ALBERT

Description: 〈h3〉Abstract〈/h3〉 〈p〉Using the sub-seasonal to seasonal forecast model of Beijing Climate Center, several key physical parameters are perturbed by the Latin hypercube sampling method to find a better configuration for representation of Madden–Julian oscillation (MJO) in the free-run simulation. We find that although model simulation is especially sensitive to some parameters, there are overall no significant linear relationships between model skill and any one of the parameters, and the optimum performance can be obtained by combined perturbations of multiple parameters. By optimization, MJO’s spectrum, intensity, spatial structure and propagation, as well as the mean state and variance, are all improved to some extent, suggesting the correspondence and interrelation of model’s performances in simulating different characteristics of MJO. Further, several sets of initialized hindcasts using the optimized parameters are conducted, and their results are compared with the hindcasts using only improved initial conditions. We show that with an optimized model, the forecast of MJO beyond 3-week lead time is not improved, and the maximum useful skill is only slightly increased, implying that a decrease of model error does not always translate into an increase of forecast skill at all lead time. However, the skill is obviously enhanced during lead times of 2–3 weeks for forecasts in most seasons and initial phases except for a few cases. Particularly, the deficiency in forecasting MJO’s propagation from the Indian Ocean to the Pacific is relieved, further highlighting the positive contribution of reducing model error compared to previous work that only reduced initial condition error. In this study, we also show benefits of multi-scheme ensemble strategy in describing uncertainties of model error and initial condition error and thus improving MJO forecast.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The accurate characterization of seasonal and inter-annual site-level wind energy variability is essential during wind project development. Understanding the features and probability of low-wind years is of particular interest to developers and financers. However, a dearth of long-term, hub-height wind observations makes these characterizations challenging, and thus techniques to improve these characterizations are of great value. To improve resource characterization, we explicitly link wind resource variability (at hub-height, and at specific sites) to regional and synoptic scale wind regimes. Our approach involves statistical clustering of high-resolution modeled wind data, and is applied to California for a period covering 1980–2015. With this approach, we investigate the unique meteorological patterns driving low and high wind years at five separate wind project sites. We also find wind regime changes over the 36-year period consistent with global warming: wind regimes associated with anomalously hot summer days increased at half a day per year and stagnant conditions increased at one-third days per year. Despite these changes, the average annual resource potential remained constant at all project sites. Additionally, we identify correlations between climate modes and wind regime frequency, a linkage valuable for resource characterization and forecasting. Our general approach can be applied in any location and may benefit many aspects of wind energy resource evaluation and forecasting.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A new set of CORDEX simulations over South America, together with their coarser-resolution driving Global Climate Models (GCMs) are used to investigate added value of Regional Climate Models (RCMs) in reproducing mean climate conditions over the continent. There are two types of simulations with different lateral boundary conditions: five hindcast simulations use re-analysis as boundary conditions, and five other historical simulations use GCMs outputs. Multi-model ensemble means and individual simulations are evaluated against two or three observation-based gridded datasets for 2-m surface air temperature and total precipitation. The analysis is performed for summer and winter, over a common period from 1990 to 2004. Results indicate that added value of RCMs is dependent on driving fields, surface properties of the area, season and variable considered. A robust added value for RCMs driven by ERA-Interim is obtained in reproducing the summer climatology of surface air temperature over tropical and subtropical latitudes. Mixed results can be seen, however, for summer precipitation climatology in both hindcast and historical experiments. For winter, there is no noticeable improvement by the RCMs for the large-scale precipitation and surface air temperature climatology. To further understand the added value of RCMs, models deviations from observation are decomposed according to different terms that reflect the observational uncertainty, the representativeness error, the interpolation error, and the actual performance of the model. Regions where these errors are not negligible, such as in complex terrain regions, among others, can be identified. There is a clear need for complementary assessment to understand better the real value added by RCMs.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The model fidelity in simulating the Northern Hemisphere storm track interannual variability and the connections of this variability to the low frequency atmospheric variations and oceanic variations are examined based on the atmospheric European Centre for Medium-Range Weather Forecasts (ECMWF) model and coupled NCAR Community Climate System Model (CCSM) systems at different horizontal resolutions. The atmospheric general circulation model (AGCM) runs are forced by observed sea surface temperatures (SST) with varying atmospheric resolutions, while the coupled general circulation model (CGCM) runs have a fixed atmospheric resolution but varying oceanic resolutions. The phases, between the North Pacific (NP) and North Atlantic (NA) sectors, of the simulated hemisphere-scale Empirical Orthogonal Function (EOF) modes of the storm track fluctuations change with the model resolution, suggesting the storm track variability in NP and NA basins are largely independent. The models can qualitatively reproduce the basin-scale EOFs of both NP and NA storm track variability. These EOFs are not sensitive to either atmospheric or oceanic model horizontal resolutions, but their magnitudes from the CGCM runs are substantially underestimated. The storm track variations over NP basin are hybrid of internal atmospheric variations and external forcing from the underlying conditions, but the fluctuations over the NA basin are merely atmospheric internal variability. The NP storm track variability from SST forcing accounts for 4.4% of the total variance in observations, while it only has less than 2% of the total in all AGCM simulations. The external forcing to the storm track variations is more realistically reproduced in the higher atmospheric resolution runs. The air–sea coupling makes the SST feedbacks to the atmospheric internal variability, absent in the atmospheric ECMWF model hindcasts, emerge in the coupled CCSM simulations.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Urban land use in East China has undergone considerable change since the 1990s. How such change affects both in situ and remote climate conditions is investigated through numerical modelling experiments with the Community Atmosphere Model Version 5.1. The results show that urbanization causes an increase in surface temperature due to reduced surface albedo but a decrease in specific humidity due to locally reduced surface evaporation. The change in specific humidity overwhelms the surface temperature change effect, leading to locally reduced precipitation. It is noted that urbanization causes changes in climate conditions not only locally but also remotely. Anomalous low-level divergence associated with the reduced precipitation in situ prevents the northward progression of the East Asian summer monsoon. As a result, the major monsoon rain band is strengthened and confined over South China and the tropical Asian monsoon zone along 12°–25°N. The increase of rainfall in the tropical zone, on one hand, induces the local overturning cell, leading to anomalous subsidence over mid-latitude Asia and the equatorial zone, and, on the other hand, perturbs the Subtropical Jet, generating a Rossby wave train disseminating along the Jet. Both of these processes cause anomalous dry and hot conditions over mid-latitude Asia.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Uncertainties in future changes of temperature and precipitation over the homogenous monsoon regions of India are investigated using the CMIP5 and CESM-LE datasets. The uncertainty is partitioned into epistemic (model) and aleatoric (internal variability) components for each season using the RCP8.5 scenario. The uncertainty in temperature change is dominated by epistemic uncertainty that increases over time. The uncertainty in precipitation change shows a more complex picture. Aleatoric uncertainty can remain quite large and comparable to epistemic uncertainty till the latter part of the twenty-first Century especially during the JJA and SON seasons. Much of the rainfall uncertainty is in the more arid Northwest region with the West Central region (part of the core monsoon area) exhibiting lower uncertainties. Considerable increase in rainfall is seen during the SON season indicating an extended monsoon season. During the DJF season aleatoric uncertainty is much larger than epistemic uncertainty over much of the century and shows considerable decadal scale variability. Using the 40-member CESM-LE ensemble to analyze the influence of ensemble size on aleatoric uncertainty we find that low ensemble sizes can lead to an underestimate of the uncertainty.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉In this study, we investigate the role of the Asian summer monsoon (ASM) anticyclone in the distribution of ozone over the southern India and tropical Indian Ocean. We present the horizontal and vertical structure of ozone in the upper troposphere and lower stratosphere (UTLS) region. The analysis shows that the region within the ASM anticyclone has low ozone, and high tropopause altitude, as compared to the region outside the anticyclone during boreal summer. The southern edge of the ASM anticyclone, i.e. the southern India and tropical Indian Ocean show a remarkably high ozone concentration in the UTLS region during summer. Analysis of daily fields shows that ozone concentration in the upper troposphere over the southern India and tropical Indian Ocean increases with the strength of the tropical easterly jet, which is an outcome of ASM circulation. Different mechanisms responsible for the ozone enhancement in the UTLS region over the tropical Indian region have been discussed in this paper. The in situ ozonesonde observations from six Indian stations also support the space-based Aura-MLS observations, concluding that ASM anticyclone effectively transports ozone from the mid-latitude stratosphere to deep tropics. Shear generated turbulence and mixing in the vicinity of easterly jet also likely to play a minor role in the local ozone distribution.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Global climate is a multi-scale system whose subsystems interact complexly. Notably, the Tropical-Andean region has a strong rainfall variability because of the confluence of many global climate processes altered by morphological features. An approach for a synthetical climate description is the use of global indicators and their regional teleconnections. However, typically this is carried out using filters and correlations, which results in seasonal and inter-annual teleconnections information, which are difficult to integrate into a modeling framework. A new methodology, based on rainfall signal extraction using dynamic-harmonic-regressions (DHR) and stochastic-multiple-linear-regressions (SMLR) between rainfall components and global signals for searching intra-annual and inter-annual teleconnections, is proposed. DHR gives non-stationary inter-annual trends and intra-annual quasi-periodic oscillations for monthly rainfall measurements. Time-variable amplitudes of quasi-periodical oscillations are crucial for finding intra-annual teleconnections using SMLR, while trends are better suited for the case of inter-annual ones. The methodology is tested over a Tropical-Andean region in southern Ecuador. The following results were obtained: (1) trans-Niño-Index (TNI) and Tropical-South-Atlantic signals are strongly connected to inter-annual and intra-annual time-scales. (2) However, TNI progressively weakens its relation with intra-annual components; meanwhile, El-Niño-Southern-Oscillation 3 gains ground for such time-scales. (3) Finally, an inter-annual connection with the North-Atlantic-Oscillation (NAO) is revealed. These results are consistent with previous literature, although the TNI and NAO connections are interesting findings, taking into account the differences in the connected scales. These results show the methodology’s capability of unraveling global teleconnections in different space and time scales using attributes embedded in an integral mathematical framework, which could be interesting for other purposes—such as the analysis of climate mechanisms or climate modeling.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Decadal changes in the teleconnection between the central tropical Pacific and the Southern Hemisphere extratropics are studied using the NCEP–NCAR reanalysis data. Concurrent and lagged relationships show that teleconnection strength in austral spring was weak (strong) before (after) 1996/1997. This decadal change coincides in time with the climate regime shift in the Pacific in the 1990s known from many studies. We show that, after the regime shift, the concurrent and delayed teleconnection with the Southern Hemisphere extratropics is insignificant in September and abruptly increases in October. Penetration of the stratospheric anomaly into the troposphere in October can indicate interacting tropospheric and stratospheric pathways of the teleconnection to strongly enhance the central tropical Pacific impact since the late 1990s. The results give evidence that the Southern Annular Mode seems to be connecting element between the two pathways in the recent decades. The common tendencies in the eastward shift of the tropical anomalies and zonal wave 1 phase in the Antarctic stratosphere in austral spring have been demonstrated. The difference between the central Pacific and eastern Pacific teleconnections is consistent with that known from previous studies and new tendencies in their decadal changes and delayed effects have been revealed. It has been found that the central Pacific contributions to the Pacific decadal oscillation and to the Northern Hemisphere stratosphere have also increased significantly after the 1990s. This characterizes the central tropical Pacific as one of the key regions impacting climate and teleconnection not only in the Southern Hemisphere, but also in the Northern Hemisphere. Our findings are consistent with and further develop the recent studies of the stratosphere–troposphere coupling in austral spring, and emphasize significant contribution of the delayed tropical signals to the climate variability in austral spring in both hemispheres.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A simple theoretical model is constructed to understand the cause of a peculiar cooling trend in North Pacific under the background of the greenhouse gases induced global warming during the past 50 years. It is found that the North Pacific cooling is caused by the increase of surface upward latent heat flux due to the atmosphere and the decrease of surface downward shortwave radiative flux. The former is attributed to enhanced low-level westerlies, while the latter is caused by the increase of stratus cloud over North Pacific. An atmosphere general circulation model is utilized to investigate the cause of the wind and low-level cloud changes. It is found that the strengthened westerly in North Pacific is the result of an atmospheric teleconnection pattern forced by the SSTAs warming in the tropical Pacific. The SSTAs warming in other tropical basins, along with the local cooling in North Pacific, tends to reduce the tropical Pacific SSTAs forcing effect. In addition, the increased local low-level cloud response to the tropical Pacific SSTAs forcing is also responsible for the cooling trend in North Pacific. The increased local stratus cloud may enhance the cooling through a positive feedback among the SST, atmospheric static stability and stratus cloud.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The effect of cumulus parameterization (CP) on simulated climatological tropical cyclone (TC) activity over the CORDEX East Asia domain has been investigated by using the weather research and forecasting model. The simulations were conducted during 1988–2009 with a 25-km horizontal resolution, driven by the ERA-Interim reanalysis. Five experiments were performed and evaluated with different CP schemes including Kain–Fritsch (KF), KF with modified convective trigger function (KFML), multi-scale KF (MsKF), simplified Arakawa–Schubert (SAS) and Betts–Miller–Janjic (BMJ) schemes. Significant differences of TC genesis locations and tracks can be found between the CP schemes, which are attributed to simulated large-scale environment discrepancies. Simulations with the KF, KFML and MsKF schemes produced more TC numbers and stronger intensities than the SAS and BMJ simulations. The eastward extension and enhancement of the monsoon trough (MT) in the KF, KFML and MsKF simulations caused a southeast shift of the main TC genesis region, and provided a suitable environment for TC development. The KFML simulation reduced the excessive rainfall and TC activities that had appeared in the KF simulation and increased the proportion of intense TCs. The reduced tropical surface latent and moisture flux in the MsKF simulation, along with weaker upward vertical motion, contributed to weaker tropical rainfall and TC intensities. The SAS simulation produced less large-scale instabilities, which led to less active convections and weaker TC genesis and intensities. The genesis region in the BMJ simulation was shifted further north due to the northward-shifted reverse-oriented MT together with enhanced wind shear over the tropical ocean, resulting in detrimental environmental conditions for TC development. In addition, the BMJ scheme produced significant upper-tropospheric warming, attributed to enhanced grid-scale convective heat transport and latent heating of condensation in high-level stratiform cloud extending to the south boundary of WPSH, this resulted in the retreat of the subtropical high and caused the TC to recurve earlier.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Extracting annual cycle properly from climate series is important in the study of annual cycle and anomaly series. However, the extracting approaches are various and may lead to inconsistent results. Since the real annual cycle is unknown in observed records, the reliability and applicability of them are hard to estimate. In this study, five popular decomposition methods used to extract annual cycle in climate series are evaluated through idealized numerical experiments for the first time; i.e., fitting sinusoids, complex demodulation, ensemble empirical mode decomposition (EEMD), nonlinear mode decomposition (NMD) and seasonal trend decomposition procedure based on loess (STL). Their performances are examined by comparing the extracted annual cycles and its amplitude with the preset one. The annual cycles are set with three different changing amplitudes: constant, linear increasing and nonlinearly varying; superposed with fluctuations of different long-term persistence (LTP) strength. Results indicate that (1) NMD performs best in depicting annual cycle and obtaining its amplitude change; (2) fitting sinusoids, complex demodulation and EEMD methods are more sensitive to LTP strength of superimposed fluctuations, which leads to over-fitted annual cycles and noisy amplitude changes, oppositely, the STL are less responsive to the variation of annual cycle; (3) when overall long-time trend of annual cycle change is the main concern, all of these methods performed well. However, over short time scales, the errors on account of noise and LTP are common in the first three methods and STL is too rough to give the details of amplitude change. Those results are also verified by applying them to observed records and the case with both amplitude and phase change.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A statistical downscaling method (SDM) has been established through multiple stepwise regressions of predictor principal components using the ERA-Interim reanalysis data and the meteorological data collected from 115 stations in the low-latitude plateau in China from 1981 to 2015. The skill of the SDM was checked by comparing the results of the different predictor combinations and the different time lengths used to construct the SDM. In addition, compared to the historical simulation of the coupled Max Planck Institute Earth System Model (MPI-ESM-LR), better performance can be achieved by using the ERA-Interim data to construct the SDM in the low-latitude plateau. The long-term changes in temperature from 1981 to 2015 in the ERA-Interim reanalysis data are calibrated by the SDM over the low-latitude plateau of China. Furthermore, the SDM is projected into the simulation results of the MPI-ESM-LR model to construct a suitable SDM (ERA-SDM), and then the ERA-SDM is implemented to evaluate the future temperature changes in the low-latitude plateau during the period of 2018–2100 using the simulation results of the MPI-ESM-LR model under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. The results showed that an increase in temperature of 0.3 °C decade〈sup〉−1〈/sup〉 was found from 1981 to 2015, in which the fastest increase of 0.4 °C decade〈sup〉−1〈/sup〉 occurred in winter and the slowest increase of 0.2 °C decade〈sup〉−1〈/sup〉 occurred in autumn. Most models in CMIP5 failed to simulate the long-term changes in temperature over the last 30 years in the low-latitude plateau region, and the temperature in the low-latitude plateau was underestimated by 2.4 °C using the 22 models. The SDM improved the annual and seasonal temperature characteristics and inter-annual and seasonal changes simulated by the MPI-ESM-LR. The future temperature predictions by the ERA-SDM indicated that the fastest temperature increase of 0.271 °C decade〈sup〉−1〈/sup〉 was found in spring under the RCP8.5 scenario. A faster rate of temperature increase was found in the northern part of the low-latitude plateau than in the southern part under the RCP8.5 scenario.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A first systematic analysis was conducted to assess near-term future changes in climate extremes over East Asia during the summer season (June–August) using five regional climate model (RCM) simulations participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM). The 20-year return values of extreme temperature and precipitation were compared between the present (1979–2005) and near-term future (2024–2049) periods, which were estimated using the generalized extreme value (GEV) analysis. Multi-RCM mean results show that temperature and precipitation will increase in both means and extremes and that the increase in precipitation extreme will follow the enhanced moisture availability with warming (~ 7% °C〈sup〉−1〈/sup〉, Clausius–Clapeyron relation). It was found that the increases in GEV location parameter (mean intensity) and scale parameter (inter-annual variability) contribute dominantly to the increase in extremes of temperature and precipitation, respectively. Robust inter-RCM relations were observed between mean and extreme projections over East Asia and even on grid scales, more strongly for temperature. Model biases and future projections exhibit a significant relationship for temperature such that RCMs with warmer biases tend to predict stronger warming and vice versa. Results from three sub-regions (South Korea, Southern China, and Mongolia and northern China) consistently indicate that temperature increase involves an overall shift of the daily temperature distribution toward warmer conditions while precipitation increases are due to dominant increases in moderate-heavy rainfall events. Our multi-RCM assessment provides new insights to the uncertainty in future climate extremes over East Asia.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The secular change of the Asian monsoon (AM)-El Niño–Southern Oscillation (ENSO) relationship has been recognized as a specter for seasonal forecast. The causes of such changes have not been well understood. How the monsoon-ENSO relationship underwent secular changes beyond instrumental period has rarely been discussed. Here we explore the multidecadal to centennial changes of the AM-ENSO relationship with the recently compiled Reconstructed Asian summer Precipitation (RAP) dataset (1470–2013) and multiple ENSO proxy indices. During the past five centuries, two leading modes of interannual variability of RAP are found to be associated with the ENSO developing and decaying phases, respectively. The mechanisms behind the modern monsoon-ENSO relationship can reasonably well explain the past monsoon behavior. In response to a developing ENSO, precipitation anomalies from the Maritime Continent (MC) via India to northern China are in phase, and this “chain reaction” tends to be largely steady since around 1620 AD when the Indian summer monsoon abruptly strengthened. Further, the strengthening of the link between developing-ENSO and Indian-northern China rainfall since 1620 AD concurred with a phase reversal of the Pacific Decadal Oscillation. During the decaying phase, however, the summer rainfall-ENSO relationship over the Yangtze River Valley-southern East China (YRV-SEC), the MC and central Asia, has gone through large multidecadal to centennial changes over the past five centuries. A remarkable reversal of sign in the AM-decaying ENSO relationship occurred roughly from 1740 to 1760 over the YRV-SEC and MC, which may be associated with the long-term strengthening of ENSO intensity. Future research should continue focusing on revealing the possible causes of the low-frequency changes in the monsoon-ENSO relationship using general circulation models and paleoclimate proxy reconstructions.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Global surface evapotranspiration is one of the most significant components of the response of the water cycle to a warming climate. However, trends in surface evapotranspiration differ considerably from the trend in climate warming according to recent studies, with some studies even showing an opposing trend. The reason for this difference in the response of surface evapotranspiration to climate warming is still not completely understood. We validated the gridded FLUXNET evapotranspiration dataset and the Global Land Surface Assimilation Dataset (GLDAS) against evapotranspiration data observed in northern China using the eddy covariance system. The response of surface evapotranspiration to an increase in temperature varied with the type of climate (classified by the amount of precipitation) and the trend of surface evapotranspiration with warming showed similar features to the transitions between these climate types. The climate type with precipitation in the range of 250–350 mm was the most sensitive to the effects of warming on evapotranspiration. In more humid climates, surface evapotranspiration increased with increasing temperature, whereas in drier climates surface evapotranspiration decreased with increasing temperature. A similar response of evapotranspiration to increasing temperatures was also observed elsewhere in regions of climate transition. There are two main mechanisms of evapotranspiration: (1) an increase in temperature resulting in a direct increase in potential evapotranspiration; and (2) an increase in temperature resulting in a loss of soil moisture due to the increase in evapotranspiration, which in turn will indirectly suppress surface evapotranspiration due to the loss of vegetation.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The rectification of intraseasonal wind forcing on interannual sea surface temperature anomalies (SSTA) and sea level anomalies (SLA) associated with El Niño–Southern Oscillation (ENSO) during 1993–2016 are investigated using the LICOM ocean general circulation model forced with daily winds. The comparisons of the experiments with and without the intraseasonal wind forcing have shown that the rectified interannual SSTA and SLA by the intraseasonal winds are much weaker than the total interannual SSTA and SLA in the cold tongue, due to the much weaker rectified than the total interannual Kelvin and Rossby waves in the equatorial Pacific Ocean. The dynamics of the rectification are through the nonlinear zonal and vertical advection by the background currents, which produces downwelling equatorial Kelvin waves during El Niño. The meridional advection is much smaller than the zonal and vertical advection, suggesting that the rectification is not induced by the Ekman dynamics or the thermocline rectification. The rectified interannual Kelvin waves are found to be much smaller than reflected at the Pacific western boundary and those forced by the interannual winds, suggesting that the latter two play a much more important role in ENSO dynamics than the intraseasonal winds. The results of this study suggest an unlikely significant role of oceanic nonlinear rectification by intraseasonal winds during the onset and cycling of El Niño.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Future hydroclimate change is expected to generally follow a wet-get-wetter, dry-get-drier (WWDD) pattern, yet key uncertainties remain regionally and over land. It has been previously hypothesized that lake levels of the Last Glacial Maximum (LGM) could map a reverse analog to future hydroclimate changes due to reduction of CO〈sub〉2〈/sub〉 levels at this time. Potential complications to this approach include, however, the confounding effects of factors such as the Laurentide Ice Sheet and lake evaporation changes. Using the ensemble output of six coupled climate models, lake energy and water balance models, an atmospheric moisture budget analysis, and additional CO〈sub〉2〈/sub〉 sensitivity experiments, we assess the effectiveness of the LGM as a reverse analog for future hydroclimate changes for a transect from the drylands of North America to southern South America. The model ensemble successfully simulates the general pattern of lower tropical lake levels and higher extratropical lake levels at LGM, matching 82% of the lake proxy records. The greatest model-data mismatch occurs in tropical and extratropical South America, potentially as a result of underestimated changes in temperature and surface evaporation. Thermodynamic processes of the mean circulation best explain the direction of lake changes observed in the proxy record, particularly in the tropics and Pacific coasts of the extratropics, and produce a WWDD pattern. CO〈sub〉2〈/sub〉 forcing alone cannot account for LGM lake level changes, however, as the enhanced cooling from the Laurentide ice sheet appears necessary to generate LGM dry anomalies in the tropics and to deepen anomalies in the extratropics. LGM performance as a reverse analog is regionally dependent as anti-correlation between LGM and future P − E is not uniformly observed across the study domain.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Short-term concurrent droughts and heatwaves accompanied by high temperatures and low soil moisture (or low precipitation) may significantly impact ecosystems, societies, and economies although the individual events involved may not themselves represent severe extremes. There is little known about the potential frequency of short-term concurrent droughts and heatwaves in the future. Here, we use the Gan River Basin as a case study area to assess the effects of different warming levels on drought and heatwave concurrences based on the coupled model intercomparison project phase 5 and variable infiltration capacity (VIC) model. The results show that the VIC model has high reliability in the simulation of soil moisture and evapotranspiration compared with other well-recognized datasets in the Gan River Basin. The warming level over the Gan River Basin is close to the global warming level. Under RCP4.5 and RCP8.5 scenarios, the multi-model ensemble medians of concurrent events increased by 0.08–0.4 pentads/decade from 2006 to 2099. The uncertainty of concurrent events encompasses a wider range as global temperature increases. Compared to the reference period (1961–2005), drought and heatwave concurrences have increased by more than 50% in the most parts of the basin under 1.5 or 2.0 °C of global warming; there is a 20% frequency difference of 0.5 °C from 1.5 to 2.0 °C. The substantial pentad increases (at least greater than 50%) existed in historical low-pentad-value areas in a 1.5 or 2.0 °C world, especially pronounced for a 2.0 °C world. The greatest increase in concurrent event pentads came from the 25th percentile values in 1.5 or 2.0 °C scenarios. Climatological median pentads of concurrent droughts and heatwaves appear likely to be 9.6–17.6% more frequent in a 2.0 °C world than a 1.5 °C world with respect to the reference period.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Winter-to-early spring non-monsoonal precipitation over the Western Himalayas (WH) primarily comes from eastward propagating synoptic-scale weather systems known as western disturbances (WDs). Earlier studies have noted that an increasing trend of synoptic-scale WD activity in the past few decades has contributed to enhanced propensity of daily precipitation extremes over the WH, although it remains unclear as to whether these regional changes are manifestations of climate change. This issue is addressed by conducting a suite of long-term climate experiments using a global variable-grid climate model with high-resolution telescopic zooming over the South Asian region. Our findings highlight that human-induced climate change has implications on the rising trend of synoptic-scale WD activity and precipitation extremes over the WH during the recent few decades, and these changes cannot be explained by natural forcing alone. A stronger surface warming, in response to climate change, is noted over the vast expanse of the high-elevated eastern Tibetan Plateau relative to the western side. The model simulations show that strengthening of positive east–west temperature gradient across the Tibetan Plateau tends to alter the background mean circulation in a manner as to favor amplitude enhancements of the synoptic-scale WDs and orographic precipitation over the WH. With continuation of global warming in future and enhancement in the east–west temperature gradient across the Tibetan highlands, the trend of precipitation extremes over the WH and synoptic-scale WD activity are projected to rise into the twenty-first century. While the high-resolution simulations of this study offers promising potential to understand changes in synoptic-scale WD activity and precipitation extremes over the WH, further investigations are necessary to decipher the multi-scale behavior and intricacies of the Himalayan precipitation variability under changing climate.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Despite the monotonically rising greenhouse gas emission, global warming rate changes again and again, especially the slowdown during 1998–2013, challenging the current global temperature change mechanisms. Recently, different-scale natural climate variabilities have been individually recognized as the potential causes of global warming rate change, particularly the recent warming slowdown, but disagreements still exist on their relative importance. Here we quantify the contribution of interannual, interdecadal and multidecadal variabilities (IAV, IDV and MDV) in modulating the global warming rate during the period 1850–2017 via decomposing the global mean temperature timeseries derived from 12 datasets into several quasi-periodic fluctuations and a monotonical secular trend (ST) using the ensemble empirical mode decomposition method. Our results show that the IAV, IDV and MDV dominate the global warming rate change together, rather than one-scale variability alone. For example, during 1998–2013 both the IAV and IDV present obvious negative trends and combine to cut 59 ± 22% of global mean surface temperature (GMST) and 65 ± 38% of sea surface temperature (SST) positive trends which are caused by the steadily warming ST and the warming phase of MDV, thus causing an apparent warming slowdown during this period. Furthermore, we illustrate that the IAV, IDV and MDV mainly originate from the El Niño-Southern oscillation (ENSO), Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO), respectively. Our work partly reconciles the controversy over the importance of different-scale natural variabilities, and provides some insights for climate change attribution and prediction research.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉In the present work, the mechanisms for the changes in moisture sources (evaporation minus precipitation; EmP) during boreal summer (May–September) are explored over the tropical Indian Ocean during 1979–2016. We apply a moisture budget analysis to quantify the thermodynamic and dynamic effects. Our results show that the EmP in the tropical central-eastern and southwestern Indian Oceans experienced significant increasing trends during boreal summer. The increased EmP in the tropical central-eastern Indian Ocean is due to the enhanced dynamic divergence (account for approximately 51%), while a stronger dynamic advection contributes more moisture supply to the southwestern Indian Ocean (account for approximately 34%). We find that during recent decades, the enhanced east–west thermal gradient in the Pacific strengthens the Walker Circulation, which leads to a westward shift in convection over the Indian Ocean warm pool, resulting in weakened convection and ascent over the tropical central-eastern Indian Ocean. The weakened convection leads to an anomalous low-level atmospheric divergent circulation, which intensifies the dynamic divergence contributing to the enhanced EmP over the tropical central-eastern Indian Ocean. Additionally, the warming climate during recent decades also increases the land–sea thermal contrast in the vicinity of the Indian Ocean, which enhances the southeastern wind in the low-level troposphere and leads to an enhanced EmP over the southwestern Indian Ocean.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The great rivers that flow from the southern Tibetan Plateau (TP) affect billions of people in the downstream countries of Asia. Understanding of the hydrological variability of these rivers is still limited, however, because of the lack of long-term streamflow records. Tree-ring width chronologies from six sites are applied to reconstruct annual streamflow of the Salween River, the last remaining large free-flowing transboundary river draining the southern TP, and a critical water source for countries of Southeast Asia. Response function analysis shows that precipitation is the main factor limiting the radial growth of the sampled trees. Linear regression of annual (September–June) Salween River streamflow on the first principal component of tree-ring chronologies explains 53.4% of the streamflow variance, 1958–2011, and yields a reconstruction for the interval 1500–2011 CE. A tally of droughts and wet periods emphasizes the severity of droughts before the start of the gauged records, and a tendency toward wetter conditions in recent decades. Regional temperature is negatively associated with the reconstructed streamflow. Cold wet summers controlled by the Asian summer monsoon are responsible for an increasing trend in streamflow over the last decades. Reconstructed hydrological change is linked to the history of mainland Southeast Asia through the impact of water shortages on Burma society. In particular, prolonged periods of low flow of the Salween River coincide with the falls of the Toungoo Empires and the First Anglo-Burmese War. This tree-ring reconstruction provides a long-term perspective on hydrological changes in the Upper Salween River Basin that can give insight for sustainable water management on the TP and in Myanmar.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The exorable climate changes leads to changes in the frequency and intensity of extreme rainfall events worldwide; however, the amendment in extreme rainfall events is not uniform over space, precisely it is more localized and a great threat to the society. Thus, study of rainfall extremes at a finer spatial scale is essential and identifying the large-scale parameters that are responsible factors is highly needed. Odisha state in India is one of the most vulnerable to weather extremes and considered as a study region. The present study is bi-fold, firstly examining the changes in the extreme rainfall (≥ 204.5 mm/day) over Odisha and exploring the foremost large-scale meteorological parameters responsible for heterogeneous characteristics of extreme rainfall within Odisha during 1980–2017 summer monsoon period. India Meteorological Department gridded high-resolution (0.25° × 0.25°) rainfall analysis and ERA-Interim (0.25° × 0.25°) reanalysis data at daily scale are used for the analysis. The study region has an increasing trend in extreme rainfall events and it is evident that the Indian Ocean is warmer during extreme rainfall events compared to the dry events, particularly near the seashore of Odisha. The stronger (weak) and cyclonic (anti-cyclonic) flows at 850-hPa exhibit during extreme rainfall (dry) events. The moisture flux is convergent during extreme rainfall events, while it is reverse during dry events. The monsoon trough has been shifted to south (north) from its normal position during extreme rainfall (dry) events. A detailed investigation is carried out for extreme rainfall events over five different regions in Odisha. It reveals that the wind at 850 hPa, omega at 500 hPa, and SST play the important role for Region I, while OLR and omega at 500 hPa are dominating for the Region IV in the occurrence of extreme rainfall. Moreover, the role of the dominant climatic parameters for the extreme rainfall occurrence varies for the other three regions. Analysis confirms that the role of main meteorological parameters is statistically significant for the extreme rainfall events over the respective region. Although the Odisha is a small state in India, not only the long-term trend in extreme rainfall varies region-to-region but also responsible factors associated with the climatic conditions differ for the occurrence of the extreme rainfall.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We analyze European temperature variability from station data with the method of detrended fluctuation analysis. This method is known to give a scaling exponent indicating long range correlations in time for temperature anomalies. However, by a more careful look at the fluctuation function we are able to explain the emergent scaling behaviour by short time relaxation, the yearly cycle and one additional process. It turns out that for many stations this interannual variability is an oscillatory mode with a period length of approximately 7–8 years, which is consistent with results of other methods. We discuss the spatial patterns in all parameters and validate the finding of the 7–8 year period by comparing stations with and without this mode.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study contrasts two types of quasi-biweekly oscillations (QBWOs) over tropical Asia in late-summer and autumn (from August to October). Using a tracking method to calculate the frequency of QBWO events over the Asian monsoon region, two types of QBWOs in monsoon rainfall are revealed. One originates from 110° to 140°E and propagates westward to southern China with a notable impact on the regional rainfall, while the other initiates from 160°E to the dateline and does not affect southern China rainfall significantly. Analysis of the vertical structure of moisture flux shows that the moisture source for type 1 events is dominated by the zonal flux component and that for type 2 the meridional flux component. The nature of the moisture flux determines whether the oscillation can propagate across 120°E and affect rainfall over southern China. Results also show that the strength of the South Asian high and the western Pacific subtropical high differently modulate the generation of the two types of QBWOs. Specifically, mutually stronger (weaker) highs favor the first (second) type of the oscillation. A close relationship also exists between the QBWOs and western Pacific sea surface temperature (SST) anomalies, suggesting that the SST anomalies can potentially trigger the QBWOs.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The presence of thin sea ice is indicative of active freezing conditions in the polar ocean. We propose a simple yet effective method to incorporate information of thin-ice category into coupled ocean–sea-ice model simulations. In our approach, the thin-ice distribution restricts thick-ice extent and constrains atmosphere–ocean heat exchange through the sea ice. Our model simulation with the incorporation of satellite-derived thin-ice data for the Arctic Ocean showed much improved representation of sea-ice and upper-ocean fields, including sea-ice thickness in the Canadian Archipelago and the region north of Greenland, mixed-layer depth over the Central Arctic, and surface-layer salinity over the open ocean. Enhanced sea-ice production by the thin-ice data constraint increased the total sea-ice volume of the Arctic Ocean by 〈span〉 〈span〉\(5 \times 10^{3}\)〈/span〉 〈/span〉–〈span〉 〈span〉\(10 \times 10^{3}\)〈/span〉 〈/span〉 km〈sup〉3〈/sup〉. Subsequent sea-ice melting was also enhanced, leading to the greater amplitude of the seasonal cycle by approximately 〈span〉 〈span〉\(2 \times 10^{3}\)〈/span〉 〈/span〉 km〈sup〉3〈/sup〉 (15% of the baseline value from the experiment without the thin-ice data incorporation). Overall, our results demonstrate that the incorporation of satellite-derived information on thin sea ice has great potential for the improvement of coupled ocean–sea-ice simulations.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉As the most significant interannual variability in the climate system, El Niño-Southern Oscillation (ENSO) has critical effects on global weather and climate patterns. To simulate and predict ENSO, coupled general circulation models (CGCMs) have become a key tool. However, the accurate simulation of ENSO is still a challenge for CGCMs. The performance of El Niño simulations conducted through FIO-ESM v1.0 is examined based on the outputs of the Coupled Model Intercomparsion Project phase 5 (CMIP5) historical experiments. The results show that FIO-ESM v1.0 suffers from similar common problems to other CMIP5 models, including an eastward shift in the central locations of El Niño, adopting a regular period of roughly 3 years, addressing excessively high amplitude, spurious eastward propagation of El Niño events, and Aborted El Niño events. El Niño composite and mixed layer heat budget analyses indicate that these simulation biases are mainly associated with the mean state biases, including a warm Sea Surface Temperature (SST) bias for the central-eastern Pacific, a cold SST bias for the western and central Pacific, seasonal cycles of SST of the equatorial eastern Pacific, and weaker trade winds. Weaker SST-cloud-shortwave radiation feedback in La Niña events than in El Niño events is what creates spurious ENSO amplitude symmetry in the model. We suggest that the improvement of El Niño simulations may be realized by focusing on the mean state and SST-cloud-shortwave radiation feedback in the tropical region. Specifically, further incremental improvements in the mean state of the tropical Pacific should constitute the first step to realizing more accurate ENSO simulation.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The precise influence of climate change on extratropical cyclone genesis and evolution is an important (but as yet unsolved) problem, given their physical and economic impact on a large portion of the planet’s population. However, extratropical cyclones are also affected by the competing influences of forcing mechanisms at a wide range of spatial scales, complicating the problem. While the advent of idealized numerical modeling has allowed great strides in addressing these complications and achieving some qualitative consensus in the literature, there is still some quantitative disagreement about response magnitude and where local maxima and minima in the response may be located. Thus, the advantages inherent in the variety of idealized numerical modeling methods used to address this problem are also a drawback, as it can be difficult to draw one-to-one comparisons across experiments. Although the effects of particular model architecture choices such as microphysical and cumulus schemes are well-documented, others are less understood. In this study, we examine the role of Coriolis approximations by comparing a new set of ETC sensitivity experiments using a linear 〈em〉 β〈/em〉-plane approximation to an existing set of extratropical sensitivity experiments using a constant 〈em〉f〈/em〉-plane approximation. ETCs within the new 〈em〉 β〈/em〉-plane experiment are found to generally decrease in strength with temperature, as measured by both minimum sea level pressure and maximum eddy kinetic energy (EKE). A small increase in EKE is observed at the warmest temperatures, likely due to diabatic influences disrupting flow within the warm conveyor belt. While seemingly contradictory to the previous 〈em〉f〈/em〉-plane results, the two experiments are instead found to be qualitatively similar upon further inspection, with an offset of approximately 8 K. This offset is primarily due to the Coriolis approximations, although the initial stability profile (affected by the Coriolis approximation) has a marginal influence.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Regional Climate Models (RCMs) are increasingly used to add small-scale processes at higher grid resolution that are not represented by their Lateral Boundary Conditions (LBCs). Rossby Centre regional atmospheric model, RCA4, has downscaled three Global Climate Models (GCMs), namely, CNRM-CM5, EC-EARTH and GFDL-ESM2M in the COordinated Regional climate Downscaling EXperiment (CORDEX) framework for Middle East North Africa (MENA) and South Asia (SA) domains. Arabian Peninsula is covered in both MENA and SA simulations, which gives a unique opportunity to study the effects of CORDEX domain and LBCs on the simulation of temperature and precipitation by RCM. It is examined by calculating the differences between MENA and SA simulations for different driving GCMs in the historical (1976–2005) and future (2071–2100) periods under RCP8.5 emission scenario, for both summer (dry) and winter (wet) seasons. RCA4 performs generally well when simulating the observed temperature and precipitation patterns, with some local wet biases over Asir Mountains and cold bias over the north eastern parts of Saudi Arabia. The simulations of temperature seem to be very sensitive to the simulation domain (i.e., MENA and SA) and less sensitive to different LBCs, whereas in case of precipitation LBCs seems to play a dominant role. The MENA simulations generally project about 2 °C warmer and drier climate compared to SA simulations by the end of this century, which is comparable to the differences arising due to different LBCs and climate change.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study investigates the diurnal variation of the warm season precipitation simulated by the Goddard Earth Observing System version 5 atmospheric general circulation model for 2 years (2005–2006) at a horizontal resolution of 10 km. The simulation was validated with the satellite-derived Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data and the Modern-Era Retrospective analysis for Research and Applications atmospheric reanalysis for atmospheric winds and moisture. The simulation is compared with the coarse-resolution run in 50 km to examine the impacts driven by resolution change. Overall, the 10 km model tends to reproduce the important features of the observed diurnal variation, such as the amplitude and phase at which precipitation peaks in the evening on land and in the morning over the ocean, despite an excessive amplitude bias over land. The model also reproduces the realistic propagation patterns of precipitation in the vicinity of ocean coasts and major mountains. The regional characteristics of the diurnal precipitation over two regions, the Bay of Bengal and the Great Plains in North America, are examined in detail, where the observed diurnal cycle exhibits a systematic transition in the peak phase due to the development and propagation of regional-scale convective systems. The model is able to reproduce this pattern as well as the diurnal variation of low-level wind and moisture convergence; however, it is less effective at representing the nocturnal peak of precipitation over the Great Plains. The model results suggest that increasing the horizontal resolution of the model to 10 km substantially improves the representation of the diurnal precipitation cycle. However, intrinsic model deficiencies in topographical precipitation and the accurate representation of mesoscale convective systems remain a challenge.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The influence of El Niño-Southern Oscillation (ENSO) on the Indian Ocean Dipole (IOD), a coupled ocean–atmosphere mode of interannual climate variability, has been widely investigated over recent decades. However, a latest study indicates that the South China Sea summer monsoon (SCSSM) might also be responsible for IOD formation. Furthermore, an abnormal SCSSM does not always coincide with ENSO during boreal summer (June–August, JJA); consequently, the individual and combined effects of the SCSSM and ENSO on the IOD remain elusive. This study shows that the amplitude of the IOD tends to be much stronger under the coexistence of SCSSM and ENSO than that under individual SCSSM or ENSO events during JJA and autumn. The findings also indicate that the SCSSM and ENSO play the dominant role around the eastern and western poles of the IOD, respectively. An anomalous local Hadley circulation closely related to the stronger SCSSM favors anomalous southeasterly off Sumatra and Java during JJA, which enhance oceanic upwelling and subsequently result in cooling of the sea surface temperature (SST) over this area. Similarly, it can be envisaged that the contemporaneous ENSO could influence JJA SST anomalies over the western Indian Ocean via the Walker circulation coupled with oceanic variations.〈/p〉

Description: 〈p〉In the original publication of the article Fig. 1 was incorrect. The correct Fig. 1 is given below.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Differences between two types of prediction skill estimates over Southern Africa are illustrated to better inform the users of seasonal precipitation forecasts over the region who desire assessments of forecast accuracy. Both seasonal precipitation prediction skill estimates for the African continent south of 15°S during the December–March rainy season are derived from the perfect-model method. The perfect-model method is based on a 40-member ensemble of Community Atmosphere Model version 5 simulations forced by observed time-evolving boundary conditions during 1920–2016. The first skill estimate is based on the verification of an ensemble mean forecast spanning many seasons and therefore unconditional on a single boundary forcing. The second skill estimate is based on the verification of an ensemble mean forecast for a single season and is therefore conditional on that year’s boundary forcing. Unconditional prediction skill calculated in 30-year increments for each of the 40 possible forecasts reveals: (1) large spread in skill among the individual forecasts for any given year and (2) temporal variations in skill for each forecast. The magnitude of conditional prediction skill varies greatly from 1 year to the next, revealing that the boundary conditions offer little prediction skill during some years and comparably large skill during others. The simultaneous behaviors of the El Niño–Southern Oscillation and the subtropical Indian Ocean Dipole are related to the largest conditional precipitation prediction skill years. Unconditional skill estimates may therefore mislead users of forecasts who desire assessments of forecast accuracy. Unconditional skill may be temporally unstable, and unlike conditional skill, is not representative of the skill for a given season.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study discusses the performance of various planetary boundary layer parameterization (PBL) schemes—the Quasi-Normal Scale Elimination (QNSE), the University of Washington Moist Turbulence (UWMT), and the Yonsei University (YSU)—for the simulation of rapidly developing North Atlantic (NA) mid-latitude winter storms. Sensitivity experiments with the three PBL schemes, YSU, QNSE, and UWMT, indicate that there are minor differences at the center of the storm while simulating the evolution of the three explosive storms Klaus (21–27 January 2009), Xynthia (25 February–03 March 2010), and Gong (16–20 January 2013). The differences are shown in terms of the central minimum pressure, 10-m wind, specific humidity, CAPE, transitional speed, boundary layer height and frictional velocity of these mid-latitude storms. One of the main result shows the capability of QNSE and UWMT PBL schemes to reproduce accurately both the cyclogenesis and explosive stage for these mid-latitude storms during the winter season, better than YSU scheme. Almost all PBL schemes show dry bias from middle to upper troposphere (600 hPa–250 hPa), while YSU scheme carries this bias at the surface boundary layer, for all simulations. Moreover, QNSE, UWMT and YMSU PBL schemes underestimate the tangential winds for these mid-latitude storms. The 24 h accumulated latent heat flux and precipitation from UWMT scheme show modified results as compared to YSU and QNSE PBL schemes. Overall results show the superiority of QNSE and UWMT PBL schemes for an accurate simulation of the explosive stage of these North Atlantic winter storms.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Despite the importance of seasonal distribution and interannual variability of rainfall to the ecosystem and society, there is a lack of regional-level studies on rainfall seasonality, and teleconnections between global climate events and rainfall seasonality are not well understood. To address these issues, this study analyzed the spatial and temporal characteristics of rainfall seasonality across China from 1961 to 2012. A novel application of information theory-based rainfall seasonality indicators was conducted at the regional scale, and observed monthly precipitation data was used. The rainfall seasonality anomalies during negative and positive phases of the El Niño–Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation, and Pacific Decadal Oscillation, and the possible physical mechanisms behind were also investigated. The results showed that rainfall seasonality increased, especially in Southeast China, which can be attributed to changes in magnitude (annual rainfall), timing, or duration of the wet season. Global climate events significantly affected rainfall seasonality indicators in Southeast China during negative and positive phases. The sea surface temperature (SST) or sea level pressure (SLP), and wind anomalies during the negative and positive phases might explain the spatial differences in the influences of global climate events on rainfall seasonality across China. These results may prove valuable for sustainable water resource management and agricultural production in China.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Coupled climate models used for long-term future climate projections and seasonal or decadal predictions share a systematic and persistent warm sea surface temperature (SST) bias in the tropical Atlantic. This study attempts to better understand the physical mechanisms responsible for the development of systematic biases in the tropical Atlantic using the so-called Transpose-CMIP protocol in a multi-model context. Six global climate models have been used to perform seasonal forecasts starting both in May and February over the period 2000–2009. In all models, the growth of SST biases is rapid. Significant biases are seen in the first month of forecast and, by 6 months, the root-mean-square SST bias is 80% of the climatological bias. These control experiments show that the equatorial warm SST bias is not driven by surface heat flux biases in all models, whereas in the south-eastern Atlantic the solar heat flux could explain the setup of an initial warm bias in the first few days. A set of sensitivity experiments with prescribed wind stress confirm the leading role of wind stress biases in driving the equatorial SST bias, even if the amplitude of the SST bias is model dependent. A reduced SST bias leads to a reduced precipitation bias locally, but there is no robust remote effect on West African Monsoon rainfall. Over the south-eastern part of the basin, local wind biases tend to have an impact on the local SST bias (except in the high resolution model). However, there is also a non-local effect of equatorial wind correction in two models. This can be explained by sub-surface advection of water from the equator, which is colder when the bias in equatorial wind stress is corrected. In terms of variability, it is also shown that improving the mean state in the equatorial Atlantic leads to a beneficial intensification of the Bjerknes feedback loop. In conclusion, we show a robust effect of wind stress biases on tropical mean climate and variability in multiple climate models.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study investigates the summertime day-to-day variability of the South Asian high (SAH) driven by atmospheric heating over Tibetan Plateau (TP) using the NCEP/NCAR reanalysis dataset. We first isolate the day-to-day variability of SAH in summertime based on the intensity of the summertime Tibetan Plateau upper-atmospheric heat source (TPUHS). It shows that anomalously stronger TPUHS days are accompanied with SAH center over Iranian Plateau (IP or the IP phase of the SAH) and the SAH center moves to TP (or the TP phase) during weaker TPUHS days, which contrasts with the corresponding relationship between SAH IP/TP phase and weaker/stronger TP heating in monthly and longer timescale. We further demonstrate that the SAH IP/TP phase coincides with stronger/weaker low surface pressure anomalies over TP. The stronger ascending and upper-tropospheric divergence anomalies above TP during stronger TPUHS days connect to compensatory stronger descending and upper-tropospheric convergence anomalies over IP. Such day-to-day SAH variability associated with TPUHS exhibits a quasi-biweekly time scale with a pronounced westward propagating signal.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Heat index (HI) provides a proven indicator of heat stress and discomfort for the general public. The index takes the integrated effects of both temperature and humidity into account, and both factors are regulated by large-scale circulation patterns. This study examines the 〈em〉impacts of the North Atlantic Subtropical High〈/em〉 (〈em〉NASH〈/em〉) 〈em〉on HI over the〈/em〉 conterminous 〈em〉United States〈/em〉 (〈em〉CONUS〈/em〉). 〈em〉The〈/em〉 analysis suggests that the HI is primarily controlled by surface air temperature over the CONUS; but is negatively correlated with relative humidity in the western and Central US north of 40°N. In addition, winds contribute to the variation of HI in the Midwest and the southeastern US. By regulating these meteorological parameters, the movement of the NASH western ridge significantly impacts HI over the US, especially the Southeast. When the NASH western ridge is located northwest (NW) of its climatological mean position, abnormally high temperatures are observed due to fewer clouds and a precipitation deficit, leading to positive HI anomalies over the southeastern US. In contrast, when the western ridge is located in the southwest (SW), temperature decreases and HI anomaly becomes negative over the Southeast, even though relative humidity increases east of 100°W. NASH has a weaker impact on the HI when it is far from the North American continent, especially during southeast (SE) ridge years. In the future, CMIP5 models project an increase in HI over the entire CONUS, while NASH-induced HI will be weakened during the NW, SE and NE ridge years but strengthened when its ridge moves to the SW quadrant. These results suggest that future increases in heat stress are likely caused by climatological warming and NASH intensification.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Variability and trends of Fram Strait sea ice area and volume exports are examined for the period of 1990–2010. Simulations from a high-resolution version of the MPIOM model (STORM project) reproduce area and volume export well when compared with NSIDC and ICESat satellite data and in-situ ice thickness observations. The fluxes derived from ice thickness and drift satellite products vary considerably, indicating a high uncertainty in these estimates which we mostly assign to the drift observations. The model captures the observed average seasonal cycles and interannual variability of ice export. The simulated mean annual sea ice area export is 860 × 10〈sup〉3〈/sup〉 km〈sup〉2〈/sup〉 a〈sup〉− 1〈/sup〉 (1990–2010), and the correlation with the NSIDC-based area fluxes is 〈em〉r〈/em〉 = 0.67. The simulated mean annual volume export is 3.3 × 10〈sup〉3〈/sup〉 km〈sup〉3〈/sup〉 a〈sup〉− 1〈/sup〉 (1990–2010), close to the ICESat/ULS values, with a correlation of 〈em〉r〈/em〉 = 0.58. The simulated monthly area export has a significant positive trend of + 10% per decade, explained by wind forcing. The major contribution to the robust trend in area export between June and September. Fram Strait ice volume export variability is mainly controlled by ice drift with a dominant role of the Transpolar Drift and, to a lesser extent thickness variability. The area export increase reflects increasing ice-drift speed, but is balanced with a reduced thickness over time when it comes to volume export, giving no significant trend in volume export. The spatial variability of ice drift indicates that the export influences a large area upstream in the Trans-Polar Drift stream, and that high volume export events lead to a thinner thickness there. The central Arctic is well connected drift-wise to the Fram Strait via the Transpolar Drift while for thickness, the region north of Greenland is dominated and controlled by the Fram Strait ice export.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉In this study, we investigate the predictability of the tropical Indian Ocean (TIO) sea surface temperature anomalies (SSTA) using the recently released North American Multimodel Ensemble dataset (NMME). We place emphasis on the predictability of two interannual variability modes: the Indian Ocean Basin mode (IOBM) and the Indian Ocean Dipole (IOD). If defined by a 0.5 correlation skill, we find that the statistically skilful predictions correspond to an approximately 9- and 4-month lead for the two modes, respectively. We then applied a newly-developed predictability framework, i.e. Average Predictability Time method (APT), to explore the most potentially predictable mode (APT1) for the TIO SSTA. The derived APT1s correlate significantly to the IOBM and IOD, but are also characterised by several significant differences, which implies that there is a close link between the variability-related modes and the predictability-defined modes. Further analysis reveals that the predictability source of the IOBM-related APT1 originates from ENSO-induced thermocline variation over the southwest Indian Ocean, whereas wind-driven upwelling near Sumatra dominates IOD-related APT1. This study provides insights into the understanding of TIO SSTA predictability and offers a practical approach to obtain predictable targets to improve the TIO seasonal prediction skill.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Marine heatwaves have been shown to be increasing in frequency, duration and intensity over the past several decades. Are these changes related to rising mean temperatures, changes to temperature variability, or a combination of the two? Here we investigate this question using satellite observations of sea surface temperature (SST) covering 36 years (1982–2017). A statistical climate model is used to simulate SST time series, including realistic variability based on an autoregressive model fit to observations, with specified trends in mean and variance. These simulated SST time series are then used to test whether observed trends in marine heatwave properties can be explained by changes in either mean or variability in SST, or both. We find changes in mean SST to be the dominant driver of the increasing frequency of marine heatwave days over approximately 2/3 of the ocean; while it is the dominant driver of changes in marine heatwave intensity (temperature anomaly) over approximately 1/3 of the ocean. We also find that changes in mean SST explain changes in both MHW properties over a significantly larger proportion of the world’s ocean than changes in SST variance. The implication is that given the high confidence of continued mean warming throughout the twenty-first century due to anthropogenic climate change we can expect the historical trends in marine heatwave properties to continue over the coming decades.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The weather and climate conditions can provide favorable or unfavorable atmospheric background for the maintenance and development of haze events. This study investigates the potential impacts of Arctic warming on the variation of Northern Hemisphere mid-latitude aerosol optical depth (AOD) in winter when haze often occurs. We first analyze the spatio-temporal variability of wintertime AOD in mid-latitudes of Northern Hemisphere from NASA MERRA-2 for the period of 1980–2016 using the empirical orthogonal function analysis and morlet wavelet analysis. It showes increasing trend for AOD in East China and North India and decreasing trend for AOD in Europe and North America during last 37 years while inter-decadal fluctuations exist. In addition to the temporal trends of AOD, two long-term periodic variations with periods of about 7 and 11 years exist, which implies the potential impacts from natural variabilities. Further analysis shows high correlations between the mid-latitude winter AOD (WA) and Arctic summer (May and June) surface temperature (T〈sub〉56〈/sub〉). Moreover, the Arctic summer surface temperature demonstrates similar periodic variations with periods of about 7–9 and 11–13 years. Both of these indicate the potential impacts of Arctic summer warming on mid-latitude winter pollution. We then analyze the temporal correlations between Arctic summer temperature and mid-latitude winter AOD in different regions. Arctic T〈sub〉56〈/sub〉 correlates negatively with WA in Europe and North America, and positively with that in East Asia, North India and Middle East. Particularly, T〈sub〉56〈/sub〉 in western sea of Novaya Zemlya has the most prominent correlation with the WA in mid-latitudes of East Asia, especially in East China. This implies that Arctic T〈sub〉56〈/sub〉 in the Arctic circle of Europe could be used for rough estimates of winter AOD in East Asia.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We investigate the impact of tropical tropopause warming on the stratospheric water vapor using the Specified-Dynamics version of the NCAR Whole Atmosphere Community Climate Model. We find that the tropical tropopause warming results in a strengthening of the Brewer–Dobson circulation (BDC). The strengthening of BDC induced by a narrow warming of tropical tropopause within 12° latitude, which is much stronger in boreal winter than that in boreal summer, propagates more dry air from the tropical tropopause into the stratosphere and thus causes a reduction of water vapor in the middle stratosphere. On the contrary, the seasonal difference of the BDC strengthening is weaker in the experiment with a broader tropical tropopause warming within 25° latitude. The drying effect of the BDC is counteracted by the moistening effects of the tropical tropopause warming and methane oxidation. This leads to the moistening in both the lower and upper stratosphere. The results suggest the control of the stratospheric humidity by the tropical tropopause temperature could be significantly offset by the associated BDC changes.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We apply the Community Ice Sheet Model (CISM2) to determine the extent to which the Last Glacial Maximum (LGM) temperature and precipitation climatologies from the Paleoclimate Modelling Intercomparison Project 3 (PMIP3) simulations support the large North American ice sheets that were prescribed as a boundary condition. We force CISM2 with eight PMIP3 general circulation models (GCMs), and an additional model, GENMOM. Seven GCMs simulate LGM climatologies that support positive surface mass balances of the Laurentide and Cordilleran ice sheets (LIS, CIS) consistent with where ice was prescribed in the GCMs. Two GCMs simulate July temperatures that are too warm to support the ice sheets. Four of the nine CISM2 simulations support ice sheets in Beringia, in absence of prescribed ice in the driving GCMs and in disagreement with geologic evidence that indicates the area remained ice-free during the LGM. We test the sensitivity of our results to a range of snow and ice positive degree-day factors, daily, monthly, and climatological temperature and precipitation inputs, and we evaluate the role of albedo and snow in the simulations. Areas with perennial snow in the GCM simulations correspond well to the presence of ice in the CISM2 simulation. GCMs with unrealistically low surface albedos over the LIS yield simulations that fail to simulate realistic ice sheets.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The South Pacific Convergence Zone (SPCZ) is poorly represented in global coupled simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), with trademark biases such as the tendency to form a “double Intertropical convergence zone” and an equatorial cold tongue that extends too far westward. Such biases limit our confidence in projections of the future climate change for this region. In this study, we use a downscaling strategy based on a regional atmospheric general circulation model that accurately captures the SPCZ present-day climatology and interannual variability. More specifically, we investigate the sensitivity of the projected rainfall response to either just correcting present-day CMIP5 Sea Surface Temperature (SST) biases or correcting projected SST changes using an emergent constraint approach. While the equatorial western Pacific projected rainfall increase is robust in our experiments and CMIP5, correcting the projected CMIP5 SST changes yields a considerably larger reduction (~ 25%) than in CMIP5 simulations (~ + 3%) in the southwestern Pacific. Indeed, correcting the projected CMIP5 warming pattern yields stronger projected SST gradients, and more humidity convergence reduction under the SPCZ. Finally, our bias-corrected set of experiments yields an increase in equatorial rainfall and SPCZ variability in the future, but does not support the future increase in the frequency of zonal SPCZ events simulated by CMIP5 models. This study hence suggests that atmospheric downscaling studies should not only correct CMIP5 present-day SST biases but also projected SST changes to improve the reliability of their projections. Additional simulations with different physical parameterizations yield robust results.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The data scarcity and poor availability of observed daily rainfalls over Southeast Asia has limited the possibility to a wider range of studies in light of impacts from climate change and extreme hydro-meteorological processes such as floods, droughts, and other watershed management practices. To fill such a gap, data assimilation was carried out in this study to construct a long-term gridded daily (0.50° × 0.50°) rainfall time series (1951–2014) over Southeast Asia. In rainfall data assimilation, the available and globally accepted high resolution gridded datasets viz. Southeast Asia observed (SA-OBS) (1981–2014), APHRODITE (1951–2007), TRMM (1998–2018), PRINCETON (1951–2008) along with limited rain gauges-based rainfalls were utilized. In this study, eight gap filling methods were employed and tested at 20 selected rainfall grids to fill the long gaps presented in the SA-OBS gridded dataset. The strength of each method and associated uncertainties were evaluated in the computed rainfalls utilizing multiple functions at missing grids. The accuracy of each method, in case of extreme rainfalls, was tested by quantile–quantile (Q–Q) plots at different quantile intervals. The distance power method based on the Pearson correlation coefficient and the multiple linear regression method performed satisfactorily and produced minimum uncertainties in filling rainfall gaps. To test the accuracy and compatibility of gap-filled SA-OBS gridded dataset with other sources of datasets, the seasonality analysis and rainfall indices comparison were carried out. Results showed that the gap-filled SA-OBS dataset was better comparable to other sources of rainfalls. For the construction of the long-term rainfall time series (1951–2014), quantile mapping was adopted for bias correction and the quality of the final merged dataset was evaluated.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Westerly wind bursts play an important role in the development of El Niño-Southern Oscillation (ENSO) events. However, the impact of easterly wind bursts (EWBs) on the development of ENSO is still unclear. In particular, a series of strong EWBs in the summer of 2014 aroused arguments about their importance in suppressing the potential warming in the summer. In this study, we conduct a series of sensitivity experiments using the fully-coupled NCAR Community Earth System Model with prescribed strong EWBs to distinguish their impact on the development of the model El Niño events, as well as the seasonality of the potential impact. Model results indicate that wintertime warming is significantly suppressed by the EWBs in summer due to the strongest ocean–atmosphere interaction associated with the most unstable background coupled system. With stronger anomalous zonal SST gradient and relatively more stable background state, the EWB-induced cooling in autumn is smaller than the cooling induced by the summertime EWBs. In spring when the ocean–atmosphere interaction is relatively weaker, the impact of EWBs depends on the EWB-forced shift of the eastern edge of warm pool (EEWP), which is critical for the establishment of positive Bjerknes feedback. A mixed layer heat budget analysis further suggests that the seasonally-dependent impact of EWBs is mainly controlled by the zonal advective feedback process associated with the subsequent ocean–atmosphere interaction and to some extent related to the thermocline feedback as well. This study demonstrates that EWBs increase the uncertainty of the prediction of ENSO initialized in boreal spring and early summer even if the ocean subsurface precursors are strong.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The zonal oscillation of the western Pacific subtropical high (WPSH) significantly influences the weather and climate over East Asia. This study investigates characteristics and mechanisms of the zonal variability of the WPSH on subseasonal time scales during summer by using a subseasonal WPSH (Sub-WPSH) index. Accompanied with the Sub-WPSH index, strong anticyclonic (cyclonic) anomalies are found over East Asia and coastal region south of 30°N on both 850 hPa and 500 hPa. During the positive period of the Sub-WPSH index, the WPSH extends more westward with enhanced precipitation over the Yangtze–Huaihe river basin and suppressed precipitation over the south of the Yangtze River in China. These precipitation anomalies can last for at least 1 week. While the subseasonal zonal variability of the WPSH is found to be closely associated with atmospheric teleconnections and local air- sea interaction, the mechanisms of the variability are different before and after mid-July (early and late summer). In both early and late summer, the East Asia/Pacific (EAP) wave train pattern affects the zonal shift of the WPSH by inducing a low-level anomalous anticyclonic/cyclonic circulation over the subtropical western Pacific, and this mechanism is stronger in late summer. In constrast, the influence of the Silk-Road pattern wave train is more important in the early summer. Meanwhile, in late summer, a stronger SST forcing on the atmosphere and a faster cycle of subseasonal variations of the WPSH are observed before the westward stretch of the WPSH, which could be related to the colder local SST anomalies. The westward stretch of the WPSH is accompanied by stronger anticyclonic anomalies in late summer.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We develop a new reconstruction of the winter North Atlantic Oscillation (NAO) index using a network of 97 Euro-Mediterranean tree-ring series. The reconstruction covers the period 910–2018 C.E., making it the longest annually resolved estimate of winter NAO variability available. We use nested correlation-weighted principal components regression and the Maximum Entropy Bootstrap method to generate a 2400-member ensemble of reconstructions for estimating the final reconstruction and its quantile uncertainties. Extensive validation testing of the new reconstruction against data withheld from the calibration exercise demonstrates its skill. The skill level of the new reconstruction is also an improvement over two NAO reconstructions published earlier. Spectral analyses indicate that the new reconstruction behaves like a ‘white noise’ process with intermittent band-limited power, suggesting that the winter NAO is stochastically forced. The ‘white noise’ properties of our reconstruction are also shown to be consistent with the spectral properties of long instrumental NAO indices extending back to 1781 and NAO indices extracted from a large number of forced climate model runs covering the last millennium. In contrast, an annually resolved multi-proxy NAO reconstruction of comparable length, based in part on speleothem data, behaves more like externally forced ‘red noise’ process, which is inconsistent with our reconstruction, long observations, and forced model runs.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The linkages between upper-level westerly jet streams and snow depth over the Tibetan Plateau (TP) in winter (from November to the following April) were investigated for the period 1979–2014 using satellite-borne passive microwave retrievals of snow depth data and ERA-Interim reanalysis data. Anomalies in atmospheric circulation, temperature, and precipitation corresponding to variation in westerly jets were examined to find the causes of variation in snow depth over the TP, using singular value decomposition, composite analysis and dynamical diagnosis. Results show that variation in intensity and meridional shifts of westerly jets, with particular attention to the North Tibetan Plateau jet (NTPJ) and the South Tibetan Plateau jet (STPJ), significantly influence the interannual variation of snow depth over the TP in late winter (February–April). For the conjunction of intense STPJ and weak NTPJ, an anomalous cold low-pressure vortex is observed over the TP. The vortex extends across the TP and spans from the ground surface to the upper troposphere. There is anomalous ascending motion above the TP due to secondary circulations immediately south and north of STPJ, with increased moisture flux from the southwest. These circulation structures cause significant cooling and increased precipitation, thus promoting snowfall and snow accumulation. Temperature is a more important influence than precipitation on snow accumulation. Cooling over the TP is caused by cold temperature advection due to intensely cold air and weakened descending adiabatic heating due to anomalous ascending motion. Local moisture is reduced, and anomalous ascending moisture advection leads to more net precipitation and snowfall over the TP.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A recent period of increased precipitation over the Argentinian Pampas expanded the boundary of rain-fed agriculture. However, such changes may not be sustainable if they arose from transient climate regime shifts. Considerable research exists on trends and cycles in sub-daily to annual precipitation metrics including the frequency and intensity of extreme precipitation. However, efforts to identify wetter and drier phases (or regimes) in this region are scant. This article aims to bridge that gap and advance our understanding of the multi-annual behavior of regional precipitation extremes, which can have the greatest impacts. It is unlikely that all extreme events are drawn from a single probability distribution or generated by the same physical processes. Hence, hidden mixtures of Poisson distributions are fitted to several precipitation frequency metrics to explore whether the annual to decadal variations in extreme precipitation frequency are greater than anticipated from a single system, and representative of regime shifts. Statistically significant improvements in the fit over single distributions were found for statistical mixture models of the frequency of very wet days, and the frequency of wet spells. This supports the hypothesis that multiple weather regimes exist giving rise to wetter or drier epochs. Posterior probabilities of hidden states from the fitted mixture distributions were used to identify wetter and drier years for comparison with sea surface temperature anomalies. This confirmed the presence of two distinct regimes, supporting other research, into the dynamical influences of precipitation behavior in the Argentine Pampas.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The main aim of this two-part study is to use a perturbed parameter ensemble (PPE) to select plausible and diverse variants of a relatively expensive climate model for use in climate projections. In this first part, the extent to which climate biases develop at weather forecast timescales is assessed with two PPEs, which are based on 5-day forecasts and 10-year simulations with a relatively coarse resolution (N96) atmosphere-only model. Both ensembles share common parameter combinations and strong emergent relationships are found for a wide range of variables between the errors on two timescales. These relationships between the PPEs are demonstrated at several spatial scales from global (using mean square errors), to regional (using pattern correlations), and to individual grid boxes where a large fraction of them show positive correlations. The study confirms more robustly than in previous studies that investigating the errors on weather timescales provides an affordable way to identify and filter out model variants that perform poorly at short timescales and are likely to perform poorly at longer timescales too. The use of PPEs also provides additional information for model development, by identifying parameters and processes responsible for model errors at the two different timescales, and systematic errors that cannot be removed by any combination of parameter values.〈/p〉

Description: 〈p〉The Introduction section of the article, in the fourth line, a mathematical expression “(T 〉 0 °C)” should be “(T 〈 0 °C)”. The original article has been corrected.〈/p〉

Description: 〈p〉The HTML version of this article was published with incorrect copyright line. The correct copyright line is “The Author(s) 2018”. This error has been corrected.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Seasonal climate predictions of spring (March‒April‒May) dust weather frequency (DWF) over North China (DWFNC) are conducted based on a previous-summer (June–July–August) normalized difference vegetation index in North China (NDVINC), winter (December–January–February) sea-ice cover index over the Barents Sea (SICBS), and winter Antarctic Oscillation index (AAOI). The year-to-year increment approach is applied to improve the prediction skill. Two statistical prediction schemes—statistical models based on year-to-year-increment-form predictors (SM-DY) and anomaly-form predictors (SM-A)—are applied based on NDVINC, SICBS, and AAOI. The results show that the prediction model using the year-to-year increment approach performs much better in predicting DWFNC, with the correlation coefficient between the average DWFNC and the cross-validated results of SM-DY (SM-A) being 0.80 (0.68) during 1983–2016. A hybrid dynamical–statistical prediction model (HM-DY) is constructed based on NDVINC, SICBS, and a spring 850-hPa geopotential height index, derived from the second version of the NCEP Climate Forecast System. Results show that HM-DY has comparable prediction skill with SM-DY. Both SM-DY and HM-DY are extended to hindcast DWF over the 245 stations in the whole of northern China, indicating comparably high skill. The results show that NDVINC and SICBS account for large variances of the dust climate over northern China. In particular, NDVINC and SICBS can enhance 64% of stations in North China in their prediction of dust climate.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The impacts of the Madden Julian Oscillation (MJO) on the South American monsoon season are analyzed in the global context of the MJO propagating anomalies of convection and circulation. Unexplored aspects, such as the continental-scale daily precipitation anomalies in the MJO frequency band and changes in the frequency of extreme rainfall events, are disclosed throughout its cycle. Among other effects, the MJO increases the average daily precipitation by more than 30% of the climatological value and doubles the frequency of extreme events over central-east South America (SA), including the South Atlantic Convergence Zone (SACZ). The evolution of the most intense precipitation anomalies depends on the interplay between tropics–tropics and tropics–extratropics teleconnections, and the topography over central-east SA seems to play a role in enhancing low-level convergence. The maximum anomalies are produced by a tropics-extratropics wave train. It not only favors precipitation anomalies over the SACZ and subtropical SA, but also strengthens the anomalies over tropical SA when the system propagates northeastward. Influence function analysis and simulations of the responses to different components of upper-level anomalous divergence associated with the MJO anomalous convection indicate the probable origin of the anomalous circulation leading to the main precipitation anomalies over SA. It is triggered by secondary anomalous convection, while the main tropical anomalous circulation is produced by the strongest equatorial convection anomalies. There are indications that MJO-related anomalies over SA contribute to the impacts on other regions and to the initiation of the MJO in the Indian Ocean.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Precipitation in California is modulated by variability in the tropical Pacific associated with El Niño/Southern Oscillation (ENSO): more rainfall is expected during El Niño episodes, and reduced rainfall during La Niña. It has been suggested that besides the shape and location of the sea surface temperature (SST) anomaly this remote connection depends on the strength and location of the atmospheric convection response in the tropical Pacific. Here we show in a perturbed physics ensemble of the Kiel Climate Model and CMIP5 models that due to a cold equatorial SST bias many climate models are in a La Niña-like mean state, resulting in a too westward position of the rising branch of the Pacific Walker Circulation. This in turn results in a convective response along the equator during ENSO events that is too far west in comparison to observations. This effect of the equatorial cold SST bias is not restricted to the tropics, moreover it leads to a too westward SLP response in the North Pacific and too westward precipitation response that does not reach California. Further we show that climate models with a reduced equatorial cold SST bias have a more realistic representation of the spatial asymmetry of the teleconnections between El Niño and La Niña.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A prominent precipitation decrease occurred over the equatorial central Pacific in the late 1990s, accompanied by precipitation increase around the Maritime Continent and over the equatorial America. Previous studies attributed the above change to La Niña-like decadal mean sea surface temperature (SST) cooling associated with a positive to negative phase switch of the Pacific Decadal Oscillation (PDO). Results of numerical experiments with an atmospheric general circulation model reveal that both the interdecadal and interannual components of SST variations contribute to the late 1990s’ precipitation reduction over the equatorial central Pacific in all the four seasons and the precipitation increase around the Maritime Continent in winter and summer. The accompanying precipitation increase over the Central America is mainly induced by the interdecadal components of SST variations. The contribution of interannual SST variations to the equatorial central Pacific precipitation decrease mostly stems from a larger rate of precipitation change with SST in positive than negative SST anomaly years, which leads to a residual decadal mean precipitation being larger during the period before than after the late 1990s. The moisture budget decomposition demonstrates that the dynamic effect associated with the vertical motion change dominates the tropical decadal mean precipitation changes in all the four seasons and the thermodynamic effect associated with the moisture change is small. This applies to the equatorial central Pacific, the Maritime Continent, and the Central America in both interdecadal and interannual SST forced simulations.〈/p〉

Description: 〈p〉In the original publication of the article Figs. 6 and 7 were published incorrectly. The correct figures are given below. The original article has been corrected.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We have investigated interannual variations of the spring (February–April average) East India Coastal Current (EICC) magnitude between 2000 and 2018 using OSCAR (Ocean Surface Current Analysis Real-time) current and a linear, continuously stratified (LCS) model. Interannual variability of the EICC shows significant decrease in magnitude during spring of 2000, 2008 and 2011, the years when high negative ONI (Oceanic Niño Index for sea surface temperature) value has been observed due to dominance of strong La Niña events. Our LCS model also successfully simulates these interannual variability of the spring average EICC between 2000 and 2018. We carried out numerical experiments using LCS model related to local and remote forcing response on EICC. Dynamics of the EICC during spring are dominated by four different forcing processes; local wind along east coast of India, remote forcing response from the eastern and northern boundary of the BoB including islands, interior BoB and the Equatorial Indian Ocean (EIO). During El Niño and normal spring years, strong poleward interannual EICC are due to very weak negligible (order of 0–5 cm s〈span〉 〈span〉\(^{-1}\)〈/span〉 〈/span〉) EICC from EIO remote response and in-phase poleward EICC formation using other three forcings. However, during La Niña spring years, weak (order of 0–10 cm s〈span〉 〈span〉\(^{-1}\)〈/span〉 〈/span〉) poleward interannual EICC are formed due to destructive interference between equatorward current (order of 10–25 cm s〈span〉 〈span〉\(^{-1}\)〈/span〉 〈/span〉) from EIO forcing and in-phase poleward current from other three forcings. We have also found propagation of interannual upwelling (downwelling) favorable Kelvin wave from EIO via eastern and western boundary of the BoB during spring in the El Niño (La Niña) years. The interannual variations in the propagation of EIO Kelvin wave are associated with the changes in the EIO zonal wind direction by climate mode like ENSO (El Niño–Southern Oscillation).〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉In this study, the parameterization of sea surface turbulent heat flux in National Center for Atmospheric Research Community Atmosphere Model version 5 (CAM5) is improved by including the contribution of mesoscale convective motion (i.e., mesoscale enhancement). The effect of mesoscale enhancement on the simulation of the East Asian summer monsoon circulation is further explored with SST-forced experiments that are conducted for the period of January 1979 to December 2015. Experiments suggest that the standard CAM5 exhibits evident biases in simulating the East Asian summer monsoon system. For example, the simulated westerlies at 850 hPa in low latitude of East Asia are too weak, the precipitations in the Bay of Bengal, the South China Sea, and the tropical western Pacific are underestimated, the simulated south Asia and western Pacific subtropical highs are too weak, and the upper and middle troposphere in the low latitudes of East Asia is too cold. By including the mesoscale enhancement in CAM5, these biases are clearly reduced. For example, the simulated summer mean precipitation in the Bay of Bengal is increased from 9.85 to 11.76 mm/day, which is closer to the observed value of 13.80 mm/day. Further analyses show that the improvements in the East Asian summer monsoon precipitations and circulations can be attributed to the enhancement of convections and the increase in water evaporation in the tropical western Pacific Ocean induced by mesoscale enhancement. Correspondingly, the latent heat due to vapor condensation in the atmosphere also increases, which reduces the cold bias in the mid-upper troposphere. Meanwhile, the geopotential height of the upper-middle-level atmosphere is elevated, which makes the simulated intensity of the south Asian and the western Pacific subtropical highs, two important components of the East Asian summer monsoon circulation, closer to the reality.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉As one of the most important indicators of nonlinear time series, temporal asymmetric (TA) or temporal irreversible behaviors of daily fluctuations from four temperature variables, including mean temperature (T〈sub〉mean〈/sub〉), maximum temperature (T〈sub〉max〈/sub〉), minimum temperature (T〈sub〉min〈/sub〉) and diurnal temperature range (DTR, DTR = T〈sub〉max〈/sub〉 − T〈sub〉min〈/sub〉), have been quantified through both observations and reanalysis over China by two TA measures. One is 〈em〉L〈/em〉〈sub〉2〈/sub〉 from directed horizontal visibility graph and the other is 〈em〉L〈/em〉〈sub〉1〈/sub〉 from consecutive increasing and decreasing steps. The results show that there are differential TA features among daily temperature fluctuations. Firstly, there are marked differences in TA strengths among different temperature variables. It is found that dominated uniformly significant TA (larger than the threshold from corresponding surrogates) emerges in almost all observed T〈sub〉mean〈/sub〉 fluctuations. However, this kind of uniformly significant TA can’t be found in T〈sub〉max〈/sub〉, T〈sub〉min〈/sub〉 and DTR for both observed and reanalysis data sets. Since both TA measures 〈em〉L〈/em〉〈sub〉1〈/sub〉 and 〈em〉L〈/em〉〈sub〉2〈/sub〉 quantify the temporal structures in the given series, this distinguishable TA strengths found in different temperature variables indicates that there are distinct temporal structures in the different temperature variables’ variations. Secondly, the TA in each temperature variable is region dependent. The TA strength for each temperature variable is spatially non-uniform with some strong and weak TA regional patterns and these strong and weak TA regional patterns may depend on local weather or climate conditions. Moreover, comparison studies of the same temperature variable reveal that time irreversible features are distinguishable between observations and reanalysis, and this differential feature can be taken as an index to evaluate the quality of reanalysis.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The meridional teleconnection over East Asia (EA-MT) is one of the major features of East Asian summer monsoon (EASM), and it is also the important pathway for the impacts from both tropical and extratropical middle-high latitudes on the EASM. To reveal the temporal-spatial structure of summer EA-MT, multivariate EOF is applied to the latitude-pressure cross section of combined summer precipitation and zonal wind anomalies over East Asia, using GPCP precipitation and NCEP/NCAR reanalysis dataset during the period 1979–2016. Two leading modes of summer EA-MT are obtained and identified as the tropical and extratropical-origin EA-MT in terms of their specific characteristics and major sources, named “EA-TMT” and “EA-XTMT”, respectively. Both of them show strong interannual variabilities, and they demonstrate a quasi-barotropic structure of westerly wind anomalies that slightly tilts northward with height in the mid-high latitudes, and accordingly significant precipitation anomalies are constrained right underneath the anomalous zonal wind around the Yangtze River valley (YRV), which in turn helps to establish and maintain the summer EA-MT. The EA-TMT is triggered by anomalous convective activities in the western North Pacific and propagates northward in the mid-low troposphere, it has close relationship with the anomalies of East Asian summer westerly jet (EASWJ) intensity and the YRV precipitation, which is superior over the East Asia/Pacific and Pacific-Japan teleconnection patterns in representing the tropical-origin EA-MT. The EA-XTMT is however mainly initiated in the southeast of Kara Sea and propagating southeastward in the whole troposphere, it is dominated by the North Asian dipole mode and mainly related to the EASWJ position anomaly, favoring a “South Flood North Drought” pattern of precipitation anomalies over East China. Meanwhile, the EA-TMT is closely related to the summer SST anomalies in the tropical Pacific-Indian ocean and partly correlated with ENSO, whereas the EA-XTMT is possibly linked to the spring sea ice concentration anomalies in the western Arctic and Barents Sea. Furthermore, the joint contributions of EA-TMT and EA-XTMT are essential for the major variability of EASM, wherein the EA-TMT plays a primary role.〈/p〉

Description: 〈p〉The article On the variation of the Pacific center: a revisit to the physical nature of Arctic Oscillation, written by Qian Cheng and Benkui Tan, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 11 December 2018 with open access.〈/p〉

Description: 〈p〉The original article can be found online.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the 〈em〉Max-Planck-Institut für Meteorologie〈/em〉 (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD.〈/p〉

Description: 〈p〉The article The North African coastal low level wind jet: a high resolution view, written by Pedro M. M. Soares, Daniela C. A. Lima1, Álvaro Semedo, Rita M. Cardoso, William Cabos and Dmitry Sein, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 15 September 2018 without open access.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Record-breaking hot and cold extremes have occurred in China in recent years and, therefore, it is compelling to investigate the long-term trend in temperature extremes at individual stations to see whether they have become more frequent. Many previous studies on the linear trend analysis of temperaure extremes in China have used oridinary least squares (OLS) regression, without consideration of non-Gaussian and/or serially dependent characteristics, or nonparametric methods, again not considering the latter, thus leaving some uncertainty in the significance testing. The present study examines in detail these characteristics in eight commonly used extreme temperature indices, on the basis of both station data and gridded data across China. The results show that 71–100% of the stations or grids cannot directly use standard OLS regression to analyze the statistical significance of the linear trend, because of either non-Gaussian or Gaussian but serially dependent characteristics in the regression residuals. Also, more than 43% of the stations and more than 54% of the grid boxes for annual indies cannot directly use the original Sen’s slope estimator and Mann–Kendall test because of serial dependence. Based on a nonparamtric method that takes into account serial dependence, the spatial patterns of the linear trend on an annual basis, as well as in hot and cold extremes, are examined for the period 1960–2017. The results show that hot extremes at most stations have increased, more than 57% of which are statistically significant; whereas, cold extremes at almost all stations have decreased, more than 32% (85%) of which are statistically significant during daytime (at night).〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉North tropical Atlantic (NTA) spring sea surface temperature (SST) tends to be warmer (cooler) than normal in Central Pacific (CP) El Niño decaying years during 1960s to mid-1980s. However, the relationship between the NTA spring SST and CP El Niño-Southern Oscillation (ENSO) is weakened after mid-1980s. This study presents this interdecadal change and investigates possible causes. Before the mid-1980s, above-normal NTA SST peaks in post-El Niño spring. The CP El Niño can affect NTA spring SST by inducing a negative phase of North Atlantic Oscillation (NAO) anomaly over North Atlantic from winter to spring. This negative NAO circulation weakens the Azores High and causes weaker than normal trade wind. As a result, less heat loses from the NTA Ocean and above-normal SST anomalies generated. In contrast, after the middle 1980s, the connection between CP ENSO and NAO-like anomaly has been disrupted. This leads to a weakening of CP ENSO influences on the NTA spring SST. The observed change in the relationship between NTA spring SST and CP ENSO is likely related to the state of the polar vortex. Before the middle 1980s, the polar vortex is weak, this favors the propagation of ENSO-related wave flux. The Rossby wave trains spread to the stratosphere during El Niño conditions and cause weaker than normal polar vortex, resulting in a negative NAO in the low levels. And the subtropical jet is enhanced and elongated which provides a potential waveguide for wave activity propagating to the Atlantic through a tropospheric way. However, the polar vortex is strong after mid-1980s, preventing the propagation of the ENSO-related wave trains through the stratosphere or the troposphere.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Anthropogenic aerosols (AA) can affect cloud and precipitation through aerosol–radiation interaction (ARI) and aerosol–cloud interaction (ACI). Over the past few decades, anthropogenic aerosol emissions have exhibited remarkable changes in the magnitude and in spatial pattern. The most significant changes are the increased emissions over both South Asia and East Asia. In this study, the atmospheric component of a state-of-the-art climate model that includes eight species of tropospheric aerosols, coupled to a multi-level mixed-layer ocean model, has been used to investigate the impacts of Asian anthropogenic aerosol precursor emission changes from 1970s to 2000s on large scale circulation and precipitation in boreal summer over East Asia. Results reveal significant changes in circulation and clouds over East Asia and over the tropical and western North Pacific (WNP). Increased Asian AA emissions lead to anomalous cyclonic circulation over the Maritime continent (MC) and anomalous anticyclonic circulation over the WNP, resulting in anomalous moisture transport convergence over the MC and therefore increased precipitation. They also lead to anomalous moisture flux divergence over both the WNP and large land areas of East Asia, especially over northern China, and therefore decreased precipitation there. These large scale circulation anomalies over the adjacent oceans are related to aerosol change induced ocean feedbacks, predominantly through ACI. It is the slow responses over the adjacent oceans (e.g., SST changes) through coupled atmosphere–ocean interaction in pre-monsoon seasons and summer that shape the changes of the East Asian summer monsoon and local precipitation. The results in this study suggest that increased Asian AA emissions from 1970s to 2000s may have played an important role for the observed southward shift of the Pacific intertropical convergence zone and precipitation belt, weakening of East Asian summer monsoon and reduced precipitation over northern China in East Asia during the latter half of the twentieth century.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Statistical and dynamical model simulations have been commonly used separately in El Niño–Southern Oscillation (ENSO) prediction. Current models are imperfect representations of ENSO and each of them has strength and weakness for capturing different aspects in ENSO prediction. Thus, it is important to utilize the results from a variety of different models. The Bayesian model averaging (BMA) is an effective tool not only in describing uncertainties associated with each model simulation but also providing the forecast performance of different models. The BMA method was developed to combine the NCEP/CPC three statistical and one dynamical model forecasts of seasonal Ocean Niño Index (ONI) from 1982 to 2010. The BMA weights were derived directly from the predictive performance of the combined models. The highly efficient expectation–maximization (EM) algorithm was used to achieve numerical solutions. We show that the BMA method can be used to assess the performance of the individual models and assign greater weights to better performing models. The continuous ranked probability score is applied to evaluate the BMA probability forecasts. As an elaboration of the reliability diagram, the attributes diagram is used that includes the calibration function, refinement distribution, and reference lines. The combination of statistical and dynamical models is found to provide a more skillful prediction of ENSO than only using a suite of statistical models, a single bias-corrected dynamical model, or the equally weighted average forecasts from all four models. Probability forecasts of El Niño events based only on winter ONI values are reliable and exhibit sharpness. In contrast, an under-forecasting bias and less reliable forecasts are noted for La Niña.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉According to El Niño–Southern Oscillation (ENSO) energetics theory, the work done by the wind on the ocean, known as wind power, has a strong forcing relationship with ENSO sea surface temperature (SST) changes, wherein negative (positive) tropical Pacific wind power anomalies contribute to warm (cold) ENSO events. The ENSO energetics framework assumes a mean state characterized by easterly winds, westward currents and a thermocline shoaling from west to east such that positive zonal wind power anomalies will induce a La Niña state and negative anomalies will induce an El Niño state. In this study, tropical Pacific wind power is computed using satellite data and its correlations with Niño 3.4 SST anomalies evaluated and compared to the conventional dynamical predictors, namely warm water volume and wind stress. Analysis of the spatial and temporal structure of climatological wind power and its variability during individual ENSO events reveals sign inconsistencies in which certain wind power anomalies (e.g. those associated with westerly wind events in the far west) are positive despite forcing the system towards an El Niño state. These results show that the conventional ENSO energetics framework makes assumptions about the climatological state that are not always consistent with observations. We apply sign adjustments to the computation of a tropical Pacific wind power index that include the directional aspect of the wind power perturbations and find that these adjustments greatly enhance the lead correlations between wind power and Niño3.4 SST anomalies, which are now comparable to conventional dynamical predictors.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The decreasing trend in rainfall in the last few decades over the Indo-Gangetic Plains of northern India as observed in ground-based observations puts increasing stress on groundwater because irrigation uses up to 70% of freshwater resources. In this work, we have analyzed the effects of extensive irrigation over the Gangetic Plains on the seasonal mean and intra-seasonal variability of the Indian summer monsoon, using a general circulation model and a very high-resolution soil moisture dataset created using extensive field observations in a state-of-the-art hydrological model. We find that the winter-time (November–March) irrigation has a positive feedback on the Indian summer monsoon through large scale circulation changes. These changes are analogous to a positive North Atlantic Oscillation (NAO) phase during winter months. The effects of the positive NAO phase persist from winter to spring through widespread changes in surface conditions over western and central Asia, which makes the pre-monsoon conditions suitable for a subsequent good monsoon over India. Winter-time irrigation also resulted in a reduction of low frequency intra-seasonal variability over the Indian region during the monsoon season. However, when irrigation is practiced throughout the year, a decrease in June–September precipitation over the Gangetic Plains, significant at 95% level, is noted as compared to the no-irrigation scenario. This decrease is attributed to the increase in local soil moisture due to irrigation, which results in a southward shift of the moisture convergence zone during the active phase of monsoon, decreasing its mean and intraseasonal variability. Interestingly, these changes show a remarkable similarity to the long-term trend in observed rainfall spatial pattern and low-frequency variability. Our results suggest that with a decline in the mean summer precipitation and stressed groundwater resources in the Gangetic Plains, the water crisis could exacerbate, with irrigation having a weakening effect on the regional monsoon.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Understanding future changes in hydroclimatic variables plays a crucial role in improving resilience and adaptation to extreme weather events such as floods and droughts. In this study, we develop high-resolution climate projections over Texas by using the convection-permitting Weather Research and Forecasting (WRF) model with 4 km horizontal grid spacing, and then produce the Markov chain Monte Carlo (MCMC)-based hydrologic forecasts in the Guadalupe River basin which is the primary concern of the Texas Water Development Board and the Guadalupe-Blanco River Authority. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset is used to verify the WRF climate simulations. The Model Parameter Estimation Experiment (MOPEX) dataset is used to validate probabilistic hydrologic predictions. Projected changes in precipitation, potential evapotranspiration (PET) and streamflow at different temporal scales are examined by dynamically downscaling climate projections derived from 15 Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). Our findings reveal that the Upper Coast Climate Division of Texas is projected to experience the most remarkable wetting caused by precipitation and PET changes, whereas the most significant drying is expected to occur for the North Central Texas Climate Division. The dry Guadalupe River basin is projected to become drier with a substantial increase in future drought risks, especially for the summer season. And the extreme precipitation events are projected to increase in frequency and intensity with a reduction in overall precipitation frequency, which may result in more frequent occurrences of flash floods and drought episodes in the Guadalupe River basin.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Sea surface temperature (SST) patterns both local to and remote from tropical cyclone (TC) development regions are important drivers of the variability of TC activity. Therefore, reliable simulations and predictions of TC activity depend on a realistic representation of tropical SST. Nevertheless, severe SST biases are common to the current generation of global climate models, especially in the tropical Pacific and Atlantic. These biases are strongly positive in the southeastern tropical basins, and negative, but weaker, in the northwestern tropical basins. To investigate the impact of the tropical SST biases on simulated TC activity, an atmospheric-only tropical channel model was used to conduct several sets of ensemble simulations. The simulations suggest an underrepresentation in Atlantic TC activity caused by the Atlantic cold bias alone, and an overrepresentation in Eastern North Pacific (ENP) TC activity due to the Atlantic cold bias and Pacific warm bias jointly. While the local impact of SST biases on TC activity is generally induced by the local anomalous SST and the associated changes in atmospheric conditions, the remote impact of the Atlantic bias on the ENP TCs is strongly driven by the change in topographically forced regional circulation. Moreover, an eastward shift in Western North Pacific TCs was generated by the Pacific SST biases, even though basin-wide TC activity indicators change insignificantly. The results indicate the importance of considering SST bias effects on simulated TC activity in climate model studies and highlight key regions where reducing SST biases could potentially improve TC representation in climate models.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The North African coastal low-level jet (NACLLJ) lies over the cold Canary current and is synoptically linked to the Azores Anticyclone and to the continental thermal low over the Sahara Desert. Although being one of the most persistent and horizontally extended coastal wind jets, this is the first high resolution modelling effort to investigate the NACLLJ climate. The current study uses a ROM atmospheric hindcast simulation with ~ 25 km resolution, for the period 1980–2014. Additionally, the underlying surface wind features are also scrutinized using the CORDEX-Africa runs. These runs allow the building of a multi-model ensemble for the coastal surface flow. The ROM and the CORDEX-Africa simulations are extensively evaluated showing a good ability to represent the surface winds. The NACLLJ shows a strong seasonal cycle, but, unlike most coastal wind jets, e.g. the California one, it is significantly present all year round, with frequencies of occurrence above 20%. In spring and autumn, the maxima frequencies are around 50%, and reach values above 60% in summer. The location of maximum frequency of occurrence migrates meridionally from season to season, being in winter and spring upwind of Cap-Vert, and in summer and autumn offshore the Western Sahara. Analogously, the lowest jet wind speeds occur in winter, when the median is below 15 m/s. In summer, the jet wind speed median values are ~ 20 m/s and the maxima are above 30 m/s. The jet occurs at heights ~ 360 m. A momentum balance is pursued disclosing that the regional flow is almost geostrophic, dominated by the pressure gradient and Coriolis force. Over the jet areas the ageostrophy is responsible for the jet acceleration.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Previous study reported that the annual-mean eastern Oyashio Extension (OE) front shifts northward while the western OE front has no obvious poleward shift during 1982–2017 by Wu et al. (Geophys Res Lett 45:9042–9048, 2018). Here we revisit this topic and focus on the seasonal variability and shifts of the OE fronts from 1982 to 2018, with observational reanalysis data and a 1.5-layer reduced-gravity model simulation. In winter, both the western and eastern OE fronts demonstrate consistent northward movement. While in summer, the eastern OE front still moves northward but the western OE front has no obvious and even southward shift. It is shown that the trade wind’s expansion during 1982–2018 favours the northward shift of the OE fronts for both winter and summer. However, there is a local cold Ekman heat transport anomaly along the western OE front in summer, which surpasses the effect of trade wind expansion and prohibits northward movement of the front. This cold Ekman advection is due to a westerly wind anomaly induced firstly by the Atlantic Multi-decadal Oscillation (AMO) and secondly by the Pacific Decadal Oscillation (PDO). In winter, the local Ekman heat transport is less effective than in summer in changing the OE front position because of the deep mixed layer. Our study demonstrates the seasonality of the OE front shift and highlights the importance of local Ekman heat transport associated with the AMO. Our results also partly explain the rainfall changes in both winter and summer in the western Pacific Ocean in the past 37 years, since the rainband east of Japan is affected by the sea surface temperature and its front.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The changes in three aspects of frequency, intensity and duration of the compound, daytime and nighttime heat waves (HWs) over China during extended summer (May–September) in a future period of the mid-21st century (FP; 2045–2055) under RCP4.5 scenario relative to present day (PD; 1994–2011) are investigated by two models, MetUM-GOML1 and MetUM-GOML2, which comprise the atmospheric components of two state-of-the-art climate models coupled to a multi-level mixed-layer ocean model. The results show that in the mid-21st century all three types of HWs in China will occur more frequently with strengthened intensity and elongated duration relative to the PD. The compound HWs will change most dramatically, with the frequency in the FP being 4–5 times that in the PD, and the intensity and duration doubling those in the PD. The changes in daytime and nighttime HWs are also remarkable, with the changes of nighttime HWs larger than those of daytime HWs. The future changes of the three types of HWs in China in two models are similar in terms of spatial patterns and area-averaged quantities, indicating these projected changes of HWs over the China under RCP4.5 scenario are robust. Further analyses suggest that projected future changes in HWs over China are determined mainly by the increase in seasonal mean surface air temperatures with change in temperature variability playing a minor role. The seasonal mean temperature increase is due to the increase in surface downward longwave radiation and surface shortwave radiation. The increase in downward longwave radiation results from the enhanced greenhouse effect and increased water vapour in the atmosphere. The increase in surface shortwave radiation is the result of the decreased aerosol emissions, via direct aerosol–radiation interaction and indirect aerosol–cloud interaction over southeastern and northeastern China, and the reduced cloud cover related to a decrease in relative humidity.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study provides the first assessment of CMIP5 model performances in simulating southern Africa (SA) rainfall variability in austral summer (Nov–Feb), and its teleconnections with large-scale climate variability at different timescales. Observed SA rainfall varies at three major timescales: interannual (2–8 years), quasi-decadal (8–13 years; QDV) and interdecadal (15–28 years; IDV). These rainfall fluctuations are, respectively, associated with El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO), interacting with climate anomalies in the South Atlantic and South Indian Ocean. CMIP5 models produce their own variability, but perform better in simulating interannual rainfall variability, while QDV and IDV are largely underestimated. These limitations can be partly explained by spatial shifts in core regions of SA rainfall variability in the models. Most models reproduce the impact of La Niña on rainfall at the interannual scale in SA, in spite of limitations in the representation of ENSO. Realistic links between negative IPO are found in some models at the QDV scale, but very poor performances are found at the IDV scale. Strong limitations, i.e. loss or reversal of these teleconnections, are also noted in some simulations. Such model errors, however, do not systematically impact the skill of simulated rainfall variability. This is because biased SST variability in the South Atlantic and South Indian Oceans strongly impact model skills by modulating the impact of Pacific modes of variability. Using probabilistic multi-scale clustering, model uncertainties in SST variability are primarily driven by differences from one model to another, or comparable models (sharing similar physics), at the global scale. At the regional scale, i.e. SA rainfall variability and associated teleconnections, while differences in model physics remain a large source of uncertainty, the contribution of internal climate variability is increasing. This is particularly true at the QDV and IDV scales, where the individual simulations from the same model tend to differentiate, and the sampling error increase.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The role of stratospheric water vapor (SWV) changes, in response to increasing 〈span〉 〈span〉\(\hbox {CO}_2\)〈/span〉 〈/span〉, as a feedback component of quantitative significance for climate sensitivity has remained controversial. Here, we calculate the SWV climate feedback under abrupt 〈span〉 〈span〉\(\hbox {CO}_2\)〈/span〉 〈/span〉 quadrupling in the CMIP5 ensemble of models. All models robustly show a moistening of the stratosphere, causing a global mean net stratosphere adjusted radiative perturbation of 〈span〉 〈span〉\(0.89\pm 0.27\,\hbox {Wm}^{-2}\)〈/span〉 〈/span〉 at the reference tropopause. The stratospheric temperature adjustment is a crucial component of this radiative perturbation. The associated climate feedback is 〈span〉 〈span〉\(0.17\pm 0.05\,\hbox {Wm}^{-2}\,\hbox{K}^{-1}\)〈/span〉 〈/span〉, with a considerable inter-model range of 0.12–0.28 〈span〉 〈span〉\(\hbox {Wm}^{-2}\,\hbox {K}^{-1}\)〈/span〉 〈/span〉. Taking into account the rise in tropopause height under 〈span〉 〈span〉\(4\times \hbox {CO}_2\)〈/span〉 〈/span〉 slightly reduces the feedback to 〈span〉 〈span〉\(0.15\pm 0.04\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\)〈/span〉 〈/span〉, with a range of 0.10–〈span〉 〈span〉\(0.26\,\hbox {Wm}^{-2} \,\hbox {K}^{-1}\)〈/span〉 〈/span〉. The SWV radiative perturbation peaks in the midlatitudes and not the tropics: this is due primarily to increases in SWV in the extratropical lowermost stratosphere, which cause the majority (over three quarters) of the global mean feedback. Based on these results, we suggest an increased focus on understanding drivers of water vapor trends in the extratropical lowermost stratosphere. We conclude that the SWV feedback is important, being on the same order of magnitude as the global mean surface albedo and cloud feedbacks in the multi-model mean.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The increase in glacial cycle length from approximately 41 to on average 100 thousand years around 1 million years ago, called the middle Pleistocene transition (MPT), lacks a conclusive explanation. We describe a dynamical mechanism which we call ramping with frequency locking (RFL), that explains the transition by an interaction between the internal period of a self-sustained oscillator and forcing that contains periodic components. This mechanism naturally explains the abrupt increase in cycle length from approximately 40 to 80 thousand years observed in proxy data, unlike some previously proposed mechanisms for the MPT. A rapid increase in durations can be produced by a rapid change in an external parameter, but this assumes rather than explains the abruptness. In contrast, models relying on frequency locking can produce a rapid change in durations assuming only a slow change in an external parameter. We propose a scheme for detecting RFL in complex, computationally expensive models, and motivate the search for climate variables that can gradually increase the internal period of the glacial cycles.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Strong El Niño events have had significant impacts on society through their association with extreme events, such as droughts and floods. However, questions remain as to the robustness of strong El Niño events in forcing regional climate variability. The strong 1982, 1997 and 2015 El Niño events were of similar type and strength, but in eastern Australia they were associated with differing spring rainfall anomaly magnitudes and patterns. To understand these differences, we first determined the most important processes for teleconnecting the El Niño signal to east Australian spring rainfall using historical relationships with winds and sea level pressure. Then, using a 60-member atmospheric model ensemble, we estimated the influence of sea surface temperatures (SSTs) on Australian atmospheric circulation and rainfall during these three El Niño events relative to internal variability. We found that the different east Australian spring rainfall anomalies for each of the three El Niño events are best explained by differences in the strength of the meridional wind component of the regional circulation. All three El Niño events exhibited a positive sea level pressure anomaly to the south of Australia, which was associated with rainfall deficits along the southeast Australian coast. The experiments indicate the regional atmospheric circulation and rainfall differences were forced by SSTs during spring of 1982 and 1997, with their influence on the circulation in 2015 remaining unclear. We also show that SSTs adjacent to Australia further contributed to the modelled rainfall differences mainly by regulating moisture availability.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study analyzes the dominant modes of interannual variability of surface air temperature (SAT) during boreal autumn over the mid-high latitudes of Eurasia and investigates their associations with snow cover, atmospheric circulation and sea surface temperature (SST). The first, second and third empirical orthogonal function (EOF) mode of autumn SAT anomalies displays same-sign distribution, an east–west dipole pattern and a south–north dipole pattern, respectively. Analysis of surface heat fluxes indicates that snow changes explain only small patches of SAT anomalies related to the first two EOFs via altering surface shortwave radiation. Atmospheric circulation anomalies have important contributions to the formation of SAT anomalies. Southerly (northerly) wind anomalies generally favor positive (negative) SAT anomalies via bringing warmer (colder) air from lower (higher) latitudes. The atmospheric circulation anomalies related to the first EOF mode are attributed to a combination of the Arctic Oscillation (AO) and the Scandinavia pattern and those related to the second EOF mode have a close relation with the East Atlantic/West Russian (EAWR) and circumglobal teleconnection (CGT) patterns. Formation of the atmospheric circulation anomalies related to the third EOF mode is partly related to the Arctic sea ice change around the Barents–Kara Seas. SST anomalies have little contribution to the atmospheric circulation anomalies associated with the first three EOF modes of Eurasian autumn SAT interannual variations. Hindcast skill of the SAT anomalies related to the first (second) EOF mode is improved when taking both the AO and Scandinavia (EAWR and CGT) patterns into account.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Bias correction is an essential technique to correct climate model outputs for local or site-specific climate change impact studies. Most commonly used bias correction methods operate on a single variable, which ignores dependency among multiple variables. The misrepresentation of multivariable dependence may result in biased assessment of climate change impacts. To solve this problem, a new multivariate bias correction method referred to as two-stage quantile mapping (TSQM) is proposed by combining a single-variable bias correction method with a distribution-free shuffle approach. Specifically, a quantile mapping method is used to correct the marginal distribution of single variable and then a distribution-free shuffle approach to introduce proper multivariable correlations. The proposed method is compared with the other four state-of-the-art multivariate bias correction methods for correcting monthly precipitation, and maximum and minimum temperatures simulated by global climate models. The results show that the TSQM method is capable of both bias correcting univariate statistics and inducing proper inter-variable rank correlations. Especially, it outperforms all the other four methods in reproducing inter-variable rank correlations and in simulating mean temperature and potential evaporation for wet and dry months of the validation period. Overall, without complex algorithm and iterations, TSQM is fast, simple and easy to implement, and is proved a competitive bias correction technique to be widely applied in climate change impact studies.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study examines the role of terrestrial forcings on the regional climate of sub-Saharan Africa through the application of a multivariate statistical method, stepwise generalized equilibrium feedback assessment, to an array of observational, reanalysis, and remote sensing data products. By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered. The approach from our 2017 study is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration (ET) partitioning in terrestrial feedbacks; and compare land surface feedbacks among four key regions, namely the Sahel, Greater Horn of Africa, West African monsoon region, and Congo. ET partitioning differs notably among sub-Saharan regions and between available observational datasets. Across sub-Saharan Africa as a whole, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions. The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions. Moisture recycling is the dominant mechanism in these regions, with positive soil moisture–vegetation–rainfall feedbacks. The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies. There is a clear need for more extensive observations of ET, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture–ET feedbacks, particularly across the Sahel.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Using nine model simulations from the PMIP3, we study simulated mean Indian summer (June–September) climate and its variability during the Last Millennium (LM; CE0850-1849) with emphasis on the Medieval Warm Period (MWP; CE1000-1199) and Little Ice Age (LIA; CE1550-1749), after validation of the simulated ‘current day (CE1850-2005)’ climate and trends. We find that the simulated above (below) mean-LM summer temperatures during the MWP (LIA) are associated with relatively higher (lower) moisture, and relatively higher (lower) number of concurrent El Niños (La Niñas). Importantly, the models simulate higher (lower) Indian summer monsoon rainfall (ISMR) during the MWP (LIA) compared to the LM-mean, notwithstanding a strong simulated negative correlation between NINO3.4 index and the area-averaged ISMR. Interestingly, the percentage of the simulated strong El Niños (La Niñas) associated with negative (positive) ISMR anomalies is higher (lower) in the LIA (MWP). This nonlinearity is explained by the simulated background climate changes, as follows. Distribution of simulated anomalous 850 hPa boreal summer velocity potential during MWP in models indicates, relative to the mean LM conditions, a zone of anomalous convergence in the central tropical Pacific flanked by two zones of divergence, i.e. a westward shift in the Walker circulation. The anomalous divergence centre in the west during the MWP also extends into the equatorial eastern Indian Ocean, triggering in an anomalous convergence zone over India and relatively higher moisture transport therein and therefore excess rainfall during the MWP as compared to the LM-mean, and hence an apparent weakening in the El Niño impact.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉We compare the representation of the Arctic liquid and solid freshwater volumes, and their transports to/from the Arctic, using simulations with different ocean and atmosphere model resolutions from models participating in the EU H2020 PRIMAVERA project. Regarding ocean resolution, we find less liquid freshwater in the central Arctic Ocean and more in the Kara and Laptev seas in the model simulations at higher resolution compared with the model simulations at lower resolution. The mean sea ice thickness does not show a systematic behaviour across models regarding model resolution increase. In terms of atmospheric resolution, we find that both liquid freshwater and mean sea ice thickness decrease when the resolution of the atmospheric model increases. We also analyze differences of Arctic liquid freshwater volume and mean sea ice thickness caused by pre-industrial and historical atmospheric forcings. Pre-industrial simulations show less freshwater volume and increased mean sea ice thickness and export from the Arctic compared with present day simulations. Finally, we find an increasing impact of Arctic freshwater export on North Atlantic convection with increased atmospheric resolution.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The sensitivity of simulation of the diurnal cycle (DC) to cumulus parameterisation is studied by using nine combinations (3 over Ocean × 3 over land) of cumulus schemes viz. Tiedtke, Emanuel, and Grell schemes for years 2008–2012 in the regional climate model RegCM4.4. The harmonic analysis is used to analyze the DC of rainfall simulated by the nine combinations of CPSs. It is seen that Emanual scheme predicts the spatial distribution of amplitude of the first harmonic and the variance of the diurnal cycle more appropriately compared to other CPSs. However, all schemes advanced the phase of the DC of rainfall by 3–6 h which is the result of the development of early convection in the model. The analysis of the development of rapid convection in the model suggests that sensible heat flux and vertically integrated moisture flux convergence peaks 3 to 6 h earlier compared to the phase of DC of rainfall estimated from TRMM rainfall. The early development of convection in the model may result in the inappropriate representation of condensation and evaporation cycle and hence DC of rainfall. The study emphasize that improvement in the phase of triggering of convection by cumulus parameterization schemes is essential to improve DC rainfall simulated by regional climate models.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Tibetan Plateau vortices (TPVs) are major rain producer over the Tibetan Plateau, which trigger heavy rainfall in southwestern and eastern China when moving off the plateau. In this work, two groups of TPVs moving off the plateau are selected according to their eastward moving speeds. The features of the atmospheric dynamic and thermodynamic fields associated with the two groups of TPVs are compared, based on the final (FNL) operational global analysis data from the Global Forecasting System of the National Centers for Environment Prediction (NCEP). The results show that the large-scale circulations and heating fields have a close relationship with the moving speed of the TPVs. The TPVs move eastward faster when wider and stronger convergence at 500 hPa, divergence at 200 hPa and the related ascending motion are observed to the east of TPVs. In addition, the stronger and further eastward stretching unstable stratification and water vapor convergence, as well as the more intensive heating field above 500 hPa to the east of TPVs, correspond to larger eastward moving speed of TPVs. Furthermore, the crucial factors modulating the moving speed of TPVs are explored through potential vorticity (PV) budget analyses, in which the physical variables are partitioned into zonal means and disturbances. The convergence of the mean zonal winds and disturbance winds at 500 hPa, as well as the vertical distribution of disturbance heating to the east of TPVs are the crucial factors influencing the eastward moving speed of TPVs, among which the vertical distribution of disturbance heating is the most dominant.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉This study describes the space–time structure of an intraseasonal oscillation with the time scale of a month over the South Asian monsoon region and the tropical Pacific for the boreal summer and winter seasons. These nonlinear oscillations were extracted by applying multichannel singular spectrum analysis on daily anomalies of three-dimensional diabatic heating separately during the summer and winter. The monthly oscillations (MOs) are distinct from the leading monsoon intraseasonal oscillation with a period of 45 days during the summer and the Madden–Julian Oscillation during the winter. The summer MO exhibits horizontal quadrupole structure predominantly in the Northern Hemisphere and propagates eastward over the Indian region and westward over the Pacific along with northward movement. The winter MO is confined to the equatorial region in the Southern Hemisphere and propagates eastward and southward. Both the summer and winter MOs consist of propagating deep vertical columns of heating and cooling anomalies. The associated fields of convection, precipitation and three-dimensional circulation show similar patterns and propagation. The corresponding specific humidity has revealed moisture preconditioning for horizontal propagation and co-located vertical advection. However, there is no clear pattern of ocean–atmosphere interaction associated with the MO as seen in the examination of sea surface temperature and latent heat flux.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The purpose of this study is to identify the vertical integrated moisture flux convergence (VIMFC) on the atmosphere of Iran. To achieve this goal, the monthly European Center for Medium range Weather Forecasting gridded data was used during the time period from 1979/1 to 2013/12. Initially, the troposphere was divided into three layers, L1 (850–1000 hPa), L2 (700–775 hPa), and L3 (500–600 hPa) based on the specific moisture amount in the atmosphere. The average long-term rate of VIMFC was plotted for each layers of the troposphere during different months of the year and relationship between VIMFC and precipitation rates was investigated on Iran. On the basis of the time series of the anomalies of the country’s precipitation, the VIMFC’S rates was divided into two periods of 1979–1998 and 1999–2013. To understand the VIMFC shifts in the different layers of the troposphere and its relationship with precipitation, probability distribution function (PDF) for VIMFC and precipitation was calculated. The findings showed that in the warm months, the VIMFC was far more than the cold months of the year and the VIMFC rate in the L1 is also higher than the other layers of the troposphere. Iran’s atmospheric moisture sources at the L1 are southern seas such as Red Sea, Arabic Sean, and Persian Gulf that is being driven toward Iran by Saudi Arabia Dynamic High Pressure System and Sudan’s Low Pressure System. In the L2, the Saudi Arabia Dynamic High Pressure is the most important atmospheric system that sends the moisture of the southern seas to Iran. The PDF shifts of Iran’s precipitation shows a very strong coordination with the VIMFC rate in different months of the year. The findings indicated that in the winter months (JFM), along with decreasing VIMFC rates, the country’s precipitation rate also decreased in the second period of 1999–2013.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A recent study shows that the current wind turbine parameterization in the weather research and forecasting (WRF) model can generally reproduce the satellite observed nighttime warming signal over wind farm (WF) regions over west central Texas, but also tends to produce a cooling effect in the WF downwind regions. The present study conducts a series of WRF simulations to further this research by addressing two fundamental questions: (i) what is the 3-D structure of simulated near-surface temperatures within and around WFs? (ii) what are the main physical mechanisms responsible for the simulated WF-induced temperature changes? Our results indicate that the WF-induced temperature changes are not only restricted to the surface but also can extend vertically to the hub-height level and horizontally in the downwind direction. The WF-induced change in sensible heat flux is the dominant factor for the simulated temperature changes at the surface, for both the warming signals over the WF region and the cooling signals behind it. Further diagnosis shows that the turbulent component of the wind turbine parameterization is responsible for the surface warming signal by enhancing vertical mixing while the momentum sink component is responsible for the surface cooling signal by enhancing near-surface thermal stratification. By analyzing the energy budget, we find two important physical processes that are critical to explain the simulated WF impacts on temperature: (i) vertical divergence of heat flux as parameterized in the planetary boundary layer scheme and (ii) resolved-scale 3-D temperature advection.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉The northern mid-latitude westerlies play an important role in the climate interactions between the low and high latitudes. Our understanding of the factors that control the latitudinal displacement of the westerlies remains incomplete due to insufficient climatic proxy. Here we present a latitudinal-shift record of the westerlies in the eastern Central Asia over the past 70,000 years, on the basis of the grain size of the loess sequence from the Tacheng basin. On millennial timescale, the variation of the reconstructed westerlies resembles that of the Greenland temperature and the Atlantic meridional overturning circulation (AMOC), indicating the role of the AMOC on the westerlies. On orbital time scale, their variation is controlled by precession and insolation. Our analyses of the LOVECLIM and CCSM3 models’ results show that the impact of insolation and AMOC on the latitudinal shift of the westerlies is through changing the latitudinal temperature and pressure gradients.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉A record of global single-layered ice cloud properties has been generated using the CloudSat and CALIPSO Ice Cloud Property Product (2C-ICE) during the period 2007–2010. These ice cloud properties are used as inputs for the NASA Langley modified Fu–Liou radiative transfer model to calculate cloud radiative heating rate profiles and are compared with the NASA CERES observed top-of-atmosphere fluxes. The radiative heating rate profiles calculated in the CloudSat/CALIPSO 2B-FLXHR-LIDAR and CCCM_CC products are also examined to assess consistency and uncertainty of their properties using independent methods. Based on the methods and definitions used herein, single-layered ice clouds have a global occurrence frequency of ~ 18%, with most of them occurring in the tropics above 12 km. Zonal mean cloud radiative heating rate profiles from the three datasets are similar in their patterns of SW warming and LW cooling with small differences in magnitude; nevertheless, all three datasets show that the strongest net heating (〉 + 1.0 K day〈sup〉−1〈/sup〉) occurs in the tropics (latitude 〈 30°) near the cloud-base while cooling occurs at higher latitudes (〉 ~ 50°). Differences in radiative heating rates are also assessed based on composites of the 2C-ICE ice water path (IWP) and total column water vapor (TCWV) mixing ratio to facilitate model evaluation and guide ice cloud parameterization improvement. Positive net cloud radiative heating rates are maximized in the upper troposphere for large IWPs and large TCWV, with an uncertainty of 10–25% in the magnitude and vertical structure of this heating.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Atmosphere–ocean coupling is critical for tropical cyclones (TC) formation and development. TCs derive their energy from the upper ocean, and the associated TC-ocean interactions can in turn modulate storm evolution. This study assesses the impact of ocean coupling on directly-simulated global TC activity in the high-resolution “TC-permitting” Community Earth System Model (CESM). Model-simulated global TC activity is evaluated in a 30-year fully-coupled CESM simulation (CPL), in which the 0.25° atmosphere component is coupled to the nominal 1° dynamic ocean (with ~ 0.27° horizontal grid spacing in the tropics). An atmosphere-only simulation (ATM) is branched from CPL, with sea surface temperature (SST) specified from CPL, which we use to isolate the effect of ocean coupling on TC activity. We find that the two-way ocean coupling can affect global TC frequency, geographical distribution, storm intensity, and interannual variability. ATM on average simulates 27% more major TC events than CPL globally, and the TC power dissipation is higher than CPL poleward of 12° latitude in both hemispheres. The lack of negative SST feedbacks in ATM allows TCs to have a longer intensification period and reach the maximum intensity at a higher latitude. In CPL, TC interannual variability is heavily influenced by El Nino/La Nina events. This relationship can be captured in ATM under strong events but is less predictable during weak and neutral years. Results help to better understand the connections and feedbacks linking air–sea coupling, tropical variability, and the directly simulated TC activity within the high-resolution Earth System Models.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉In this study, the Weather Research and Forecasting (WRF) model is used to quantify the effects of land use and cover change (LUCC) on the near-surface wind speed (SWS). The simulated results show that the SWS based on land use cover data for the 2010s (LUC10) is lower than that based on land use cover data for the 1980s (LUC80) by a difference of 0.17 m s〈sup〉−1〈/sup〉; the LUCC effects also result in a decrease of 9.0% of the probability of strong wind. The LUCC effects induce significant alteration of the roughness length, causing changes in the drag coefficient and friction velocity, and thereby decrease SWS. A 0.1 m increase in roughness length could cause a 0.003 increase in drag coefficient and a 0.015 m s〈sup〉−1〈/sup〉 increase in friction velocity. The contributions of LUCC to the SWS changes vary among different regions. The increase of SWS in Northeastern China is caused by the changes from deciduous broadleaf to deciduous needleleaf forests, mixed forests and croplands, and these changes decrease the surface roughness length, drag coefficient and friction velocity. The significant decrease of SWS over the middle reaches of the Yangtze River is induced by the changes from closed shrubland and cropland/natural vegetation mosaic to evergreen broadleaf and deciduous broadleaf forest. The slowdown of SWS over the Shandong Peninsula, the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Pearl River Delta can be attributed to the extension of urban and built-up areas and the decrease of croplands and the cropland/natural vegetation mosaic. The slowdown in SWS caused by LUCC is also revealed by the friction wind model (FWM); however, the FWM presented more significant effects of LUCC on decrease in SWS.〈/p〉

Description: 〈h3〉Abstract〈/h3〉 〈p〉Change to precipitation in a warming climate holds many implications for water management into the future, and an enhancement of a precipitation decrease or increase on or around mountains would have numerous impacts. Here, an intermediate resolution regional climate model (RCM) ensemble projects enhanced precipitation decrease on the windward slopes of over many mid-latitude mountains in winter, consistent with theory and model studies of idealised mountain ranges. This ensemble projects that an increase in convective rainfall determines the sign of total rainfall change in many regions in summer, only some of which are on or near mountains such as the European Alps. These same projected changes are present in inland slopes of the Australian Alps compared to surrounding regions as simulated by three RCM ensembles (the intermediate resolution and two high resolution ensembles), which agree on an enhanced precipitation decrease on the windward slopes in winter and spring, as well as an enhanced precipitation increase in summer driven by an increase in convective rainfall. The ensembles disagree on an enhanced precipitation decrease in autumn. The results represent regional-scale added value in the climate change signal of projections from high resolution models in cooler seasons, but suggest that the specific model components such as convection schemes strongly influence projections of summer rainfall change. Confidence in the simulation of change in convective rainfall, or convection-permitting modelling may be needed to raise confidence in summer rainfall projections over mountains.〈/p〉