ALBERT

Description: ABSTRACT A 175 years long homogenized composite record of monthly mean temperatures is presented for Oslo, the capital of Norway. The early raw data have been digitised and quality controlled, and monthly means have been calculated. Some early original observations carried out in a Wild screen (1877–1936) were found to be spuriously high because of inappropriate sheltering from sunlight. These spurious temperatures were not used in the composite record, but alternative temperatures measured (1837–1933) by thermometers placed outside windows at the Astronomical Observatory were used instead. No inhomogeneity was detected in the latter series after adding an instrument correction of +0.3 °C, but the start year of the correction remains uncertain. The more recent part of the composite record used the long-term series (1937 to present) from Blindern in Oslo, the premises of The Norwegian Meteorological Institute. Two small inhomogeneities were detected in the Blindern series, possibly caused by a weak urban heat island effect or growing/cutting of trees. The study revealed that the annual mean temperature has increased by 1.5 °C in the period 1838–2012. The most pronounced increase in annual temperature occurred during the last 50 years, and in the early 20th century that ended with a local maximum in the 1930s. The temperature has increased significantly in all seasons; however, the temperature increase in summer was less than a half of that in winter and spring, which were the seasons with largest increase. In addition the monthly mean temperature of the coldest month in each year has increased two times faster than the warmest one. The most significant temperature variations were associated to ∼ 5-year time scales in its early part, but since 1930 and up to present, the dominant time scales were 10–20 years.

Description: ABSTRACT The onset, retreat and the length of growing season in the north-eastern region of Sri Lanka were investigated using daily rainfall data for the period 1961 to 2000. Data from three weather stations situated in the coastal belt in the northern and eastern parts of Sri Lanka (Jaffna, Trincomalee and Batticaloa) that receive rainfall predominantly from the northeast monsoon were selected for this study. A method based on cumulative rainy days was utilized in the determination of the onset and retreat dates. It is shown that there is substantial interannual variability in onset and retreat dates. The mean onset and retreat dates fall on the standard week 38.3 ± 2.7 and 53.0 ± 2.9, respectively. The mean duration of the growing season is 14.7 ± 3.4 weeks. The retreat date and thus the length of growing season could be extended by 2 weeks if the probability of occurrence of rain during the onset is favourable for the retreat. The results indicate that there has been no significant trend in the onset and retreat dates during the last 40 years in the dry zone of Sri Lanka. The onset date and the length of growing season are weakly correlated with early onset dates leading to longer growing seasons. The study concludes that rainy days could be used successfully to determine the mean rainfall onset and retreat dates in the dry zone of Sri Lanka.

Description: ABSTRACT A 256-year composite monthly rainfall record representative of the lowlands around Carlisle, northwest England is presented, providing the third longest instrumental record of rainfall available in the UK and expanding the sparse network of long homogenous rainfall series. This article describes the construction of the rainfall record for the period 1757–2012 and presents analyses of long-term annual and seasonal variability, with a particular focus on wet/dry extremes. Three primary rainfall records from Carlisle underpin the reconstruction, with others selected based on length of record and proximity to the primary recording stations. Linear regression and adjustment factors were applied to create a homogenous continuous rainfall record, assessed by cross-comparison with other long-term UK rainfall records. Double-mass curve and standard normal homogeneity tests using long records representative of Manchester and Appleby confirmed that the Carlisle record is homogenous, but includes a period of uncertainty during the period 1886–1911, which is within the recognized instrumental phase of recording. Analysis of the series shows long-term temporal rainfall variability, with seasonal rainfall totals showing a significant increase in winter rainfall. An increasing trend in annual rainfall was also identified but is not significant. Several previously documented notable extreme wet (e.g. winter 1834) and dry (e.g. summer 1995) seasons were identified, along with several additional seasons (e.g. winter 1764 and summer 1891) that can be considered as extreme and occurred during the more poorly understood 18th and early 19th centuries. These results allow recent extremes to be placed within the context of long-term natural variability. At the decadal timescale seasonal rainfall totals are highly variable. The wettest season fluctuates between autumn and summer until the late 20th century (1990s), when winter became wetter than any other season for the first time on record.

Description: ABSTRACT Policymakers, governments and aid agencies require operational environmental monitoring in support of evidence-based policy-making and resource deployment in crisis situations. For Africa, this is only feasible at sub-continental scale with a large network of automated meteorological stations, a large number of highly coordinated field observers or with satellite remote sensing. The challenge with satellite data lies in the derivation of meaningful environmental indicators. This article describes a conceptual framework for understanding satellite-derived indicators of rainfall and vegetation greenness trends over Africa. It attributes observed vegetation changes to climatic (i.e. rainfall linked) and non-climatic drivers. A decade of annual rainfall and vegetation data over sub-Saharan Africa was analysed using satellite-based rainfall estimates [Famine Early Warning System Rainfall Estimation 2.0 (FEWSNET RFE 2.0)] from National Oceanic and Atmospheric Administration's (NOAA's) Climate Prediction Centre and the Normalized Difference Vegetation Index (NDVI) obtained from the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VGT) sensor. Rainfall and vegetation greenness trends were analysed for 759 administrative regions of sub-Saharan Africa to identify those regions that have experienced a negative, positive or stable rainfall/vegetation trend over the period 2001–2010. The character of the relationship between the annual rainfall and max NDVI trends were examined to identify areas where the changes in greenness could be attributed to climatic (rainfall) and non-climatic (human land use or ecological disturbance) changes. Regions where increasing rainfall was associated with vegetation greening were found in West Africa, Central African Republic, West Cameroon and northeastern part of South Africa, whereas areas with evidence of ‘climatic vegetation degradation’ were located in Southern Madagascar, Nigeria, Kenya and the Garden Route region of South Africa.

Description: ABSTRACT The North African climate is analysed for August during a 32-year period using the European Centre for Medium Range Weather Forecast (ECMWF) global data set to investigate the intensity variability at 600 mb of the subtropical highs, Africa easterly jet (AEJ) with two embedded local wind maxima, and African easterly waves over North Africa and the Arabian Peninsula. The variability of these synoptic weather systems is higher in East Africa. The most noticeable variability of intensity occurred with easterly waves. Maintenance of easterly waves from the Arabian Peninsula into East Africa is dependent on strong zonal gradients from the AEJ through shear vorticity. These zonal gradients were induced by the strengthening of the subtropical highs and the presence of a westerly jet in Central Africa and south of the Arabian Peninsula. During positive ENSO periods, these systems are generally weaker while in negative periods are stronger. The focus of this research is to investigate the role of the Arabian High and eastern local wind maximum (LWM E ) on complementing the Saharan High and western local wind maximum (LWM W ). It is found that an intense local wind maximum in East Africa helps maintain the easterly waves and their westward propagation from the Arabian Peninsula.

Description: ABSTRACT The purpose of this paper is to describe the variability of sunshine duration and air temperature and to assess the relationship between these variables. The paper is based on daily means of air temperature and daily sunshine duration totals from the 1884–2012 period. The variability analyses of these variables for the whole period is supplemented by additional trend analyses for two separate time periods described in the literature as dimming (1958–1985) and brightening (1985–2012). All the data come from the Jagiellonian University Research Station in Krakow. In Krakow, there is a decrease in the number of sunshine hours in the 1950s to 1980s period followed by an increase in the last two decades of the 20th century. The long-term course of air temperature in Krakow confirms the results obtained in other places in the world and exhibits increasing warming of the climate. The temperature increase is visible in each month but is highest in winter (exceeding 1.5 °C per 100 years). Therefore, it may be assumed that the increase in air temperature, which has been particularly strong since the 1980s, showed the full effect of global warming in the brightening period that was previously masked by global dimming as shown in the sunshine duration records. The time course of air temperature for the whole study period (1884–2012) shows a statistically significant positive linear trend. The present warming is influenced probably by the air-quality improvement (brightening period) and an increase in sunshine duration in the years 1980–2012.

Description: The relationship between long-term variations in summer temperature in Japan since the early 20th century and the large-scale atmospheric circulation field was analysed. The combined influence of various circulation predictors on temperature variations was analysed via a multicomponent canonical correlation analysis (CCA). The positive phase of the first CCA mode is related to a positive temperature anomaly across Japan, characterized by a weak blocking high over the Okhotsk Sea, and a strong North Pacific subtropical high (NPSH) over Japan. The positive phase of the second CCA mode corresponds to a positive temperature anomaly in southwestern Japan, and a negative anomaly in northern Japan, characterized by an anticyclonic circulation anomaly over eastern China and a cyclonic anomaly over the northwestern Pacific. By investigating the temporal changes in CCA scores, we detected an abrupt increase in the first CCA score in the early 1910s and a long-term increasing trend in the second CCA score since the early 20th century. The abrupt increase in the first CCA score indicates an abrupt increase in temperature throughout Japan. By investigating changes in the circulation field associated with this abrupt warming, we determined that intensification of zonal flow over the Okhotsk Sea was responsible. The increasing trend of the second CCA score indicates an increase in the regional difference in summer temperatures between northern and southwestern Japan. After investigating changes in the circulation field before and after the mid-20th century, we suggest that the southwestward shift of the NPSH and the weakening of anticyclonic circulation anomalies over the northwestern Pacific were responsible for this increase in the regional temperature difference.

Description: ABSTRACT The vegetation green-up date (GUD) is widely expected to advance to an earlier date in the year in response to increasing spring temperature. However, although it is well known that climatic warming has been more intensive at higher latitudes than at lower latitudes in the Northern Hemisphere, it is not known whether this greater climatic warming at higher latitudes has led to a greater advance of vegetation GUD during the past few decades. We have first determined GUD from the satellite-derived greenness vegetation index for all the vegetated land between 30 and 75°N from 1982 to 2008, and then investigated the latitudinal pattern of the inter-annual trend of GUD and its relation to pre-season temperature. The results show a generally greater GUD advance in lower latitudes, in spite of the faster increase in pre-season temperature in higher latitudes. We find that 88% of the latitudinal variability in the GUD trend can be explained by the sensitivity of the GUD response to pre-season temperature. The GUD change has also resulted in a northward shift of GUD isolines by 1°–4° between 50 and 65°N during the period. These findings highlight the sensitivity of vegetation response to temperature in shaping the spatial pattern of spring phenological change and suggest that temperate ecosystems may experience greater phenological change if the current latitudinal pattern of climatic warming continues.

Description: ABSTRACT In this study, we investigated the impact of the spring North Pacific Oscillation (NPO) on typhoon frequency over the Western North Pacific (WNP, north of the equator and west of dateline). To reduce the statistical uncertainty, all the data we used have been excluded the El Nino/Southern Oscillation signals. We found that the spring NPO positively correlated with the annual typhoon number over the WNP (hereafter TNWNP) during the period 1968–2010, with a correlation coefficient of 0.62 (above the 99% significance level). When the Northern Low and Southern High pattern over the north Pacific weakens, the TNWNP tends to increase. A positive phase of spring NPO is associated with the tropical circulation and sea surface temperature (SST) anomalies in the North Pacific, which may lead to unfavorable dynamical and thermal conditions for typhoon genesis over the WNP during JJAS. The negative anomaly of SST over the WNP, associated with the positive spring NPO anomaly, is connected to the tropical atmospheric circulations from spring to summer via good oceanic seasonal persistence and air–sea interaction. Thus, the spring NPO-related variability of the tropical atmospheric circulation as well as the SST can affect typhoon activity over the WNP. In addition, the spring NPO can also be adopted as a predictor for the summer rainfall in South China, since the spring NPO can modulate the WNP SST and western Pacific subtropical high from spring to summer.

Description: ABSTRACT Climate change is almost certain to affect snow and ice processes. Even at lower latitudes, changes in snow cover at high altitudes can significantly affect catchment hydrology. This article uses data from a transient Regional Climate Model projection (HadRM3Q0) for 1950–2099 (A1B emissions) to drive hydrological models for three nested catchments on the river Dee in north-east Scotland, to assess potential changes in flood frequency and timing using annual maxima and moving-window analyses. Some results are also shown for an upland catchment in northern England. Modelling is performed both with and without a snow module, to demonstrate the effects of snowfall/melt and how these change through time and vary between catchments. Modelled changes in flood magnitude and timing are nonlinear, with most changes for daily mean flows not significant. For longer duration (30-day) flows with snow there are significant decreases in peak magnitude, particularly for the smaller higher altitude Dee catchments, with peaks occurring months earlier in future (changes without snow are generally not significant). There is a general convergence in results with and without snow later in the period, as snow processes become less important, but convergence occurs at different times for different catchments and occurs differently for daily and 30-day peak flows due to the differential effects of snow at different durations. This not only highlights the importance of including snow processes for such catchments, particularly for longer duration flows, but also highlights the complexity of interactions: Physical catchment properties, the balance between precipitation occurrence and temperature, and how this balance alters as the climate changes will each be critical in determining the impact on the magnitude and timing of peak flows, making it hard to generalize results.

Description: ABSTRACT This article is the first of two companion articles providing details of the development of two separate models for statistically downscaling monthly precipitation. The first model was developed with National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis outputs and the second model was built using the outputs of Hadley Centre Coupled Model version 3 GCM (HadCM3). Both models were based on the multi-linear regression (MLR) technique and were built for a precipitation station located in Victoria, Australia. Probable predictors were selected based on the past literature and hydrology. Potential predictors were selected for each calendar month separately from the NCEP/NCAR reanalysis data, considering the correlations that they maintained with observed precipitation. Based on the strength of the correlations, these potential predictors were introduced to the downscaling model until its performance in validation, in terms of Nash–Sutcliffe Efficiency (NSE), was maximized. In this manner, for each calendar month, the final sets of potential predictors and the best downscaling models with NCEP/NCAR reanalysis data were identified. The HadCM3 20th century climate experiment data corresponding to these final sets of potential predictors were used to calibrate and validate the second model. In calibration and validation, the model developed with NCEP/NCAR reanalysis data displayed NSEs of 0.74 and 0.70, respectively. The model built with HadCM3 outputs showed NSEs of 0.44 and 0.17 during the calibration and validation periods, respectively. Both models tended to under-predict high precipitation values and over-predict near-zero precipitation values, during both calibration and validation. However, this prediction characteristic was more pronounced by the model developed with HadCM3 outputs. A graphical comparison of observed precipitation, the precipitation reproduced by the two downscaling models and the raw precipitation output of HadCM3, showed that there is large bias in the precipitation output of HadCM3. This indicated the need of a bias-correction, which is detailed in the second companion article.

Description: ABSTRACT This article is the second of a series of two articles. In the first article, two models were developed with National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and HadCM3 outputs, for statistically downscaling these outputs to monthly precipitation at a site in north-western Victoria, Australia. In that study, it was seen that the downscaling model developed with NCEP/NCAR reanalysis outputs performs much better than the model developed with HadCM3 outputs. Furthermore, it was found that there is large bias in HadCM3 outputs which needs to be corrected. In this article, the downscaling model developed with NCEP/NCAR reanalysis outputs was used to downscale HadCM3 20th century climate experiment outputs to monthly precipitation over the period 1950–1999. In all four seasons, the precipitation downscaled with HadCM3 20th century outputs, displayed a large scatter and the majority of precipitation was overestimated. The precipitation downscaled with HadCM3 outputs was bias-corrected against the observed precipitation pertaining to the period 1950–1999, using three techniques: (1) equidistant quantile mapping (EDQM), (2) monthly bias-correction (MBC) and (3) nested bias-correction (NBC). Although all these bias-correction techniques were able to adequately correct the statistics of downscaled precipitation, the magnitude of the scatter of precipitation remained almost the same. Considering the performances and its ability to correct the cumulative distribution of precipitation, EDQM was selected for the bias-correction of future precipitation projections. HadCM3 outputs for the A2 and B1 greenhouse gas scenarios were introduced to the downscaling model and the downscaled precipitation for the period 2000–2099 was bias-corrected with the EDQM technique. Both A2 and B1 scenarios indicated a rise in the average of future precipitation in winter and a drop in it in summer and spring. These scenarios showed an increase in the maximum monthly precipitation in all seasons and an increase in percentage of months with zero precipitation in summer, autumn and spring.

Description: ABSTRACT Hailstorms have become a serious meteorological risk in mid-latitude countries because of their small-scale development and short time span, and their forecasting remains problematic. Moreover, the lack of reliable hailstorm databases is an important handicap for Numerical Weather Prediction (NWP) model validation, time trend studies and establishment of hailstorm relationships with global warming and climate change. However, this can be overcome by ascertaining physical relationships between favourable synoptic patterns and mesoscale trigger factors for hailstorm development in a local study area. North-eastern Spain is one of the European regions with largest number of hailstorm days (HD) observed in the summer. Since 2001, from May through September, reliable databases of hailstorm occurrence in the middle Ebro Valley have been constructed, which include intensity, temporal frequency and spatial coordinate data. June and July 2006 had the largest number of HD in 2001–2010. With the objective of analysing meteorological factors responsible for this anomaly, atmospheric patterns at low and mid-tropospheric levels were studied. We determined a set of special synoptic configurations, with an evident deviation from climatic values generating anomalies of 850 hPa temperature relative to the characteristic values of 2001–2010 and 1950–2010. An analysis of these anomalies detected a positive trend of 850 hPa temperature and geopotential height in the western Mediterranean area. As a consequence, the characteristic synoptic circulation has changed since 1950, towards low-level patterns favouring adequate thermodynamic environments for hailstorm development in north-eastern Spain. Finally, after a cluster analysis, we studied periodicities in the monthly 850 hPa temperature field to improve knowledge for seasonal forecasting of hailstorms.

Description: ABSTRACT Tree-ring-based climate reconstructions are typically derived from either (1) a single species from one or multiple locations or (2) multiple species from multiple locations. Here, we investigate the ability of using multiple co-occurring canopy-dominant species from a single location for climate reconstructions based in the eastern United States. Using a variety of techniques, we first compare the climate signals of three canopy-dominant species ( Quercus rubra, Quercus alba, Liriodendron tulipifera ) at an old-growth forest in southern Indiana. We then determine if a composite time series of these co-occurring species increases or decreases the reconstruction model skill. Climate–growth correlation analysis of the species reveals strong and consistent relationships with summer [June–August (JJA)] Palmer Drought Severity Index (PDSI) during the period 1895–2012. We first use a split-sample reconstruction technique to compare the performance of species reconstruction models. We then use a nested technique to build a composite chronology against which to compare the individual species chronologies. The composite chronology of all three species accounts for up to 38% of the mean variation in JJA PDSI, and verification statistics indicate robust statistical skill from 1870 to 2012. The composite chronology reconstruction also outperforms each individual species model, indicating that using multiple co-occurring species increases reconstruction skill, at least from a single study site. Furthermore, model performance is improved by using nested reconstruction techniques, and implicates the potential ability to use multiple co-occurring species across multiple locations in the eastern United States.

Description: ABSTRACT Phenology can be used to track plant responses to climate change. In China, several studies have found the earlier trends of spring phenophases over the past 50 years. However, few studies put these phenological changes into historical perspective. Based on specific phenophases records from historical diaries and Chinese Phenological Observation Network, we developed spring phenology index (SPI) time series in temperate and subtropical regions of eastern China from 1850 to 2009. We firstly compare the temporal change of SPI and seasonal temperature anomaly. Subsequently, we search for common shifts in phenological and temperature time series by applying the moving t -test method, and discuss temperature sensitivity of SPI by using the moving linear regression method for both regions. Results show that the SPI in temperate region revealed lower interannual variability than in subtropical region, while the seasonal temperature variability was higher in temperate region. In temperate region, the timing of significant shift towards earlier SPI (in 1979) coincides with the timing of shift in spring temperature time series. The temperature sensitivities of SPI differ among the two regions. The mean sensitivity of SPI to spring temperature in subtropical region (−3.7 days °C −1 ) is stronger than in temperate region (−2.5 days °C −1 ). The temperature sensitivity of SPI varies among consecutive 30-year periods. In recent three decades, temperature sensitivity of spring phenophases became stronger in both regions.

Description: ABSTRACT Spatial structures of hourly precipitation fields were studied from three simulations of the Canadian Regional Climate Model (CRCM) and observations of the National Centers for Environmental Prediction (NCEP) Stage IV analysis. Each precipitation structure, defined as a contiguous area of precipitation above a given threshold, was analysed through geometric characteristics (position, area, major and minor axes, eccentricity, orientation) and intensity characteristics (volume, mean and maximum intensities, precipitation distribution within the structure) for 16 climatic regions covering North America. While providing new insights on the spatial facet of precipitation, this study aimed to: (1) assess the performance of the CRCM to reproduce observed precipitation structures and (2) analyse the changes in precipitation structures between historical (1961–1990) and future (2071–2100) periods. In addition, the effect of internal variability was investigated using two CGCM-driven CRCM simulations. In order to assess the CRCM performance, a reanalysis-driven CRCM simulation was first compared with observations and then with CGCM-driven CRCM simulations. Results suggest that reanalysis-driven CRCM precipitation structures displayed intensities spatially more homogeneous than observed ones for the central and eastern United States and showed significantly lower precipitation volumes, intensities and areas. However, annual cycles of characteristic values were well reproduced. In addition, CGCM-driven CRCM showed significantly lower precipitation volumes and intensities during summer months for southeastern regions when compared to reanalysis-driven CRCM. Precipitation structures were also larger and shifted further north. Boundary conditions seemed to influence mainly central and eastern regions of North America. In future climate, results suggest more convective summer precipitations for central and eastern regions (increases in volumes, intensities and heterogeneity of structures), drier spring and summer conditions for southwestern regions (decreases in numbers of structures), wetter winter and spring conditions for northern regions (increases in numbers of structures) and wetter autumn conditions for southeastern regions (increases in volumes and intensities).

Description: ABSTRACT In this report monthly thunderstorm days (TD) in 14 large cities of Brazil from 1951 to 2010 are compared with data obtained in the first part of the 20th century in the same cities and correlated with sea surface temperature (SST) of the equatorial Pacific Ocean and Tropical Atlantic Ocean. On average over all cities, 77 TD are reported each year after 1951, against 43 TD in the first part of the 20th century, an increase of 79%. The increase seems to be related to increase in the urbanization in these cities, and not to global warming. A comparative analysis of TD for the whole country with El Niño–Southern Oscillation (ENSO) events suggests that the tendency for El Niño to increase the thunderstorm activity is evident in the South (only in the Spring/Summer), Southeast, Northeast and North (only in the Fall/Winter) regions. Regarding the Tropical Atlantic Ocean SST, a similar analysis using the Tropical South Atlantic (TSA) and Tropical North Atlantic (TNA) indices suggests that no significant differences exist between the thunderstorm activity for the two extreme positive and negative TSA conditions in the South and Southeast regions, while in the Northeast and North regions there is a significant increase in the thunderstorm activity during extreme positive TSA. Differently, only in the Northeast region there is a significant influence of TNA on thunderstorm activity. The influence is such that the thunderstorm activity is larger for the extreme negative TNA than for extreme positive TNA. All significant changes were quantified and significant variations were observed. For all parameters investigated (ENSO, TSA and TNA) the Northeast region showed the most significant changes.

Description: ABSTRACT The diurnal variation of precipitation at four stations in and around Manaus (03°S, 60°W) is studied using hourly observations for the period 2006–2011. The rainfall at midforest stations is 20% greater than that at the city stations, especially in the afternoon hours. The frequency of rain events varies substantially with the hour of the day, but the mean intensity of rain events does not. Daytime [06–18 local time (LT)] frequency is more than two times the nighttime (19–05 LT) frequency. The hours with highest frequency are 12–17 LT. The wet season November through May (NDJFMAM) frequency is approximately three times that of the dry season June through October (JJASO) frequency at all hours and at all stations. The diurnal frequency peak in the afternoon is more pronounced at the forest stations than at city stations. For smaller intensities of hourly rainfall the afternoon peaks are very pronounced while larger intensities of rainfall (15 mm h −1 and above) do not show preference for any hour of the day. Higher rainfall totals in the rainy season are due to more frequent rainfall rather than higher intensities of the rain events. Higher frequencies in the early morning hours close to the river are possibly due to the river breeze effect.

Description: ABSTRACT Reliability of GCM (general circulation model) simulations is a significant predictor selection criteria and seems to be essential for outcomes of the statistical downscaling. This article investigates the reliability of a wide ensemble of CMIP5 climate models in reproducing seasonal atmospheric circulation patterns over Europe and the North Atlantic, namely sea level pressure (SLP) and 500 hPa geopotential height (G500). GCMs were evaluated with respect to 1971–2000 NCEP/NCAR reanalysis data by means of MAE, correlation coefficient and standard deviation. An attempt was made to determine the range of biases introduced into the statistical models by biases in the GCM simulations. For this purpose, canonical correlation analysis (CCA) models linking large-scale atmospheric circulation and air temperature in Poland were driven by historical GCM simulations expressed as anomalies with reference to the reanalysis data. It was shown that reliability of GCMs varies considerably, both seasonally and on an inter-model basis, thus becoming unfavourable in the context of statistical downscaling application. Overall, GCM ability to reproduce G500 values is better than for SLP. The most important finding from the statistical downscaling perspective is that SLP and G500 biases may introduce considerable air temperature biases (T-GCM biases ) into the downscaled reconstructions or projections of climate change. Seasonally, the highest T-GCM biases were found in DJF, when a significant overestimation of air temperature results from a GCM tendency to overestimate the meridional pressure gradient. A similar situation appears to be a significant factor in MAM and SON. Multiyear average GCM biases do not, however, explain a significant part of the inter-model variability of T-GCM bias , thus highlighting the need for a more in-depth evaluation. Nevertheless, good GCM performance seems to ensure that T-GCM bias is not of a considerable value. Overall, the results of the article emphasise the necessity for undertaking an application-oriented assessment of GCM reliability prior to any statistical downscaling approach.

Description: ABSTRACT Observations of local-scale urban surface energy balance (SEB), which include fluxes of net all-wave radiation ( Q *), and eddy covariance measurements of sensible ( Q H ) and latent heat ( Q E ) were collected in an arid Phoenix, AZ suburb from January to December 2012. We studied diurnal variations in SEB partitioning over four distinct seasons: winter, equinoxes, and summer; the latter period is further subdivided into (1) months prior to and (2) months occurring during the North American Monsoon. Largest flux densities were observed in summer, with most available energy partitioned into Q H . Much less energy is partitioned into Q E , but this term is strongly affected by monsoonal precipitation, where greater-than-average Q E can be discerned for several days after storm events. The presence of a positive daily flux residual (RES) [i.e. Q * − ( Q H  +  Q E )] for most of the summer indicates that anthropogenic heat ( Q F ) from residential cooling is likely a significant factor influencing SEB. Analysis of hourly ensemble SEB fluxes during all seasons also indicates that RES is largest in the morning, but Q H dominates in the afternoon. Results of SEB trends and magnitudes from Phoenix were also compared with other urban sites, especially in (sub)tropical cities. When normalized with net radiation terms, a consistent diurnal hysteresis between ensemble Q H and RES occurs, suggesting a robust parameterization of this relationship for model development during clear-sky conditions. SEB dynamics also appear to be affected by local surface characteristics, with regular nocturnal negative Q H associated with a high urban sky-view factor. Measured Q E fluxes during dry seasons were larger than expected based on the small proportion of irrigated plan area vegetated surfaces. A probable explanation could be an enhanced micro-scale advective forcing of evapotranspiration arising from leading-edge effects over patchy residential lawns, which has possible implications for modelling evapotranspiration in hot arid cities.

Description: ABSTRACT The global increase of temperature, together with more frequent severe winters and summer heat waves may lead to a change in energy consumption and agricultural production. Cooling, heating, and growing degree-days (CDD, HDD, and GDD), respectively, are used to quantify the energy needed to condition or heat buildings, and to study the growing season. Using a new dataset made of 4023 daily T N – T M – T X series for the period 2001–2011 and 3897 monthly T M homogenized series for the period 1951–2011, we computed CDD, HDD, GDD, and Winkler Index (WI) for Europe. We developed a model that correlates degree-days calculated with daily T N – T M – T X data with degree-days obtained by monthly T M data, in the overlapping period 2001–2011. A set of parameters for each station was then applied to the corresponding 1951–2011 monthly records. We interpolated the parameters and the reconstructed degree-day series onto a European 0.25° × 0.25° grid: with these gridded parameters, one can estimate the degree-days for any European location if only monthly T M is available. We present maps of HDD, CDD, GDD, and WI for the period 1951–2010. To validate them, we run a comparison in the Carpathian area using an independent dataset (from the CARPATCLIM project). The regional records show high correlations, especially for HDD ( r  〉 0.99) and WI ( r  〉 0.98). Subsequently, we performed a linear trend analysis on European and regional basis. HDD showed a significant decrease almost everywhere in Europe, whereas CDD, GDD, and WI showed a significant increase in particular in the last 30 years in the Mediterranean region. Moreover, WI indicated that new areas in France and central Europe became suitable for grape cultivation in the last decades.

Description: ABSTRACT Since the 1970s the Canadian Prairies have experienced a steady replacement of summer fallow with continuous cropping practices. It has been suggested that such regional scale changes in agricultural land use result in the modification of the regional climate and its variability. Our study explores this influence using linear discriminant analysis (LDA) to determine whether agricultural land use variables can discriminate the classes of exceedance (positive/negative beyond a given small scale variability range) found in the maximum and minimum daily temperature, diurnal temperature range (DTR), daily precipitation and daily incoming solar radiation. These classes of exceedance describe whether the climate was warmer/cooler, drier/wetter and sunnier/cloudier relative to the small scale variability range. The land use data consisted of summer fallow, annuals and perennials for the 127 ecodistricts in the Prairies ecozone. The climate data were neighbouring station data interpolated to the ecodistrict's centroid. Both data sets covered the period 1951–2006 and the analysis covered the entire data period with focus on 1971–2006 that coincided with the decline in summer fallow practice. It considered the primary growing season months of June, July and August and used the winter months of January and February as a contrast. Our approach showed that where large scale changes in agricultural land cover occurs we can establish a statistical relationship between such changes and the modification of the climate's variability. June coincided with the period of maximum positive growth rate and hence land cover change. The greatest discriminating power was therefore found to occur in June for the exceedance classes of maximum and minimum temperature and solar radiation over the 1971–2006 period with success rates ranging from 85 to 93%. The greatest success in discriminating the DTR classes was at 82% in July.

Description: This contribution employs documentary-based precipitation indices and long homogenized series of precipitation totals for quantitative reconstruction of seasonal and annual precipitation in the Czech Lands (now the Czech Republic) from AD 1501. Final calibration is based on linear regression using fully independent indices and data measured during the 1804–1854 overlap period, with subsequent variance scaling. Correlation analysis demonstrates that Czech documentary indices explain a significant amount of precipitation variability in all months and seasons of the entire overlapping period. Reconstruction results are best for annual values and for autumn (SON), for which proxy and target data share 36% of common variability. The coefficient of determination for summer (June-July-August – JJA) is 35%, for spring (March-April-May – MAM) 33%, while for winter (December-January-February – DJF) it is only 26%. Verification statistics [reduction of error (RE), coefficient of efficiency (CE)] computed for early (1804–1829) and late (1830–1854) overlapping periods indicate acceptable reconstruction skill for precipitation indices in JJA and annual values. However, for the other seasons they failed in the early or late calibration period, indicating possible chronological instability of reconstruction results in MAM, SON (September-October-November), and DJF seasons. The final reconstructions are complemented with uncertainty estimates. Reconstructed Czech precipitation series do not indicate long-term trends but reveal quite high inter-annual and inter-decadal variability. Smoothed reconstructed DJF and JJA precipitation totals show the highest values in the second part of the 16th century, while the driest 30-year period occurred during the 18th century in DJF, MAM, JJA, and in annual series. Direct comparisons with two other reconstructions (tree-ring-based for southern Moravia and gridded multi-proxy for Central Europe) not only show significant correlations for a substantial part of the common period, but also disclose several periods with loss of coherence. Finally, uncertainties in reconstructions are discussed.

Description: ABSTRACT The prospects of validating areal data from climate models by site observations depend critically on the spatial representativeness of the sites. This paper introduces a simple parameter-free approach to quantify the spatial representativeness of single stations with an application to time series of daily near surface air temperature and precipitation at European weather stations. Complementing classical methods such as spatial auto-correlation and variogram, our approach provides a well defined area around each station for which the station is representative, based on a similarity threshold but otherwise without any limiting assumptions about distribution or spatial stationarity of the data. This area is interpreted as the station's ‘inverse footprint’ and its areal extent provides a measure of representativeness. We find a generally higher representativeness for temperature compared to precipitation, but also a strong seasonal dependence. For instance, temperature representativeness in boreal winter is related to the influence of circulation with large ‘inverse footprints’ over Central and Eastern Europe and Scandinavia. Representativeness in summer exhibits similar patterns but is lower. Precipitation representativeness displays related patterns of representativeness and circulation control in winter, but vanishes in summer, probably due to the small-scale characteristics of convective precipitation. Precipitation representativeness is strikingly high around the Mediterranean, which is a consequence of the large numbers of synchronous dry days in this region. The physical plausibility of the results underlines the applicability of our approach. Although not investigated here, the ‘inverse footprint’ also provides information on the directional dependence of representativeness at the station level.

Description: ABSTRACT Streamflow forecasts at monthly and sub-monthly time scales, e.g. 10-day period, are critical for making decisions to allocate water for different users and mitigate possible flooding. Adaptive forecasting of 10-day streamflow is still challenging, although persistence prediction models sometimes have good performance when streamflow has strong lag-correlation. This study proposes a scheme of proving monthly and sub-monthly flow forecasts at the beginning of the month and updating sub-monthly forecasts subsequently. It examines a principal component regression method to provide monthly average streamflow and sub-monthly, e.g. 10-day, average streamflow forecasts, utilizing gridded precipitation forecasts from climate models and soil moisture estimates from hydrological models. Monthly streamflow forecasts are first obtained. It is then disaggregated to 10-day streamflow based on historical observations using a nonparametric approach. The disaggregated 10-day streamflow forecasts are further improved by incorporating streamflow and soil moisture estimates in the previous 10 days. Hence, sub-monthly flow can be improved adaptively. The proposed approach is demonstrated for monthly and sub-monthly streamflow forecasts in July at the Yangtze River, the largest river in China. The correlation between monthly streamflow forecasts and observation is 0.46 in leave-one-out cross-validation mode. Updated sub-monthly streamflow shows better skill than disaggregated sub-monthly forecasts. To examine the impact of the accuracy of monthly streamflow forecasts on disaggregated 10-day streamflow, synthetic streamflow time series of different level of forecasting skills were examined. Results show that the higher skill of synthetic monthly streamflow forecasts, the lower forecasts error. The value of soil moisture estimates in proving streamflow forecasts is also examined.

Description: ABSTRACT This study investigates changes in the frequency and timing of tropical cyclone landfalls over the south-west Indian Ocean during the last 66 years. Little is known about the spatial and temporal trends of such storm landfalls during recent historical times, specifically the last ca. 100 years. By analysing three storm track records spanning periods of 66–161 years, we establish that much of the perceived change in storm numbers can be attributed to improvements in storm detection methods over the past century. Furthermore, we find no statistically significant trends in the frequency of tropical cyclone landfalls over Madagascar and Mozambique over the past 6 decades, despite more comprehensive records during the most recent period. There is, however, considerable interannual variability in the number of storms making landfall over the countries investigated; most probably driven by cyclical atmospheric forcing, including El Niño-Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO). Recent trends indicate an increasing number of tropical cyclones tracking to the south of Madagascar, potentially associated with the southward shift of the 26 °C isotherm, combined with a decrease in the steering flow during La Niña years.

Description: ABSTRACT A cluster analysis-based synoptic classification scheme, known as the Kidson types, was applied to reanalyses and Coupled Model Inter-comparison Project phase 3 (CMIP3) general circulation model (GCM) output over New Zealand to identify the potential for future changes in regional circulation. Results indicate that a number of GCM 20th century control runs reproduce the type frequencies observed in reanalysis data. Application to future scenario runs for the periods 2046–2065 and 2081–2100 displays little variation in the annual frequency of the synoptic types relative to the 20th century, especially when uncertainty associated with the model ensemble is considered. This is surprising in the context of previous work on possible future movements in jet position and subsequent impacts on weather patterns. A sensitivity analysis that mimics the movement of the jet position was performed, revealing that the annual type frequencies are relatively insensitive to change. To determine whether this is a problem with the synoptic typing scheme, a correlation-based classification technique was also used, but showed similar results. This work highlights issues with applying synoptic classification schemes to GCM output and indicates that if such schemes are to be used they should be designed and tested with this application in mind.

Description: ABSTRACT Southeastern South America has been identified as a hot spot of soil moisture and evapotranspiration coupling efficiency during austral summer in a previous study. Here, hydrological processes such as coupling and memory of soil moisture, evapotranspiration and precipitation and the links between these variables are discussed on the daily time scale over this region. The correlations between surface variables, rainfall persistence and soil moisture memory are discussed over three subregions selected on basis of their coupling efficiency and mean daily intensity of precipitation. The relationship between surface climate and land cover is qualitatively assessed. The memory, or statistical persistence, is longer and has a more robust spatial pattern for the root zone than for the top soil moisture. Where the coupling efficiency between soil moisture and evapotranspiration is high, the evapotranspiration is regulated by soil moisture conditions independently on the intensity of precipitation, whereas in a region with low coupling efficiency and high intensity, the evapotranspiration is regulated by the atmosphere. The coupling efficiency is in general related to the memory of the root-zone layer, since the soil state is modified when the soil moisture and the atmosphere interact, resulting in an anticorrelation between these metrics. The persistence of rainfall is another factor that modulates the memory. Nevertheless, there are some areas around the La Plata River where both the coupling efficiency and the memory are relatively high, such as Uruguay and the northeast of Argentina, where an improvement of soil moisture initial conditions could improve predictability of surface variables on a monthly timescale.

Description: ABSTRACT Various types of studies require a sufficiently long series of data processed identically over the entire area. For climate analysis, it is necessary that analysed time series are homogeneous, which means that their variations are caused only by variations in weather and climate. Unfortunately, most of the climatological series are inhomogeneous and contain outliers that may significantly affect the analysis results. The 137 stations with precipitation measurement belonging to the meteorological station network governed by the Meteorological and Hydrological Service of Croatia were selected for the present analysis. Most of the data series cover a period from the late 1940s or early 1950s through the year 2010. For quality control and homogenization, an approach based on the software ProClimDB/Anclim was applied. In this study, we describe the results from the quality control and homogenization process for monthly precipitation sums as well as the spatial relationship of precipitation in the Croatian region. The precipitation network in Croatia is fairly homogeneous as only 23% of the 137 analysed stations are found to be inhomogeneous.

Description: ABSTRACT The intention of this study was to identify a suitable Generalized Linear Model (GLM) for modelling multi-site daily rainfall in the Onkaparinga catchment in South Australia and to examine the suitability of the model for downscaling of General Circulation Model (GCM) rainfall projections. A GLM was applied and multi-site daily rainfall was downscaled using National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis datasets. Nineteen large-scale atmospheric and circulation variables were selected at first and these were eventually reduced, based on correlation with daily rainfall, to 10 final variables to be used in the model. First, logistic regression was used to identify the wet and dry days, then wet day rainfall was modelled using a gamma distribution. The model was fitted for a calibration period (1991–2010) and it was then validated over the period 1981–1990. Several summary statistics including mean, standard deviation, number of wet days, maximum rainfall amount and lag 1 and lag 2 autocorrelations were used to check the model performance. The 2.5th and 97.5th percentiles of the simulated rainfall statistics were plotted against the observed rainfall statistics and it was shown that most of the observed statistics were within these bounds. Area averaged and station wise monthly, seasonal and annual totals for observed and simulated rainfall were estimated and compared. The overall performance of the GLM to downscale rainfall was considered satisfactory. However, a few discrepancies were observed in different performance statistics. Parameterization of the model to capture the local convective variability of rainfall would increase the model performance. It was found overall that the GLM can be applied for downscaling of GCM rainfall projections for this catchment.

Description: ABSTRACT In this study, different interpolation techniques in a geographical information system (GIS) environment are analysed and compared for estimating the spatial distribution of precipitation in the province of Ontario, Canada. A high-resolution regional climate modelling system [Providing Regional Climates for Impacts Studies (PRECIS)] is used to simulate the present (1961–1990) and future (2071–2100) precipitation events for 12 meteorological stations over Ontario. The results verify that for the present case PRECIS simulates well the precipitation events when compared with observed data. The future precipitation events can be projected after the validation of PRECIS. Six interpolation methods are then used to generate spatial distribution of precipitation based on the projections of future precipitation of 12 meteorological stations; they include inverse distance weighting (IDW), global polynomial interpolation (GPI), local polynomial interpolation (LPI), radial basis functions (RBF), ordinary kriging (OK), and universal kriging (UK). Cross-validation is applied to evaluate the accuracy of interpolation methods in terms of the root mean square error (RMSE). The results indicate that LPI is the optimal method with the least RMSE for interpolating the PRECIS precipitation. LPI is then used to analyse spatial variations of the average annual precipitation for the period of 2071–2100 over Ontario.

Description: ABSTRACT This article investigates extratropical winter cyclone activity in the Southern Hemisphere (SH) in a multi-model ensemble (MME) of coupled atmosphere–ocean general circulation model (AOGCM) simulations of recent and potential future climate conditions. Most individual models and also the ensemble mean yield good reproductions of the typical cyclone characteristics found in reanalysis data, although some individual models show peculiarities, and a large inter-model spread in terms of quantity of identified cyclone tracks is found. We use a scaling approach to combine the cyclone statistics from different models into a MME. In the future climate simulations, the total number of SH cyclones is reduced, whereas an increased number of strong cyclones is found in most models and in the ensemble mean. The long term trend with respect to all cyclones is a robust feature throughout the simulations. It is associated with a general poleward shift, shown to be related to both tropical upper tropospheric warming and shifting meridional sea surface temperature gradients in the Southern Ocean. The magnitude of increased strong cyclone activity has a focus on the Eastern Hemisphere. It is clearly influenced by natural variability and thus depends on specific time periods considered.

Description: ABSTRACT Dynamically downscaled simulations are an attractive source of information for those requiring greater regional detail than what Global Climate Models (GCMs) can provide. However, an important question is whether the information derived from downscaled simulations is plausible. Some recent studies have attempted to answer this question using an ‘added value’ framework. This study takes an alternate approach by comparing projected changes of climate extremes from Regionally Dynamically Downscaled Model (RDM) ensembles to the host GCM ensemble over the Australian continent. Bias-corrected sea-surface temperatures (SSTs) from five Coupled Model Inter-comparison Program Phase 3 (CMIP3) GCMs are used to force two different configurations of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Conformal Cubic Atmosphere Model (CCAM), run at 60 km. For each member of the two CCAM ensembles and each GCM ensemble member, a selection of extreme events and their changes were calculated for minimum temperature, maximum temperature and precipitation for the climate of the 20th century (20c3m; 1980–1999) and A2 (2081–2100) simulations. We find that CCAM shows finer spatial detail in the current distribution of extremes and also the projected climate change signal than GCMs. While the projected change in extreme temperatures has a similar pattern in CCAM compared to the host GCMs, the projected changes in rainfall are not only more spatially detailed but also different at the large scale. This, however, does not infer that climate change signal in CCAM is necessarily more or less physically plausible than the GCMs. In order to ascertain the plausibility and usefulness of RDM simulations, we strongly encourage a critical assessment of the required simulations before their use in adaptation and impacts planning, which includes a comparison to similar simulations from the host GCM(s).

Description: ABSTRACT This study examines the changes in monsoon rainfall of India using a suite of extreme indices defined by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI) to make the Indian results comparable internationally, in addition to the use of some relevant indices particularly developed for the Indian climate. To this end, the recently developed high resolution daily gridded (0.5° × 0.5°) rainfall dataset for the period 1971–2005 has been analysed using robust nonparametric techniques. Despite the high interannual variability and spatial diversity of the Indian climatology, the results reveal signal of changes for several extreme rainfall indices, generally consistent with the simulated outcome of an intensified Indian monsoon rainfall in the context of global warming. A predominant decrease in wet days, moderate and total rainfall is observed in the high rainfall regions of northeast, central and southwest India. In the active monsoon months of July and August, the dry spells defined by the maximum length of consecutive dry days (CDD) have increased significantly over the north and central regions of India, suggesting a serious threat to the Indian agriculture. Simultaneously, the extreme rainfall indices, based on the percentile and absolute values, show increasing trends over large parts of the country. The probability density function (PDF) of several indices show noticeable changes since the 1990s over the homogeneous central and northeast parts of India. The indices representing the total monsoon rainfall and dry spells are better correlated with the El Niño–Southern Oscillation (NINO3.4), compared to that of the Indian Ocean Dipole Mode Index (IODMI). The mapping of the observed rainfall trends and their correspondence to the large scale circulation modes is expected to assist the policy makers to prioritize the mitigation and adaptation strategies.

Description: ABSTRACT In this article, role of extratropical circulation features in modulating Indian Summer Monsoon Rainfall (ISMR) is examined. Principal component (PC) analysis of extratropical tropospheric temperature data of the monsoon season for 1951–1980 and 1981–2010 years was performed separately. Analysis revealed that a PC (PC 3) of the first period and two PCs (PC 2 and PC 6) of the second period had significant correlation with the ISMR. Composite geopotential height anomaly of middle and upper troposphere, for the dates when extratropical tropospheric temperature anomaly pattern was similar to that of Eigen Vector of the PC 3 of the first period and PC 6 of the second period, highlighted presence of standing waves in the extratropics. These waves had trough over northwestern/northern parts of the Indian subcontinent and adjoining extratropics and ridge eastwards. Such circulation anomaly pattern of the extratropics apparently reduced the north-south tropospheric temperature gradient required for good monsoon flow. This led to weak monsoon currents, resulting subdued ISMR activity during the period. This pathway of interaction of the extratropical circulation anomalies and the ISMR was reported by earlier studies also. Composite geopotential height anomaly of the middle and upper troposphere, for the dates when extratropical tropospheric temperature anomaly pattern was similar to that of Eigen Vector of the PC 2 (explaining larger variance of the temperature data) of the second period also depicted presence of standing waves. These waves were of relatively large amplitude and wavelength and were located at more northern latitudes. The configurations had warm high/ridge with centre over higher latitudes to the north of India and cold low/trough eastwards. Further analysis highlighted a new pathway of modulation of the ISMR by the extratropical circulation anomalies with above features.

Description: This study compares Climate Research Unit version 3 reference observations in the period 1980–2009 with Coupled Model Intercomparison Project Five (CMIP5)-simulated climate patterns and trends over the Ethiopian highlands (7–14N, 36–40E) using the rcp6 scenario. Three metrics are used in a stepwise statistical evaluation: (1) mean annual cycle of area-averaged rainfall ( R ) and maximum temperature ( T x ), (2) spatial pattern of R and T x over Ethiopia and (3) interannual (1.5–6 years) R and T x variability. Those models passing the first step by simulating a unimodal annual cycle reaching 28 °C in March–May and 9 mm day −1 in July–August are then evaluated for their ability to represent the cool, wet ‘island’ pattern over the highest elevation. Finally, the models' ability to follow observed area-averaged R and T x anomalies from 1980 to 2009 is analysed by correlation. The stepwise metrics are designed to improve confidence in the use of CMIP5 models for future resource management and development planning across the Ethiopian highlands. The models with optimal performance in the most categories include the HAD, CCSM and GFDL.

Description: ABSTRACT Hailstorms can pose a significant threat to society, by damaging property and disrupting livelihoods. An understanding of how hailstorm characteristics may change under a warming climate is therefore important for assessing the risk of hail damage for the insurance industry. A simple model of hailstone formation has been driven using meteorological data produced by a regional climate model (RCM) to project how hailstorm numbers and hailstone sizes could change during the 21st century in the UK. Evaluation of the modelled hailstone sizes, numbers and spatial distributions showed that they agreed reasonably well with observations. The effect of climate change on the numbers of damaging hailstorms in the UK (hailstones with diameters greater than 15 mm) was then investigated. A downward trend in the total number of damaging hailstorms during the 21st century was projected, with statistically significant trends for hailstones with diameters between 21 and 50 mm. Melting of hailstones made little contribution to the projected reductions. The results are subject to large uncertainties, some of which originate with the convective parameterization scheme used by the climate model.

Description: ABSTRACT Flood events is the natural hazard that originated more damages and fatalities in the Iberian Peninsula in the last decades. While most 20th century extreme precipitation and flood episodes in Iberia have been documented, the same does not hold for most events that took place during the 19th century. This article describes the unusually high precipitation and associated impacts recorded during the 1855/1856 hydrological year. We combine newspaper reports, early instrumental precipitation series and sea level pressure (SLP) reconstructed gridded fields. The early instrumental precipitation time series includes 11 observatories that were not previously digitized and preceded the implementation of the official meteorological observation network in Spain. We show that high values of precipitation were mostly recorded during the months of September, October 1855 and January 1856, with most of the flooding and damages occurring in the last month. The use of daily circulation weather types and monthly differences of SLP are particularly useful to explain the heavy precipitation in October and January, which were clearly associated with unusual high frequencies of wet weather types. However, SLP patterns cannot explain the September records, which could be associated to upper cold air intrusions in the Iberian Peninsula.

Description: ABSTRACT The relevant literature on extreme rainfall events in the Pacific remains relatively sparse compared to other regions (e.g. the coterminous United States, Europe, etc.). Moreover, several recent reports on climate in the Pacific mention the paucity of extremes information and often list ‘trends in historical climate’ as a necessary next step. This scientific assessment meets this need by examining historical trends in and drivers of extreme rainfall events across the entire Pacific Basin, inclusive from Alaska southward to Australia, and longitudinally from the Philippines eastward to North America, with an emphasis on island and coastal locations (within 200 km of the coastline). There is evidence of a general decrease in the frequency of annual extreme rainfall events, yet the amount of extreme precipitation contributing to annual and seasonal totals appears to be on the rise. Region-wide, the number of consecutive dry days is increasing for those locations that are already dry, while the number of consecutive wet days is increasing for the already wet locales. The data for extreme rainfall statistics are considered to be relatively high quality for trend detection, while the level of understanding of the physical causes behind extreme rainfall is positively high. Since the ability to analyze the changes in historical rainfall extremes with some confidence is relatively recent, understanding is expected to improve in the future with the advancement of new datasets and ‘climate reanalysis’ projects.

Description: ABSTRACT For climate impact assessment regarding hydrology, the availability of long precipitation time series with high temporal and spatial resolution is essential. A possible approach to obtain this data is the statistical downscaling of precipitation simulated by a global climate model (GCM) using a stochastic rainfall model with parameters conditioned on circulation patterns (CP). This approach requires: (1) the existence of a strong relationship between CP and precipitation, (2) the sufficient reproduction of CPs by the GCM, (3) the adequate simulation of precipitation by the rainfall model and (4) either stationarity of the relationship between precipitation and CPs or an approach to account for non-stationarity. The objective of this research is the careful evaluation and discussion of the above stated four hypotheses. For this purpose, a case study for the Aller–Leine river basin in Northern Germany has been created. It has been found that CPs can be defined which show significant differences in precipitation behaviour. The CPs derived from re-analysis data are well reproduced by the GCM simulations. In addition, the hourly stochastic rainfall model simulates the observed precipitation characteristics well, except for a certain overestimation of the extremes. However, the change in rainfall between past and future time periods as predicted by a regional climate model could not be explained by the change in CP frequency, due to the non-stationarity of the relationship between rainfall and CP. This can be best accounted for by re-estimating the parameters of the stochastic rainfall model for future conditions based on corrected observations using a delta change approach regarding simulated rainfall from a regional climate model.

Description: ABSTRACT Ongoing global warming raises the hypothesis of an intensification of the hydrological cycle, extreme rainfall events becoming more frequent. However, the strong time–space variability of extreme rainfall makes it difficult to detect meaningful trends in the regime of their occurrence for recent years. Using an integrated regional approach, it is shown that over the last 10 years, the Sahelian rainfall regime is characterized by a lasting deficit of the number of rainy days, while at the same time the extreme rainfall occurrence is on the rise. As a consequence, the proportion of annual rainfall associated with extreme rainfall has increased from 17% in 1970–1990 to 19% in 1991–2000 and to 21% in 2001–2010. This tends to support the idea that a more extreme climate has been observed over 2001–2010: this climate is drier in the sense of a persisting deficit of rainfall occurrence compared to 1950–1969, while at the same time there is an increased probability of extreme daily rainfall.

Description: Long-term instrumental records that provide estimates about the natural range of long-term climate fluctuation are lacking in Iran. Ring-width chronologies were developed from two oak sites in the central Zagros Mountains, dating back to 1705 A.D. Due to high correlations between the local site chronologies, a mean regional chronology (RC) was calculated. Correlations with regionalized climate data showed significant negative correlations with maximum temperature in December of the previous year and February, May, June and August of the current year. However, May–June maximum temperatures of the current growing season showed the highest negative correlation coefficient with regional tree growth patterns. Based on this relationship, maximum temperature of May–June was reconstructed over the last 170 years (1840–2010). The average length of cold periods was shorter than that of warm periods. Further sampling may allow the analysis of long-term climatic trends in this region.

Description: ABSTRACT This paper reports the development of a relationship between incoming shortwave solar radiation and bright sunshine duration. The daily temperature range (DTR) is melt into the existing Angstrom equation to include the advection of atmospheric constituents. The proposed DTR plus Angstrom equations were tested against field investigation. Measurements of solar radiation and sunshine duration from 1997 to 2006 at 20 meteorological stations were used to calibrate and validate the suggested equation. The model parameters required to specify the nature of the relationship between solar radiation and sunshine duration were determined by automatically minimizing the difference between the modeled and measured solar radiation. At the 20 meteorological stations, the root mean square error (RMSE) is improved by 6% for the original Angstrom equation with DTR, while 2% for the modified Angstrom equation with DTR. The average value of the coefficient of determination is 0.889 (0.908) for the original (modified) Angstrom equation whereas 0.901 (0.911) for the original (modified) Angstrom equation with DTR. It is encouraging that the newly suggested equation with DTR generally provides better performance than the existing Angstrom equation that is constructed with brightness sunshine duration only.

Description: ABSTRACT On the basis of Coupled Model Intercomparison Project phase 5 (CMIP5) models, this study have examined the ability of models to capture the El Niño/Southern Oscillation (ENSO)–Indian Ocean Basin Mode (IOBM) relationship, and investigated the characteristics of interdecadal change of ENSO–IOBM relationship as well as the response of the ENSO–IOBM relationship to the global warming. Among 23 CMIP5 models, the capability of models in representing the IOBM depends largely on the simulation of ENSO. Moreover, half of the models can reproduce the unstable ENSO–IOBM relationship. Considering the simulations of ENSO, ENSO–IOBM relationship and interdecadal change, 6 of 23 CMIP5 models are chosen for further investigation. The interdecadal change of ENSO–IOBM relationship is relative to the three ENSO-related processes. During the high correlation (HC) period, the tropospheric temperature (TT) mechanism, oceanic Rossby waves and antisymmetric wind pattern are strong, prolonging the persistence of IOBM. In comparison, during the low correlation (LC) period, the three processes are weak. The results show that the shallow thermocline in the southwestern Indian Ocean (SWIO), increased interannual variability and prolonged periodicity of ENSO are all responsible for the interdecadal change. Furthermore, the possible changes of ENSO–IOBM relationship in the future are investigated. The ENSO-related tropical Indian Ocean (TIO) warming is strengthened under global warming. Despite the deepened thermocline over SWIO and unchanged ENSO activity, the ENSO-related TIO warming is strengthened by the enhanced TT mechanism, which is caused by the increased saturated specific humidity. The results reveal that there is more downward net heat flux (NHF) over the TIO, which is conducive to the TIO warming, and the latent heat flux (LHF) change makes a great contribution to the NHF change. The weakened upward or strengthened downward LHF is possibly due to the decreased anomalous sea–air temperature difference by strengthened TT mechanism.

Description: ABSTRACT Many regions of the world are affected by a major land cover change resulting from the encroachment of woody plants and the conversion of grasslands into shrublands. In the southwestern United States, such a change in vegetation cover has been found to increase the winter nighttime temperature, thereby contributing to a positive feedback between shrub encroachment and microclimate in areas encroached by cold-sensitive shrubs. Temperature measurements show that winter minimum temperatures are on average ∼2 K higher in shrubland than in adjacent grassland sites. It is unclear how the nighttime warming induced by shrub encroachment compares with regional climate trends. We address this question by analysing both the historical and future regional temperature trends in central New Mexico. The estimated regional increase in minimum winter temperature ranges from 1 to 4 K per century using observations and climate models. Thus, the warming resulting from shrub encroachment is equivalent to a change in regional climate over a time period of century scale, which suggests that shrub encroachment has an overall important effect on the regional climate.

Description: ABSTRACT Using a sky camera, episodes characterized by overcast low clouds in the Valencia region of Spain have been selected for analysis. One year of cloud optical depth data have been produced by inverting UV erythemal irradiance measured with a UVB-1 radiometer from Yankee Environmental Systems using the LibRadtran radiative transfer model. Measurement uncertainties, aerosol single scattering albedo and cloud properties are, in order of decreasing importance, the most important factors influencing the accuracy of cloud optical depth retrieval when using UV erythemal radiometers. Statistics for cloud optical depth show a highly skewed frequency distribution best described by a gamma distribution with highest frequency between optical depths of 10 and 15 and optical depths exceeding 100 at the extreme high end.

Description: ABSTRACT Since the late 1980s, Australian forecasters have used the seasonal climate forecast (SCF) statement In the next three months, the probability of getting above median rainfall is 30%. Study one ( n  = 63) established a baseline of whether laypersons interpreted this statement as forecasting wetter or drier conditions than normal. Although the statement is forecasting a greater likelihood of drier conditions than normal, 76% incorrectly interpreted the statement as forecasting a wetter season than normal. Using testing conditions identical to study one, in study two ( n  = 71), to improve accuracy, we inserted the word only in the statement (i.e. … probability of getting above median rainfall is only 30% ). While the probability itself had not changed, a drop to just 24% errors suggested participants were ambiguous about how to interpret this probability. A body of research by Gigerenzer and others shows peoples' ability to reason with probabilities is enhanced by frequency probabilities rather than single-event probabilities. Study three ( n  = 51) used the frequency (i.e. 3 in 10 ) rather than single-event (i.e. 30% ) format tested in studies one and two. Only 22% made errors showing participants better understood how to interpret the frequency probability. We discuss formats for presenting the SCF and argue the frequency format more effectively conveys the chance nature of forecasts.

Description: ABSTRACT: Here, we present an analysis of monthly, seasonal, and annual long-term precipitation time-series compiled from coastal meteorological stations in Greenland and Greenland Ice Sheet (GrIS) ice cores (including three new ice core records from ACT11D, Tunu2013, and Summit2010). The dataset covers the period from 1890 to 2012, a period of climate warming. For approximately the first decade of the new millennium (2001–2012) minimum and maximum mean annual precipitation conditions are found in Northeast Greenland (Tunu2013 c. 120 mm water equivalent (w.e.) year −1 ) and South Greenland (Ikerasassuaq: c. 2300 mm w.e. year −1 ), respectively. The coastal meteorological stations showed on average increasing trends for 1890–2012 (3.5 mm w.e. year −2 ) and 1961–2012 (1.3 mm w.e. year −2 ). Years with high coastal annual precipitation also had a: (1) significant high number of precipitation days ( r 2 = 0.59); and (2) high precipitation intensity measured as 24-h precipitation ( r 2 = 0.54). For the GrIS the precipitation estimated from ice cores increased on average by 0.1 mm w.e. year −2 (1890–2000), showing an antiphase variability in precipitation trends between the GrIS and the coastal regions. Around 1960 a major shift occurred in the precipitation pattern towards wetter precipitation conditions for coastal Greenland, while drier conditions became more prevalent on the GrIS. Differences in precipitation trends indicate a heterogeneous spatial distribution of precipitation in Greenland. An Empirical Orthogonal Function analysis reveals a spatiotemporal cycle of precipitation that is linked instantaneously to the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation and with an ∼6 years lag time response to the Greenland Blocking Index.

Description: ABSTRACT Using surface meteorological data at 20 sites in Beijing area during 1961–2007, the variability and trend of surface solar radiation (SSR) and their potential drivers were investigated. Cloud cover was an important factor determining the interannual variation of SSR reflected in the linear correlation coefficients ( R ranged from −0.65 to −0.89) between interannual variations of SSR and cloud cover. Aerosol optical depth (AOD) also contributed to the interannual variability of SSR, as shown by negative correlations between AOD and SSR ( R ranged from −0.44 to −0.81). SSR decreased by 2.29 (winter), 3.63 (spring), 7.45 (summer), and 3.76 W m −2 (fall) per decade during 1961–2007. The observed decrease in cloud cover should have resulted in solar brightening instead of dimming, indicating that cloud cover is not the driver of the long-term trend of SSR. AOD was observed to increase by 0.02–0.04 per decade, which was consistent with the SSR trend. Therefore, we argue that AOD, instead of cloud cover, is the major driver of the long-term SSR trend in Beijing metropolitan area. The largest dimming was observed in urban sites as a result of the largest increased AOD trend observed there. SSR trends in rural sites were about 30%–54% of the trends in urban stations, which was mostly due to the smaller decreasing AOD trends that were observed in rural sites.

Description: ABSTRACT A study of electrically severe thunderstorms (〉2000 cloud-to-ground flashes per day) in the Spanish territory of Castilla-Leon (northern plateau of the Iberian Peninsula) has been performed using 11 years (2000–2010) of data. These episodes were classified according to average upper-level synoptic patterns. Seven synoptic patterns emerged: shortwave and very shortwave troughs, three types of lows, cyclonic vortex and ridge. The moisture content at low levels and static instability were also considered. In general, all the episodes were associated with instability and moderate moisture (11 g kg −1 for the average mixing ratio at 925 hPa). The electrically severe thunderstorms associated with five synoptic patterns (shortwave and very shortwave troughs, and three types of lows) generated hail, strong winds, and intense precipitation. By contrast, the cyclonic vortex and ridge synoptic types were not associated with severe weather.

Description: ABSTRACT Projections of future climate conditions are carried out by many research institutions, each with their own general circulation model to do so. The projections are additionally subjected to distinct anthropogenic forcings, specified by future greenhouse gas emissions scenarios. These two factors, together with their temporal effects and interaction, create several potential sources of variation in final climate projection output. Multilevel statistical models, and specifically multilevel ANOVA, have come to be widely used for many reasons, not least of which is their ability to comprehensively assess many different sources of variation. In this article, a Bayesian multilevel ANOVA approach is applied to climate projections to assess each of these sources of variation, estimate the uncertainty regarding the assessment, and to allow comparison across all sources. The data originate from phase three of the Coupled Model Intercomparison Project (CMIP3), consisting of 11 circulation models and three emissions scenarios over nine decadal time periods for boreal summer and winter. Data from the next phase, CMIP5, is now becoming available. As this approach towards ANOVA is relatively novel, and particularly so for spatial data, a short discussion of conventional ANOVA and the new methodology is provided.

Description: ABSTRACT Both land-cover/land-use change (LCLUC) and greenhouse gas (GHG) concentrations have been shown to influence regional climate, albeit at different spatial scales. In East Africa, climate changes due to changing GHG concentrations are broadly projected to be warmer and wetter. LCLUC projections include trends towards both agricultural intensification and agricultural expansion into savannas, which may result in complex climate interactions and impacts. The primary objective of this study was to examine the regional responses to future GHG, LCLUC, and their combined effects in East Africa, and to better understand how hydrometeorological mechanisms might be altered by LCLUC in future scenarios. In this study, we present high-resolution decadal simulations from a regional climate model that compare the relative and combined effects of projected LCLUC and GHG. This research suggests that taken separately, these two climate forcings may significantly alter regional precipitation patterns both temporally and spatially but in potentially different and independent ways. In combination, some portions of the region exhibit responses dominated by either LCLUC or GHG effects, but certain areas show complex effects resulting from the combined influence of these two forcings. Perhaps most importantly, the results suggest that projected precipitation changes around major population areas may be as strongly influenced by LCLUC as by GHG effects.

Description: ABSTRACT Austral summer rainfall trends are analysed over South America from observations and simulations of the Coupled Model Intercomparison Project version 5 between 1902 and 2005. Positive trends in southeastern South America (SESA) and negative ones in the southern Andes (SAn) are the most significant observed features. Mean trends obtained from an ensemble of 59 simulations from 14 models for the historical experiment (including both natural and anthropogenic forcings) are able to reproduce those precipitation changes, although weaker than observed. Most of the simulations reproduce the right sign of the precipitation changes at both regions. However, associated uncertainty ranges (due to both inter-model dispersion and internal climate variability) are still large. Mean trends for the historical experiment are statistically distinguishable from those obtained for the natural-forcing-only experiment, which exhibit negligible mean values at both regions. Results allow concluding that the anthropogenic forcing has at least a partial contribution in explaining the precipitation changes observed in both SESA and SAn regions during the last century.

Description: ABSTRACT We discuss the value of a clustering approach as a tool for evaluating daily rainfall output from climate models. Ascendant hierarchical clustering is used to evaluate how well South African recurrent daily rainfall patterns are simulated during the austral summer (December to February 1970–1971 to 1998–1999). A set of 35-km regional climate simulations, run with the WRF model and driven by the ERA40 reanalysis, is chosen as a case study. Six recurrent patterns are identified and compared to the observed clusters obtained by applying the same methodology to 5352 daily rain gauge records. Two of the WRF clusters describe either a persistent and widespread dryness (65% of the days) or patterns similar to the seasonal mean rainfall gradient (13% of the days). The four remaining WRF clusters (∼20% of the days) are wetter; they describe the weakening, conservation or strengthening of the average rainfall gradient. The WRF cluster rainfall patterns and their associated circulation match the observed clusters rather well, but their frequency of occurrence is greatly overestimated by WRF during dry events, and underestimated for near-normal rainfall conditions. The weak model biases found at the seasonal timescale conceal strongly biased intraseasonal rainfall variability. The WRF-simulated rainfall patterns are then temporally or spatially projected on to the observed clusters. Spatial projection proves to be the more useful of these two approaches in quantifying model skill by assessing both the temporal co-variability between WRF and observations, and the rainfall biases of the model with or without temporal dephasing. The WRF model simulates transient rainfall activity partially out of phase with observations, which induces large rainfall biases when temporal dephasing is not removed. Rainfall biases are significantly reduced, however, when temporal dephasing is removed. The clustering approach therefore proves its efficiency to highlight climate model strengths and deficiencies.

Description: ABSTRACT In this study, circulation types, their long-term mean occurrence frequencies and relationships with precipitation are investigated for the region Marmara, which is the most populated, agriculturally developed and industrialized area in Turkey. Automated Lamb Weather Types classification method is applied on NCEP/NCAR daily mean sea level pressure data to determine the circulation types. Northeasterly (NE) and easterly (E) types are found to be the most frequent both on the annual basis and during winter (DJF, the wettest season in the region). Circulation types with the highest rainfall potential, namely the cyclonic (C) and the northerly (N), are among the least frequent; therefore they are not the dominant ‘rainfall modes’. Instead, NE and E have the greatest contribution to the regionally averaged rainfall amount, although they do not have the highest potential to create precipitation. This shows that Marmara Region receives a substantial amount of precipitation from northerly and easterly maritime trajectories, implying a profound influence of the Black Sea on the rainfall regime in this area. However, rainfall at the stations that are far away or less affected by the Black Sea (especially at the ones in the west) occurs during types with a southerly component (S, SW and SE). Our results reveal that, in Marmara Region, the response of precipitation to atmospheric circulation is rather complex and spatially inhomogeneous; in line with the complex topography of the area. Therefore, water management policies should be adopted accordingly, taking all local characteristics into account.

Description: ABSTRACT Mountain snow cover plays an important role in regional climate due to its high albedo, its effects on atmospheric convection, and its influence on runoff. Snowpack water storage is also a critical water resource and understanding how it varies is of great social value. Models are often employed to reconstruct snowpack and explore and understand snow cover variability. Here, we use a new, accurate satellite-derived snow product to evaluate the ability of the Weather Research and Forecasting (WRF) regional climate model, combined with the Noah land surface model with multi-parameterization options (Noah-MP), to simulate snow cover fraction (SCF) and snow water equivalent (SWE) in a 3-km domain over the central Sierra Nevada. WRF/Noah-MP SWE simulations improve on previous versions of the Noah land surface model by removing an early bias in snow melt, though a 2-day positive melt bias in SWE timing remains significant at the 90% confidence level. In addition, WRF/Noah-MP identifies the areas where snow is present to within 94.3% and captures large-scale variability in SCF. Temporal root mean squared error (RMSE) of the domain-average SCF was 1938.6 km 2 (24%). However, our study shows that WRF/Noah-MP struggles to simulate SCF at finer spatial scales. The parameterization for SCF fails to produce temporal variations in grid-scale SCF, and depletion occurs too rapidly. As a result, the WRF/Noah-MP SCF parameterization reduces to a binary function in mountain environments. Sensitivity tests show that adjustment of the parameterization may improve simulation of SCF during accumulation or melt but does not remove the bias for the entire snow season. Although WRF/Noah-MP accurately simulates the presence or absence of snow, high-resolution, reliable SCF estimates may only be attainable if snow depletion parameterizations are designed specifically for complex topographical areas.

Description: This study examines the Pacific meridional mode (PMM) simulated in the pre-industrial simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The spatial pattern and intensity of the PMM were found to be reasonably simulated by CMIP5 models, as was the subtropical atmosphere–ocean coupling associated with the PMM. However, the persistence of the coupling, which sustains the PMM's duration and extends its pattern equatorward, was found to be underestimated in most of the CMIP5 models. Many of the simulated PMMs do not have a pattern that extends far enough into the tropical Pacific to influence El Niño-Southern Oscillation (ENSO). The CMIP5 models that do produce longer persistence for the PMM coupling show a higher correlation of the PMM with the Central-Pacific (CP) type of ENSO than with the Eastern-Pacific (EP) type of the ENSO. This study concludes that (1) the PMM and its associated subtropical Pacific ocean–atmosphere coupling are important to the generation of the CP type of ENSO; (2) the so-called seasonal footprinting mechanism that sustains an equatorward extension of the PMM is not well simulated in a majority of the CMIP5 models; and (3) the persistence of the subtropical Pacific coupling is more important than the other properties in gauging a model's skill in the PMM simulation.

Description: ABSTRACT Changes in extreme precipitation are expected to be one of the most important impacts of climate change in cities. Urban floods are mainly caused by short duration extreme events. Hence, robust information on changes in extreme precipitation at high-temporal resolution is required for the design of climate change adaptation measures. However, the quantification of these changes is challenging and subject to numerous uncertainties. This study assesses the changes and uncertainties in extreme precipitation at hourly scale over Denmark. It explores three statistical downscaling approaches: a delta change method for extreme events, a weather generator combined with a disaggregation method and a climate analogue method. All three methods rely on different assumptions and use different outputs from the regional climate models (RCMs). The results of the three methods point towards an increase in extreme precipitation but the magnitude of the change varies depending on the RCM used and the spatial location. In general, a similar mean change is obtained for the three methods. This adds confidence in the results as each method uses different information from the RCMs. The results of this study highlight the need of using a range of statistical downscaling methods as well as RCMs to assess changes in extreme precipitation.

Description: ABSTRACT This study aims to assess the capability of regional climate models (RCMs) to simulate precipitation climatology over the southeastern Alpine flanks, where complex orography prevails. Precipitation simulations from 14 different 40-year downscaling experiments (1961–2000) driven by the ERA-40 reanalysis from the ENSEMBLES project are analysed in terms of realistic reproduction of spatial and temporal seasonal precipitation patterns over Slovenia. The best RCM performance was found for winter when precipitation is mainly caused by large-scale processes. A significantly lower model performance was observed for summer when precipitation is mainly caused by convective processes. Indeed, the largest spread of simulated precipitation between ensemble members was observed in summer, which is likely due to differences in the simulation of convective processes by the models. In addition, the simulations were analysed using partial least-square regression to quantify dependence of the simulated precipitation on physiographic factors. The applied regression model showed that orography and longitude are the most important variables associated with the spatial variability of precipitation in Slovenia. The empirical orthogonal functions were used to analyse the spatial patterns of inter-annual precipitation variability. The analysis showed that all models reproduced the most dominant mode of variability, but significant differences occurred between the models, especially in summer. In general, a thorough analysis has shown that the quality of simulations is highly variable among different regions as well as for different seasons.

Description: ABSTRACT This paper focuses on testing appropriate methods to produce gridded rainfall surfaces based on the daily rainfall observed at 43 meteorological stations in the Sichuan Province during rainy seasons of 2008–2013. Rainfall is extremely variable in both spatial and temporal distribution. Therefore, three methods, namely Ordinary Kriging (OK), Inverse Distance Weighting (IDW) and ordinary CoKriging (CK), have been selected and examined. First, we choose a suitable model by adjusting relevant parameters including the power exponent, the Neighbours to Include and the Include at Least. Then, cross-validation is used to verify the prediction performance of the three methods. The results for spatial interpolation of daily rainfall show that: (1) both OK and CK methods recorded smaller mean absolute error and the root-mean-square error than IDW method. (2) A preferable combination of assigning 2 to power exponent, 15 to Neighbours to Include and 5 to Include at Least is identified for IDW method. As for the best combination of OK and CK methods, Neighbours to Include is assigned with 15 while Include at Least almost has no effect on their performance. (3) CK is the optimal method for spatial interpolation of the daily rainfall in the rainy season of Sichuan.

Description: ABSTRACT Soil moisture dynamics and their temporal trends in the Czech Republic are forced by various drivers. The methodology of applying remotely sensed data with both high temporal and spatial resolutions provides detailed insight and objective quantification of the causes of changes in soil moisture patterns. Our analysis of temporal trends indicates that shifts in drought severity between 1961 and 2012 (especially in the April, May, and June period, which displayed a 50% increase in drought probability between 1961–1980 and 2001–2012) are alarming. We found that increased global radiation and air temperature together with decreased relative humidity (all statistically significant at the 0.05 level) led to increases in the reference evapotranspiration in all months of the growing season; this trend was particularly evident in April, May, and August, when more than 80% of the territory displayed an increased demand for soil water. This finding was shown to be consistent with the measured pan evaporation (1968–2012) that was characterized by increasing trends, particularly during the April–June period. These changes, in combination with the earlier end of snow cover and the earlier start of growing season (up to 20 days in some regions), led to an increased actual evapotranspiration at the start of growing season that tends to deplete the soil moisture earlier, leaving the soil more exposed to the impacts of rainfall variability. These results support concerns related to the potentially increased severity of drought events in Central Europe. The reported trend patterns are of particular importance with respect to the expected climate change, given the robustness and consistency of the trends shown and the fact that they can be aligned with the existing climate model projections.

Description: ABSTRACT The objective of this study was to investigate the changes in heavy precipitation and floods and the causes of flood risk changes in the Beijiang River basin in southern China. Peak flow, daily discharge, and precipitation data from 1969 to 2011 were examined. Trends were calculated using Sen's slope estimator. The statistical significance of the observed trends was checked with the Mann–Kendall method. Change points were detected using the Pettitt test and moving T -test methods. The hydrological periodicity was revealed by wavelet transformation. The results showed that the changes in monthly and monthly maximum 1- and 5-day precipitation and discharges during the flood season showed very similar characteristics. They experienced positive (negative) trends mainly in June–July (April, May, and August), and mostly did not experience significant change points. Compared with the period 1969–1990, monthly and monthly maximum 1(5)-day precipitation and discharges showed increasing (decreasing) trends, mainly in June–July (April–May) in 1991–2011. Overall, the changes in flood risk were mainly influenced by precipitation variability. However, human activity (including urbanization and the construction of reservoirs, soil and water conservation measures, and land use change, among others) have probably affected the flooding process in the study area. The decreases in peak flows during the late 1980s and early 1990s were probably caused by large-scale soil and water conservation measures. Construction of reservoirs in the past 20 years also played a role in the reduction of peak flows. The results of this study are of great scientific value to better understand the changing flood risk under the changing environment in the Beijiang River basin.

Description: ABSTRACT Monthly records for the period 1871–1970 from 91 stations across the British Isles are used to place very high rainfall totals during the 1870s, 1872 and 1876–1877 in particular, in context. Comparisons are drawn with 2012 and the winter of 2013–2014, both of which were exceptionally wet in parts of the British Isles. Traditional Lamb weather type count and objective measures of atmospheric circulation obtained from reanalysis of surface pressure charts are used to classify the weather conditions under which these very high rainfall totals were generated. The normally wettest locations in the British Isles, i.e. the uplands in the north and west, were not unusually wet in the 1870s, whereas locations with extremely high rainfall totals (relative to mean annual rainfall) tended to be further south and east in the lowlands. These exceptionally high totals were associated with a high frequency of cyclonic weather types and high scores for atmospheric vorticity; at the same time, the frequency of anticyclonic weather and of westerly winds tended to be very low. The winter of 2013–2014, remarkably wet in southern England, was somewhat different in that both the frequency of westerly air flow and the resultant flow were very high and so were vorticity and the frequency of cyclonic weather types; the year 2012 experienced similar atmospheric conditions. The results confirm the importance of cyclonic weather for large rainfall totals across much of the British Isles; strong westerly winds seem only to favour the uplands and northwest coastal locations.

Description: ABSTRACT Regional frequency analysis (RFA) may provide more accurate estimates of rainfall quantiles than at-site frequency analysis (ASFA), especially in regions with short records. In this study, RFA is applied to 1-, 2-, 3-, 6-, 9-, 12-, 15-, 18-, 24-, and 48-h annual maximum rainfall series at 67 sites in South Korea. Procrustes analysis is used to select 33 rainfall-related and geographical variables that represent most of the statistical information from among 42 candidate variables. Both factor analysis and cluster analysis, such as fuzzy c-means (FCM) and Ward's method, are used to identify the homogeneous regions, and five regions are identified through heterogeneity measures. It is found that FCM-based regions are more appropriate to the precipitation in South Korea in terms of the homogeneity of the identified regions. To investigate the effectiveness of FCM-based regions, region-of-influence approach was applied. It is shown that the spatial pattern of rainfall is affected by main mountain ranges, the prevailing Westerlies, and the proximity of the coast. Six distributions are applied, and the generalized extreme value distribution is selected as the best-fit distribution from goodness-of-fit measures. RFAs, such as the index flood method (IFM) and regional shape estimation based on the regional L-moments algorithm, are applied to determine the growth curves of regions. Using Monte-Carlo simulations, it is concluded that RFA is more accurate than ASFA for the annual maximum rainfall data of South Korea. The IFM provides more accurate estimates than regional shape estimation in homogeneous regions, while regional shape estimation is more appropriate for use in heterogeneous regions and in homogeneous regions with a lower L-CV (coefficient of L-variation) and for the estimation of quantiles in higher tails over a 100-year return period for the applied data.

Description: ABSTRACT In this study, the spatio-temporal variability and trends of droughts across Bolivia between 1955 and 2012 were investigated using two climate drought indices: the Standardized Precipitation Index (SPI), which is based on precipitation data, and the Standardized Precipitation Evapotranspiration Index (SPEI), which is based on the difference between the precipitation and the reference evapotranspiration (ETo). We found that the average drought conditions across the country showed a temporal behaviour mainly characterized by decadal variations. The spatial pattern of drought evolution showed marked differences between the Amazonian region and the Bolivian Altiplano. Both regions showed different drought periods, a lower frequency of drought variability in the Amazon region and trends towards drier conditions in the Altiplano, mainly due to a higher atmospheric water demand as a consequence of increased ETo. We also showed that inclusion of ETo, obtained from maximum and minimum temperature records, increased the spatial heterogeneity of the drought evolution in relation to the evolution observed when only precipitation droughts were considered. The SPEI, the calculation of which includes precipitation and ETo, indicated intensification in drought severity in the last years analysed relative to the pattern found when precipitation droughts alone were considered, and also indicated an increase in the magnitude and duration of drought events. The potential for increasing drought conditions under various climate change scenarios is discussed.

Description: ABSTRACT Limited research has been performed examining the relationships between southeast US wildfire and weather type patterns using modern techniques and data sets. The purpose of this article is to examine the relationship between wildfire ignitions in the central Gulf Coast, United States and weather type occurrences in an effort to identify regional patterns associated with wildfire ignitions. Wildfire occurrence data are obtained for nine national forests in the central Gulf Coast for the period 1970 to 2011. The Spatial Synoptic Classification scheme (SSC) is used to classify daily weather type variations for each national forest. Years with high numbers of ignitions experience statistically higher numbers of dry tropical (DT) weather types than years with low numbers of ignitions in five of nine national forests. These differences range from 17 to 160% more DT days during periods of high ignitions. Statistically significant positive Spearman rank correlations exist between annual number of ignitions and annual number of DT days in a given forest. While understanding such relationships on an annual scale is useful, it says nothing about the actual timing of weather types leading up to an ignition. An analysis of weather type activity 30, 90, and 180 days prior to ignitions reveals that the median ratio of DT days to moist moderate (MM) and moist tropical (MT) days is statistically higher for periods leading up to a fire. Positive phases of the North Atlantic Oscillation (NAO) result in an increased number of DT days. This confirms previous studies that have suggested the strength of the westerlies increases during the positive phase of the NAO, driving DT weather types eastward from their southwest US/Mexico source region. We can therefore also conclude that the positive phase of the NAO is linked with increased wildfire activity in the central Gulf Coast, United States.

Description: ABSTRACT Previous tornado climatology research has relied primarily upon a mean value of tornadoes or tornado days fixed on one period to define regions of elevated tornado risk. However, a more comprehensive understanding of the climatological distribution of tornadoes is achieved by analysing the spatial and temporal variability of tornado days. Two methods of analysing tornado days for predefined areas across the continental United States using a refined version of the Storm Prediction Center's tornado data set for 1950–2011 are considered in this study. Statistical analyses of averages and return periods reveal the variability in the record, while consecutive tornado days present an alternative method to assess the seasonal repeatability and risk for historic, multi-day tornado outbreaks. The results of this research better define the climatological variability of tornado events in addition to offering insight regarding the spatial patterns of locations with the greatest tornado risks, especially those with higher interannual variability.

Description: ABSTRACT Theoretical probability distributions of seasonal rainfall totals have potential applications in fitting models and generating synthetic data. One of the major challenges in fitting distributions for seasonal rainfall from countries like Australia is that the data differ significantly for various seasons across stations. The wet stations may possess strictly positive rainfall amounts only, whereas dry stations may observe seasons with no rainfall. Furthermore the data ranges from approximately symmetric to highly skewed. We explore fitting distributions from the Tweedie family of distributions to model seasonal rainfall. The Tweedie family of distributions includes continuous-symmetric (normal), continuous-skewed (gamma) and mixture-type (Poisson–gamma, P–G) distributions. This study analysed seasonal rainfall totals from 989 Australian stations with data for about 100 years. For various seasons, within the Tweedie family the P–G distributions were optimal for about 50% of stations, the gamma distributions were near-optimal for approximately 40% and the normal distributions were near-optimal elsewhere. Most of the stations where the gamma distributions are near-optimal are concentrated on the Australian coastline. The quantile–quantile (QQ) plots indicate that the models fit well to the seasonal rainfall totals of selected stations. Almost everywhere, various statistics of observed seasonal rainfall are within the empirical 95% confidence intervals of the respective statistics of simulated data using the Tweedie models. The model performs better in modelling extremely high rainfall events (95th percentiles) than the extremely low (5th percentiles) rainfall events. In addition, the P–G distribution within the Tweedie family models the probability of no rainfall and, for about 97% of stations, the observed probability of no rainfall is within the 95% confidence interval of the simulated probability of no rainfall. The ability of the Tweedie models to simulate the extreme rainfall amounts and the probability of no rainfall can be useful in drought monitoring and in water resources planning and management.

Description: ABSTRACT The improvements in representing the Indian summer monsoon features are assessed using the latest coupled global reanalysis, the climate forecast system reanalysis (CFSR) from National Centre for Environmental Predictions (NCEP) with respect to widely used NCEP-reanalysis 2 (NCEP2). To validate the reanalysis product corresponding observations are also used. CFSR is more realistic in terms of spatial pattern of seasonal mean rainfall, first and second empirical orthogonal function (EOF) modes of interannual variability as compared with NCEP2 reanalysis. Percentage of total variance was explained by northward and westward propagating intraseasonal oscillation modes in CFSR that are better captured than those from NCEP2 reanalysis. Northward propagating mode is well depicted in CFSR as compared with that of NCEP2 and may be attributed to the strong vertical shear of zonal wind and strong meridional gradient of specific humidity in CFSR. Distribution of the north–south and east–west spectra of CFSR suggests much better conformity with observation as compared with NCEP2. Surface wind patterns of CFSR are having relatively small errors compared to Quick Scatterometer (QuikSCAT) winds. CFSR has some success in simulating observed sea surface temperature (SST)–rainfall relationship as well as in depicting the coupled ocean-atmosphere phenomena of El Niño and Southern Oscillation (ENSO) in terms of Indian summer monsoon rainfall (ISMR) teleconnections. Overall monsoon features in CFSR are much closer to the observation as compared with NCEP2, and these may be because of the realistic representation of ocean–atmosphere feedback owing to the coupled model-based reanalysis. This study will help in establishing the credibility of the CFSR in terms of realistic representation of Indian summer monsoon as compared with widely used atmospheric only reanalysis.

Description: ABSTRACT Previous research highlights the dominant role of Pacific sea surface temperatures (SSTs) and their associated large-scale teleconnections in modulating the North American monsoon (NAM). At the regional scale, feedbacks associated with land-surface boundary conditions have been shown to provide ‘memory’ in the system. Here, a previously unexplored second-order linkage between aerosol generated by late-spring wildfires and subsequent summer precipitation delivered by the NAM in the Arizona-New Mexico (AZNM) region is proposed. Correlations between June/July organic carbon and elemental carbon (OC/EC) in Inter-agency Monitoring of Protected Visual Environments (IMPROVE) aerosol data (Gila Wilderness and Bandelier) and NAM precipitation in southern AZNM over the period 1994–2012 are shown to be negative ( r  = –0.4), suggesting that active antecedent wildfire seasons tend to be immediately followed by a weak late summer monsoon. This result is consistent with a previous study linking precipitation and area burned in wildfires in AZNM. A survey of extant literature suggests a sound basis for potential mechanisms related to convective processes and cloud microphysics, and furthermore suggests that this forcing could be of similar magnitude to well-documented land-based second-order NAM forcings (antecedent snowpack and soil moisture, vegetation, and mineral dust). Based on these results, we believe that the role of aerosols in modulating summer precipitation deserves further investigation both observationally and in modeling studies. If indeed wildfire smoke does contribute to the modulation of NAM intensity, by virtue of its close temporal association with NAM season, it may well represent a factor that could contribute effectively to improved seasonal prediction of summer precipitation in the NAM region.

Description: ABSTRACT Polar front jet stream variability is responsible for instances of extreme weather and is crucial for regional climate change. The North Atlantic Polar Front jet stream is of particular significance to the heavily populated areas of western Europe and eastern North America as storm track variability, atmospheric modes of variability such as the North Atlantic Oscillation (NAO), temperature and rainfall are all intimately linked with jet stream changes. Although seasonal and interannual variability are often attributed to internal variability, there are several possible drivers of polar front jet stream changes that are reviewed in this study. Cryospheric effects from sea-ice extent and snow cover, oceanic effects from North Atlantic sea-surface temperatures and tropical influences such as the El-Niño Southern Oscillation, and stratospheric effects due to stratospheric circulation variability, solar variability, volcanic eruptions and the Quasi-Biennial Oscillation are all identified in the literature as factors that impact on the Atlantic Polar Front jet stream. These drivers of jet stream variability can oppose or reinforce one another, and there are some indications of possible nonlinear interactions between them. We also review the modelling of jet stream variability. While a consensus has now been reached that some observed drivers can be reproduced in climate models, we conclude that improved understanding of more recently identified drivers of the Atlantic extratropical jet stream is crucial for making progress in regional climate predictions on all timescales from months to decades ahead.

Description: ABSTRACT The Arabian Sea and Bay of Bengal (BoB) regions are special interested sea areas in the Northern Hemisphere with large seasonal variability. This study focused on the long-term wind and wave in the central BoB from 1979 to 2012 based on the ECMWF ERA-Interim reanalysis data sets. Data were validated with the nearest available buoy data for the years 2003, 2004 and 2005, and good correlation was observed (root mean square error ≈ 0.17–0.43 m). A clear seasonality was noted with intensified wind and waves during the southwest monsoon season. We observed statistically declining trends in the mean and extreme wind speed (90th percentile) with increasing trend in extreme significant wave height (SWH). Seasonal analysis also investigated and found that the stronger events/winds during the southwest (SW) monsoon season are weakening. Conflicting trends in the wind and wave height were mainly due to the swell dominance at the region which was identified by the separate trend analysis of wind-sea and swell height. The area average analysis is carried out to investigate the sensitivity of the identified trend results for the point location and found similar trends for extreme wind speed and SWH. The high (〉5 m) annual maximum SWH in the study area was attributed to the influence of tropical cyclones in the BoB, and all of these high waves occurred before 1996 indicating that the influence of tropical cyclones in the study area decreased after 1996.

Description: ABSTRACT Despite earlier studies over various parts of the world including equatorial Eastern Africa (EEA) showing that intraseasonal statistics of wet and dry spells have spatially coherent signals and thus greater predictability potential, no attempts have been made to identify the predictors for these intraseasonal statistics. This study therefore attempts to identify the predictors (with a 1-month lead time) for some of the subregional intraseasonal statistics of wet and dry spells (SRISS) which showed the greatest predictability potential during the short rainfall season over EEA. Correlation analysis between the SRISS and seasonal rainfall totals on one hand and the predefined predictors on the other hand were initially computed and those that were significant at 95% confidence levels retained. To identify additional potential predictors, partial correlation analyses were undertaken between SRISS and large-scale oceanic and atmospheric fields while controlling the effects of the predefined predictors retained earlier. Cross-validated multivariate linear regression (MLR) models were finally developed and their residuals assessed for independence and for normal distribution. Four large-scale oceanic and atmospheric predictors with robust physical/dynamical linkages with SRISS were identified for the first time. The cross-validated MLR models for the SRISS of wet spells and seasonal rainfall totals mainly picked two of these predictors around the Bay of Bengal. The two predictors combined accounted for 39.5% of the magnitude of the SST changes between the July–August and October–November–December periods over the Western Pole of the Indian Ocean Dipole, subsequently impacting EEA rainfall. MLR models were defined yielding cross-validated correlations between observed and predicted values of seasonal totals and number of wet days ranging from 0.60 to 0.75, depending on the subregion. MLR models could not be developed over a few of the subregions suggesting that the local factors could have masked the global and regional signals encompassed in the additional potential predictors.

Description: ABSTRACT The Markov chain statistical technique was employed to fill few missing values of daily precipitation observed at nine long-term (≥50 years of data) climate stations of Western Canada. Statistical properties of the gap filled precipitation data are compared with those of the original data to ensure that this approach preserves the statistical characteristics of the historical data. After gap filling missing data, 10 precipitation indices that represent magnitude and frequency of precipitation properties were computed from those 9 stations and the other 20 stations without missing records. Next, the Wilcoxon rank-sum test was used to detect possible change points of these precipitation indices. Based on the analysed results, there had been an increasing trend in the maximum number of consecutive wet days and the annual maximum 1-day precipitation and a decrease in the maximum number of consecutive dry days over most of British Columbia (BC). The annual total precipitation index of many stations had increased in southern BC and decreased in central parts of Canadian Prairies. Similar change was detected in the number of days when precipitation is equal and greater than 10 or 20 mm, and indices for the annual monthly maximum 1-day precipitation – precipitation that exceeds the 95 and 99 percentiles – and the simple precipitation intensity index. On the basis of the above results, the diurnal temperature range (DTR) of Western Canada has decreased, and predominant negative correlations between precipitation indices and DTR, it seems that Western Canada has generally become wetter since the middle of the 20th century partly because increase in the minimum daily temperature has been higher than the increase in the maximum daily temperature, leading to a decrease in DTR, which is likely related to climatic warming.

Description: Surface greenness and rainfall in spring have changed from the 1980s to 1990s over the North China Plain (NCP). The greenness changes are characterized by large increase in north and little in south with an obvious greening zone from the centre of the NCP to the northeast. The rainfall change has a similar spatial pattern with reversed sign. The correlation between changes in greenness and rainfall is significant and the correlation ( r  = −0.71, p  〈 0.001) is highest for light rainfall. The number of light rainfall days decreased by only ∼10% at the stations where the Normalized Differences Vegetation Index (NDVI) did not change, whereas it decreased by up to ∼30% at the stations where NDVI increased by 20%. Further analyses found that surface greening increased evaporation wetting the atmosphere and, meanwhile, reduced sensible heat flux to cooling surface air. The cooling surface promotes the air stability and thus suppresses the occurrence of rainfall. This finding supports that surface cooling effects from greening play a more dominant role on occurrence of spring rainfall than the wetting effect in the NCP.

Description: ABSTRACT Isobaric equivalent temperature ( T E ) is the temperature that an air parcel would have if all associated water vapour were condensed and the resulting latent heat used to increase the temperature of the parcel. It is therefore an ideal metric for assessing changes in (1) total near-surface heat content associated with both temperature and moisture content and (2) the joint behaviour of temperature and humidity, which is relevant to both lower atmospheric stability and human heat stress during extreme temperature events. We present results from an analysis of 50 years (1961–2010) of daily T E and its temperature and moisture components at seven stations in the central United States. The annual means of daily T Emax and T Emin increased at all stations during the period of analysis with the largest changes occurring in T Emin , largely as a result of increasing minimum air temperature. At western locations significant increases in the annual mean T Emax were also observed, resulting from a combination of increases in T max and humidity. Despite small summer (JJA) trends in maximum air temperature, summer T E trends were generally larger than their annual counterparts. The timing of the observed variations and the resulting spatial pattern are consistent with observed changes in meridional moisture flux associated with the Great Plains low-level jet. Heat waves in the region were found to be characterized by increasing T Emin , primarily resulting from increases in minimum air temperature. At western stations, heat waves were also characterized by increasing T Emax as a result of positive trends in humidity. In most cases, equivalent temperature provides a perspective on local environmental change that differs from what is provided by consideration of temperature alone.

Description: ABSTRACT Very small glaciers (area 〈0.1 km 2 ) have received increased scientific attention during recent years, both for their rapid responses to the climate forcing and because they are characterized by microclimatic conditions, often marginal to glacier formation. They are particularly sensitive to climate changes and characterized by a great mass turnover, particularly evident in maritime areas with high precipitation. Here we consider the evolution from 1920 of the ‘Canin Eastern Glacier’ (Italian Southeastern Alps) in order to correlate its evolution to the precipitation–temperature trends. We reconstructed a precipitation–temperature record at the altitude of the glacier, filling a lack of knowledge in this alpine sector. We observed a decrease in the mean annual precipitation of 10% in 90 years and a warming trend of 0.1°C decade −1 since 1851, and of 0.7°C decade −1 in the last 20 years. An inverse correlation between precipitation and mean air temperature during summer and ablation periods was also observed. Glacier dynamics revealed a phase of stability between 1945 and 1985 that seems to be a peculiar characteristic of this area. Moreover, through a general regression model the glacial terminus variations seem to be statistically influenced only by winter precipitation. This fact opens interesting perspectives for the possible future evolution of this small glacier and, more in general, to other small glaciers in maritime areas in regard to climate change scenarios.

Description: ABSTRACT Extratropical cyclone (ETC) tracks across eastern Canada are examined by applying a Lagrangian tracking algorithm to the lower-tropospheric relative vorticity field of reanalysis data. Both the seasonal cycle and the interannual variability of ETCs are quantified in terms of overall cyclone frequency, intensity, and regions of development and decay. We find that ETCs travelling to eastern Canada tend to develop over the Rockies, the Great Lakes and the US East Coast. The ETCs are most intense over Newfoundland and the North Atlantic Ocean, confirming previous findings. While ETCs at cities along the Atlantic coastline (e.g. St. John's) are dominated by East Coast cyclones (which are intense in winter), those inland (e.g. Toronto) track primarily from the Great Lakes. ETCs that develop over the Gulf of Mexico affect eastern Canada infrequently, but those that do tend to be intense. The interannual variability of the wintertime ETCs is influenced by the El Niño-Southern Oscillation (ENSO). Significant ENSO-related variability is found over most regions of southern Canada, except on the east coast. Although ETCs at Toronto are significantly modulated by ENSO, no visible changes are found at St. John's. These ENSO-related ETC changes are mostly due to the shifts in ETC development regions, with minor changes in the travelling direction of ETCs.

Description: ABSTRACT Despite the many improvements that have been achieved in prediction methods, considerable uncertainties in the models and the observing systems remain in El Niño Southern Oscillation predictions. One of the uncertainties is the definition of El Niño and La Niña years. Because academia has accepted too many indexes, there is much confusion among scientists regarding whether El Niño and La Niña events have occurred. In the view of this author, the oceans on this planet can be vividly called ‘ocean stabilization machines’ (OSMs). When some part of an OSM loses control for unknown reasons, other parts of the OSM function stabilize the atmospheric circulation. As a result, El Niño or La Niña events occur. In this study, we use a most-recognized principle to determine El Niño (La Niña) years based on a K-line diagram technique. This technique not only focuses on the anomaly of five accepted indexes, but also aims at the signals of an on-going crash downward or a dramatic upward tendency of the sea-surface temperature. To achieve this purpose, a new terminology, ‘suspected El Niño (La Niña) years’ and an Ocean Stabilization Index (OSI) expressing the state of the Pacific are proposed. The results indicate that there were only 10 El Niño years and 12 La Niña years from 1950 to 2012. Significant statistical relationships between the annual OSI and 14 indexes are also found.

Description: ABSTRACT Fundamental changes in the hydrological cycle are to be expected in a future warmer climate. For Switzerland, recent climate change assessments based on the ENSEMBLES regional climate models project for the A1B emission scenario summer mean precipitation to significantly decrease by the end of this century, whereas winter mean precipitation tend to rise in Southern Switzerland. From an end-user perspective, projected changes in seasonal means are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we investigate the projected changes in seasonal precipitation by considering changes in frequency and intensity, precipitation type (convective vs stratiform) and temporal structure (wet and dry spells) over Switzerland. As proxies for rain-type changes, we rely on the parameterized convective and large-scale precipitation components simulated by the models. The study reveals that the projected summer drying over Switzerland at the end of the century is mainly driven by a widespread reduction in the number of precipitation days. Thereby, the drying evolves altitude-specific: over low-land regions it is associated with a decrease in both convective and large-scale precipitation. Over elevated regions it is primarily associated with a decline in large-scale precipitation only, whereas convective precipitation remains at current levels. As a consequence, almost all the models project an increase in convective fraction at elevated altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in the number of multi-day wet (dry) spells. This future shift in multi-day episodes also lowers down the likelihood of short dry spell occurrence in all of the models. The models further project a higher mean precipitation intensity in spring and autumn north of the Alps, whereas a similar tendency is expected for the winter season over most of Switzerland.

Description: ABSTRACT Given the availability of a new generation of general circulation model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive, we attempt to evaluate the model output by using three variants of the transformed Mielke measure to assess (1) the performance of the models in simulating historical surface temperature and precipitation, (2) the climate change response of the models to future greenhouse gases (GHGs) scenarios, and (3) the consistency of the projected change of each model with that of the multi-model ensemble (MME) mean. Most models exhibited varying degrees of skills, depending on the region and season, whereas a few models were identified as performing well globally, including the CMCC models, IPSL-CM5A-MR, and BCC-CSM1.1M. Models with the highest and lowest climate sensitivities, as well as those that project future climate changes most resembling the MME mean, were identified. The future precipitation and temperature changes projected by the MPI models and NCAR-CESM1 models were found to best resemble the overall MME. Finer resolution was found to improve model performance in simulating historical climate in most regions and seasons, particularly for temperature; however, it does not have a significant effect on the response of model climates to future GHGs scenarios. We found that no model can simultaneously exhibits good performance in simulating historical climate and in projecting a future climate that is close to the MME mean. Determining the ‘best’ overall model is difficult because ‘best’ is dependent on the specific applications for which a model will be used. Evaluating climate models is an important step to build confidence in their application for impact assessment. Our study provides a basis for concerned groups choosing climate models for their subsequent studies.

Description: Statistical models for the seasonal prediction of hurricane strikes on the Eastern Seaboard of the United States (ESUS) are developed with the application of the statistical software (SAS) generalized linear model (GENMOD) to perform a Poisson regression linked by a logarithmic function. Preseason climatic/oceanic signals of the El Nino South Oscillation (ENSO), the Atlantic Meridional Mode (AMM), the Atlantic Multi-decadal Oscillation (AMO), Sahel rainfall (20°–10°N, 20°W–10°E) and the North Atlantic sea surface temperature (SST) across a selected domain, all of which are closely associated with the dominant principal components of the North Atlantic Hurricane Track Density Function (HTDF), are applied as predictors. While using the Poisson regression without dividing the season into differing levels of activity types greatly degrades the model, classification of season types [based on accumulated cyclone energy (ACE)] before using the Poisson regression, can significantly improve the model performance. With this proposed new methodology, landfall counts in hyperactive and above-normal season type years can be predicted with 56.01 and 71.36% skill improvements respectively, compared with merely using climatology.

Description: ABSTRACT Climate-induced changes in the annual regime of snow-fed rivers have serious implications for water resource management. In the Central Andes (CA, 28°–36°S) of Argentina–Chile, the snow accumulated in high-elevation mountains in winter is the dominant component of streamflows during the spring–summer melting season. Although topography introduces complexity in snowpack responses to the annual temperature cycle, streamflow series over a century in length make the CA particularly suitable for identification of long-term hydrological changes. Principal component (PC) analysis of Río Atuel annual hydrographs from 1906 to 2012 discriminates between precipitation- and temperature-related components associated with variations in snow accumulation (49% of variance) and advances/delays of the streamflow annual peak (21% of variance), respectively. The temporal evolution of PC1 loadings reveals a predominant negative period from 1917 to 1976 and from 1988 to present, suggesting the propensity to undergo long periods with reduced flows. In turn, the PC2 pattern is predominantly positive from 1948 to the present, revealing a tendency to more frequent peak flows in late spring since the mid-20th century. Above-average streamflows related to abundant snowfalls in the CA are associated with northward shifts in stormtracks that are remotely induced by above-average sea surface temperatures in the equatorial Pacific. On the other hand, earlier streamflow peaks in November-December are concurrent with above-average temperatures across the Atuel basin induced by enhanced meridional circulation from the Tropics due to the strengthening of the South Atlantic anticyclone. These circulation anomalies are linked to the persistent positive phase of the Southern Annular Mode during the last decades. Additionally, years with reduced streamflows in January, and proportionally larger flow contributions in November-December, are associated with anomalous air cooling at high levels induced by low pressure centres over the region as part of a quasi-zonal stationary Rossby wave train that extends from Australia to the South American–South Atlantic sector.

Description: ABSTRACT Water vapour, an important greenhouse gas in the atmosphere, is crucial for hydrological, atmospheric, and meteorological processes. This study first compared five precipitable water vapour (PWV) products from multi-sensors including radiosonde, AERosol RObotic NETwork (AERONET) sunphotometer, Global Positioning System (GPS) and MODerate resolution Imaging Spectroradiometer (MODIS), and then characterized the spatial and temporal trends of PWV in mainland China. Intercomparison results indicate good agreements among PWV products with correlation coefficients ranging from 0.775 to 0.937. As for spatial analysis, 13 years of MODIS MOD05 products were investigated and the spatial distribution of PWV is closely correlated with the topography, e.g. latitude and altitude, in mainland China. A monotonically increasing annual trend was detected in some radiosonde sites in China between 1976 and 1999, but a decreasing trend was observed between 2000 and 2012. Analysis of the differences in PWV between weekdays and weekends indicated a marked weekend effect, suggesting the influence of anthropogenic activities. Diurnal variations in PWV were also studied from 1999 to 2009 using GPS data. A pronounced diurnal cycle of PWV was observed in most of the sites during summer and spring seasons.

Description: ABSTRACT The two-fold utility (data projection and cluster analysis) of a two-phase batch self-organizing map (SOM) procedure (CP2) has been previously explored using the NCEP/NCAR geopotential height data for east Australia. That study focused on examining the performance of CP2 in comparison with a traditional cluster analysis procedure, CP1, for the purpose of synoptic typing. The present paper provides additional documentation on the implementation of CP2 for the same region, with broader considerations on the effect of SOM map size, seasonality, data standardization and the choice of neighbourhood functions. A total of 215 SOMs (classifications) were trained through CP2 with various data processing and parameter settings. The examination of these SOMs shows that the two-fold utility of CP2 leads to supplementary visualization of the dominant synoptic patterns over the study region. For SOMs of the same map size (i.e. number of synoptic types), cluster analysis via CP2 provides data groupings with relatively high accuracy and large separation but reduced level of pattern self-organization, while data projection via CP2 tends to create data groupings with a high level of pattern self-organization but reduced accuracy and separation. The choice of map size affects the accuracy, separation and self-organization of data groupings. As a compromise, a map size of 10–20 for cluster analysis and 20–30 for data projection is recommended for the study region. To account for the seasonality and latitudinal heterogeneity in the activity of synoptic systems, a relatively larger SOM size is needed to capture typical synoptic features prevailing in different seasons. Data standardization helps to provide a relatively balanced representation between larger-scale synoptic systems (e.g. anticyclones) and smaller-scale synoptic features (e.g. thermal lows), and also improves the level of pattern self-organization on the SOM across seasons. The additional documentation in this paper encourages a wider application of CP2 in environmental research.

Description: ABSTRACT In this study, statistical downscaling of general circulation model (GCM) simulations to monthly inflows of Kemer Dam in Turkey under A1B, A2, and B1 emission scenarios has been performed using machine learning methods, multi-model ensemble and bias correction approaches. Principal component analysis (PCA) has been used to reduce the dimension of potential predictors of National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. Then, the reasonable GCMs were selected by investigating the rank correlations between the selected predictors in NCEP/NCAR reanalysis data and those in GCMs for 20C3M scenario between periods 1979 and 1999. Upon the training of feedforward neural network (FFNN), least squares support vector machine (LSSVM) and relevance vector machine (RVM) downscaling models, the general performance of the downscaled predictions using NCEP/NCAR reanalysis data for Kemer watershed showed that the trained RVM model produced adequate results. The effectiveness of RVM model was illustrated by its integration with 20C3M scenario between periods 1979 and 1999 and A1B, A2, and B1 future climate scenarios between periods 2010 and 2039. Afterwards, the flow forecasts were obtained by building a multi-model ensemble through the selected GCMs followed by a bias correction approach. Finally, the significance of the probable changes in trends was identified through statistical tests based on the corrected forecasts. Results showed that decreasing flows trends in winter, spring and fall seasons have been foreseen over the study area for the period between 2010 and 2039.

Description: ABSTRACT High-resolution tree-ring records covering past centuries in the western Sichuan Plateau of China are scarce, yet essential for developing a complete understanding of the regional patterns of climate change for the Tibetan plateau. This paper presents a temperature reconstruction for the Wolong Natural Reserve of the western Sichuan Plateau based on a tree-ring width chronology of a cypress species ( Sabina saltuaria ) endemic to the Tibetan plateau. The annual (prior October to current September) temperature reconstruction, which spans from 1840 to 2011, was developed using a linear regression model. The reconstruction explains 54.1% of the actual temperature variance during the calibration period from 1956 to 2010. The noteworthy warming periods of the reconstruction occurred between 1864–1882 and 1927–1960, while the most pronounced cold episodes were found between 1886–1926, 1788–1822, and 1961–1996. Spectral analysis revealed the existence of multi-decadal, decadal, and annual cycles that might correspond to the related cycles of Atlantic Multidecadal Oscillation, solar activity, and ENSO-type variability, respectively.

Description: ABSTRACT In this study, a detailed spatial analysis of the reference evapotranspiration ( ET o ) estimates provided by the MAK-Adv approach and the well-known Penman-Monteith equation (PM-FAO56) has been carried out. MAK-Adv approach considers a regionally calibrated Makkink equation based on a combination of remotely sensed solar radiation, R s , provided by the Land Surface Analysis Satellite Applications Facility (LSA SAF), and numerical weather forecasts of near-surface air temperature, T 2m , provided by the European Centre for Medium-range Weather Forecasts (ECMWF). This analysis evaluated the performance of these approaches with data measured by 57 weather stations under different weather conditions within a semi-arid region, Andalusia, located at Southern Spain, and determined the role of certain physical and climate variables, such as wind speed and sensible heat advection, on the quality of the ET o estimation. For three years (2007–2009), daily R s and T 2m provided by LSA SAF and ECMWF were compared with measured data showing very good estimates, with RMSD equal to 1.47 W m −2 and 1.53 °C, respectively. Equally, ET o using MAK-Adv approach with data provided by LSA SAF and ECMWF was compared with ET o provided by the PM-FAO56 approach with measured data, obtaining RMSD = 0.69 mm, linear regression slope = 0.94, and R 2 = 0.92. Although ET o estimates using both approaches were similar between them, the small differences in terms of estimation ET o were mainly correlated with the wind speed ( u ) and the advection index ( I a ), depicting the critical role of these factors in the ET o estimations under semi-arid conditions, and increasing the uncertainty in ET o estimation when wind speed and/or I a are high. The comparison of MAK-Adv and PM-FAO56 approaches has proved the usefulness in providing ET o values at a regional scale and detecting those areas where the ET o estimation had higher uncertainty, contributing to an improvement in water management.

Description: ABSTRACT The estimation of large-scale evapotranspiration (ET) is complex, and typically relies on the outputs of land surface models (LSMs) or remote sensing observations. However, over some regions of Africa, inconsistencies exist between different estimations of ET fluxes, which should be investigated. In this study, we evaluate and combine different ET estimates from moderate-resolution imaging spectroradiometer (MODIS), Global Land Data Assimilation System (GLDAS) and terrestrial water budget (TWB) approaches over the Volta Basin, West Africa. ET estimates from water balance equation are obtained as residuals from monthly terrestrial water-storage (TWS) changes derived from Gravity Recovery and Climate Experiment (GRACE), Tropical Rainfall Measurement Mission (TRMM)'s rainfall data, and in situ discharge from Akosombo Dam (Ghana). An averaged estimation of ET time series is derived from all the ET estimations under study, while taking into account their uncertainties. The resulting ensemble-averaged ET was then used to assess each of the individual ET estimates. Overall, out of the seven investigated ET estimates (two from the water balance approach of which one considers water storage using GRACE-derived TWS and the other ignoring it, four from GLDAS and one from MODIS), only MODIS (28.12 mm month –1 ), GLDAS–NOAH (32.74 mm month –1 ) and TWB (32.84 mm month –1 ) were found to represent the range of variability close to the computed averaged reference ET (30.25 mm month –1 ). ET estimations inferred from MODIS were also found to represent relatively lower magnitude of uncertainties, that is, 3.99 mm month –1 over the Volta Basin (cf. 7.06 and 18.85 mm month –1 for GLDAS-NOAH and TWB-based ET estimations, respectively).

Description: ABSTRACT The sensitivity of regimes dominated by low clouds has been identified as the largest contributor to uncertainties in tropical cloud feedback estimates in climate models. The Atmospheric Model Intercomparison Project simulations of the low cloud response to sea surface temperature (SST) are compared with satellite observations in the southeastern Pacific subsidence region. The model ensemble annual average cloud fraction is only about 10% lower than Moderate Resolution Imaging Spectroradiometer observations; however, many models compensate by overestimating the cloud liquid water path (LWP), especially in areas typically associated with shallow cumulus. Analysis of the monthly distribution also shows that models have considerable difficulty in simulating the annual cycle in the cloud radiative effect (CRE), cloud fraction, and LWP likely due in part to underestimation of the strength of lower tropospheric stability and the depth of the boundary layer. The interannual sensitivity of CRE to SST agrees with observations in about half of the models, with the other half generally underestimating the cloud radiative forcing sensitivity. Model-observational differences are driven by the varying interannual responses in cloud fraction and LWP. Most models, including those that capture the mean interannual sensitivity of CRE to SST, have lower sensitivity in cloud fraction that is compensated by oversensitivity in the cloud LWP, especially in areas of more frequent shallow cumulus. Results presented here also highlight the possibility of using the vertical gradient of moist static energy (MSE) to test the fidelity of a model's representation of clouds and cloud sensitivity. Models that reproduce the observed distribution of cloud fraction with the lower tropospheric MSE gradient not only show better regional distribution and annual cycle in clouds and radiative forcing, but also demonstrate cloud and radiative sensitivities to SST that are more well correlated with the observed cloud sensitivities.

Description: ABSTRACT A World Meteorological Organization (WMO) committee evaluated the record sea-level pressure (SLP) measurement of 1089.4 hPa on 30 December 2004 in Tosontsengel, Mongolia (1724.6 m). Although instrumentation and data collection procedures were properly followed according to the assessment of the committee, concern was raised regarding the reliability of SLP adjustment from such a high-elevation station. This paper addresses this concern with a number of analyses that look at relationships between SLP extremes and corresponding station elevation and temperature. First, we selected data from stations extracted from the Integrated Surface Database (ISD-Lite) of NOAA's National Climate Data Center. A spatial analysis indicates that elevation shows little to no association ( R 2 values essentially zero) to extreme SLP. However, a second analysis between extreme SLP and air temperature indicates that high regionalism exists in spatial correlations (local R 2 ) between those two variables. This relationship to temperature is likely the result of differences in SLP adjustment formulae used around the world. Based on this analysis, on the need to differentiate the SLP values adjusted using extremely cold temperatures (and generally high elevation), and following past WMO SLP guidelines, the WMO Rapporteurs for Climate and Weather Extremes therefore have created two distinct SLP records: (a) highest adjusted SLP (below 750 m), currently 1083.3 hPa recorded on 31 December 1968 at Agata, Evenhiyskiy, Russia; and (b) highest adjusted SLP (above 750 m), currently 1089.4 hPa (by Russian method; 1089.1 hPa by WMO formula) on 30 December 2004 in Tosontsengel, Mongolia. Future WMO guidance regarding SLP adjustment may lead to re-evaluation of this and other SLP records.

Description: ABSTRACT We considered shifts in the Köppen climate zones and the corresponding impact on the crop yields in Serbia by comparing (1) the results of downscaling with the ECMWF Hamburg Atmospheric Model 5 (ECHAM5) and regional Eta Belgrade University (EBU)-Princeton Ocean Model (POM) model for the A1B and A2 scenarios over 2001–2030 and 2071–2100 and (2) the present climate simulations for the period 1961−1990. We analyzed the EBU-POM regional climate model complexity by calculating the corresponding metrics. The yields of winter wheat, maize and soybeans were evaluated with the Decision Support System for Agrotechnology Transfer (DSSAT) model. In the future, the Köppen climate zones of Serbia will shift in coverage percentage and altitude from the present climate simulations toward warmer and drier climate zones. The calculated climate indices feature changes in the following parameters: increases in the mean annual temperature, growing season temperature, number of growing degree days (higher than 5 °C) and the frequency of tropical days; and decreases in the mean annual precipitation, growing season precipitation and frequency of frost days. Yields of crops (winter wheat, maize and soybeans) will increase on average under both scenarios, with the exception of maize in non-irrigated conditions and under the A2 scenario.

Description: ABSTRACT Tree rings and documentary evidence are the most important palaeoclimatic archives with annual resolution that continuously span several centuries. Despite this benefit, local to regional-scale temperature reconstructions and their spatial signatures tend to be irregularly distributed, and the appropriate extent of low-frequency variability captured in these proxy records remains uncertain. Here, the first summer temperature reconstruction from the Czech Sudetes Mountains that extends to 1700 AD was introduced. An ensemble reconstruction approach using 251 new high-elevation spruce ring width samples suggests particularly cold June–July temperatures at the beginning of the 18th century, in the 1740s and around 1820. Markedly warm conditions occurred in the 1790s and during the most recent decades. The reconstructed decadal summer temperature amplitude from ‘Little Ice Age Cooling’ to ‘Recent Anthropogenic Warming’ ranges from −3.5 °C between 1700 and 1710 to 1.3 °C in 1999–2009, with respect to the 1961–1990 mean climatology. Comparison of our new reconstruction with existing tree-ring chronologies from the Alps reveals a significant level of coherency that is much higher than the agreement with geographically closer documentary evidence from Central Europe. Our study confirms the importance of independent regional climate reconstructions, which capture the full range of past variability and also fill spatial gaps in large-scale networks.

Description: ABSTRACT A total of 107 climate runs from 48 Coupled Model Inter-comparison Project 5 (CMIP5) general circulation models (GCMs) were evaluated for their ability to skillfully reproduce basic characteristics of late 20th century climate over Central America. The models were ranked according to metrics that take into consideration the mean and standard deviation of precipitation ( pr ) and surface temperature ( tas ), as well as the El Niño-Southern Oscillation (ENSO)- pr teleconnection. Verification was performed by comparing model runs to observations and a reanalysis dataset. Based on the rankings, the best 13 models were further evaluated. Not surprisingly, the models showed better skill at reproducing mean tas patterns throughout the year. The skill is generally low for mean pr patterns, except for some models during March, April, and May. With a few exceptions, the skill was low for reproducing the observed monthly standard deviation patterns for both pr and tas . The ENSO- pr teleconnection was better simulated in the best 13 model runs compared to the sea-surface temperature global pattern characteristic of ENSO which showed low skill. The Inter-tropical Convergence Zone (ITCZ) appeared better modeled in July than in January. In January, there were instances of a double ITCZ pattern. Some models skillfully reproduced the seasonal distribution of the Caribbean Low-Level Jet index (CLLJ). More detailed research evaluating the specific performance of the models on a variety of time-scales and using parameters relevant to these and other climatic features of Central America is needed. This study facilitates a pre-selection of models that may be useful for this task.

Description: ABSTRACT This study investigated the influence of the land–air temperature difference on spring rainfall over North China and its feedback mechanism by using station observations for the period 1951–2000 and the ERA-40 reanalysis for the period 1958–2002. The analysis identified a significant negative correlation between the land–air temperature difference and the spring rainfall over North China. The analysis results suggested that the sinking motion and northeasterly anomalies were dominated over North China. These anomalous northeasterly winds substantially weakened the amount of moisture supplied to North China and are helpful for a decrease in the humidity over North China. Moreover, the decrease in sea level pressure was caused by an increase in surface air temperature. The North China was located to the west of Low system where divergence and sinking motion were favoured. The results also suggested that the positive sensible heat flux anomalies and negative latent heat flux anomalies over North China were induced by an increase in the land–air temperature difference. The increase in surface downward solar radiation association with a decrease in low clouds may cause an increase in surface air temperature and decrease in relative humidity, which in turn contributed to a decrease in spring rainfall over North China. These results suggested that there was a strong negative feedback mechanism between the temperature difference and rainfall.

Description: ABSTRACT The European Mediterranean region is governed by a characteristic climate of summer drought that is likely to increase in duration and intensity under predicted climate change. However, large-scale network analyses investigating spatial aspects of pre-instrumental drought variability for this biogeographic zone are still scarce. In this study we introduce 54 mid- to high-elevation tree-ring width (TRW) chronologies comprising 2186 individual series from pine trees ( Pinus spp.). This compilation spans a 4000-km east–west transect from Spain to Turkey, and was subjected to quality control and standardization prior to the development of site chronologies. A principal component analysis (PCA) was applied to identify spatial growth patterns during the network's common period 1862–1976, and new composite TRW chronologies were developed and investigated. The PCA reveals a common variance of 19.7% over the 54 Mediterranean pine chronologies. More interestingly, a dipole pattern in growth variability is found between the western (15% explained variance) and eastern (9.6%) sites, persisting back to 1330 AD. Pine growth on the Iberian Peninsula and Italy favours warm early growing seasons, but summer drought is most critical for ring width formation in the eastern Mediterranean region. Synoptic climate dynamics that have been in operation for the last seven centuries have been identified as the driving mechanism of a distinct east–west dipole in the growth variability of Mediterranean pines.

Description: ABSTRACT Recent changes are found in the means and variability of the North Atlantic Oscillation (NAO) index. There has been a sustained significant recent decrease in the summer NAO since the 1990s and, at the same time, a striking increase in variability of the winter – especially December – NAO that resulted in three of five (two of five) record high (record low) NAO Decembers occurring during 2004–2013 in the 115-year record. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI, high pressure over Greenland) in summer and a more variable GBI in December. The enhanced early winter NAO variability originates mainly at the southern node of the NAO but is also related to the more variable GBI in December. Transition seasons (spring and autumn) have remained relatively unchanged over the last 30 years. These results are corroborated using several NAO indices. The Arctic Oscillation (AO) index, although strongly correlated with the NAO, does not show the recent sustained significant summer decrease, but it does show enhanced early winter variability. These recent observed changes are not present in the current generation of global climate models, although the latest process studies do offer insight into their causes. We invoke several plausible climate forcings and feedbacks to explain the recent NAO changes.

Description: ABSTRACT In this study, the atmospheric moisture sources affecting three sub-regions of East China, which are South China (SC), the middle and lower Yangtze River Valleys (YRV), and North China (NC), are identified and compared based on the simulation results of a Lagrangian particle dispersion model, FLEXPART, for the period 2000–2009. The investigation is conducted for ‘non-precipitation’ and ‘precipitation’ cases of summertime (May–September) and wintertime (October–April). Furthermore, the contributions of moisture originating from the land area, western Pacific Ocean, and Indian Ocean to the precipitation in the three sub-regions of East China are quantitatively estimated. The results indicate that during summertime, the transport of moisture from the Indian Ocean and western Pacific dominates the precipitation in SC, with almost equivalent contributions; evaporation over the land area seems to be the key contributor to the precipitation in YRV and NC, followed by the evaporation over the western Pacific. During wintertime, the precipitated moisture in SC originates largely from the western Pacific, while evaporation over the land area is the predominant contributor to the precipitation in YRV and NC. The results of this study indicate that the precipitation in the three sub-regions of East China reflect the contributions of the Indian monsoon and East Asian summer monsoon to different degrees.

Description: ABSTRACT Three homogenization software packages – AnClim, RhTestsV3 and HOMER – have been applied to monthly and annual temperature and pressure series from Portugal and its ex-colonies in Africa and Asia to detect non-climatic breaks. Homogenization tests in both absolute and relative mode were performed with an a posteriori statistical assessment to select the most probable breakpoints. Time series from neighbouring stations as well as reanalyses data were used as reference series. The reanalyses data sets were used due to lack of suitable neighbouring stations and also to test reanalyses as proxy data. A list of probable shifts is produced and will be used to support future global reanalyses. Moreover, temperature and pressure series were adjusted using adjustment factors that were obtained by calculating the difference between certain periods before and after the breaks. The accuracy of the adjusted series was verified subjectively (visually) and objectively using three verification methods: correlation coefficient, central root-mean-square error and standard deviation. A positive impact of the applied adjustment in terms of all three scores was found in a majority of cases.

Description: ABSTRACT This study employs Geographical Information Systems software to develop a classification system for typhoons (TYs) affecting Japan (1951–2011) and uses that system to investigate the spatial and temporal variations of storm tracks and their connection to the location and strength of the North Pacific subtropical high (NPSH). TYs coming within a 300-km buffer zone around the four main islands of Japan (JZOI) are grouped into two main types: those that remain on the Pacific Coast (PC) and those that enter the Japan Sea (JS). Results indicate that fewer TYs enter the JZOI when the NPSH extends strongly to the west and more reach Japan when it extends to the northwest. The winds around the periphery of the NPSH affect the recurvature of TYs directing them either west towards the China Mainland or around the western edge of the high towards Japan. More importantly, during periods when greater numbers of TYs affect the PC side of Japan (PC+), the NPSH extends to the southwest. However, during periods when greater numbers of TYs affect JS side of Japan (JS+), the NPSH extends to the northwest closer to Japan. The southwest extension of the NPSH enables TYs to recurve and pass to the eastern side (PC) of Japan while the northwest extension forces TYs around or across Japan into the JS. An important finding is that the moderately different positions of the NPSH change the atmospheric circulation around Japan dramatically and affect whether TYs pass over the PC side or the JS coast side of Japan. At the interannual time scale, increased JS+ years were observed since 1980 because of the frequent occurrence of the Pacific-Japan pattern. We also found that at the interdecadal time scale, PC+ years have increased due to the southwestward extension of the NPSH since 1980.