover interesting spatial, temporal and subseasonal variability and teleconnection patterns. Precipitation anomalies during wet and dry years extend throughout Northern Africa and also, during September extends over Indian subcontinent, suggesting large‐scale variability of wet/dry patterns. Wet (dry) years are accompanied by La Nina like (El Nino like) conditions in the tropical Pacific and extending into Atlantic and Indian Oceans. Through Bayesian dynamical linear modeling we find that temporal changes in seasonal precipitation correspond to changes in the strengths of SST teleconnections, and that the relative strengths of these teleconnections rather than one dominant teleconnection influences precipitation variability. During three precipitation epochs in this region, the mid‐century pluvial, the late‐century drought, and the early 21st century, we find that changes in precipitation are related to changes in the main dynamical features of precipitation. These findings suggest that Kiremt season precipitation is in a new regime, and is of key interest to the agricultural and water resources communities who rely on accurate forecasts of precipitation to make operational decisions. This article is protected by copyright. All rights reserved.

Description: The average annual precipitation for recent decades shows a downwards trend and is contrary to what was observed for the last decades of the 20th century over humid subtropical climate areas. Maximum daily precipitations over the Paraná River basin showed trends of decrease or increase, depending on the type of climate and season. In terms of monthly maximum trends, February, July, and October are the months with the highest probability of an extreme weather event occurring in the basin. Abstract The main objective of this study was to investigate the trends on average and extreme events in time series of daily precipitation from 1980 to 2010 in the Paraná River basin, Brazil. The nonparametric Mann–Kendall test was applied to detect monotonic trend in the precipitation series. The occurrence of extreme values was analysed based on three generalized extreme values (GEV) models: Model 1 (stationary), Model 2 (non‐stationary for location parameter), and Model 3 (non‐stationary for location and scale parameters). The GEV parameters were estimated by the Generalized Maximum Likelihood method (GMLE) and for the non‐stationary models, the parameters were estimated as linear functions of time. To choose the most suitable model, the maximum likelihood ratio test (D) was used. From the results observed at the monthly scale, it was possible to infer that the months with the highest probability of an extreme weather event occurrence are February (climates Aw and Cfa), July (Cfa and Cfb), and October (Aw, Cfa, and Cfb). Approximately 90% of the 1,112 stations presented no trend regarding the GEV parameters. The non‐stationarity showed by other stations (Models 2 and 3) might be associated with several factors, such as the alteration of land use due to the north expansion of the agricultural border of the Paraná River basin.

Description: Abstract This article presents a review of the scientific literature on detection, sources of variability, and predictability of the timing of monsoons. The timing of monsoons is characterized by the beginning (commonly referred to as onset) and end (commonly referred to as demise, cessation, retreat, or withdrawal) dates of the summer monsoons. The main methods used to detect the timing of monsoons are divided into two categories: local‐scale methods and regional‐to‐large‐scale methods. The sources of variability of the timing of monsoons are also separated into two categories: local‐scale and large‐scale sources. Finally, the article presents a summary of the literature on the predictability of the timing of monsoons using both dynamical and statistical approaches. We show that all methods are parameterized in some way. A comparison between two different methods shows that while there might be large differences in the definition of onset and demise dates at the local level, spatial aggregation usually reduces the noise and enhances the regional monsoonal signal, which may be predictable. This article is protected by copyright. All rights reserved.

Description: Abstract The Australian Alpine region is highly vulnerable to extreme climate events such as heavy rainfall and snow falls, these events subsequently impact rainfall erosivity and hillslope erosion in the region. In this study, the relationship between extreme rainfall indices and rainfall erosivity was examined across the Alpine region in New South Wales (NSW) and Australian Capital Territory (ACT) and the surrounding areas including Murray Murrumbidgee and South East and Tablelands (SET). Rainfall erosivity, hillslope erosion and their changes were estimated in the future periods using the revised universal soil loss equation and the NSW/ACT Regional Climate Modeling (NARCliM) projections. Results from the study demonstrate a good relationship between extreme rainfall indices (especially Rx5Day) and rainfall erosivity. The rainfall erosivity and hillslope erosion are projected to increase about 2% and 8% for the near future (2020–2039), further increase to 8% and 18% for the far future (2060–2079) in the Alpine region assuming the groundcover is maintained at the current condition. The change in rainfall erosivity and erosion risk is highly uneven in space and in season with the highest erosion risk in summer with an increase about 33% in the next 50 years. The highest erosion risk area is predicted within SET (maximum rate 19.95 Mg ha−1 year−1), but on average, the ACT has the highest erosion rate, which is above 1.36 Mg ha−1 year−1 in all periods. The snowmelt in spring in the Alpine region is estimated to increase the rainfall erosivity by 13% in the baseline period, up to 24% in the near future, but far less (about 1%) in the far future due to predicted temperature rise and less snow available in the Alpine region in the next 50 years. This article is protected by copyright. All rights reserved.

Description: International Journal of Climatology, Volume 39, Issue 10, Page i-iv, August 2019.

Description: Location of the GHAS and GHAN regions Abstract Regional‐scale seasonal climate outlooks are typically produced using forecast information either local to the region or from another area with teleconnections to the region. Dynamical global long‐range forecast (LRF) systems can provide both types of information, and these two approaches are compared in the context of seasonal rainfall forecasts for two adjoining areas in the Greater Horn of Africa region in tropical East Africa. The direct method utilizes the unprocessed LRF outputs for the region. For the “indirect” method, canonical correlation analysis is used and works by identifying patterns in historical LRF predictions over large tropical domains that relate to observed variability in the East Africa regions. For a given year, projections of the LRF forecasts onto those patterns can then be employed to construct the regional forecasts. This approach takes advantage of the tendency for LRF systems to have greater skill for large‐scale variability than for smaller regional‐scale features. Using case studies, it is found the two approaches contain complementary information: the indirect approach can provide notable skill benefits in years with strong large‐scale forcing while in some years, particularly when large‐scale signals are weak, the “direct” forecast are superior. Skill comparisons over many years found that, although results are region/season dependent, in general the indirect approach has higher skill overall—with improvements equal to or greater than those afforded by a 1‐month reduction in lead time with the direct approach. Results for both methods used separately and in combination are provided for the March–April–May and September‐to‐December seasons in the two regions, using data from currently operational dynamical LRF systems. Skill was best for the September‐to‐December season in the southern region, using “indirect” forecasts. The “direct” approach was better than “indirect” for the March‐to‐May season in the northern region. In general, combination did not produce a substantial benefit.

Description: Topography elevation (m) map of Mediterranean Sea, central North Africa and Southwest Asia. The EMED, wISM and BoB regions are denoted. The cross corresponds to the reference point. Data are available from NOAA US Department of Commerce under data announcement 88‐MGG‐02. Abstract Etesians are north to south direction winds in the lower atmosphere, blowing over the Aegean basin from early summer to early autumn. They are an important circulation component for the East Mediterranean (EMED) area, linked to the subsidence and ascent circulation over EMED and the extended Indian monsoon region, respectively. In this study we investigate the evolution of Etesian days and the associated wind speed (10 m) over the recent past (1979–2005) in simulations from Earth System Models (ESMs) available from the Coupled Model Intercomparison Project Phase 5. Results from this analysis are compared to the ERA‐Interim reanalysis. Moreover, we study the connection of the Etesians to the atmospheric circulation over EMED and the wider Indian monsoon area, in particular over the west Indian summer monsoon (wISM) and the Bay of Bengal (BoB). Our findings suggest that while the ESMs underestimate the wind speed of the Etesians, their frequency and summer cycle are in good agreement to reanalysis. ESMs can accurately represent the summer atmospheric circulation and depict the connection between EMED and Indian summer monsoon (ISM), capturing the link between them. Finally, we highlight here the capability and efficiency of ESMs in representing the climatology of Etesians and related atmospheric circulation.

Description: Abstract This study investigates the relative contribution of internal variability and external forcings on summer (June–August) surface air temperature (SAT) over the Central Indian landmass. Here we use Community Earth System Model Large Ensemble (CESM‐LE) data to assess the historical (1966–2005) and future (2010–2060) climate change in presence of internal climate variability. The summer SAT trend during the historical period exhibit an amplified cooling (〈−3°C), whereas, a warming trend (〉= 4°C) is projected in all the ensemble members under RCP8.5 scenario. The total trend is then partitioned into contributions from the externally forced response and internal climatic variability. Over the Indian region, the external forcing displays a strong cooling trend during the historical period and warming trend under RCP8.5 scenario. On the other hand, natural variability displays mainly cooling trends and it introduces a wide range of uncertainty to the future projection in climate models. In historical period, the signal to noise ratio (SNR) i.e. ratio of external forcings and internal variability is less than 1, which indicates that the internal climatic variability dominates over the forced response. But in future decades the SNR is much higher than 1 i.e. external forcing overrides the internal variability. However, to a greater extent natural variability will mask the warming trend over the Indian region, even under RCP8.5 scenario. This article is protected by copyright. All rights reserved.

Description: Abstract An intercomparison of three regional climate models (PRECIS‐HadRM3P, RCA4, and RegCM4) was performed over the Coordinated Regional Dynamical Experiment (CORDEX) ‐ Central America, Caribbean and Mexico (CAM) domain to determine their ability to reproduce observed temperature and precipitation trends during 1980‐2010. Particular emphasis was given to the North American monsoon (NAM) and the mid‐summer drought (MSD) regions. The three RCMs show negative (positive) temperature (precipitation) biases over the mountains, where observations have more problems due to poor data coverage. Observations from the Climate Research Unit (CRU) and ERA‐Interim show a generalized warming over the domain. The most significant warming trend (≥ 0.34°C decade‐1) is observed in the NAM, which is moderately captured by the three RCMs, but with less intensity; each decade from 1970 to 2016 has become warmer than the previous ones, especially during the summer (mean and extremes); this warming appears partially related to the positive Atlantic Multidecadal Oscillation (+AMO). CRU, GPCP and CHIRPS show significant decreases of precipitation (less than ‐15% decade‐1) in parts of the Southwest United States and Northwestern Mexico, including the NAM, and a positive trend (5% to 10% decade‐1) in June‐September in eastern Mexico, the MSD region, and northern South America, but longer trends (1950‐2017) are not statistically significant. RCMs are able to moderately simulate some of the recent trends, especially in winter. In spite of their mean biases, the RCMs are able to adequately simulate interannual and seasonal variations. Wet (warm) periods in regions affected by the MSD are significantly correlated with the +AMO and La Niña events (+AMO and El Niño). Summer precipitation trends from GPCP show opposite signs to those of CRU and CHIRPS over the Mexican coasts of the southern Gulf of Mexico, the Yucatan Peninsula, and Cuba, possibly due to data limitations and differences in grid resolutions. This article is protected by copyright. All rights reserved.

Description: Abstract This study has addressed the spatiotemporal distribution of the daily rainfall concentration and its relation to the teleconnection patterns across the Mediterranean (MR). Daily Concentration Index (CI) and the ordered n index (nor) are used at annual time scale to reveal the statistical structure of precipitation across the MR based on 233 daily rainfall series for the period 1975–2015. Eight teleconnection patterns, North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), Western Mediterranean Oscillation (WeMO), Upper Level Mediterranean Oscillation index (ULMO), East Atlantic (EA) pattern, East Atlantic/West Russia (EATL/WRUS) pattern, Scandinavia (SCAND) pattern and Southern Oscillation (SO) at annual time scale are selected. The spatiotemporal patterns in precipitation concentration indices, annual precipitation and their teleconnections with previous large‐scale circulations are investigated. Results show a strong connection between the CI and the nor (r = 0.70, p〈0.05) which present the same relative areas of high and low concentration. The annual values range from 0.57 to 0.70 for CI and 0.49 to 0.71 for nor index which show a high daily precipitation concentration across the MR. Trend analysis demonstrated mostly significant increasing trends for both indices. This increase is mainly found in south France, northern coastlands of the Iberian Peninsula (IP), Greece and Tunisia. An inverse relationship between the number of rainy days and concentration indices is evident. Both of WeMO and MO can play an important role in modulating rainfall in the northwest Mediterranean. The positive EATL/WRUS phase is mainly connected with positive precipitation mean anomalies in the Eastern Mediterranean and vice versa in the west. The high daily precipitation concentration values over south France, northeast Spain, Croatia and Tunisia are linked to the low values of WeMO and high values of EA. These results could pave the way for new possibilities regarding the projection of precipitation concentration and precipitation irregularity in downscaling techniques. This article is protected by copyright. All rights reserved.

Description: Abstract The combined impact of Greenland sea ice, Eurasian snow, and the El Niño–Southern Oscillation (ENSO) on the out‐of‐phase relationship between the Indian summer monsoon (ISM) and Korean summer monsoon (KSM) were investigated through numerical experiments. The results revealed that Indian and Korean summer rainfalls showed nonlinear responses to ENSO and Greenland sea ice forcing when the events co‐occurred. Above‐normal Greenland sea ice and a concurrent La Niña showed a distinct in‐phase relationship with ISM and out‐of‐phase relationship with KSM. Below‐normal and above‐normal Greenland sea ice during boreal autumn surrounded the Greenland region with anomalous low pressure and high pressure, respectively. These were associated with a barotropic +west/−east or –west/+east dipole pattern, respectively, over Eurasia during the subsequent winter and spring seasons. Furthermore, these patterns led to positive and negative snow depth anomalies, respectively, over western Eurasia and the opposite snow tendency over eastern Eurasia during the subsequent spring. This variability in Eurasian snow patterns may play a crucial role in ISM and KSM. The co‐occurrence of ENSO variability also generates high‐ and low‐pressure anomaly patterns over the Indian Ocean that may be related to unfavorable or favorable ISM, respectively, while influencing the negative or positive phases of a Pacific Japan (PJ)‐like teleconnection pattern that may be related to unfavorable or favorable KSM, respectively. Therefore, coexisting ENSO forcing may play a dominant role in ISM and KSM, but Greenland sea ice forcing and Eurasian snow variation intensify the out‐of‐phase relationship between ISM and KSM. This article is protected by copyright. All rights reserved.

Description: A Landsat‐7 image (07 July, 2001) of the study area, known as the Sermeq Kajulleq ablation region, commonly referred to as the Jakobshavn ablation region, or JAR (within red box). The study area is north of the glacier (red dashed line) in west‐central Greenland. In the region surrounding the melt‐lakes is a linear transect of three automated weather stations, JAR‐2 (568 m), JAR‐1 (962 m), and Swiss Camp (1,149 m) that are part of the Greenland Climate Network Abstract Along the west‐central Greenland ice sheet (GrIS) ablation zone, the time of annual maximum occurrence of surface melt‐lakes, or peak lake period (PLP) averages June 18–July 3. This study combines atmospheric reanalysis and automatic weather station data from the Greenland Climate Network to assess the roles of synoptic circulation patterns and local climate variables, respectively, in the total melt‐lake area and count in the Sermeq Kujalleq ablation region (SKAR) for the PLPs of 2000–2016. Melt‐lake information is obtained from analysis of Landsat‐7 images. Two surface climate parameters (e.g., temperature, incoming shortwave radiation) having a strong combined effect on melt‐lake area in the SKAR are the June mean temperature, and May mean incoming solar radiation (r = .96). Incorporating the May insolation into a regression equation permits predictability of total melt‐lake area for the study area into late June. June months classified as high melt correlate regionally with mid‐tropospheric ridging, warm air advection, and reduced cloud cover, while low melt June months are associated with a trough, cold advection, and greater cloud amount. A localized feature that we found to be prevalent during the high‐melt years are piteraq, or downsloping winds, which provide additional warming to the SKAR from adiabatic compression. Atmospheric circulation indices comprising the North Atlantic Oscillation index (NAOI) teleconnection and Greenland blocking index (GBI) pattern augment the reanalysis gridded data. We find statistically significant correlations of the NAOI and GBI with melt‐lake area (r = −.62 and r = .77, respectively). The correlations with melt‐lake count however, are not significant; greater combined lake area and count tend to accompany the meridional mode of high amplitude Rossby waves and/or anti‐cyclonic blocking in the Greenland sector. Determining the local and synoptic‐scale atmospheric controls on supraglacial lake variability helps clarify the role of climate in the surface hydrology of the GrIS.

Description: Abstract The influence of synoptic‐scale circulation on air temperature variation in the ice‐free and glaciated areas on the eastern side of the Antarctic Peninsula have been analysed. For this purpose, a new classification of atmospheric circulation with fifteen synoptic patterns in the Antarctic Peninsula region was developed using the self‐organizing maps technique. The synoptic patterns were compared with air temperature observations from coastal and glacial sites on James Ross Island, north‐eastern Antarctic Peninsula, in the period 2005–2015. The most frequent synoptic pattern with a frequency of 13.7% was dominated by a low‐pressure centre in the north‐western Bellingshausen Sea, which extended over the Antarctic Peninsula to the Weddell Sea. On the other hand, the largest interannual variability was observed for a synoptic pattern with a low‐pressure centre in the southern Bellingshausen Sea. This synoptic pattern also had the highest air temperature anomalies at both investigated sites year‐round. Air temperature anomalies at the lower lying site (Mendel station) were the lowest during a high‐pressure ridge dominating the AP region due to a combination of local and synoptic‐scale processes. At Davies Dome, the glacial site, southerly barrier winds advecting cold air from the ice‐covered Weddell Sea during a strong low‐pressure system in the Weddell Sea ensured the coldest air temperature anomalies. This article is protected by copyright. All rights reserved.

Description: Time series of Changma retreat date (CRD, solid line with a closed circle) for 30 years (1985–2014) and statistical change‐point analysis (dotted line). Abstract This study applied statistical change‐point analysis to the time series of the Changma retreat date (CRD) on the Korean Peninsula over a recent 30‐year period (1985–2014) and detected that the CRD has been delayed by about 10 days since 2000. The average CRD is July 14 for 1985–1999 and July 24 for 2000–2014. Corresponding to the CRD delay, the July rainfall is concentrated in the northern South Korea during 2000–2014, whereas tends to be intense along the southern coast during 1985–1999. The delayed CRD is associated with, in the lower and mid‐troposphere, a strengthened cyclonic circulation around Lake Baikal–eastern Sea of Japan and an enhanced anticyclonic circulation in East China Sea. Thus, northerlies from strengthened cyclones and anomalous southerlies from the enhanced anticyclones converge at the northern‐central Korean Peninsula. The anomalous anticyclone is associated with the strengthening of the western North Pacific subtropical high that has strengthened in meridional direction in the later epoch, supplying warm and moist air to Korean Peninsula. The result is verified by the enhanced warm and moist anomalous upward flows in the latitude where Korean Peninsula is placed. The delayed CRD in the latter epoch is related to the decreased spring snowfall over East Asia except for the vicinity of the Lake Baikal, which results in severely hot weather in the East Asia continent from spring to July. The continent heating from spring to July weakened (increases), the thermal gradient between continent and ocean, thereby forming a low‐pressure system on East Asia and a high‐pressure system in western North Pacific, resulting in the strengthening of Changma rain belt in July and delayed the Changma withdrawal.

Description: The gridded weather typing classification (GWTC) methodology, and dataset, is expanded worldwide. The global GWTC (GWTC‐2) classifies every day at every location into one of 11 intuitive weather types, 1979–present. With half‐degree spatial resolution, this results in over 259,000 global locations and more than 3.7 billion location/days currently classified, with another 7–8 million added each month. The GWTC‐2 identifies more extreme weather types compared to the original, and extending the classification over the ocean allows for new oceanographic applications. Abstract Synoptic climatology uses classifications of atmospheric data to relate the larger‐scale atmosphere to surface‐based responses. One of the two primary modes of classification is the weather typing classification, whereby the multivariate surface‐based meteorological conditions at an individual location are categorized into a daily weather type (WT), and this methodology is then iterated at numerous locations within the domain in order to identify synoptic‐scale air masses. One such classification that was recently developed is the gridded weather typing classification (GWTC) for North America. The current research describes the extension of this GWTC methodology, and dataset, to the global scale, along with a number of other key updates. Using data from the Climate Forecast System, the global GWTC (GWTC‐2) classifies every day from 1979 to present into one of 11 intuitive weather types. With half‐degree spatial resolution, this results in over 259,000 global locations and more than 3.7 billion location/days currently classified, with another 7–8 million added each month. Updates to the GWTC methodology also allow for the identification and visualization of more extreme weather types compared to the previous version, and the extension of the classification over the global ocean will allow for new oceanographic applications.

Description: Abstract This study assesses the potential changes in regional hydroclimates over South Korea in response to 1.5 and 2.0 °C of global warming above preindustrial levels based on multi‐model ensemble projections forced by a representative concentration pathway (RCP4.5) scenario. The meteorological inputs, which are derived from five global climate models after removing systematic bias using quantile mapping, are fed into a distributed hydrological model, the variable infiltration capacity model, to estimate the hydrologic responses to different levels of greenhouse gas concentrations in future periods. The changes in seasonal mean precipitation differ between monsoon and inter‐monsoon seasons. An increase in summer precipitation and a decrease in winter precipitation commonly occur under 1.5 and 2.0 °C of global warming, resulting in intensified precipitation seasonality. However, changes in spring and fall precipitation show opposite change signals or relatively little robustness (as measured by model agreement) in response to different degrees of warming. Spatial and seasonal changes in precipitation are directly transferred to runoff patterns, increasing the disparity between wet and dry seasons. Global warming also leads to changes in the distributions of daily precipitation and streamflow, and the projected changes systematically involve an increase in high‐intensity precipitation and a decrease in relatively low‐intensity precipitation. This behavior tends to be amplified under 2.0 °C in comparison to 1.5 °C of global warming, with potential implications for increased water stress under a much warmer climate. More importantly, under 2.0 °C of global warming, the magnitude of extremes such as the annual maximum day flow in Korean basins is likely to be enhanced. This study demonstrates that changes in precipitation characteristics can explicitly modulate runoff and subsequently streamflow patterns, suggesting positive benefits of half a degree less warming in terms of the frequency and intensity of extreme streamflow. This article is protected by copyright. All rights reserved.

Description: Abstract Previous study has suggested a northwestward shift of tropical cyclone (TC) genesis position during autumn over the western North Pacific (WNP) after the late‐1990s. This study replenishes two mechanisms to explain this interdecadal change in the WNP TC genesis position. The first mechanism is related to the mean state change. According to observational analysis and numerical simulations with the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric general circulation model, a La Niña‐type Pacific sea surface temperature (SST) change and the northern Atlantic Ocean warming in the late‐1990s cause a dipole pattern of lower‐level circulation change, with cyclone over the northwestern WNP and anticyclone over the southeastern WNP. This pattern is favorable for more TC genesis in the northwestern WNP. The sensitivity experiments show that the contribution from the Pacific Ocean is larger than that from the northern Atlantic Ocean. The second mechanism is related to the change in the intraseasonal oscillation intensity, particularly the quasi‐biweekly variation. The activity of intraseasonal oscillations over the southeastern WNP shows a decadal decrease around the late‐1990s. Meantime, when the intraseasonal oscillations with tilted structure move northwestward, they provide a favorable condition for TC genesis to be located more northwestward after the late‐1990. This article is protected by copyright. All rights reserved.

Description: Abstract The Eastern Pacific (EP) and Central Pacific (CP) El Niño‐Southern Oscillation (ENSO) types and their impacts on the Tropical North Atlantic (TNA) SST variability and 15°N‐15°S South American precipitation during the warm and cold phases of the Atlantic Multidecadal Oscillation (WAMO and CAMO) were evaluated during the 1901‐2012 period. The results show more frequent ENSO events during the CAMO. The El Niño (EN) (La Niña (LN)) events, regardless of type (EP or CP), during the WAMO (CAMO) were accompanied by a warming (cooling) in the TNA after its mature phases. In these cases, extratropical teleconnection patterns are established through variations in the Pacific/North America (PNA) teleconnection pattern and are accompanied by variations in the Walker circulation. For the EN (LN) in the CAMO (WAMO), the tropical teleconnections occur predominant, through the Walker cell and the zonal inter‐basin gradient, which is intensified due to the SST gradient between the eastern equatorial Pacific (non‐neutral anomalies) and the equatorial Atlantic (neutral anomalies). These circulation pattern changes affect the precipitation patterns in the 15°N‐15°S South American sector during December‐January‐February (D(0)JF(+1)) and March‐April‐May (MAM(+1)). The EP EN (EPEN) events are associated with the intensification of the negative precipitation anomalies in northeastern Brazil (NEB) during the WAMO and in the central part of the Amazon during the CAMO. In the case of CP EN (CPEN) events, the greatest differences between the AMO phases occur during MAM(+1), with reverse sign anomalies over northwestern South America. In the case of LN events, the largest differences occur in NEB, with reduced rainfall in the WAMO, regardless of type EP or CP. The results presented here highlight the role of low frequency oscillations in defining the teleconnection patterns between tropical Pacific and Atlantic Oceans, not discussed previously. This article is protected by copyright. All rights reserved.

Description: Abstract The Asian summer monsoon is characterized by the presence of a low‐level westerly jet stream (LLJ) in the lower troposphere and a tropical easterly jet stream (TEJ) in the upper troposphere. It is interesting to develop an index based on the vertical zonal wind shear and associated rainfall intensity over a monsoon region. The conventional method used to estimate wind shear takes the difference in wind speed between the zonal winds at 850 hPa and 200 hPa. These two fixed levels do not represent the maximum wind speeds at these altitudes and therefore fail to obtain the maximum vertical wind shear. In this study, we propose a new index (the Shinu Mohan index ‐ SM Index) by defining the vertical zonal wind shear between the core heights of the low‐level jet stream in the lower troposphere and the tropical easterly jet stream in the upper troposphere, which represents the maximum zonal wind shear in a vertical column of the atmosphere over the summer monsoon region. The core heights of the LLJ and TEJ vary depending on the terrain and the strength of the monsoon circulation. The SM index provides precise vertical shear at each grid point and represents better spatial variability under different terrain conditions. Vertical shear plays a major role in convection and the production of rainfall over a region. Vertical wind shear during extreme monsoon events and the active and break spells of monsoons were analysed by using the SM index and conventional indices. It is interesting to note that the newly defined SM index gives a much better representation of the monsoon intensity compared to conventional indices. This article is protected by copyright. All rights reserved.

Description: Abstract Hot day and night occurrences in Tallahassee, Florida, U.S.A. are analyzed and modeled. A hot day is defined as one during which the high temperature exceeds 100° F (37.8° C). A hot night is defined as one during which the low temperature fails to drop below 77° F (25° C). The U.S. National Weather Service Office (WSO) Tallahassee official record shows an upward trend in the number of hot days at a rate of 2.1% [±.96% margin of error (moe)] per year and a more pronounced upward trend in the number of hot nights at a rate of 4.5% (±.71% moe) per year. Increasingly frequent hot days and nights result from more and longer hot events (consecutive hot days/nights). Upward trends estimated from a 127‐year time‐series of annual hot day/night counts, with the years prior to 1940 adjusted for location, are consistent with upward trends estimated over the shorter, more recent, period. With projected continued warming we expect more hot days and nights making uncomfortable and unhealthy conditions more common in the city. This article is protected by copyright. All rights reserved.

Description: Spatial distribution of Rmax between SPEI and EVI for spring (a), summer (b), autumn (c), winter (d). Abstract Located in the subtropical monsoon climate area of China, the Yangtze River Basin (YRB) had been frequently affected by drought events recently. Based on standardized precipitation evapotranspiration Index (SPEI) and enhanced vegetation index (EVI), the characteristics of drought in the YRB and the influence of drought on vegetation in different seasons were investigated by maximum correlation (Rmax) between 1981 and 2015. The results showed that: (a) Droughts occurred frequently but had no obvious regularity in the YRB from 1981 to 2015. The drought intensity in autumn and winter were slightly higher than that in spring and summer. The autumn droughts in Sichuan Basin were the most serious, followed by the spring droughts in the middle and lower reaches of the YRB; (b) Annual SPEI series at 102 stations exhibited a downward trend and 72 stations exhibited an upward trend. There was no station showing a significant downward trend and two stations showing a significant upward trend. There was a drying trend in autumn and winter, and a wetting trend in spring and summer. The eastern area of the YRB shows a more arid trend in spring and autumn, as well as in the southwest in winter; (c) 90% of YRB showed a significant positive correlation (p 〈 .05) between SPEI and EVI during the growing season (March–October), and the vegetation was more sensitive to short‐term and medium‐term drought. However, there were spatial and seasonal differences in the impact of drought on vegetation. Different types of land cover had different responses to droughts. Grasslands and croplands were more sensitive to droughts, grasslands at low elevation was dominated by short‐term droughts, while at high elevation was influenced by medium‐long‐ and long‐term droughts. Croplands and woodlands were more vulnerable to short‐term droughts.

Description: ABSTRACT Realistic estimates of surface wind speed are an essential pre‐requisite for process‐based air‐sea interaction studies and numerical modelling needs. In this context, historical and projected wind speed estimates obtained from global and regional climate models warrants proper assessment and necessary bias corrections before it can be optimally used for rigorous analysis and research needs. Adequate evaluation and bias correction of wind speed estimates are therefore crucial to understand the extremes. For example, they have direct implications on extreme wind‐wave characteristics that can influence the coastal zones. The present study performed a detailed evaluation of wind speed obtained from the Coupled Model Inter‐comparison Project Fifth Phase (CMIP5) products to assess their projections for the Bay of Bengal region. A suite of global climate models is employed to generate the CMIP5 projections under four Representative Concentrative Pathways (RCPs) of 2.6, 4.5, 6.0, and 8.5 and based on differential CO2 emission scenarios. The present study also used the Research Moored Array for African‐Asian‐Australian Monsoon Analysis and Prediction (RAMA) buoys located in the central Bay of Bengal in order to validate and skill assess the CMIP5 wind products under varying RCPs. Besides, an inter‐comparison exercise that was performed between RAMA buoys data and merged satellite altimeter data from the French Research Institute for Exploitation of the Sea/Laboratory of Oceanography from Space (IFREMER/CERSAT) provided the necessary confidence to ascertain the quality of CMIP5 wind speed products. The study signifies that a moderate positive correlation was noticed in the wind speed comparison between CMIP5 GCM products and the RAMA buoys (maximum correlation of 0.64), and the correlation factor varied between the suite of models used in CMIP5 experiments. This exercise would provide detailed know‐how on the performance of various GCMs and also provide a basis to select the best‐performing GCMs for the Bay of Bengal region. Analysis of the upper 10% (90th percentile) showed a maximum under‐estimation/over‐estimation of 2.5 m/s and 1.5 m/s respectively for wind speed comparison between CMIP5 and RAMA buoys data. Probability density of wind speed data fitted to Weibull distribution showed an increase of moderate wind speed (6‐8 m/s) during the period of study. Although the CMIP5 GCMs are not able to represent the contemporary wind speed climatology satisfactorily, the models such as HadGEM2‐ES, HadGEM2‐CC, CanESM2, and ACCESS‐1.3 showed the best performance concerning near‐surface wind speed for the Bay of Bengal region. This article is protected by copyright. All rights reserved.

Description: Various characteristics of precipitation concentration index and its possible teleconnection with atmospheric circulation patterns in China between 1960 and 2016. The precipitation concentration index (PCI) is a powerful indicator for temporal precipitation distribution and is also very useful for the assessment of seasonal precipitation changes. The primary objectives of this study are to investigate and analyse the temporal–spatial variability patterns of annual and seasonal PCI values based on monthly precipitation data. These data were collected from 597 meteorological stations located throughout China, for the time period of 1960–2016, and were used to assess the impacts of geographical parameters (latitude, longitude, and altitude) on the PCI. Additionally, the possible teleconnection with the large‐scale circulation pattern was investigated. Our results reveal that the variation trend of annual PCI values has decreased significantly at a rate of −.234/10 year (α = .01) in China over the past 57 years. For all studied station records, 434 (72.7%) stations showed decreasing trends of PCI values, and these stations are distributed over large areas in China. On an annual scale, the average PCI value ranged from 11 in Hunan province to 44 in Qinghai province. The precipitation concentration in China can be described as strongly irregular in the western and northern parts of the northwest and in the northern region of the Tibetan Plateau, while it is irregular in the southwest and the north of China, and moderately irregular in some parts of the middle‐lower regions of the Yangtze River and southern China. The regularity of the annual precipitation pattern significantly decreased in spring, autumn, and winter from southeastern to northwestern China, and was the most in winter. However, the summer precipitation dispersion and the pattern in the considered period were more regular than those of the other seasons. Furthermore, changes in the PCI appear to be rather complex and possibly related to global atmospheric characteristics as well as geographical factors (latitude, longitude, and altitude). The results presented in this study indicate that the PCI is an essential feature for water resource planning, prediction of risk due to droughts or floods, and the management of natural resources.

Description: International Journal of Climatology, Volume 39, Issue 12, Page i-iv, October 2019.

Description: Water in Northern Chile, mainly characterized by the Atacama Desert, is a very scarce resource, and precipitations are the principal providing source of it. Under very challenging climate change scenarios, to study, not only the amount evolutions but also the irregularity of rainfall is of high interest, so models can be improved. Climate projections can be more confident, so policymakers can develop more appropriate politics and can take more accurate decisions to manage water in this area. Abstract Northern Chile is one of the most arid regions in the world, as it includes the Atacama Desert. At high elevations, most precipitation is observed only during a short period of the year, from December until March. This renders water availability a major concern for policymakers. Accumulated rainfall varies considerably from one year to another, and for this reason, climate projections have a very low degree of confidence in this area. Consequently, in this region, it is more interesting to study the irregularity of precipitation itself than accumulated rainfall values, as they express in a clearer way the behaviour of precipitation. According to daily data from 161 meteorological stations, four irregularity indices of precipitation were calculated: concentration index, entropy, persistence index, and fractal dimension. These indices were measured according to observed values, and their spatial distribution was subsequently determined by interpolating following multivariate regression models that consider different geographical variables such as latitude, distance to the Amazon Basin, elevation, orientation, and curvature. The temporal trends of each index and for each meteorological station were also calculated, displaying different results depending on the latitude and elevation. These changes agree with the observed modifications on the inter‐tropical atmospheric circulation and with changes in the precipitation diurnal cycle. These results will help improve climate projections for this region, in the process facilitating the development of more accurate climate models and informing the formulation of water management policies.

Description: ABSTRACT Sea surface temperature anomalies (SSTAs), including their spatial patterns and temporal evolution, are an important source of potential predictability for climate anomalies, especially on seasonal to interannual timescales. In this study, the spatial patterns and temporal evolution of tropical SSTAs are identified by applying an extended empirical orthogonal function (EEOF) analysis of observed data from autumn to the following spring. The positive phase of first EEOF mode (EEOF1) displays an El Niño–Southern Oscillation (ENSO) phase‐locking evolution pattern in the tropical Pacific, with accompanying warming in the Indian and Atlantic oceans. EEOF2 is characterized by the development of ENSO in the eastern tropical Pacific and a phase transition in the Indian Ocean and the tropical North Atlantic. The most noticeable feature of EEOF3 is the development of the central Pacific ENSO. The first three EEOF modes account for 44.7% of the total variance of tropical SSTAs over the course of the three seasons. EEOF1 is closely related to the tropical atmospheric circulation, especially over the western Pacific region, reflecting the strengthening effect of the three tropical oceans on the anomalous anticyclone over the tropical Northwest Pacific during the decaying phases of El Niño. EEOF2 significantly impacts the circulation anomalies over the Indian Ocean and western Pacific. A linear regression model is established using the time series of first four EEOF modes to forecast the June–August 500 hPa geopotential height anomalies. The forecasts show higher skill than a similar linear regression model using seasonal mean regional SST anomaly indices. The results reveal that EEOF modes could be used as a good indicator in the monitoring of tropical SSTA evolution patterns. This article is protected by copyright. All rights reserved.

Description: Abstract The Caspian Sea Level (CSL) has undergone variations of more than 3 m during the past century with important implications for the life of coastal people, economy and the ecosystem. The origin of these variations as well as future changes in the Caspian water budget are still a matter of debate. Here, the major modes of North Atlantic winter climate variability and atmospheric teleconnections that have a potential effect on the hydroclimate of the Caspian catchment region are examined. The skill of the Community Earth System Model (CESM1.2.2) regarding the simulation of the modern climatology in the Caspian region and the major North Atlantic modes are analysed using different atmospheric grid resolutions and setups of the atmospheric component, the Community Atmosphere Model (CAM4 and CAM5). CESM1.2.2 with CAM5 atmosphere physics and 1° atmospheric grid resolution shows reasonable skill in simulating the regional Caspian basin climatology and the winter North Atlantic Oscillation (NAO). Using this model version, a weakly positive (r=0.2) statistically significant (p〈0.05) correlation between the catchment winter water budget (precipitation minus evaporation, P‐E, integrated over the catchment area) and the NAO is found for the historical period 1850‐2000. Climate projections of the 21st century under the Representative Concentration Pathways RCP4.5 and RCP8.5 show that the NAO remains the leading mode of winter variability with a dominant influence on the climate in the Caspian catchment region. Under the RCP4.5 scenario the correlation between the winter NAO and winter P‐E over the Caspian catchment region increases (r=0.5, p〈0.05). For RCP8.5, however, this correlation disappears due to a north‐south dipole pattern with a positive P‐E anomaly over the northern and a negative anomaly over the southern parts of the Caspian catchment region, cancelling out an effect on the total Caspian water budget. Nevertheless, due to increasing annual evaporation over the Caspian Sea in the warming climate, the model predicts an additional CSL decrease of about 9 m and 18 m between 2020 and 2100 for the RCP4.5 and RCP8.5 scenarios, respectively. Even though the model tends to overestimate the total evaporation due to a too large Caspian Sea surface area, these values are larger than previous projections of CSL decline. This article is protected by copyright. All rights reserved.

Description: Abstract By separating variations on different time scales, the present study reveals important differences in the North Atlantic Oscillation (NAO)‐related sea ice concentration (SIC), surface air temperature (SAT) and sea surface temperature (SST) patterns for trend, interdecadal and interannual variations. The SIC has a prominent decreasing trend in the Greenland Sea and the Barents Sea, collocating with an increasing SAT trend and a weak increasing SST trend in the high‐latitude North Atlantic. The wind trends display a weak NAO signal. Corresponding to the positive interdecadal NAO phase, the SIC shows a decreasing trend in the Greenland and Barents Seas. The SAT change features a west negative‐east positive pattern along with positive anomalies extending to the Greenland Sea. The SST change is very weak in the Greenland Sea. Corresponding to the positive interannual NAO phase, the SIC change is opposite between the Greenland/Barents Seas and the Labrador Sea. The SAT change is characterized by a broad west‐east pattern over the mid‐high latitudes. The SST change features an east‐west dipole pattern in the mid‐latitude North Atlantic Ocean. In both interdecadal and interannual variations, NAO‐related meridional wind anomalies induce anomalous advection that contributes to the SAT change together with upward longwave radiation. The SIC and SAT changes are coupled closely through surface heat fluxes in all the three time scales. The present results suggest that it is necessary to distinguish time scales in studying the relationship among SIC, SAT and SST variations. This article is protected by copyright. All rights reserved.

Description: Abstract The global temperature has increased approximately 0.9 °C over the past 50 years and is projected to continue to increase. Many efforts have been taken to investigate the evolutionary dynamics of climate classification zones in response to the rising temperature. However, the changing dynamics of the spatial climate patterns remain poorly understood. It is thus desired that the unobserved characteristics of the global climate patterns, such as aggregation and subdivision, are explored from the landscape perspective. Here, we demonstrate that the global climate zones have undergone a process of aggregation during the past 100 years and that this dynamic is expected to continue in the future. The climate aggregation effect is especially evident in the Arctic, Tibet, and East Africa. We find that the tropical, arid, temperate, and cold climates are aggregating while the polar climate zone exhibits subdivision. Furthermore, our analysis demonstrates a clear spatial aggregation process with a latitudinal feature. We should pay enough attention to the phenomenon of patch aggregation of global climate landscape pattern, which will undoubtedly help us to deepen our understanding of global climate change and help to further explore the feedback relationship between climate and biological systems. This article is protected by copyright. All rights reserved.

Description: Abstract Climate anomaly has caused substantial shifts in phenology of mountain ecosystems, but the underlying mechanism of phenological responses to climate change is still not well understood. In essence, the abundance of vegetation communities increases the complexity of phenology‐climate relationships, leading to a certain limitation in predictions of future dynamics among different vegetation types using a unified model. In this study, we focused on the climatic constraints on spring phenology in arid mountains (AMs) of China, and emphasis was laid on accurate representation of mechanisms that control phenology across different vegetation types. We Firstly explored spatiotemporal variations in satellite‐derived estimates of starting date of vegetation growing season (SOS) over the period 2000–2015 using Moderate‐resolution Imaging Spectro‐radiometer (MODIS) normalized difference vegetation index (NDVI). Phenological models in response to climate variability were then established by using mixed‐effect models based on satellite observations and an extensive dataset of climatic measurements. Our results showed that the climatic regulation on SOS varied greatly over vegetation types. More climatic factors that regulate phenological development were found in grassland than forest and shrubland. At ecosystem level, two critical climate factors, daily minimum temperature (Tmin) and precipitation, explained 74 to 95% of total variability in predicted SOS. The observed sensitivity to Tmin is expected to be closely linked with the risk of frost damage, while preseason precipitation determines water availability in spring. The varying ecosystem sensitivity revealed the different resilience and adaptability to changing climate among vegetation types, which have been linked to their eco‐physiological characteristics (e.g., water use efficiency; Reed et al., 2018) and environmental conditions (e.g., elevation). Overall, our results indicate a strong dependence of spring phenology on Tmin and precipitation, and create an opportunity for a more realistic representation of vegetation phenology and growth of AM plants in China in land surface models. This article is protected by copyright. All rights reserved.

Description: Abstract Extreme temperatures have caused various damages to society around the world. In Brazil, an example of that is the impact of cold and heat waves on public health. In order to analyze the temporal and spatial variability of such events, this study applied a single criterion to identify cold and heat waves. The study collected data on the events from daily temperature records from 264 weather stations over 56 years (1961–2016). The following parameters were used to describe each event: frequency, duration, severity, and intensity. The results showed that in all the Brazilian regions the frequency of heat waves increased and that of cold waves decreased between the years 1961 and 2016. The number of heat waves per year, notably, was greater than that of cold waves, and the mean duration of heat waves was about 1 day longer than that of cold waves. Additionally, it was found that cold waves were more severe and intense in areas often reached by cold air masses with temperatures below zero in most of Southern Brazil. In terms of severity and intensity of heat waves, two different configurations were observed: they were more severe in the Southern region and more intense in the Midwestern region of the country, and not so expressive in the Northern and Northeastern regions. Those findings justify the need for continuous updating of public policies focused on sectors often affected by cold and heat. This article is protected by copyright. All rights reserved.

Description: This study investigates the impacts of climate change in the Sono, Manuel Alves da Natividade and Palma basins, in the Brazilian Cerrado by means of hydrologic simulations. The results show an increase of the hydrological and meteorological droughts and a significant reduction in the streamflow throughout the 21st century, for both RCP4.5 and RCP8.5, which may bring risks for the ecology of the Cerrado biome and for the electric energy production in northern Brazil. Abstract Brazilian Cerrado biome is the largest and richest tropical savanna in the world. In order to understand the effects of climate changes on the hydrology of the Cerrado basins, this paper investigates the hydrological impacts of climate change throughout the 21st century under different emissions scenarios on the streamflow and on the droughts in the Sono, Manuel Alves da Natividade and Palma basins, located in the Brazilian Cerrado. For this purpose, the SWAT hydrological model driven by the downscaling of the HadGEM2‐ES and MIROC5 global climate models associated with RCP4.5 and RCP8.5 scenarios were used in three time slices (2011–2040, 2041–2070 and 2071–2099). The Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSFI) were used to characterize droughts. In general, the results showed that the duration, intensity and frequency of the meteorological and hydrological droughts are expected to increase during the future periods. However, the hydrological droughts are projected to be larger than the meteorological droughts. Reductions in the streamflow are indicated in all future time slices and under both RCPs, especially, during dry periods, which may cause negative impacts in the ecological functions of the Cerrado biome, risk for reduction of the recharge of aquifers and risk for the electric energy production in northern Brazil.

Description: Abstract The development of nonstationary frequency analysis models is gaining popularity in the field of hydro‐climatology. Such models account for nonstationarities related to climate change and climate variability but at the price of added complexity. It has been debated if such models are worth developing considering the increase in uncertainty inherent to more complex models. However, the uncertainty associated to nonstationary models is rarely studied. The objective of this paper is to compare the uncertainties in stationary and nonstationary models based on objective criteria. The study is based on observed rainfall data in the United Arab Emirates (UAE) where strong nonstationarities were observed. In this study, a nonstationary frequency analysis introducing covariates into the distribution parameters was carried out for total and maximum annual rainfalls observed in the UAE. The Generalized Extreme Value (GEV) distribution was used to model annual maximum rainfalls and the gamma (G) distribution was used to model total annual rainfalls. A number of nonstationary models, using time and climate indices as covariates, were developed and compared to classical stationary frequency analysis models. Two climate oscillation patterns having strong impacts on precipitation in the UAE were selected: the Oceanic Niño Index and the Northern Oscillation Index. Results indicate that the inclusion of a climate oscillation index generally improves the fit of the models to the observed data and the inclusion of two covariates generally provides the overall best fits. Uncertainties of estimated quantiles were assessed with confidence intervals computed with the parametric bootstrap method. Results show that for the small sample sizes in this study, the width of the confidence intervals can be very large for extreme nonexceedance probabilities and for the most extreme values of the climate index covariates. The weaknesses of nonstationary models revealed by the bootstrap uncertainties are discussed and words of caution are formulated. This article is protected by copyright. All rights reserved.

Description: Composites of spatial distributions during the peak of heatwaves (HWs) over South Korea in 1994, 2013, and 2016: (a) P−E, (b) OLR (W m−2), (c) −〈q∇ ∙ ν〉, (d) 500 hPa ω (pa s−1), (e) −〈ν ∙ ∇q〉, (f) 〈ω∂ph〉, (g) Fnet, and (h) −〈ν ∙ ∇T〉. The unit for the other terms is W⋅m−2 shown at the bottom colour bar. Abstract The characteristics of heatwaves (HWs) in South Korea are studied using data from the European Centre for Medium‐Range Weather Forecasts Reanalysis Interim (ERA Interim) dataset and from automatic surface weather stations. The synoptic conditions of three specific years (1994, 2013, and 2016) during which serious HWs affected South Korea are examined. HWs in South Korea are related to the northwestwardly extension of the western North Pacific subtropical high (WNPSH) toward the Korean Peninsula. Examination of the blocking indices revealed widespread blocking over the northern Pacific Ocean and Asia during South Korean HWs, and blocking is related to stationary weather patterns. The severe temperatures associated with HWs in this region are due to prolonged subsidence. Analysis of the moist static energy (MSE) budget indicated that the energy source of subsidence is derived from both MSE advection and the net heat flux. When compared to the synoptic situation during an HW in South Korea, the relative southward movement of the WNPSH is found before and after the HW. The blocking indices also revealed weak signals and changes in vertical motion due to MSE advection.

Description: The extreme precipitation is usually influenced by different climate indices, mutual offset is unavoidable to occur, and thus, rotated empirical orthogonal function was used to identify different influences of climate indices on extreme precipitation in space and time. The variation of extreme precipitation in data‐scarce region is also concerned, hence, an improved spatiotemporal regional frequency analysis model was further developed, therein the identified spatiotemporal influences of climate indices on extreme precipitation were quantified using Bayesian hierarchical method. Abstract Quantifying spatiotemporal influence of climate index on extreme precipitation will help to better understand the variability of extreme precipitation. The extreme precipitation is usually influenced by different climate indices, and mutual offset is unavoidable to occur, thus the rotated empirical orthogonal function was used to identify the different influences of climate indices on extreme precipitation in space and time. The variation of extreme precipitation in data‐scarce region is also concerned, hence, an improved spatiotemporal regional frequency analysis model was further developed, therein the identified spatiotemporal influences of climate indices on extreme precipitation were quantified using Bayesian hierarchical method. In this study, the in situ seasonal maximum one‐day precipitation amount (Rx1day) was used to represent seasonal precipitation extremes from 1957 to 2010 in the Poyang Lake basin, and spatiotemporal influences of El Niño‐Southern Oscillation (ENSO), North Atlantic oscillation (NAO) and Indian Ocean Dipole (IOD) on seasonal Rx1day were quantified. Results indicated that the seasonal Rx1day was influenced by different climate indices in the Poyang Lake basin, ENSO tends to affect spring and autumn Rx1day, IOD tends to affect summer Rx1day, and NAO tends to affect spring and winter Rx1day. The response of extreme precipitation on climate index is varied in different regions, and this was well distinguished and verified, such as negative ENSO (in the same year) events tends to cause spring Rx1day slight decrease in the southern part of the basin while increase about 15% in the northern part with center around the Poyang lake.

Description: Annual and monthly mean rainfall for the period 1981–2015 at 13 stations in the CH. Abstract In this study, different criteria to determine the rainy season onset date (RSOD) and its predictability in the Central Highlands (CH) of Vietnam are investigated. Using daily rainfall amounts from 10 meteorological stations for the period 1981–2015, four criteria to determine the RSOD were tested in order to select the one that most reasonably depicts the climatology of the RSOD over the CH. Results show that the RSOD varies strongly from year to year. In the long‐term mean, the onset starts first in southern parts of the CH and then progresses to the northern parts. The earliest onset date is around the beginning of April, and the latest in the second half of May. The average RSOD is on 28 April with a standard deviation of 14 days. Thus, the RSOD is distinct from the summer monsoon onset, namely, leading the mean summer monsoon onset by about 3 weeks in some years. In terms of remote influences, the RSOD in the CH has a high correlation with the El Niño–Southern Oscillation phenomenon, with most RSODs being later during El Niño years, while being earlier during La Niña years. The RSOD in the CH also shows high correlations with sea surface temperatures (SSTs), 850‐hPa zonal winds (U850) and mean sea level pressures (PMSL) over certain regions of the Pacific and Indian Oceans. Building on these relationships, the RSOD can be successfully predicted using large‐scale fields of SST, U850 and PMSL as predictors in two different approaches, namely the field mean and principal component analysis. This suggests that the overall approach can also be applied in predicting the RSOD in the CH on sub‐seasonal to seasonal timescales.

Description: This study presents Multifractal Detrended Fluctuation Analysis (MF‐DFA) to describe the multifractality of Standardized Precipitation Index (SPI) series from 30 meteorological subdivisions of India estimated at different aggregation time scales (3, 6 and 12 months) based on long term monthly rainfall datasets of 1871‐2016 period. The plots of fluctuation function and generalized Hurst exponents confirmed that multifractality is evident in most of the SPI series, however it is found that its strength and persistency differ with time scale and space. The Hurst exponents of long term (SPI‐12) and medium term (SPI‐6) drought series of all subdivisions showed long term persistence irrespective of the climatic conditions of the region, while the short‐term droughts (SPI‐3) of six subdivisions displayed short term persistence. Further, the analysis by partitioning the data to four time spells: 1871‐1905, 1906‐40, 1941‐75 and 1976‐2016 showed that the persistency of long and medium term drought is rather permanent. The analysis on changes in multifractal properties with respect to the climatic shift of 1976/77 period showed that there is a clear increase in multifractal properties of all types of drought series in the recent past (post 1976 period). This study also finds that the Hurst exponents and degree of multifractality of all types of droughts increases with increase in aggregation time scales. The multifractality of all the long‐term drought series (SPI‐12) and most of the SPI‐6 series are found to be due to correlation properties, while that of SPI‐3 is because of joint effect of correlation properties and the broadness of probability distribution.

Description: The aim of the article was to provide a detailed analysis of pressure conditions, employing the anomalies of geopotential heights, during the occurrence of heat waves in Central Europe, but also in the days preceding and following their occurrence. The study uses data from 1966 to 2015 from the Institute of Meteorology and Water Management – National Research Institute, Deutscher Wetterdienst and the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR). A heat wave was defined as a sequence of at least 3 days with a maximum daily air temperature of 〉30°C. The study showed an increase in the number of hot days, which was statistically significant in the majority of the area. In the analysed years, an increasing number of heat waves was recorded, and this occurrence was associated with high pressure systems. Anticyclonic blocking in the summer inhibits the zonal flow of air masses and intensifies meridional flow, which in Central Europe in the summer means the presence of polar continental and tropical air masses. During heat waves, there were positive anomalies of isobaric surface heights over the study area with a maximum in the upper troposphere. On average, anomalies at the 300 hPa pressure level began to form over the Atlantic Ocean. Determining atmospheric preconditions of persisting blocking events in summer resulting in heat waves may be helpful in predicting thereof. This article is protected by copyright. All rights reserved.

Description: The extreme precipitation regimes have been changing as the climate system has warmed. Investigating the nonstationarity and better estimating the changes of the extreme precipitation are valuable for informing policy decisions. In this study, two precipitation indices are employed to describe the extreme events, including maximum 5‐day precipitation amount (RX5day) and the number of very heavy precipitation days (R20). The generalized additive models for location, scale and shape (GAMLSS) is emplyed to characterize nonstationarities in extreme precipitation events and related climate indices in 13 stations in the Hanjiang River basin (HJRB). Three models including stationary model without change (M0), nonstationary models over time (M1) and nonstationarity models with large‐scale climate indices (M2) as predictors, respectively, are considered to analyze occurrence rates of extreme precipitation. The optimal model and the significant predictors were selected by the Akaike information criterion (AIC). To investigate the main predictors at reginal scale, the homogeneous sub‐regions for precipitation extremes are identifed by clustering analysis. Results indicate that: (1) the nonstationarities of RX5day series and R20 series at all stations are identified in the HJRB; (2) extreme precipitation behavior is significantly influenced by climate indices and nonstationary model 2 to describe the the changes of extreme precipitation is better than nonstationary model 1, indicating the impact of large‐scale climate forcing on the changes of extreme precipitation regimes; (3) the HJRB can be categorized into three homogenous regions. The optimal distributions and the main predictors of extreme precipitation events in most stations of each sub‐region are basically the same; (4) the dominated climate indices influencing the extreme precipitation events are different in different regions and have regional patterns. The results highlight the modeling of extreme precipitation events under nonstationarity conditions and provide information for developing strategies of mitigation and adaptation to climate change impacts on extreme precipitation. This article is protected by copyright. All rights reserved.

Description: Choosing downscaling techniques is crucial in obtaining accurate and reliable climate change predictions, allowing for detailed impact assessments of climate change at regional and local scales. Traditional statistical methods are likely inefficient in downscaling precipitation data from multiple sources or complex data patterns, so using deep learning, a form of non‐linear models, could be a promising solution. In this study, we proposed to use deep learning models, the so‐called Long Short‐Term Memory (LSTM) and Feedforward Neural Network (FNN) methods, for precipitation downscaling for the Vietnamese Mekong Delta. Model performances were assessed with the 2036 – 2065 period, using original climate projections from five climate models under the Coupled Model Intercomparison Project Phase 5 (CMIP5), for two Representative Concentration Pathways scenarios (RCPs 4.5 and 8.5). The results exhibited that there were good correlations between the modeled and observed values of the testing and validating periods at two long‐term meteorological stations (Can Tho and Chau Doc). We then analyzed extreme indices of precipitation, including the annual maximum wet day frequency (Prcp), 95th percentile of precipitation (P95p), maximum 5‐day consecutive rain (R5d), total number of wet days (Ptot), wet day precipitation (SDII) and annual maximum dry day frequency (Pcdd) to evaluate changes in extreme precipitation events. All the five models under the two scenarios predicted that precipitation would increase in the wet season (June – October) and decrease in the dry season (November – May) in the future compared to the present‐day scenario. On average, the means of multi‐annual wet season precipitation would increase by 20.4% and 25.4% at Can Tho and Chau Doc, respectively, but in the dry season, these values were projected to decrease by 10% and 5.3%. All the climate extreme indices would increase in the period of 2036 – 2065 in comparison to the baseline. Overall, the developed downscaling models can successfully reproduce historical rainfall patterns and downscale projected precipitation data. This article is protected by copyright. All rights reserved.

Description: High winds and storm surges associated with torrential rain from tropical cyclones (TCs) cause massive destruction to property and cost the lives of many people. The coastline of the Bay of Bengal (BoB) ranks as one of the most susceptible to storm surges in the world due to low‐lying elevation and a high frequency of TC occurrence. This study uses data from 1885 to 2011 and a bivariate statistical copula to describe the relationship and dependency between empirical TC storm surge and reported wind speed before landfall at the BoB. Among the copulas and their families, an Archimedean, Gumbel copula with margins defined by the empirical distributions is specified as the most appropriate choice for the BoB. The model provides return periods for pairs of TC storm surge and 12‐hour pre‐landfall wind along the BoB coastline. On the shortest time scale, the BoB can expect a TC with 12‐hour pre‐landfall winds of at least 24 m s−1 and surge heights of at least 4.0 m, on average, once every 3.9 years. On the other hand, the long‐term, worst case scenario suggests the BoB can expect 12‐hour pre‐landfall winds of 62 m s−1 and surge heights of at least 8.0 m, on average, once every 311.8 years. Using a copula to model the combined frequency of cyclone wind speeds along with storm surges along the BoB coastline increases the understanding of the dangerous TC characteristics in this region, which can reduce fatalities and monetary losses. This article is protected by copyright. All rights reserved.

Description: The spring Sudan low and its Red Sea Trough (RST) were detected objectively using sea level pressure (SLP) data obtained from an NCEP/NCAR reanalysis dataset spanning the period from 1955 to 2014. The climatology of the detected lows suggested that the Sudan low was active for approximately 69.5% of the spring and that approximately 56.2% of this time the Sudan low developed into the RST. Furthermore, three main genesis regions of the RST, which generated 95.25% of the RST, were identified over Sudan, South Sudan and the Red Sea, approximately 61.76% of which was over South Sudan. Additionally, three main outermost areas of the RST, which received 94.1% of the RST, were specified to the west, east and north of the Red Sea, approximately 54.88% of which was in the eastern region. Synoptically, the orientations of the detected RST around the Red Sea are strongly influenced by the Siberian and Azores high systems. The RST is directed along the western side of the Red Sea if the Siberian high extends westward and the Azores high shrinks westward, whereas the RST is oriented to the east if the Siberian high shrinks eastward and the Azores high extends eastward. The RST extends directly northward if the Siberian and Azores high systems withdraw eastward and westward, respectively. These results also demonstrate that the core position and strength of the upper maximum winds play an important role in the generation of RST. The selected case studies have confirmed the synoptic climate results and indicate that the Sudan low will not develop into RST when the northern region has been affected by a high‐pressure system and the core of the upper maximum wind is located over the northern Arabian Peninsula. This article is protected by copyright. All rights reserved.

Description: The amplitude of El Niño, measured by the Nino3.4 SST anomaly index, has exhibited an interdecadal change with a weakening trend since the late 1990s, characterized by the distinct Bjerknes stability index between 1980–1998 and 1999–2014. Statistical results suggest that this was primarily induced by the attenuation of the zonal wind stress and low‐level wind anomalies in response to the zonal equatorial sea surface temperature anomalies (SSTA) gradient. The weakened atmospheric responses to the zonal equatorial SSTA gradient were associated with the obvious westward extension of the negative sea level pressure anomalies (SLPA) over the tropics. This was mainly attributed to the transition of the dominant atmospheric circulation over the North Pacific, where the Aleutian Low (AL) mode was replaced by the North Pacific Oscillation (NPO) mode after the late 1990s. Numerical experiments from the long‐term historical simulations of the GFDL‐CM3 model indicate that both of the AL and NPO were dominant over the North Pacific and alternated on the interdecadal time‐scale. When the NPO mode was dominant, it became more effective at playing a role in triggering an El Niño in the central Pacific via the seasonal footprinting mechanism over the subtropical northeastern Pacific. Such a change might cause the westward shift of the tropical SLPA and the attenuated atmospheric responses to the zonal SSTA gradient, ultimately resulting in the weakening of the El Niño amplitude.

Description: In this study, the variation and trend of specific humidity (SH) of the troposphere (1000 to 500 hPa) over Iran was analyzed using the monthly European Center for Medium range Weather Forecasting (ECMWF) Re‐Analysis Interim (ERA‐Interim) gridded data from January 1979 to December 2016. By using nonparametric modified Mann‐Kendall test, the trend of values for each gridded point was tested in eight different atmospheric levels at 95% confidence level. The Sen’s slope estimator test was used to estimate the change rate. The findings showed that the annual trend of SH is decreasing in most of Iran and is only increasing on the northern and southern coast of the country. The highest increasing trend of the SH is observed on the southern coast of Iran in 1000 hPa. The regression line fitting on the standardized time series of Iran’s area average SH showed that the highest decreasing rate occurred in the first layer (1000 – 850 hPa) and only the third layer (600 – 500 hPa) has had a significant increase of SH trend over Iran. Area average annual anomaly of the tropospheric cross sections indicates that the studied period is divided into two periods: a wet period (1979 – 1998) and a dry period (1999 – 2016). This article is protected by copyright. All rights reserved.

Description: Arctic glaciers have been, and are predicted to remain, an important sea‐level rise contributor over the 20th and 21st centuries. However, multi‐annual observations of their basic meteorological characteristics, which drive melt processes, are very sparse, contributing to uncertainties in sea‐level rise projections. This paper presents a methodology to process and analyse six years (September 2011–September 2017) of glacier meteorology data collected by an automatic weather station on the ablation zone of a small valley glacier in Svalbard (~79°N). The study focuses on the microclimate of the study glacier and its differences with that of large glaciers in the region, namely slightly increased summer air temperature with steep near‐surface lapse rates, frequently superadiabatic, reduced wind speed and incoming shortwave radiation flux. These differences are likely related to the adjacent complex relief and non‐ice‐covered surfaces within the basin of the study glacier and, as such, pose a challenge for accurate simulation of alpine glacier microclimates in regional melt assessments in the Arctic. The processing routine applied in this paper might serve as a reference for future similar studies. This article is protected by copyright. All rights reserved.

Description: Rainfall in Bangladesh exhibits persistent wet and dry anomalies associated with occurrences of floods and droughts. Assessing inter‐annual variability of rainfall is vital to account these hydrological extremes in the design and operations of water systems. However, the inter‐annual variability obtained from short record rainfall data might be misleading as it does not contain whole climate variability which signifies the utmost importance of stochastic rainfall models. Since the inter‐annual variability and stochastic models have not been explored adequately for rainfall in Bangladesh, this study evaluated (i) the spatio‐temporal variability of rainfall focusing on inter‐annual variability, and (ii) applicability of a stochastic daily rainfall model, referred as the Decadal and Hierarchical Markov Chain (DHMC) model. Daily rainfall data of 1973‐2012 for 18 stations across Bangladesh were used to investigate the probability distributions and autocorrelations of rainfall, and the model performances. Results show a higher magnitude of inter‐annual variabilities of rainfall depth (standard deviation 80‐250 mm) and wet spells (standard deviation 4‐6 days) in wetter months (June to September) across rainfall stations in the east region of the country. In contrast, higher rates of inter‐annual variabilities (i.e. coefficients of variations) were observed in drier months across the west region. Spatially, the dry spells were observed consistent across the country. Monthly rainfall showed decreasing trend over the region from west to the middle part of the country, whereas monthly number of wet days showed increasing trend over the eastern part. The DHMC was found to preserve the observed variabilities of rainfall at daily to multiyear resolutions at all stations, except a tendency to underestimate the autocorrelation of monthly rainfall depth. Despite this limitation, DHMC can be considered as a suitable stochastic rainfall simulator for a tropical monsoon climate like Bangladesh.

Description: In this study, the performances of 31 global climate models (GCMs) from Phase 5 of the Couple Model Inter‐comparison Project (CMIP5) were evaluated using observed temperature and precipitation datasets for mainland Southeast Asia (MSA). In addition, the technique for order preference by similarity to ideal solution model (TOPSIS), which is an effective multi‐objective decision method and has been widely applied in systems engineering, was used to comprehensively evaluate the GCMs on a regional scale. The meteorological variables employed included monthly mean, maximum, and minimum temperature series and annual/seasonal precipitation during the period 1961–2004. Results showed the overall Ci values ranged from 0.56 to 0.80. Overall, ACCESS1.0, HadGEM2‐A, HadGEM2‐CC, and CESM1 (BGC) performed better than the other models with respect to air temperature and precipitation over MSA. For meteorological variables, The Ci of extreme temperature by GCMs was 0.65 and higher than mean temperature at 0.61. The performance of GCMs in simulating precipitation during wet season was superior to that for annual and dry season precipitation. With respect to evaluation indicators, most of the GCMs assessed in this study failed to capture observed mean annual air temperature and annual precipitation (they underestimated annual air temperature and overestimated mean annual precipitation). When evaluating the performance of the GCMs with respect to reproducing individual climatic variables, the use of various statistical evaluation criteria provided inconsistent results. These results demonstrate the need to consider the influence of different statistical eigenvalues and to employ multiple indicators when possible to enable a comprehensive evaluation of GCMs. The results of this study provide useful information for climate change, water resource, and agricultural management research in MSA.

Description: During the latter part of the 20th century and into the 21st century, research has focused on evaluating how to more effectively utilize upper‐air soundings and satellite analysis of atmospheric water vapor transport pathways typically referred to as “atmospheric rivers” (ARs) in order to better forecast heavy rainfall events. Rainfall associated with ARs may include a significant portion of monthly and seasonal rainfall when they occur within the North Central Mississippi Valley Region. A comprehensive analysis of surface and upper air maps and upper‐air soundings and the associated vertical wind profiles is conducted to help build a relationship between the intensity and duration of heavy rainfall events during the period 2000‐2015. The goal is to develop a proxy by which rainfall events can be predicted more accurately and work towards developing improved operational forecast protocols. In addition, a secondary goal is to evaluate possible connections between AR dynamics as highlighted using Hybrid Single‐Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectories, and the intensity as well as duration of heavy rainfall events. We find that while the synoptic‐scale pattern that produces ARs is similar to other AR studies, there are some differences in the synoptic‐scale environments consistent with the study of interannual variability in this region. Also, while much of the moisture ingested by ARs comes from the Gulf and Caribbean, if moisture comes from the Atlantic region there is a potential for larger rainfall events. Finally, an analysis of upper air soundings shows some key differences between warm and cold season ARs, and possibly interannual variations as well. This article is protected by copyright. All rights reserved.

Description: Accurate terrestrial evapotranspiration (ET) estimation and understanding the causes of ET variation are essential for water resource management and irrigation planning. In this research, the complementary relationship (CR) between actual evapotranspiration (ETa) and potential evapotranspiration (ETp) was evaluated. An Advection‐Aridity (AA) model was calibrated and validated using eddy covariance measurements. The spatiotemporal variations of ETa, ETp and associated meteorological variables were examined through Mann‐Kendall (MK) testing and Theil‐Sen's estimator, using daily weather data from 137 meteorological stations in Huai River Basin (HRB) during 1961‐2014. Moreover, the influences of meteorological factors on ETa and ETp were quantified by the differential equation method. The results indicate that CR theory is applicable in the HRB and the calibrated AA model can simulate the ETa well. ETa exhibited a significant increasing trend before 1990 and then decreased significantly. However, ETp decreased significantly before 1990 and then declined slightly. During 1961‐1990, except for significant increasing relative humidity (RH), other meteorological variables exhibited decreasing trends. The aerodynamic component dominated ETa and ETp trends in general. The wind speed at 2‐metre height (u2) dominated ETa trends except for summer and growing season and ETp trends except for summer, when the dominant factor is net radiation (Rn). During 1991‐2014, mean temperature (Ta) and RH showed distinct increasing and decreasing trends, respectively, whereas significant decline in u2 palpably slowed. The absolute value of the radiative component was larger than that of the aerodynamic one. The dominant factor of ETa trends shifted from u2 to RH in spring and to Rn in autumn, winter and annual time scales. Moreover, the dominant factor of ETp trends changed from u2 to RH in spring, winter and annual time scales and to Rn in growing season and autumn. Rn always played a pivotal role in both ETa and ETp trends in summer. This article is protected by copyright. All rights reserved.

Description: Abstract Globally, few precipitation records extend to the 18th Century. The England Wales Precipitation (EWP) series is a notable exception with continuous monthly records from 1766. EWP has found widespread use across diverse fields of research including trend detection, evaluation of climate model simulations, as a proxy for mid‐latitude atmospheric circulation, a predictor in long‐term European gridded precipitation datasets, the assessment of drought and extremes, tree‐ring reconstructions and as a benchmark for other regional series. A key finding from EWP has been the multi‐centennial trends towards wetter winters and drier summers. We statistically reconstruct seasonal EWP using independent, quality‐assured temperature, pressure and circulation indices. Using a sleet and snow series for the UK derived by Profs. Gordon Manley and Elizabeth Shaw to examine winter reconstructions, we show that precipitation totals for pre‐1870 winters are likely biased low due to gauge under‐catch of snowfall and a higher incidence of snowfall during this period. When these factors are accounted for in our reconstructions, the observed trend to wetter winters in EWP is no longer evident. For summer, we find that pre‐1820 precipitation totals are too high, likely due to decreasing network density and less certain data at key stations. A significant trend to drier summers is not robustly present in our reconstructions of the EWP series. While our findings are more certain for winter than summer, we highlight i) that extreme caution should be exercised when using EWP to make inferences about multi‐centennial trends, and; ii) that assessments of 18th and 19th Century winter precipitation should be aware of potential snow biases in early records. Our findings underline the importance of continual re‐appraisal of established long‐term climate datasets as new evidence becomes available. It is also likely that the identified biases in winter EWP have distorted many other long‐term European precipitation series. This article is protected by copyright. All rights reserved.

Description: Abstract Reference evapotranspiration (ET0), which is an indicator of atmospheric evaporation demand over a hypothetical reference surface, is expected to alter along with global climate change. In this study, the changes and driving forces of historical ET0 and its future projections in Xinjiang, China, were comprehensively conducted. The trend analysis revealed that regional ET0 decreased significantly at a rate of ‐4.1 mm yr‐2 during 1961‐1993 and increased at a rate of 3.4 mm yr‐2 during 1994‐2010. To explore the possible causes, the contributions of major climatic variables to the ET0 trends were derived based on the differential equation method. During 1961‐1993, the decreasing trend of ET0 was primarily ascribed to the wind speed. The integrated negative effect from the decrease in wind speed (U) and increase in relative humidity (RH) was more significant than the positive effect from the increase in air temperature (T), resulting in the decrease in ET0. During 1994‐2010, combined with increasing T and decreasing RH, the increase in U offset the effect of the net radiation (NR) decrease and led to an increase in ET0. Future ET0 projections over three periods (2010‐2039, 2040‐2069, and 2070‐2099, which are named as 2020s, 2050s, and 2080s, respectively) were conducted based on the general circulation models under two representative concentration pathways scenarios (RCP4.5 and RCP8.5). A continuous increasing trend in ET0 was demonstrated in the 21st century. The increase in ET0 will increase the irrigated water resource consumption and bring new challenge to water resource management in this area. This article is protected by copyright. All rights reserved.

Description: Abstract This study presents a comprehensive and quantitative evaluation on the mean state of summer atmospheric circulation over East Asia. Attention is paid to the South Asian high (SAH), western North Pacific subtropical high (WNPSH) and Indian low (IL) at upper, middle and lower troposphere, respectively. 31 state‐of‐the‐art climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used as example for the analysis. Most models can basically simulate the three closed‐circulation systems (CCSs), although there is a certain inter‐model spread and an underestimation of their intensity. In terms of geographic location, models have the best performance for SAH and the poorest performance for WNPSH. The latter shows generally a south‐westward shift compared to NCEP reanalysis. Five atmospheric fields (zonal and meridional wind at 850hPa, geopotential height at 500 and 100hPa, and sea level pressure) are inspected and generally well reproduced in models, with Taylor‐S indices all larger than 0.84 for 90% of the models. The best performance is for 500hPa geopotential height with an average Taylor‐S index of 0.98. Models skill in simulating the sea level pressure is the lowest. It shows however a significant positive correlation with models’ resolution. Almost all models underestimate 100hPa geopotential height over East Asia, mainly due to the common cold bias in the troposphere. As a whole, CCSM4, CNRM‐CM5, CESM1‐CAM5 and NorESM1‐M are identified as high‐skill models for simulating the East Asian atmospheric circulation. High‐skill models show a better simulation of precipitations in East China as well, with 21.3% decrease of dry biases in Southeast China. It is also shown that the physical explanation for this linkage resides in the center position of the western North Pacific subtropical high which determines the quality of 850hPa winds and water vapor transport in Southeast China.

Description: ABSTRACT Snowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt, and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981‐2010, and two Coupled Model Intercomparison Project phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981‐2100. The analysis is presented in 30‐year periods (i.e., 1981‐2010, 2011‐2040, 2041‐2070, and 2071‐2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0‐1000 m) show decreases of 41.3% and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1000‐2000 m), the reductions are smaller at 13.5%, and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and UtqiaĠvik (Barrow) show no significant trend. This article is protected by copyright. All rights reserved.

Description: Abstract This study presents the first global‐scale comprehensive climatology of marine fog and is based on ICOADS ship present weather observations for the period 1950‐2007. In general, the median marine fog occurrence away from the polar oceans is low (0.2%). Substantially greater marine fog occurrences are limited to four regions, not including the polar region. Fog occurrence maxima along the western side of the subpolar ocean gyre occur during the warm season and over the shelf, which includes one centered over the Northwest Pacific Kuril Islands (60%) and one over the Northwest Atlantic Grand Banks (45%), while a third lies over the Argentinean shelf break. Fog maxima over seven marginal seas occur over the Okhotsk Sea, Sea of Japan, Yellow Sea, South China Sea, Nova Scotia, North Sea, and Baltic Sea. Five wind‐driven coastal upwelling zone maxima comprise the California – Oregon, Namibia‐South Africa, Peru, Morocco and Arabian regions. Maximum upwelling fog occurrence during the warm season was found to be inversely proportional to the minimum sea surface temperature (SST). Most fog maximum occurrence locations lie over SST minima in shallow water during the warm season and are capped by a stable lower atmosphere. Positive correlations (up to 0.79) were found between 5‐year moving averages of fog in the Kuril Islands and the North Pacific Oscillation. Five‐year moving averages of fog in the Grand Banks were positively and significantly correlated (up to 0.56), with the North Atlantic Oscillation represented by the sea level pressure difference between Gibraltar and Reykjavik. In contrast, 5‐year moving averages of fog in the Grand Banks and the Atlantic Multidecadal Oscillation index were negatively and significantly correlated (up to ‐0.75). This article is protected by copyright. All rights reserved.

Description: Abstract Seasonal prediction of extreme precipitation has long been a challenge especially for the East Asian Summer Monsoon region, where extreme rains are often disastrous for the human society and economy. This paper introduces a decision‐tree (DT) method for predicting extreme precipitation in the rainy season over South China in April‐June (SC‐AMJ) and the North China Plain in July‐August (NCP‐JA). A number of preceding climate indices are adopted as predictors. In both cases, the DT models involving ENSO and NAO indices exhibit the best performance with significant skills among those with other combinations of predictors and are superior to their linear counterpart, the binary logistic regression model. The physical mechanisms for the DT results are demonstrated by composite analyses of the same DT path samples. For SC‐AMJ, an extreme season can be determined mainly via two paths: the first follows a persistent negative NAO phase in February‐March; the second goes with decaying El Niño. For NCP‐JA, an extreme season can also be traced via two paths: the first is featured by ‘non El Niño’ and an extremely negative NAO phase in the preceding winter; the second follows a shift from El Niño in the preceding winter to La Niña in the early summer. Most of the mechanisms underlying the decision rules have been documented in previous studies, while some need further studies. The present results suggest that the decision‐tree approach takes advantage of discovering and incorporating various nonlinear relationships in the climate system, hence is of great potential for improving the prediction of seasonal extreme precipitation for given regions with increasing sample observations. This article is protected by copyright. All rights reserved.

Description: The intraseasonal variation of precipitation over Iran is examined in terms of the combined effects of the Madden‐Julian Oscillation (MJO), Indian Ocean Dipole (IOD) and El Niño‐ Southern Oscillation (ENSO), using daily observations during the wet season (October to May) from 1961 to 2015. We have examined how the probability of daily rainfall above the upper tercile varies across MJO phases during positive and negative IOD and ENSO states. The results indicate that the response of Iran’s wet season rainfall to the MJO is affected more by large‐scale atmospheric variations associated with the IOD than by ENSO. The negative (positive) IOD strengthens (suppresses) the MJO‐rainfall relationship in the wet and dry MJO phases. The variation in the atmospheric variables (relative humidity and vertical velocity) indicates more (less) humidity and upward (downward) motion which increases (decreases) precipitation in wet (dry) MJO phases during the negative IOD. The rainfall relationship with the MJO during the negative IOD is statistically significant, while the relationship during the positive IOD is weak; and no significant relationship is found during either phase of ENSO.

Description: The Goddard Earth Observing System version 5 (GEOS‐5) global climate model with a 50‐km horizontal resolution is forced by observed sea surface temperature (SST) to examine the fidelity of the seasonal‐mean and interannual variation of tropical cyclones (TCs) in the western North Pacific (WNP) and the North Atlantic (NATL). The standard Relaxed Arakawa Schubert (RAS) deep convection scheme is modified to improve the representation of TCs, where the scheme implements a stochastic limit of the cumulus entrainment rate. The modification drives mid‐ and upper‐tropospheric cooling and low‐ to mid‐tropospheric drying in the background state, which tends to increase atmospheric instability. This enables the model to increase convective variability on an intraseasonal timescale and improve the simulation of intense storms. Five‐member ensemble runs with the modified RAS scheme for 12 years (1998–2009) exhibit realistic spatial distributions in the climatological‐mean TC development area and their pathways over WNP and NATL. The GCM is able to reproduce the interannual variation of accumulated cyclone energy (ACE) by prescribing yearly varying observed SST even though the individual TC intensity is still underpredicted. A sensitivity of TC activity to El Niño‐Southern Oscillation (ENSO) phase is also reproduced realistically over WNP in terms of the spatial pattern changes in the main development region and TC pathways. However, the model exhibits a notable deficiency in NATL in reproducing the observed interannual variation of TC activity and the sensitivity to the ENSO.

Description: Based on the 30‐year (1988‐2017) radiosonde observations, the climatological characteristics of the planetary boundary layer height (PBLH) over Japan, as well as the long‐term changes, are investigated. We firstly compared 4 different methods to determine the PBLH. Results show that the bulk Richardson number (BRN) method has the best performance among all these methods. At all studied stations, monthly median PBLHs in the morning are generally higher than the ones in the evening. Bimodal structure of seasonal PBLHs are found over Japan. Daytime PBLH peaks in spring and autumn and achieves the minimum in summer and winter. Nighttime PBLH shows less seasonal variations. It is found that the PBLHs in the central and southern part of Japan could be dominant by the variations of surface temperature, while the variations of surface RH may be responsible for the PBLHs in the northern part of Japan. Moreover, sea fog which is associated with high RH and temperature inversion also has an obvious influence on PBLHs in northern Japan. Trend study shows that PBLHs in most stations slightly increased during the past 30 years.

Description: ABSTRACT Tree‐ring density has been suggested to be a useful proxy for revealing long‐term late summer or growing season temperature variability on the Tibetan Plateau (TP). However, the current chronology length of tree‐ring density records on the TP is obviously shorter than both tree‐ring width and tree‐ring isotope records. This phenomenon implies the possibility of extending the current tree‐ring density record into earlier times and provides us with an opportunity to evaluate recent warming on a longer time scale. In this study, we present a 640‐year tree‐ring maximum latewood density (MXD) chronology of Balfour spruce back to 1375 CE in the eastern TP. This tree‐ring MXD chronology is longer than the previous ones on the TP. Growth‐climate relationship analysis shows that the established MXD chronology correlates significantly and positively with August‐September mean temperatures recorded at the nearest meteorological station over the common period of 1954‐2014 (r= 0.66, effective degree of freedom (edf)= 62.7, P〈 0.0001). Based on the growth‐climate response relationship, the August‐September mean temperature was reconstructed from 1625‐2014, which is the reliable period of the MXD chronology, with the expressed population signal (EPS) greater than 0.85. The reconstructed August‐September temperatures show an increasing trend since the late 19th century, and this reconstruction suggests that the last 10‐, 30‐, 50‐ and 100‐year periods all appear to be the warmest over the past 390 years. Together with preciously published temperature reconstructions based on tree‐ring MXD near our study area, the results of this study demonstrate that the southeastern TP has experienced post‐industrial warming since the late 19th century. This article is protected by copyright. All rights reserved.

Description: Abstract The olive tree is one of the most important crops in the Mediterranean basin. Given the strong climatic influence on olive trees, it becomes imperative to assess climate change impacts on this crop. Herein, these impacts were innovatively assessed, based on an ensemble of state‐of‐the‐art climate models, future scenarios and dynamic crop models. The recent‐past (1989–2005) and future (2041–2070, RCP4.5 and RCP8.5) olive growing season length (GSL), yield, growing season temperature (GST) and precipitation (GSP), potential (ETP) and actual (ETA) evapotranspiration, water demand (WD) and water productivity (WP), were assessed over southern Europe. Crop models were fed with an ensemble of EURO‐CORDEX regional climate model data, along with soil and terrain data. For the recent‐past, important differences between western and eastern olive growing areas are found. GSL presents a strong latitudinal gradient, with higher/lower values at lower/higher latitudes. Yields are lower in inner south Iberia and higher in Italy and Greece, which is corroborated by historical data. Southern Iberia shows higher GST and lower GSP, which contributes to a higher ETP, lower ETA and consequently stronger WD. Regarding WP, the recent‐past values shows similar ranges across Europe. Future projections point to a general increase in GSL along with an increase in GST up to 3°C. GSP is projected to decrease in Western Europe, leading to enhanced WD and consequently a yield decrease (down to ‐45%). Over eastern European, GSP is projected to slightly increase, leading to lower WD and to a small yield increase (up to +15%). WP will remain mostly unchanged. We conclude that climate change may negatively impact the viability of olive orchards in southern Iberia and some parts of Italy. Thus, adequate and timely planning of suitable adaptation measures are needed to ensure the sustainability of the olive sector. This article is protected by copyright. All rights reserved.

Description: Abstract We investigated the spatiotemporal features of the air mass and its transport during the lifetime of the four main blocking highs (the Greenland, Atlantic–Europe, Ural and North Pacific blocking highs) observed in the northern winter using the daily European Centre for Medium‐Range Weather Forecasts Re‐Analysis Interim dataset for the time period 1979–2016. The results showed that the positive mass anomalies corresponding to a blocking high only appear in the mid‐troposphere, while negative mass anomalies persist in the lower layer during blocking events. Budget analysis based on the mass continuity equation under isentropic coordinates indicated that adiabatic mass transport is the main contributor to the build‐up of blocking highs and is always convergent in the mid‐troposphere before the peak day of blocking. By contrast, diabatic mass transport always moves the air mass from the mid‐ to lower troposphere and acts to destroy the blocking high. The meridional flow makes the strongest contribution to mass convergence in the Greenland and North Pacific blocking highs in the mid‐troposphere, whereas zonal flow is the main contributor to mass convergence in the Atlantic–Europe blocking high. Both zonal and meridional flows contribute to mass convergence in the Ural blocking high, although meridional flow makes a greater contribution. This article is protected by copyright. All rights reserved.

Description: Abstract This study examines the spatial and temporal characteristics of high‐wind events (HWEs) based on the National Weather Service (NWS) high‐wind criteria for 391 first‐order weather stations in the eastern U.S. from 1973 to 2015. A geographical analysis on the frequency of sustained and gust HWEs shows that the highest occurrences were reported in the Great Plains and Great Lakes, while the lowest number of observations occurred in the Mid‐South and Southeast. Linear trends show that the yearly frequency of sustained and gust HWEs are significantly decreasing (‐0.579 days yr‐1) and increasing (0.943 days yr‐1) respectively during the 43‐year study period. These trends do not persist when the HWE data is normalized (long‐term mean is removed from the yearly count), but shows a cyclical anomaly pattern for both sustained and gust winds. Overall, 90% and 82% of all sustained and gust HWEs occur from the northwest or southwest quadrant, but when interpreted from a spatial perspective the mean wind direction of HWEs can be classified into specific regional wind groupings. However, this persistent southwesterly wind direction has gradually shifted to a more southerly (northerly) orientation for sustained (gust) HWEs over the study period. This article is protected by copyright. All rights reserved.

Description: Abstract This study reveals a significant effect of the winter sea surface temperature (SST) anomaly (SSTA) in the tropical eastern Pacific (TEP) on the following summer tropical cyclone precipitation (TCP) in mainland China. During the period 1979‐2015, the positive winter TEP SSTA forces a SST zonal tripole pattern anomaly, which is positive SSTA in the tropical Indian Ocean (TIO), negative SSTA in the tropical western Pacific (TWP), and positive SSTA in the TEP. This SSTA pattern triggers two simultaneous zonal circulation anomalies. One exhibits lower‐level convergent winds, mid‐tropospheric ascendant flows and upper‐level divergent winds over the western TIO, and reversed situations over the TWP, producing anomalous lower‐level easterlies and upper‐level westerlies between the TIO and TWP. The other shows lower‐level convergence, mid‐tropospheric ascent, upper‐level divergence over the TEP, and reversed situations over the TWP, which create lower‐level westerlies and upper‐level easterlies between the TWP and TEP. The two circulation anomalies further warm the TEP (western TIO) by driving ambient warm water toward this region and cool the TWP by inducing local upwelling, which facilitate the persistence of the anomalies until the summer. Consequently, the lower‐level negative vorticity, strong vertical wind shear and the lower‐level anticyclone anomalies over most of the western North Pacific (WNP) are accompanied with anomalous mid‐tropospheric westerlies over the coastal regions in mainland China, suppressing TC genesis and movement toward mainland China so as to decrease the summer TCP in mainland China. These results provide an important implication that the winter TEP SSTA is a potential indicator for seasonal prediction of the WNP TC activity and the TCP in mainland China. This article is protected by copyright. All rights reserved.

Description: Abstract The impact of North American (NA) snow cover on the Northern Hemisphere climate has drawn increasing attention in recent years. This study reveals a negative relationship between NA snow cover in December and surface air temperature (SAT) over the midlatitude Asia in the following January. The results show that, in December, the extensive snow cover decreases SAT over NA via local diabatic cooling, which further intensifies the Atlantic jet stream by enlarging the meridional gradient of the 1000‐ to 300‐hPa layer thickness especially along 40°N. Meanwhile, we found negative sea surface temperature (SST) anomalies over the western North Atlantic, and enhanced transient eddy activity over the eastern North Atlantic due to anomalous net energy conversion from the mean flow. In January, a zonally‐oriented dipole of transient eddy anomalies straddles the North Atlantic, with the negative−positive (west−east) anomaly centers attributing to local oceanic cooling and the persistence of the eddy−mean flow interaction, respectively. Such dipole of transient eddy activity in turn favors the downstream development of the Atlantic jet stream. Besides, the changes in surface turbulent heat flux over the North Atlantic trigger a Rossby wave train that propagates across Europe and toward the Far East. Coincident with the strengthened Siberian High and the accelerated East Asian jet stream in January, SAT decreases over the midlatitude Asia. Hence our analysis indicates that December NA snow cover could potentially be exploited for sub‐seasonal predictability over Asia. This article is protected by copyright. All rights reserved.

Description: ABSTRACT Observational analyses reveal substantial cooling anomalies in East China, during the global hiatus period (1998–2013), particularly in winter. The factors contributing to the winter cooling anomalies and the underlying mechanisms are studied. The results highlight the substantial roles played by two factors: Arctic sea ice reduction (i.e., sea ice area in Barents‐Kara Seas, SIA) and the SST cooling anomalies in the Kuroshio extension region (KSST). Together, these factors contribute to approximate 90% of the trend anomaly of East China's area averaged surface air temperature (ECT). The individual contributions from SIA and KSST are investigated based on observational diagnostic analyses and sensitivity experiments. The results show that the contributions from the two factors are similar. Both SIA and KSST induce intensified geopotential height over the mid–to–high latitudes of the Eurasian continent, with the maximum over the Ural Mountains extending toward Lake Baikal. These anomalies intensify the Ural blocking activities and Mongolian cold high. Meanwhile, both forcings cause negative 500–hPa geopotential height (Z500) anomalies over the central North Pacific that extend westward to East Asia, intensifying the climatological East Asian grand trough. However, KSST causes positive Z500 anomalies over the Bering Sea, but SIA does not. The enhanced Ural blocking activities and the deepened East Asian grand trough jointly favor the intensification of the East Asian winter monsoon, thus causing cooling anomalies in East China. This article is protected by copyright. All rights reserved.

Description: Abstract Previous studies suggested that sea surface temperature (SST) anomalies in the tropical central‐eastern Pacific (TCEP) and tropical Northern Atlantic (TNA) both have significant impacts on the interannual variation of precipitation over the monsoon transitional zone (MTZ) in China during August‐September. This study further reveals that the relationship between TCEP (TNA) SST and MTZ precipitation during August‐September is strongly modulated by the sign of the TNA (TCEP) SST. When TCEP and TNA SST anomalies have the same‐sign, connections of the TCEP and TNA SST with the MTZ precipitation are unclear. By contrast, TCEP and TNA SST changes both have a significant relation with the MTZ precipitation when they have the opposite‐sign. During the same‐sign years, the anticyclonic (cyclonic) anomaly over the western North Pacific generated by the TCEP SST cooling (warming) is weakened by the cyclonic (anticyclonic) anomaly triggered by the TNA SST cooling (warming). Thus, connections of the MTZ precipitation with the TCEP and TNA SST are weak. However, during the opposite‐sign years, the anticyclonic anomalies over the western North Pacific generated by the TCEP SST anomalies have a constructive superposition on those induced by the TNA SST changes. As such, connections of the TCEP and TNA SST with the MTZ precipitation variation are significant. Further analysis shows that the prediction skill of precipitation over the MTZ is enhanced if taking both the TCEP and TNA SST signals into account. This article is protected by copyright. All rights reserved.

Description: Abstract This study explored the interannual relationship between autumn Arctic sea ice concentration (SIC) and the subsequent summer precipitation over East Asia (EASP). Since the late‐1990s, the declining SIC in the Kara‐Laptev Seas has been significantly correlated with EASP as well as extremely positive anomalies in northern China and intensely negative anomalies in central‐eastern East Asia. However, there was a weak correlation between autumn SIC and EASP before the late‐1990s. Furthermore, the anomalous precipitation pattern in summer and its connection with autumn SIC variability can be explained by the seasonal persistence of continental processes (snow depth and soil moisture) into the spring. In particular, a decreasing SIC was connected with simultaneously positive and negative precipitation anomalies over northeastern China and the Siberian region, respectively, since the late‐1990s and tends to produce corresponding soil moisture anomalies over the Eurasian continent. Declining SIC also favors increased snow depth anomalies in winter over northeastern East Asia. These anomalous signals of surface processes can persist from winter into the subsequent spring, making the connection between the autumn SIC and EASP possible. The Community Earth System Model Large Ensemble simulations further verified these physical processes. More detailed mechanism for this relationship needs to be stressed in further work by numerical simulations. The results have important implications for extending the seasonal prediction validity of EASP. Moreover, before the late‐1990s, SIC‐related circulation anomalies shifted westward and northward as negative precipitation anomalies developed over west Siberia in autumn. As a result, anomalous dry soil conditions in Siberia persisted into the subsequent spring and then led to wetter‐than‐normal conditions through locally negative soil moisture‐precipitation feedback before the late‐1990s. This article is protected by copyright. All rights reserved.

Description: The study area encompasses the reservoir watersheds, located West‐Of‐Hudson, to supply drinking water to the New York City. Points denote the rain‐gauge stations used in this study. Abstract Information on the variability of precipitation in time and space is critical for many water resource projects. However, precipitation records at the location of interest are often either limited or unavailable due to an inadequate network of rainfall measurements. To address this need, regionalization methods have been employed to characterize spatial patterns of precipitation and to transfer precipitation information from one location to another where records are scarce. Hence, the overall objective of the present paper is to propose a stochastic weather model for generating daily precipitation at ungauged locations. The proposed approach consists of two components: (a) a regionalization approach for identifying homogeneous groups of observed daily precipitation series, and (b) a stochastic model for constructing daily precipitation events at ungauged locations within homogeneous groups. This statistical approach identifies groups of precipitation stations with similar statistical characteristics based on the combination of two multivariate statistical techniques: principal component analysis (PCA) and ordinal factor analysis (OFA). While the application of PCA in climatological regionalization studies based on precipitation amount is common, the application of OFA to include precipitation occurrence in the identification of regions is unusual. The feasibility of the approach is assessed using daily precipitation data from a network of precipitation stations in the Catskill Mountain region of New York State, United States.

Description: Abstract A characterization of the diurnal cycle of precipitation (DCP) over the whole South America is still lacking in the literature and the scarcity of sub‐daily rain ground measurements limits the data available for analysis and forbids a correct validation of alternative datasets. In this paper we analyze the climatological mean DCP during the monsoon active season using five gridded datasets: two satellite precipitation estimates, two regional climate models and one reanalysis. Amazonia, the Brazilian Highlands, the northeastern South American coast, the Andes and the western Colombian coast are identified as the areas with most prominent DCPs. The afternoon convection triggered by solar heating over land and the coastal and topographic effects are the main modes of sub‐daily variability, based on an EOF decomposition of the 3 hourly mean precipitation fields. We explore the contribution of mean frequency and intensity to amount of precipitation and nighttime‐daytime differences. In general, both models precipitate earlier and more frequently than the satellite products and do not reproduce correctly areas of observed predominant nighttime precipitation where mesoscale convective systems are active, like La Plata Basin or Amazonia. Over the analyzed areas, the high frequency of precipitation is the driving mechanism of total amount in the models, whereas in the satellite products there is also considerable contribution from intensity. Overall, the reanalysis shows features in between the models and the satellite estimates, sharing characteristics with both types of data. The results presented here point at the diversity of sub‐daily precipitation characteristics in South America, the issues with conventional climate models and the uncertainty in satellite products and reanalyses. The growing interest in the DCP by the scientific community and the development of new techniques like convection permitting modeling will hopefully continue improving our knowledge of the precipitation dynamics and its influence on climate. This article is protected by copyright. All rights reserved.

Description: In this paper, we present the variability and trends of landfalling ARs (LARs) along the higher (53.5°N–60.0°N) and lower (47.0°N–53.5°N) latitudes of British Columbia and southeastern Alaska (BCSAK) during the latter half of the twentieth century and early twenty‐first century. Moreover, we present the synoptic evolution and distribution of LARs in BCSAK during different phases of ocean‐atmosphere climate variability. Abstract Atmospheric rivers (ARs), defined as narrow, transient corridors of strong moisture transport in the lower troposphere, are important phenomena for freshwater recharge and water resources, especially along the west coast of North America. This study presents the variability and trends of landfalling ARs (LARs) along the higher (53.5°–60.0°N) and lower (47.0°–53.5°N) latitudes of British Columbia and southeastern Alaska (BCSAK) during the 1948–2016 period. Moreover, we present the synoptic evolution and distribution of LARs in BCSAK during different phases of ocean–atmosphere climate variability using a six‐hourly AR catalogue from the Scripps Institution of Oceanography and reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research. During 1948–2016, BCSAK averages 35 ± 5 LARs annually, with the highest frequency during fall (13 ± 2) and lowest during spring (5 ± 2). The frequency of LARs across BCSAK rises during the study period, and the increase between 1979 and 2016 is statistically significant (p 〈 .05). A strong ridge over the Pacific Northwest and BC and a trough over the Gulf of Alaska and the Northeastern Pacific Ocean favours AR landfalls at the higher and lower latitudes, respectively. BCSAK experiences greater numbers of LARs during neutral phases of El Niño/Southern Oscillation, the 2013/2014 Pacific oceanic blob, and during the positive phases of the Pacific Decadal Oscillation and Pacific North American Pattern.

Description: Abstract Much of our current risk assessment, especially for extreme events and natural disasters, comes from the assumption that the likelihood of future extreme events can be predicted based on the past. However, as global temperatures rise, established climate ranges may no longer be applicable, as historic records for extremes such as heat waves and floods may no longer accurately predict the changing future climate. To assess extremes (present‐day and future) over the contiguous United States, we used NOAA's Climate Extremes Index (CEI), which evaluates extremes in maximum and minimum temperature, extreme one‐day precipitation, days without precipitation, and the Palmer Drought Severity Index (PDSI). The CEI is a spatially sensitive index that uses percentile‐based thresholds rather than absolute values to determine climate “extremeness,” and is thus well‐suited to compare extreme climate across regions. We used regional climate model data from the North American Regional Climate Change Assessment Program (NARCCAP) to compare a late 20th century reference period to a mid‐21st century “business as usual” (SRES A2) greenhouse gas‐forcing scenario. Results show a universal increase in extreme hot temperatures across all models, with annual average maximum and minimum temperatures exceeding 90th percentile thresholds consistently across the continental U.S. Results for precipitation indicators have greater spatial variability from model to model, but indicate an overall movement towards less frequent but more extreme precipitation days in the future. Due to this difference in response between temperature and precipitation, the mid‐21st century CEI is primarily an index of temperature extremes, with 90th percentile temperatures contributing disproportionately to the overall increase in climate extremeness. We also examine the efficacy of the PDSI in this context in comparison to other drought indices. This article is protected by copyright. All rights reserved.

Description: Abstract We developed a new hindcast for storm surge at a 0.25° spatial scale for the whole New Zealand area using a statistical downscaling technique that links the mean local atmospheric conditions with the maximum storm surge levels at a daily scale. After validating the hindcast against sea level instrumental records from 17 tidal gauges around New Zealand, the same technique has been applied to obtain storm surge projections until 2,100 using different global climate models. The global climate models have been previously classified according to their ability to reproduce the past climatology in the studied area and 7 models have been selected in order to explore their effect on storm surge projections. For the 2 representative Concentration Pathways studied, the projections indicate that the storm surge associated with the 50 years return period will increase in magnitude in the southern areas while it will decrease in the northern region. Even where a decreasing linear trend over the annual maxima is observed in the future time series, sporadic events of higher magnitude than the historical peaks can be. This article is protected by copyright. All rights reserved.

Description: Abstract Based on multiple data sets and methods, this study investigates the impacts of intra‐seasonal oscillations (ISOs) on the South China Sea summer monsoon (SCSSM) withdrawal. A daily SCSSM withdrawal date is established, which can capture reasonably the consistent transition of low‐level zonal wind from westerly to easterly over the South China Sea (SCS). The bandpass‐filtered outgoing longwave radiation and low‐level winds are then composited with respect to the monsoon withdrawal date. It is found that a 30–60‐day oscillation originating from the equatorial Indian Ocean and a quasi‐biweekly oscillation (QBWO) propagating from the equatorial western Pacific collectively contribute to the SCSSM withdrawal. Under the background of slow annual cycle (weak zonal wind during late September), the local convectively inactive phases of these ISOs induce anomalous easterly winds, which could trigger monsoon withdrawal over the SCS. The boreal summer ISO indices also confirm that both the 30–60‐day oscillation and the QBWO could modulate SCSSM withdrawal, which is more likely to occur when the suppressed convection caused by these ISOs is either encroaching on or occupying the SCS.

Description: Abstract Understanding the spatial and temporal variations of soil moisture is important since the feedback between soil moisture and precipitation is a key control of the climate. This is also important as soil moisture data is a key input in regional climate models. The inter‐annual and inter‐decadal variability of soil moisture has been investigated here using the European Space Agency's Climate Change Initiative (ESA‐CCI) active and passive combined soil moisture product over different climate regimes of India. The observed soil moisture and rainfall are positively correlated and their relationship in this study suggests that both positive and negative feedback occur. The analysis showed an increasing soil moisture trend with a significant increase in the monsoon and autumn seasons for the past two decades over central India, where the frequency of extreme precipitation increased in the same period. An overall increase in soil moisture over the western arid region is also significant. A decreasing trend in soil moisture prevailed throughout the monsoon season over eastern India, where monsoon depressions make landfall, signaling the recent climate trends over the Indian subcontinent. This article is protected by copyright. All rights reserved.

Description: Abstract The emerging precursor in December Arctic Oscillation (AO) for the following January temperature over East Asia (TEA) has been noticed by recent researches. This study evaluates the precursor in December AO for the following January TEA using 35 climate models from the Coupled Model Intercomparison Project Phase 5. Results indicate that, 24 (MME‐GOOD) out of total 35 models reproduce the statistically significant positive correlation between the December AO and the January TEA identified in the observation, but the remaining 11 models (MME‐BAD) fail. Further, the investigation focuses on these models’ simulations for the December AO‐associated atmospheric circulation in January. Eighteen (MME‐GOOD‐18) out of the above 24 models reproduce the persistence of December AO‐related atmospheric circulation, including the seesaw structure of the sea level pressure anomalies, the sweeping southerly 850‐hPa wind anomalies over the East Asia‐Northwest Pacific region, the weakening of the East Asian trough, and the weakened meridional shear of the East Asian jet stream in January following an enhanced December AO. It is found that the propagation of stationary planetary waves plays a crucial role in connecting the December AO and the January TEA. Therefore, the models’ ability to simulate the stratosphere‐troposphere interaction is essential for the successful simulations on the persistence of December AO. Additionally, the future projections indicate that the precursor in December AO for the following January TEA is still robust during the 21st century. This article is protected by copyright. All rights reserved.

Description: ABSTRACT A large‐scale high air temperature event in China during July 2017 is examined using observational reanalysis data. Based on this case study, summer extreme hot events (EHEs) over China are classified into five types using the self‐organizing map (SOM) method. The five EHE types include those over northeast China (NEC type), northwest China (NWC type), north China (NC type), mid‐eastern China (MEC type) and south China (SC type). All types are associated with sustainable anticyclones (EHE anticyclones). Composite analysis shows that the EHE anticyclone in northern China (corresponding to the NEC, NWC and NC types) is primarily formed by downstream wave train propagation from upstream blocking, while EHE anticyclone formation in southern China (corresponding to the MEC and SC types) is driven by the joint action of downstream wave train propagation and westward movement of the western Pacific subtropical high. Moreover, the upstream blocking and downstream EHE anticyclone embedded in the wave train play important roles in maintaining the wave train. The upstream blocking acts as an energy source for downstream EHE anticyclone intensification and leads to EHE formation, with the intensified zonal wind at certain latitudes affecting the wave train propagation direction. This finding indicates that the upstream blocking with intensified zonal wind at certain latitudes may serve as an indicator for the prediction of EHE anticyclones over China. As a consequence of the persistent EHE anticyclone, the land surface is primarily warmed by enhanced shortwave radiation through reduced regional cloud cover. For the NWC and NC types, heating of the lower atmosphere takes place via the sensible heat flux; whereas, for the NEC, MEC and SC types the main heating terms are the latent heat flux, sensible heat flux and upward longwave radiation. This article is protected by copyright. All rights reserved.

Description: Abstract In this study, 85 tree cores from 45 Schrenk spruces (Picea schrenkiana) were used to establish a regional tree‐ring chronology. A 256‐year pJune–May precipitation (where p denotes a month from the previous year) for northern Kyrgyzstan in Central Asia was reconstructed using this newly developed chronology. The tree‐ring based precipitation reconstruction tracks the observed data well (r=0.622, p〈0.0001, n=105). Spatial correlation proved that the reconstructed precipitation series contains climatic signals representative of a larger area, including eastern Kyrgyzstan and parts of Kazakhstan. A comparison between the newly reconstructed precipitation series and four tree‐ring based precipitation reconstructions for the surrounding areas reveals similar variations, particularly in the high‐frequency domain. Furthermore, this reconstructed precipitation series matches nine flood (1785, 1786, 1792, 1952, 1953, 1970, 1971, 1973, and 2000) and four drought (1917, 1919, 1927, and 1944) events noted in the historical documents, and captures a dry decade that occurred in the 1910s in Central Asia. This article is protected by copyright. All rights reserved.

Description: The locations of the study area and meteorological stations. Abstract The variation in the number of extreme low‐temperature days (NELD) during winter over China is examined. The NELD mainly has a significant decreasing trend across China. The leading NELD empirical orthogonal function (EOF) mode also shows consistent change characteristics over China, and a Mann–Kendall (MK) test of its time coefficients indicates that the NELD abruptly changed in approximately 1980. The impact of sea ice concentrations in the Arctic Ocean on the NELD is investigated. Sea ice concentration declines in the Barents Sea and the sea east of Greenland have significant negative effects on the NELD. Sea surface temperatures in these regions are negatively correlated with the NELD. The study analyses the influence mechanism by researching the composite atmosphere variable anomalies between years with below‐normal NELD and those with above‐normal NELD.

Description: In July–August (JA) 2018, the western Pacific subtropical high (WPSH) was stronger than normal, with its ridge line located the most north in history and above three times of the standard deviation. The convective activities in the western Pacific should play an important role in the extremely north WPSH in JA 2018, including the convection over the western Pacific, the Madden–Julian oscillation, and the tropical cyclone activities. Abstract In July–August (JA) 2018, the western Pacific subtropical high (WPSH) was stronger than normal. Its ridge line was located the most north in history and the position was above three times of the standard deviation. On the intra‐seasonal timescale, the high ridge was mostly more north than normal from July 5 till the end of August in 2018 and had two significant northward jumps in the first 10 days and last 5 days of July 2018, respectively. The convective activities in the western Pacific should play an important role in the extremely north WPSH in JA 2018. The convection over the western Pacific was the strongest in JA 2018 during the past 38 years. It induced significant subsidence anomalies, an anomalous low‐level anticyclone and positive anomalies of 500‐hPa geopotential height in eastern East Asia. On the daily timescale, the northward movement of the active convection over the western Pacific occurred about 5 days earlier than the northward jump of the WPSH. Additionally, the strong and long‐lasting Madden–Julian oscillation in the western Pacific (Phase 6) also favoured the suppressed convection and positive anomalies of 500‐hPa geopotential height in eastern East Asia. This result could provide a good precursor signal about 5 days advance for the northward jump of the WPSH in summer.

Description: Abstract Precipitation is one of the most important atmospheric variables to assess, particularly in the context of climate change. This study evaluates future changes in precipitation over the Iberian Peninsula under the RCP8.5 scenario. Changes are assessed for two future climate periods namely (2046‐2065) and (2081‐2100), relative to a recent reference climate (1986‐2005). Here we introduce the concept of precipitation episodes and estimate their statistical properties for the present climate and, their changes for future climate scenarios. Precipitation episodes are defined by considering a full range of durations as well as intensities. This constitutes a novel approach to estimate changes with relevance for example, for water resources applications. The climate simulations are performed with the WRF model. These are compared to an ensemble of other similar simulations from the CORDEX initiative. This was done to evaluate the performance of the WRF model and also to estimate uncertainty of the derived future projections. Since models may present systematic errors, results from all simulations were previously bias corrected relative to observations using the same quantile mapping method. Under climate change, a great part of the region is expected to experience reduced annual precipitation of approximately 20%‐40% and reaching 80% in summer by the end of the XXI century. For the precipitation episodes, a large reduction in the average number of days and duration of all types of precipitation episodes is expected across all seasons and regions. The average intensity of episodes is projected to increase in winter and spring and decrease in summer. These results imply that climate change will likely influence precipitation and precipitation extremes in the 21st century, mostly in southern areas. These, together with projected warming may amplify desertification already taking place in the southern regions of the Iberian Peninsula and cause stresses to water resources. This article is protected by copyright. All rights reserved.

Description: (a) Histogram of JJA mean MDA8 (red solid), OWI (black hollow), 10‐m meridional wind (red hollow), DT (blue hollow), and boundary layer height (green hollow) from 2015 to 2017. (b) Scatter diagram of MDA8 and daily precipitation. Abstract Surface ozone pollution is the main form of summer air pollution in North China and damages human and ecosystem health. Long‐term meteorological observations show that late spring Arctic sea ice and ozone‐related meteorological conditions are positively correlated; this result was further verified by numerical experiments. The Eurasia teleconnection pattern bridged the sea ice over Gakkel Ridge to the local meteorological conditions associated with O3. The sea ice anomalies over the Canada Basin and the Beaufort Sea mainly influenced the O3 pollution in North China via the summer west Pacific pattern. Furthermore, changes in the relationships were also included. The anticyclonic circulation over North China, that is, the joint centre of the Eurasia teleconnection and west Pacific patterns, could significantly lead to suitable weather conditions to accelerate the photochemical reactions to transfer the precursors to surface ozone. This finding helps to improve the understanding of the interannual variation in ozone pollution in North China.

Description: Abstract Drought events occur worldwide and possibly incur severe consequences. Trying to understand and characterize drought events is of considerable importance inorderto improvethepreparednessforcoping with future events. In this paper, we present a methodology that allows for the delineation of drought events by exploiting their spatiotemporal nature. To that end, we apply operators borrowed from mathematical morphology to represent drought events as connected components in space and time. As an illustration, we identify drought events on the basis of a 35‐year data set of daily soil moisture values covering mainlandAustralia. We then extract characteristics reflecting the affected area, duration and intensity from the proposed representation of a drought event in order to illustrate the impact of tuning parameters in the methodology presented. Yet, this paper we refrain from comparing with other drought delineation methods. This article is protected by copyright. All rights reserved.

Description: Abstract We investigate factors influencing European winter (DJFM) air temperatures for the period 1979‐2015 with the focus on changes during the recent period of rapid Arctic warming (1998‐2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and back‐trajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least four days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large‐scale pattern analysis reveals that cold spells are associated with the negative phase of the North Atlantic Oscillation (NAO‐) and the positive phase of the Scandinavian (SCA+) pattern, which in turn are correlated with the divergence of dry static energy transport. Warm European extremes are associated with opposite phases of these patterns and the convergence of latent heat transport. Airmass trajectory analysis is consistent with these findings, as airmasses associated with extreme cold events typically originate over continents, while warm events tend to occur with prevailing maritime airmasses. Despite Arctic‐wide warming, significant cooling has occurred in northeastern Europe owing to a decrease in adiabatic subsidence heating in airmasses arriving from the southeast, along with increased occurrence of circulation patterns favouring low temperature advection. These dynamic effects dominated over the increased mean temperature of most circulation patterns. Lagged correlation analysis reveals that SCA‐ and NAO+ are typically preceded by cold Arctic anomalies during the previous 2 to 3 months, which may aid seasonal forecasting. This article is protected by copyright. All rights reserved.

Description: Constellation of actors at the downscaling interface, illustrating the transdisciplinary setting, the different sectors actors may recruit from, as well as the main perspective the actors have on the data/information. The application of climate change impact assessment (CCIA) studies in general and especially the linkages between different actor groups typically involved is often not trivial and subject to many limitations and uncertainties. Disciplinary issues like competing downscaling approaches, imperfect climate and impact model data and uncertainty propagation as well as the selection of appropriate data sets are only one part of the story. Interdisciplinary and transdisciplinary challenges add to these, as climate data and impact model data provision and their usage require at least a minimum of common work and shared understanding among actors. Here, we provide the VALUE perspective on current disciplinary challenges and limitations at the downscaling interface and elaborate transdisciplinary issues that hamper a proper working downscaling interface. The perspective is partly based on a survey on user needs of downscaled data that was distributed among 62 participants across Europe involving 22 sectors. Partly, it is based on the exchanges and experiences gained during the lifetime of VALUE that brought together different actor groups of different disciplines: climate modellers, impact modellers, statisticians and stakeholders. We outline a sketch that summarizes the linkages between the main identified actor groups: climate model data providers, impact modellers and societal users. We summarize review and structure current actors groups, needs and issues. We argue that this structuring enables involved actors to tackle these issues in a more organized and hence effective way. A key solution to several difficulties at the downscaling interface is to our understanding the development of guidelines based on benchmark tests like the VALUE framework. In addition, fostering communication between actor groups—and financing this communication—is essential to obtain the best possible CCIA as a prerequisite for robust adaptation.

Description: International Journal of Climatology, Volume 39, Issue 9, Page 3689-3691, July 2019.

Description: The largest and most comprehensive to date intercomparison of statistical downscaling methods is presented, with a total of over 50 downscaling methods representative of the most common approaches and techniques. Overall, most of the downscaling methods greatly improve raw model biases and no approach is superior in general, due to the large method‐to‐method variability. The main factors influencing the results are the seasonal calibration of the methods and their stochastic nature, for biases in the mean and variance. VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using “perfect” reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques. Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on). Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value‐cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value‐cost.eu/validationportal.

Description: The weather and climate model CCLM, coupled with the multi‐layer urban canopy model DCEP (CCLM‐DCEP), is used at increasing resolution from 1 km to 250 m grid spacing to simulate the pronounced heat wave event of June‐July 2015 over the city of Zurich, Switzerland. CCLM‐DCEP showed the potential to represent the urban climate at the neighbourhood scale when used at high (sub‐kilometre) resolution, which is needed to support applications such as urban planning, building energy use and urban air quality. Abstract In the face of an increasing number of urban climate modelling studies performed at sub‐kilometre resolution, systematic investigations of the performance of high‐resolution urban climate simulations and their dependency on spatial resolution are still very sparse. This study investigates the impact of the scale of representation of the urban area on the urban climate simulation with a multi‐layer urban canopy model (UCM) integrated in a mesoscale numerical weather prediction model for different sub‐kilometre resolutions. The potential of using such a model system for representing the intra‐urban climate variability is explored. The weather and climate model COSMO in Climate Mode (CCLM), coupled with the multi‐layer UCM Double‐Canyon effect parameterization (CCLM‐DCEP), was used at increasing resolution from 1 km to 250 m grid spacing to simulate the pronounced heat wave event of June–July 2015 over the city of Zurich, Switzerland. Air temperature and wind speed measurements from a network of urban stations as well as surface temperatures (STs) from Landsat 7 imagery have been used to evaluate the model results. CCLM‐DCEP showed good performance against observed air temperature, ST, and wind speed in the urban area. The model performance did not change significantly with model resolution and a performance improvement with model resolution was not found. Small‐scale features such as urban parks and large railway areas started to be resolved at sub‐kilometre grid spacing. At the finest model resolution (250 m), a spatial variability in air temperature of up to 2 K and wind speed of up to 1.5 m/s was found within the grid cell of the coarsest resolution grid (1 km). CCLM‐DCEP showed the potential to represent the urban climate at the neighbourhood scale when used at high (sub‐kilometre) resolution, which is needed to support applications such as urban planning, building energy use and urban air quality.