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This paper examines the changes of El Niño–Southern Oscillation (ENSO) associated winter rainfall relationship in Southeast Asia (SEA) in the historical period (1981–2010) and future period (2071–2100) based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) models simulations. Twenty general circulation models (GCMs) are chosen from the Scenario Model Intercomparison Project (ScenarioMIP) highest emission scenario—Shared Socioeconomic Pathway (SSP) 5‐8.5. This study focuses only on the GCMs that have been able to replicate the consistent associated patterns observed, referred to as "teleconnection‐consistent models" (TCMs). During historical period, ENSO has significant negative association with SEA winter rainfall, particularly over Indochina mainland, Maritime Continent (MC) and northern Borneo. The significant negative‐associated teleconnection affected area has increased under future climate, particularly over southern part of South China Sea (SCS). The weakening of south westerlies at Western North Pacific (WNP) centred near 20°N reduces the moisture transport from Indochina into south of China, increase the negative correlated affected area in the SEA regions above equator. The northeasterlies/easterlies that prevailed from the WNP anticyclone (AC) brings significant moisture flux into southern Borneo, causing increment of significant positive‐associated moisture flux convergence to that region. The weakening of upward motion in TCM results in less warm and moist air rising over SEA MC, reducing the rainfall availability. The 1° eastward expansion of WC downward branch eastern edge leads to suppression of convective activities, increasing the dry affected area. The results suggest that the ENSO has a larger influence on the negative‐associated SEA rainfall and atmospheric circulation in the December–January–February (DJF) late‐21st century when compared to the 1980–2010. [ABSTRACT FROM AUTHOR]

The latest version of the atmospheric general circulation model ARPEGE‐Climat was used to perform 5‐member ensemble simulations for both present and RCP8.5 scenario climates (mid‐21st century). The rotated/stretched configuration enables a local horizontal resolution of less than 15 km over the tropical North Atlantic basin. Moreover, a tracking algorithm was used to extract tropical cyclones (TCs) simulated by the model. Through an Eulerian approach, this paper focuses on the relationships between TCs and rainfall over three French islands in the West Indies. Although the model underestimates the occurrence of TCs over this latitude band, especially in September, precipitation rates during TC days are realistic. Indeed, the model shows a good capacity to reproduce different relationships between island rainfall and TC characteristics such as proximity and intensity. In addition to rainfall distribution, the TC contribution to annual cumulative rainfall is also well captured by the model. We used three different series characterizing precipitation at the island scale to underline that the model overestimates the area that is impacted by TC rainfall. According to the simulations, the number of minor TCs tends to decrease in the future (about −15%) over the study domain (50–70°W × 10–25°N) despite a +1.6°C over ocean warming. In contrast, no trend was detected in the number of major hurricanes. Except for annual precipitation that decreases significantly in the future (about −15%), no significant change was detected in the relationships between TC properties and island rainfall. [ABSTRACT FROM AUTHOR]

It is often desirable to simulate a single temperature series or a collection (network) of temperature series. Accurate simulations can enhance our understanding of temperature trends and variabilities. Simulation can also be used to generate data with known specifications, which are useful in assessing climate data processing routines such as quality control and homogenization algorithms. Possessing multiple realistic temperature series is often beneficial as only one natural record of our climate is available. The current popularity of general circulation models (GCMs) demonstrates how important simulation techniques are. However, even with sophisticated downscaling, it is difficult to replicate station temperature data that have realistic seasonal cycles as well as realistic temporal and spatial correlations. This paper reviews and studies statistical time series methods that can replicate a single series or a network of series from data. The methods are purely statistical—no atmospheric dynamics are involved—and attempt to produce replicates of the records under study. The work here develops (a) methods that simulate temperatures from a fixed season (say a particular day or month of the year) that match the distributional characteristics of the observed data; (b) methods for simulating an entire series that matches the series' temporal autocorrelations and seasonal cycle; and (c) methods for simulating a network of series that reproduce the data's observed seasonal cycles and spatial and temporal autocorrelations. Applications are given throughout, including one where a GCM series and local station data are used in tandem to describe long‐term trends and inject realistic station‐level short‐term fluctuations. This paper can be used as a tutorial for the simulation of a single climate observation, an entire climate series, or a network of multiple climate series simultaneously. Extensions of the ideas that involve GCMs are also examined. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are developed to simulate the past climate and generate future climate predictions. In the context of global warming, their important roles in identifying possible solutions to water resources planning/management are recognized by the world. However, in actual and regional implementation, due to many factors like initial and boundary conditions, parameters and model structures and so forth, there are great variabilities and uncertainties across the future climate projections of GCMs outputs, which has attracted criticism from water resources planners. Thus, the GCMs usually must be evaluated for assessing their performances in simulating the historical observations. Currently, there are many different conclusions and opinions as to whether the optimal individual model is more advantageous or whether the combined consideration of MME works better. The purpose of this paper is to compare the advantages and disadvantages between the selection of the optimal single GCM and multi‐model ensemble (MME) based on one of the more objective selection methods called TOPSIS. The results show that the performances of GCMs in simulating precipitation and temperature in different climate subregions over China are not identical. For CMIP6 GCMs simulations, the optimal precipitation GCM is CMCC‐CM2‐SR5 for EC, MIROC6 for SC, SWC and NWC, CESM2‐WACCM for NC and NEC, and FGOALS‐g3 for QTP. As for temperature, only NESM3 and BCC‐ESM1 are the optimal GCM for QTP and NWC, respectively; in other subregions, MME is better than single GCM. In general, a simple arithmetic averaging approach employed to generate the MME model is not superior to the optimal GCM, although the error metric with the observed data is reduced, at the cost of a severe compression of the interannual variability. [ABSTRACT FROM AUTHOR]

Understanding the reliability of global climate models (GCMs) to reproduce the historical surface wind fields is integral part of building robust projections of surface wind‐climate, and other wind‐dependent geophysical climatic variables. Understanding the skill of atmosphere‐only models (AGCM), coupled atmosphere–ocean models (AOGCM) and fully coupled earth system models (ESM) is likewise paramount to assess any systematic model improvements. In this paper, we systematically assess whether surface wind fields obtained from 28 CMIP5 GCMs can represent large‐scale spatial patterns and temporal variability of historical surface winds. We show that inter‐model uncertainty is typically 2–4 times larger than the uncertainty associated with GCM internal variability, although the latter can be significant within specific regions. We also find that CMIP5 models are typically capable of reliably reproducing large‐scale spatial patterns of historical near‐surface winds, but considerable uncertainty lies within the CMIP5 ensemble with strong latitudinal dependence. CMIP5 models show limitations in their ability to reliably represent inter‐annual and inter‐seasonal variability particularly within tropical‐cyclone‐affected regions. In further analysis, we quantify and intercompare historical wind bias from different types of models with different dynamical cores, based on multiple CMIP5 diagnostic experiments. We find that bias in surface wind fields are largely intrinsic to the atmospheric components of the models, and that the inclusion of carbon‐cycle dynamics has insignificant effect on simulated surface winds (at decadal time‐scales). Inconsistencies between AGCM and AOGCM simulations are largely driven by errors in sea surface temperatures (SST); though such differences are not statistically significant relative to the inter‐model uncertainty within the CMIP5 ensemble. These results show that the dominant source of bias in simulated wind fields lies in the underlying physics of the atmospheric component of the models. [ABSTRACT FROM AUTHOR]

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

Over the last decades, general circulation model (GCM) simulations have been regularly evaluated in terms of their ability to reproduce the historical frequency of significantly recurrent weather patterns (WP) observed at the regional scale. Thus, a good simulation of the frequency of these particular WP by the GCM is generally conditioning the good representation of the regional statistics of surface variables such as temperature and precipitation. In this paper, the seasonal frequency of eight particular WP have been calculated using the daily geopotential height fields simulated by an ensemble of 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCM. These WP are known as significantly influencing the French regional hydro‐climatology in terms of both frequency of low‐flows and high‐precipitation events. Four different bias correction methods have been applied on the simulated geopotential height fields before the calculation of the seasonal WP frequencies. The GCM ensemble showed overall good performances in terms of the simulation of WP seasonal frequencies. The application of a spatially and temporally non‐homogenous correction of simulated geopotential height fields improved significantly the simulation of WP frequencies for the four seasons. Finally, the evolution of the WP frequencies over the next century has been quantified. Three WP (WP2, WP4 and WP8) have pronounced seasonal changes, with WP2 and WP4 being less frequent in summer and autumn seasons, respectively, while WP8 being more frequent over spring, summer and autumn seasons. The strong simulated frequency evolution of WP2 and WP8 is an interesting result, which predicts the climate to be drier with time for France. Thus, WP2 (western oceanic circulation), grouping rainy days over the northern France region, is simulated as less frequent in future summers, while WP8 (anticyclonic situations), which groups non‐rainy days over France, is simulated as more frequent in future summers. [ABSTRACT FROM AUTHOR]

ABSTRACT The biases in the Global Circulation Models ( GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed residual-based bagging tree ( RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modelling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared with the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios ( RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44, 2.59, and 4.71 °C by the end of the century, respectively, when compared with the average temperature during 1970-1999. [ABSTRACT FROM AUTHOR]

One way in which global climate model (GCM) output can be utilized to infer local impacts is through the use of synoptic climatology: creating a set of atmospheric patterns that capture the variability in the climate system, and then analyzing trends and variability in the frequency of these patterns moving into the future. In this paper, we demonstrate a new synoptic climatological technique for classifying atmospheric patterns that can be used in conjunction with GCM output data (in this case, the Community Climate System Model 3). We apply this method to 850-hPa temperature patterns over the contiguous United States to derive daily categorizations. A total of 15 clusters are created from the data set; once the mean GCM bias is removed, historical cluster frequencies in the GCM data set are not statistically different from those of the reanalysis data set. In the future, significant changes in frequency are observed across most of the transition season clusters, as they broaden in seasonality at the expense of winter clusters, some of which nearly entirely disappear. Changes are greater moving further into the future, and greater for the more carbon-intensive special report on emissions scenarios (SRES) scenarios (A1FI, A2) than the less-intensive scenario tested (B1). Diagnostics test how well the mean patterns of the reanalysis data set, GCM historical data set and the future GCM data sets resemble each other. For some clusters, mean bias between the historical and future data sets grows substantially by the end of the 21st century under the more carbon-intensive scenarios. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper investigates the relationships between the Global Circulation Model (GCM)-simulated 1000 hPa geopotential heights (taken from the ERA40 reanalysis) over the North Atlantic and the regional wind over the Iberian Peninsula for springtime (March to May). The main goal is to recognize the atmospheric circulation patterns linked to wind anomaly configurations. The method used for the downscaling is singular value decomposition (SVD). After applying a Monte Carlo approach to assess the statistical significance of the obtained modes, the SVD analysis highlighted that the covariability is dominated by three main large-scale features of the atmospheric circulation over the North Atlantic: (1) a first mode that relates local wind to the Scandinavian pattern (SCAN), by which a blocking pattern is linked to below-normal winds, (2) a second covariability mode associated with the North Atlantic Oscillation (NAO) pattern that correlates with wind over Iberia. An enhanced spring NAO pattern is related to positive (negative) wind correlations over the northern (southern) Iberia and (3) a third SVD mode that relates wind to the East Atlantic (EA) pattern promoting a dissimilar behaviour in the Iberian wind with positive (negative) wind correlations in the western (eastern) part of Iberia. To conclude, composite maps were built up to give an average circulation associated with coherent wind variability over Iberia. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Point validation of land surface schemes in general circulation models (GCMs) can only provide limited insight into the performance of the schemes when used over the large GCM grid cells. Streamflow, which integrates information over large areas, is a potentially useful diagnostic for assessing the land surface schemes at large spatial scales. This paper discusses the use of streamflow for assessing the performance of the CSIRO9 land surface scheme over the Amazon and the Mississippi River Basins. The paper shows that although streamflow can be a useful diagnostic tool for testing land surface schemes over large scales its utility is undermined by various problems: the atmospheric control on evapotranspiration, the possibility of compensating errors within large basins, and most importantly the lack of reliable grid-averaged atmospheric data at large spatial scales. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Five regional climate models (RCMs)—CCLM, RegCM, HadGEM3‐RA, SNURCM and WRF—participating in the Coordinated Regional Climate Downscaling Experiment‐East Asia (CORDEX‐EA) Phase 2 project are evaluated for their ability to simulate spatiotemporal variability in Asian summer precipitation. For this purpose, two dynamical downscaling sets, experiments forced by ERA‐Interim reanalysis data (reproduction experiment) and historical data from three Coupled Model Intercomparison Project 5 (CMIP5) general circulation models (GCMs) (historical experiment) are analysed. The horizontal resolution of the downscaled results is 25 km, and the analysis period is from 1981 to 2005 (25 years). The RCMs show reasonable performance in simulating the spatial and temporal characteristics of summer precipitation in CORDEX‐EA Phase 2 domain. To assess spatiotemporal patterns in Asian precipitation, cyclostationary empirical orthogonal function (CSEOF) analysis is used. In the first mode representing seasonal variations, the model ensemble results of both the reproduction experiment (Rep_ENS) and the historical experiment (His_ENS) simulate the peak times, location of precipitation and progression of the monsoons in Asia reasonably. Their features are greatly influenced by the moisture flux, indicating that the relation between precipitation and 850 hPa moisture flux is depicted well by RCM ensembles. In the second mode, which represents intraseasonal variations, the Rep_ENS depicts the western North Pacific summer monsoon break (WNPSM break) phenomenon similar to the observation. Although the His_ENS simulates the WNPSM break later than the observation, it does present the intraseasonal variation in the East Asian summer monsoon region. Based on these results, the five RCM ensemble results show the ability to capture spatiotemporal characteristics of summer precipitation in CORDEX‐EA Phase 2 domain, as well as added value from dynamical downscaling. [ABSTRACT FROM AUTHOR]

The present research focuses on temperature change signals over the Carpathian Basin with a special focus on selected lowland and mountainous subregions. High‐resolution (0.11°) EURO‐ and Med‐CORDEX regional climate model (RCM) simulations of near‐surface air temperature are analysed based on raw and bias‐adjusted data. The mini‐ensemble consists of eight RCM simulations driven by five different general circulation models for the period 1976–2099 under the high‐end RCP8.5 scenario. The high‐resolution, homogenized and quality controlled CARPATCLIM was used as a reference dataset. The selected subregions cover eight municipalities located at diverse altitudes: Bratislava, Budapest, Brassov, Debrecen, Hoverla, Novi Sad, Pécs and Poprad. The following climate indices are assessed: summer days, ice days, frost days, tropical nights, the coldest day, the warmest day, the coldest night and the warmest night. In general, for the reference period (1976–2005) bias‐adjusted RCM data showed almost perfect match with observations. Accordingly, no best performing RCM is found for all indices. The ensemble mean of the bias‐adjusted RCM simulations projects an increase (decrease) of 32% and 112% (18% and 25%) in the annual number of summer days and tropical nights (frost days and ice days) for the period 2021–2050. For 2070–2099 we can expect more frequent tropical nights (about five times) with respect to the reference period and the frequency of frost days can be halved. Profound warming manifests in the increase of the warmest temperature of day of up to 2–3°C by the near future and of 5–7°C by the end of the 21st century, which means the absolute maximum temperature can reach 44–47°C for the period 2070–2099. Our results also highlight the need for bias‐adjusted data adapted by different sectors (human health, agriculture, transport, disaster management, heritage conservation) under the national adaptation strategies. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is one of the most important modes of climate variability on interannual timescales. We aim to find out whether a change in ENSO frequency can be predicted for the nearer future. We analyse the unforced pre‐industrial control run and the forced 1%/year CO2 increase run for an ensemble of 43 general circulation models that participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We assume that the uncertainty of ENSO frequency trend estimates from an ensemble is caused by apparent trends as well as model differences. The part of the uncertainty caused by apparent trends is estimated from the pre‐industrial control simulations. As a measure for ENSO frequency, we use the number of El Niño‐ and La Niña‐like months in a moving 30‐year time window. Its linear decadal trend is calculated for every member. The multimember mean of the trend for both experiments is less than 0.7 events per decade. Given that the standard error is of the same order of magnitude, we consider this a negligible trend. The uncertainties are large in both experiments and we can attribute most of the intermember variability to apparent trends due to natural variability rather than different model reactions to CO2 forcing. This means that the impact of intermodel differences might have been overstated in previous studies. Apparent trends make it very difficult to make reliable predictions of changes in ENSO frequency based on 120‐year time series. [ABSTRACT FROM AUTHOR]

The Northeast Brazil (NEB) is considered a region that is strongly vulnerable to extreme rainfall events due to climate change. In this context, this study evaluates the performance of 12 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the number of dry (DD) and heavy rainfall days (HRD) over NEB in the historical period (1981–2005) and their projections for the near (2016–2040) and far future (2076–2100) under three Shared Socioeconomic Pathways (SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5) scenarios. For selection of extreme rainfall days, we used the absolute threshold of less than 1 mm for DD and the 99th percentile for HRD. The results indicate that four (three) models show an overall superior performance in reproducing the dry (heavy rainfall) days, being common in both aspects only the EC‐EARTH3. Thus, the skill of the CMIP6 models for NEB varies according to the extreme rainfall conditions analysed. For the future climate (near and far), results show that dry days are project to increase over the entire NEB territory, especially during DJF and MAM and more pronounce in the east coast, with projections that these conditions will be more severe under the SSP5‐8.5 scenario. The number of dry days may increase up to 15%. For HRD, although the results indicate that the number of days with heavy precipitation will be more frequent in the future (the increase can exceed 140%), the analysis show that under the low (SSP2‐4.5) or intermediate (SSP3‐7.0) forcing scenarios the HRD tends to be higher than in the most pessimistic scenario (SSP5‐8.5). Such result was explained according to the dryness of the atmosphere. Therefore, this study shows that it might either rain too much within a short range of time or the water scarcity will be longer‐lasting in the future in NEB. [ABSTRACT FROM AUTHOR]

Historical simulations and projections of climate extremes indices of precipitation and temperature were analysed over South America until the end of the 21st century through 31 general circulation models (GCMs) under four Representative Concentration Pathways. Simulations were compared with reanalysis data, and a Bayesian inference method was used to assess the uncertainties involved in the multi‐model climate projections. Regarding the precipitation extremes indices, the GCMs' simulations reasonably approached the reanalysis data, but with heterogeneous biases, both in sign and in the location of the highest values. The temperature extremes indices presented the smallest biases when compared to precipitation. Projections show a gradual growth of precipitation extremes events as the analysed radiative forcing scenario increases, both in magnitude and extent, over a large part of South America. Projections also indicate a decrease in cold days and nights and an increase in warm days and nights, more pronounced in the equatorial region. Bayesian inference method smoothed changes in precipitation extremes events, both in magnitude and extent, compared to the simple GCMs' ensemble mean. There was no considerable variation in the temperature indices when applying the Bayesian inference. Finally, the probability density functions resulted in a predominance of multimodal and wide curves for the precipitation indices, showing great uncertainties in the GCMs' results, differently from those for the temperature indices, where the GCMs presented good agreement represented through unimodal and narrow curves. [ABSTRACT FROM AUTHOR]

Understanding of future changes in drought characteristics is crucial for climate change adaptation and drought impact mitigation. We analysed the projected changes in drought characteristics relative to historical drought conditions in Central Asia using the Standardized Precipitation Evapotranspiration Index based on both gridded observations and an ensemble of bias‐corrected and spatially disaggregated global circulation models (GCMs) from phase 6 of Coupled Model Intercomparison Project (CMIP6). The results suggest that precipitation and potential evapotranspiration are projected to increase across Central Asia. Even though the change in wetness may not be significant and robust, a "dry gets drier and wet gets wetter" pattern may emerge in future under different scenarios. Drought events in Central Asia's semi‐arid and arid regions (aridity index <0.5) are projected to become more frequent (>125%), with longer duration (>55%), higher severity (>74%) and intensity (>8%) by the end of the 21st century under four Shared Socioeconomic Pathway (SSP) scenarios. In the coming period of 2021–2050, Central Asia is expected to have more drought events with a longer duration but lower intensity. Comparisons between different SSP scenarios stress the importance of climate change mitigation strategies to avoid more drought occurrence, longer drought duration and higher drought severity. The long‐term mitigation and adaptation studies for increasing drought impacts are also imperative in Central Asia. [ABSTRACT FROM AUTHOR]

It has been challenging to simulate the East Asian summer monsoon (EASM) using general circulation models. By evaluating the cloud layers unified by binormals (CLUBB) model and its revised version in the version‐5 Community Atmosphere Model, we find that EASM simulations benefit from improving the reproduction of low clouds over the Tibetan Plateau. When a cloud‐top radiative cooling scheme (RAD) is coupled with CLUBB, it significantly improves the resulting EASM rain belt and western Pacific subtropical high (WPSH) simulations compared to the default simulations without RAD; in these default simulations, the low‐level southwesterlies, WPSH ridge, and EASM rain belt are displaced northward. The moisture budget analyses indicate that the improvements in EASM simulations are mainly contributed to by the improved presentation of low‐level stationary eddy meridional flow convergence over East Asia; this convergence shifts northward during the default model runs. Because the RAD scheme enables the model to better represent the subgrid radiation–turbulence interaction, the model produces stronger turbulent fluxes and lower clouds but reduces incoming solar radiation over the Tibetan Plateau. It thus shifts the Tibetan High southward, ultimately resulting in an improved simulation of the low‐level southwesterlies. These improvements in CLUBB_RAD highlight the importance of improving the representation of low clouds when simulating EASM rainfall. [ABSTRACT FROM AUTHOR]

Analysing three high resolution coupled model simulations for the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA) regimes, available as the last millennium simulations of the PMIP3, we find that Northeastern Indian summer monsoon rainfall (NEISMR) did not change appreciably from the MCA to the LIA. This is in contrast to the signals in the rest of the Indian region. Our results from all the models suggest that, during the MCA, the simulated 100‐hPa tropical easterly jet (TEJ) becomes relatively more intense than that during LIA, due to a stronger Tibetan High. This strengthening of the TEJ results in an associated increase in relative vorticity at the 500 hPa over the Head Bay of Bengal and neighbouring east coast of the Bay of Bengal. This results in higher moisture availability and increased summer monsoon rainfall in the neighbourhood, including the central Indian region, during the MCA. However, the simulations do not show any such changes over northeastern India, indicating a relatively stable simulated NEISMR from MCA through LIA. Furthermore, just as the current day observations, the simulated correlations between the NEISMR with various concurrent ENSO indices are weak and statistically insignificant during the MCA and LIA regimes. Interestingly, an analysis of time‐slice simulations for the MCA and LIA from an atmospheric general circulation model broadly agree with the above conclusions, indicating that the tropical ocean and atmospheric coupling may not have played a major role in the northeast climate. [ABSTRACT FROM AUTHOR]

Even if the thresholds set out in the Paris Agreement are reached, several impacts on the climate system are still inevitable, generating new vulnerabilities and amplifying those that already exist. In this sense, the objective of this work was to analyse the impact of a global warming of 1.5 and 2°C in the regional climatological patterns of the near‐surface air temperature and precipitation over South America, locating the most affected regions and briefly discussing the possible impacts to be faced on biodiversity and agriculture. The simulations and projections of 26 General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 were used, forced in four different Representative Concentration Pathways (RCPs) scenarios. Projections for 1.5 or 2°C global warming indicate a local increase even higher, of at least +0.5°C, in almost the entire South American continent. Regarding precipitation, a similar pattern was also found between the two thresholds of global warming. GCMs project an increase of about 100 mm year−1 in the southern region of Brazil and in the northern portion of the Brazilian Northeast, in northern Argentina, Uruguay, and parts of Peru, Ecuador, Colombia and Venezuela; while the areas between the south of Chile and Argentina and the extreme north of South America show reductions of up to 150 mm year−1. In addition, both the temperature and precipitation patterns were practically similar between the four analysed RCPs scenarios. The results presented in this study indicate that even if the Paris Agreement is very successful, South America will still suffer several impacts and will need to take effective adaptation measures in the short term. This may have pervasive implications for the biodiversity and genetic resource base of the subcontinent, as well as may impair agricultural productivity or incur into considerable adaptation costs for the sector. [ABSTRACT FROM AUTHOR]

This study analyzes local‐scale temperature and precipitation projections in the Shire River Basin (SRB) in Malawi using 10 global circulation models (GCMs) available in the coupled model intercomparison project phase 5 (CMIP5), under two representative concentration pathways (RCP 4.5 and RCP 8.5). For nine stations in the study area, large‐scale maximum temperature (Tmax), minimum temperature (Tmin) and precipitation data from the selected GCMs were downscaled by the sixth version of the Long Ashton Research Station Weather Generator (LARS‐WG6). The mean seasonal and annual change projections for Tmax, Tmin and precipitation during two future periods, that is, the middle future (2041–2070) and late future (2071–2100) periods were analyzed. Modelling results demonstrated that the LARS‐WG model is capable of simulating temperature more accurately than precipitation in the SRB. All 10 GCMs revealed that continually rising temperatures are anticipated in the study area; however, the projected magnitude of change varied across GCMs and between RCPs. Generally, the increase in average Tmax and Tmin was observed to be higher under RCP 8.5 compared with RCP 4.5 due to unmitigated greenhouse gas emissions (GHGs). Future precipitation change results showed more complexity and uncertainty than for temperature; not all GCMs agree on whether there will be positive or negative changes in precipitation and no systematic variations under RCP4.5 and RCP8.5 were observed during the two future time period, illustrating that both GCMs and RCPs are important sources of the relatively large uncertainties in future precipitation projections in the SRB. Thus, this study indicated that uncertainties constrained by both GCMs and RCPs are crucial and need to always be considered when executing climate impact studies and adaptation, particularly at river basin level. [ABSTRACT FROM AUTHOR]

This study examines the improvement in Coupled Model Intercomparison Project Phase Six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS data set using robust statistical techniques for 1981–2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6 multi‐model ensemble mean (hereafter MME) shows improved performance in the local annual mean cycle simulation with a better representation of the rainfall within the two peaks, especially the MAM rainfall relative to their predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to CMIP5. The CMIP6‐MME performed better than the CMIP5‐MME with lesser biases in simulating Simple Daily Intensity Index (SDII), consecutive dry days (CDD), and very heavy precipitation days >20 mm (R20mm) over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). Some CMIP6 models (e.g., NorESM2‐MM and CNRM‐CM6‐1) depict robust performance in reproducing the observed indices across all analyses. OND season shows wet biases for some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm in CMIP6 models. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance as compared with individual models due to the cancellation of some systematic errors in the individual models. Generally, CMIP6 depicts improved performance in the simulation of MAM rainfall compared with CMIP5 models. However, the new model generation is still marred by uncertainty, thereby depicting unsatisfactory performance over the East Africa domain. This calls for further investigation into the sources of persistent systematic biases and a methodology for identifying individual models with robust features that can accurately simulate observed patterns for future usage. [ABSTRACT FROM AUTHOR]

Many studies based on observed data indicate the inverse relationship between the Eurasian snow cover/depth and the Indian summer monsoon rainfall (ISMR). The purpose of this study is to confirm the inverse snow-ISMR relationship by using the observed snow depth data as boundary conditions in the spectral general circulation model (GCM) of Indian Institute of Technology, Delhi (IITD), and to examine the influence of Eurasian snow depth on the monsoon circulation. The original model belonging to the European Centre for Medium range Weather Forecasts (ECMWF) at resolution T21 has been modified extensively to a higher resolution of T80L18 at IITD. A two-dimensional Lanczos digital filter has been used to represent the orography realistically. The Historical Soviet Daily Snow Depth (HSDSD) version II data set has been used for conducting sensitivity experiments using the above model. Two sensitivity experiments have been designed, corresponding to two contrasting cases: one with high Eurasian snow depth in spring followed by deficient ISMR and the second with low snow depth followed by excess ISMR. The difference fields of mean monsoon circulation simulated in the above two experiments are examined in detail in order to confirm the influence of Eurasian snow depth on ISMR and to examine the Asian summer monsoon circulation and rainfall. Copyright © 2006 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Researchers are aware of certain types of problems that arise when modelling interconnections between general circulation and regional processes, such as prediction of regional, local-scale climate variables from large-scale processes, e.g. by means of general circulation model (GCM) outputs. The problem solution is called downscaling. In this paper, a statistical downscaling approach to monthly total precipitation over Turkey, which is an integral part of system identification for analysis of local-scale climate variables, is investigated. Based on perfect prognosis, a new computationally effective working method is introduced by the proper predictors selected from the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis data sets, which are simulated as perfectly as possible by GCMs during the period of 1961–98. The Sampson correlation ratio is used to determine the relationships between the monthly total precipitation series and the set of large-scale processes (namely 500 hPa geopotential heights, 700 hPa geopotential heights, sea-level pressures, 500 hPa vertical pressure velocities and 500–1000 hPa geopotential thicknesses). In the study, statistical preprocessing is implemented by independent component analysis rather than principal component analysis or principal factor analysis. The proposed downscaling method originates from a recurrent neural network model of Jordan that uses not only large-scale predictors, but also the previous states of the relevant local-scale variables. Finally, some possible improvements and suggestions for further study are mentioned. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The skill of General Circulation Models (GCMs) in mimicking the observed climate is assessed through various procedures and are ranked. The performance of a GCM is site‐specific and the ranking pattern varies spatially. In general, a set of best performing GCMs is extracted to study the impact of climate change. As, there is no universally accepted ranking procedure, the ranking of GCMs is prone to subjectivity. In this study, it is aimed to address the effect of this subjectivity on the GCM rankings. The past performance of GCMs from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the maximum and minimum temperature across India are evaluated and ranked by different ranking procedures. These ranking procedures involve combinations of various components present in the ranking procedure such as model evaluation criteria, criteria weightage allocation methods, Multicriteria Decision Making methods (MCDM) and reference gridded datasets. Different criteria and methods involved in the ranking procedures are carefully selected to address the subjectivity involved in ranking of GCMs. The effect of each individual component on the ranking pattern is systematically analysed and the spatial distribution of grids with same ranking patterns across all the combinations are considered as grids with same ranking. The performance of best performing GCM is attributed to homogenous climatic zones and its corresponding topological features. An ensemble of frequently performing top five GCMs among 16 different ranking procedures are extracted for each climate zone as the most suitable set of GCMs. [ABSTRACT FROM AUTHOR]

Trends of 15 extreme and non‐extreme daily rainfall indices for Mexico and the southern United States are analyzed for the extended boreal winter (November–March) and summer (June–October) during 1981–2010. The analysis includes gridded observations (CHIRPS and Livneh), reanalyses (ERA5, ERA‐Interim, MERRA2, and CFSR), the regional climate model RegCM4.7 (forced by ERA‐Interim), and four general circulation models (GCMs) from the CMIP5 (HadGEM2‐ES, CNRM‐CM5, MPI‐ESM‐MR, and GFDL‐ESM2M). The domain is divided into 13 regions with similar seasonal rainfall patterns according to the k‐means algorithm applied to CHIRPS monthly precipitation, as a reference. Gridded observations and reanalyses (O&R) show similar regional annual cycles and metrics of precipitation. The two observational data sets show the largest differences in the magnitude of some indices in the wettest region (southeastern Mexico) and in the monsoon. During summer, O&R show positive significant trends in extreme rainfall indices in regions commonly affected by tropical cyclones (southern Baja California Peninsula, northeastern Mexico, and the southeastern United States), while negative significant trends of seasonal accumulation of rainfall are seen in the Mediterranean Californias and the Sonoran Desert region. There is an agreement among most data sets that the frequency and intensity of extreme winter precipitation indices have declined in northwest Mexico and the southwestern United States, but trends are not statistically significant, while southeastern Mexico shows significant increases in 5‐days accumulation (rx5d). ERA5 followed by MERRA2 show the best performance. RegCM4.7 reproduces the annual cycle of precipitation in most of the regions and captures the main trend signals especially in winter, but it has difficulties in reproducing the summer interannual variability of few indices. The GCMs tend to overestimate (underestimate) the annual cycle of precipitation and the median values of extreme indices in the driest (wettest) regions. They are not able to capture the regional trends of the indices. [ABSTRACT FROM AUTHOR]

Synoptic downscaling from global circulation models (GCM) has been widely used to develop local and regional-scale future precipitation scenarios under global warming. This paper presents an analysis of the linkages between the Canadian Centre for Climate Modelling and Analysis first version of the Canadian Global Coupled Model (CCCma CGCM1) 2000 model output and local/regional precipitation time series. The GCM 500 hPa geopotential heights were visually classified for synoptic patterns using a geographical information system. The pattern frequencies were statistically compared with historical data from Changnon et al. for the winter period 1961?85. The CGCM1 synoptic frequencies compare favourably with the historical data, and they represent a substantial improvement over the 1992 Canadian Climate Centre Global Circulation Model synoptic climatology output. The CGCM1 output was used to forecast future winter precipitation scenarios for five geographically diverse climate stations in western North America.

A group of earlier investigations has identified some specific regions over the world in which hydrometeorological surface parameters (i.e. precipitation and streamflow) appear to have consistent relationships with the extreme phases of the Southern Oscillation (SO). This paper examines a climatic link between the monthly streamflows in Turkey and the tropical El Niño and La Niña events using a large data set and comprehensive empirical methodology. Coherent and significant streamflow responses were detected in two core regions, namely the northwestern Anatolia (NWA) and the eastern Anatolia (EA). The areal extent of both regions with a defined seasonal signal for the case of each tropical event was determined. Some subregions whose indications are considered to be better than those for the whole core region were also isolated within the core region. In the Susurluk subregion identified in the NWA, the April–October seasonal positive streamflow anomalies were found to have a highly significant relation with the El Niño events. Although there is a possibility that the NWA region is influenced by the El Niño events, this was not confirmed by the hypergeometric test used to assign a significance level for the relationship. A similar analysis has shown that the La Niña events have no noticeable influences on streamflows in the NWA. For the EA region, above normal conditions have been observed during the April(0)–November(0) period and the May(0)–February(+) period for the El Niño and La Niña events, respectively. Moreover, the annual cycle analysis somewhat implies a modulation of regional streamflow in the core regions during the signal period. In some parts of the core regions, correlation results confirm these signals. The results of this study are discussed and are said to be in agreement with the most relevant previous studies concerning precipitation to understand complex global circulation dynamics. In conclusion, mid-latitude streamflow responses to the extreme phases of SO are detectable over Turkey. Copyright © 2001 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

A number of previous studies have indicated that boreal spring Pacific Meridional Mode (SPMM) can exert notable impacts on the occurrence of El Niño‐Southern Oscillation (ENSO) event during the subsequent winter. Here, we reveal that the impact of the SPMM on the following winter ENSO is asymmetric. During positive SPMM (+SPMM) years, strong westerly wind anomalies are induced over the tropical western Pacific via wind‐evaporation‐SST (WES) feedback. These westerly wind anomalies lead to pronounced sea surface temperature warming in the tropical central and eastern Pacific, which further develop to an El Niño‐like pattern via positive atmosphere–ocean interaction. However, easterly wind anomalies over the tropical western Pacific during negative SPMM (−SPMM) years are much weaker. The weak easterly wind anomalies cannot lead to a clear La Niña‐like pattern in the following winter. We suggest that the asymmetric strength of the westerly and easterly wind anomalies over the tropical western Pacific is due to the asymmetric intensity of the WES feedback over the tropical north Pacific, with stronger intensity in the +SPMM years. The asymmetric trade wind charging process also partly contributes to the asymmetric SPMM–ENSO relation. Atmospheric general circulation model simulations confirm that the intensity of the +SPMM‐generated westerly wind anomalies over the tropical western Pacific is stronger than that of the easterly wind anomalies related to the −SPMM. The present study indicates that it is necessary to consider the phases of the SPMM when predicting winter ENSO events based on the preceding SPMM. [ABSTRACT FROM AUTHOR]

Changes in the tropical atmospheric overturning circulation can strongly influence the global weather pattern via affecting the location, extent, and strength of tropical convective heating. However, due to limitations in obtaining reliable global data before the satellite era, there are still uncertainties on long‐term changes in the tropical overturning features, such as the Walker Circulation. By analysing the 20th century reanalysis products, ship‐based observations and gauge‐based land precipitation data, robust intensification of convection is found over the western equatorial Pacific and Maritime Continent (WEP‐MC; 90°E–150°E/15°S–15°N), where rainfall and total cloud cover increased by 15–20% in boreal spring during 1901–2010. The signal is noticeably seasonally dependent, and both rainfall and cloud cover show consistent and significant increasing trends only in the boreal spring season. General circulation model (GCM) experiments were conducted using two different reconstructed SST data sets as forcing; results from both runs indicate springtime intensification of WEP‐MC convection, even with relatively uniform SST warming. Further, numerical experiments using a simplified model show that the Pacific trade wind can be accelerated by intensifying cumulus heating; however, this can be sensitive to the location of convection, and only occurs if the latter is within ±5° in latitude along the equator. Our findings suggest that the secular change in the Walker Circulation is potentially discovered from the current reanalysis and observational data sets if "regional‐up" approaches are applied. [ABSTRACT FROM AUTHOR]

Newtonian relaxation applied at boundaries of RCM (regional climate model) is a widely‐used technique for climate downscaling and regional weather forecasting. It allows RCM to be nested into GCM (global climate model) and to follow the evolution of the latter. An idealized framework to mimic this general practice is constructed with the LMDZ (Laboratoire de Météorologie Dynamique, Zoom) modelling platform and used to assess effects of the relaxation procedure. The assessment is on both synoptic variability and long‐term mean. LMDZ is a global atmospheric general circulation model that can be configured as a regional model when the outside domain is relaxed to a driver. It thus plays the role of both GCM and RCM. Same physical parameterization and identical dynamical configuration are used to ensure a rigorous comparison between the two models. The experimental set‐up that can be referred to as "Master (GCM) versus Slave (RCM)" considers GCM as the reference to assess the behaviour of RCM. In terms of mean climate, there are noticeable differences, not only in the border areas, but also within the domain. In terms of synoptic variability, there is a general spatial resemblance and temporal concomitance between the two models. But there is a dependence on variables, seasons, spatiotemporal scales and spatial modes of atmospheric circulation. Winter/Summer has the most/least resemblance between RCM and GCM. A better similarity occurs when atmospheric circulation manifests at large scales. Weak‐correlation cases are generally remarked when the dominant circulation of the region is at smaller scales. A further experiment with identical framework but RCM in a higher resolution allows isolating the effect of relaxation from that of mesh refinement. [ABSTRACT FROM AUTHOR]

Maize production on the North China Plain (NCP) is critical to food security in China; however, currently, it is affected by climate change. Understanding the spatiotemporal distribution of the climate suitability for maize on the NCP in the present and future may help sustainably use climate‐related resources to ensure food security in China. In this study, 30 general circulation models from the Coupled Model Intercomparison Project Phase 5 and a statistical downscaling model (NWAI‐WG) were used to project meteorological data in 2021–2100 under representative concentration pathway 4.5 (RCP4.5) and RCP8.5 for 23 national climatic stations on the NCP. Based on agricultural climate suitability theory and the fuzzy mathematics method, the suitability of temperature, precipitation, and solar radiation on summer maize were analysed. The results showed that temperature suitability is decreasing for 2021–2100, especially during the stages from jointing to maturity; temperature suitability is the lowest in the southwest and increases to the northeast under both scenarios. Compared to 1996–2015, the precipitation suitability in 2021–2100 increases greatly under both scenarios, especially in the central part under RCP4.5 and in the north part under RCP8.5. Solar radiation suitability shows a decreasing trend for 1996–2015, however, an increasing trend for 2021–2100 under both scenarios. At spatial scale, the solar suitability increases from southwest to northeast. The integrated climate suitability under RCP4.5 in 2021–2100 is averaged approximately 0.8 and varies slightly, indicating climate change may do small effect on maize growth, though the high values shifting from the central part in 2021–2040 to the northern part in 2081–2100; however, under RCP8.5, the integrated climate suitability shows a downward trend, indicating that climate change will make many regions less suitable for maize growth. These results could provide basic information for agriculture to adapt to climate change and ensure food security for China. [ABSTRACT FROM AUTHOR]

Future changes in climate variable exhibit prominent impact on flood magnitudes, crop yields, and freshwater withdrawal. Researchers typically ignore the large degree of uncertainty translated from climate projections to the estimated climate change magnitudes while applying pre‐processing approaches on climate change projections. General Circulation Models (GCM) exhibit substantial uncertainty in projecting future changes in the seasonal temperature, which is evaluated by estimating the shift in either the mean or variance. Bias between the observed changes (1950–1999) and GCM simulated changes vary across models, climate regions, seasons, and under emission scenarios. The simplest approach to reduce model structural uncertainty, equal weighting of GCMs, does not consider superiority of one or multiple GCMs compared to the rest. The current study adopts a performance‐based model combination approach that has shown efficiency in streamflow and weather forecasting, and GCM precipitation simulation. The optimal model combination approach has been modified to combine multi‐model climate change information, while yielding the spatial correlation in climate change information within a geographic region. The optimal model combination approach, along with a simple bias‐correction, is applied on 10 GCMs over nine climate regions across the coterminous United States (CONUS). We found that the optimal combination exhibits lower RMSE values as compared to the equal combination. Correlations between the model combined projections under optimal combination and the observed changes are strong and positive (>0.5). Future (2000–49) model combined projections exhibit an increase in the mean seasonal temperature by 2°C for winter and by 1°C for summer over almost all climate regions. [ABSTRACT FROM AUTHOR]

Heat waves in India during the pre‐monsoon months have significant impacts on human health, productivity and mortality. While greenhouse gas‐induced global warming is believed to accentuate high temperature extremes, anthropogenic aerosols predominantly constituted by radiation‐scattering sulfate are believed to cause an overall cooling in most world regions. However, the Indian region is marked by an abundance of absorbing aerosols, such as black carbon (BC) and dust. The goal of this work was to understand the association between aerosols, particularly those that are absorbing in nature, and high‐temperature extremes in north‐central India during the pre‐monsoon season. We use 30‐year simulations from a chemistry‐coupled atmosphere‐only general circulation model (GCM), ECHAM6‐HAM2, forced with evolving aerosol emissions in an interactive aerosol module, along with observed evolving SSTs. A composite of high‐temperature extremes in the model simulations, compared to climatology, shows large‐scale conditions conducive to heat waves. Importantly, it reveals concurrent positive anomalies of BC and dust aerosol optical depths. Changes in near‐surface properties include a reduction in single scattering albedo (implying greater absorption) and enhancement in short‐wave heating rate, compared to climatological conditions. Alterations in surface energy balance include reduced latent heat flux, but increased sensible heat flux, consistent with enhanced temperatures. Thus, chemistry‐coupled GCM simulations capture an association of absorbing aerosols with high‐temperature extremes in north India, arising from radiative heating in the surface layer. [ABSTRACT FROM AUTHOR]

Socioeconomic development and natural ecosystems of China are strongly affected by droughts. The socioeconomic risk of droughts in China should be quantified under climate change. This study assessed drought impacts on population and gross domestic product (GDP) under the 2.0°C‐warmer climate scenario, by implementing multiple general circulation model (GCM) simulations under the representative concentration pathway (RCP). Using the standardized precipitation evapotranspiration index (SPEI), we calculated drought frequencies in the base period (1986–2005) and 2.0°C‐warmer climate (2040–2059 in RCP4.5). Then, population and GDP exposures were evaluated by combining the drought frequency with population and GDP simulations under a shared socioeconomic pathway (SSP). Droughts were likely to occur more frequently under the 2°C‐warmer climate, especially for inland areas of northern China (i.e., Xinjiang, Xizang, Qinghai, Ningxia, Shaanxi, Gansu provinces), consisting mainly of mild and moderate droughts. Population exposure to drought was projected at 4.94 ± 0.36 × 109 person‐months, around 2% increase over the base period value. GDP exposure would increase significantly to 2.08 ± 0.15 × 1014 PPP $‐months, approximately 14‐fold over the base period. Probability analysis showed nearly 50% of the grid cells of China's entire territory undergoing more than an 11‐fold increase in GDP exposure. Our findings indicated the climate and GDP effects were primary contributors, respectively, to the changed population and GDP exposures to drought. Population and GDP exposures were distributed unequally across the country, having a large impact in the east where both population and economic activity are highly agglomerated. Our results reveal an urgent need to design and implement effective adaptation measures to overcome droughts, especially in eastern China. [ABSTRACT FROM AUTHOR]

Despite intense research on climate change (CC), regional studies for Central America, which is considered a CC hot spot, remain scarce. The information provided by general circulation models (GCMs) is too coarse to accurately reproduce local‐scale climatic features, which are needed for impact assessment. Thus, downscaling techniques are employed to address this scale mismatch. Costa Rica is the present case study, for which suitable predictors were tailored for downscaling related to regional climatic characteristics, such as the Inter‐Tropical Convergence Zone, El Niño Southern Oscillation, the Caribbean Low‐Level Jet, and the Mid‐Summer Drought. Statistical downscaling models were calibrated for precipitation, maximum and minimum temperature, using the perfect prognosis methodology by means of station data, ERA‐INTERIM reanalysis and artificial neural networks, yielding satisfactory results. As found in several studies, the temperature models replicated more accurately the statistics of the observed datasets. However, here, through the implemented approach and the tailored predictors, the precipitation models conveyed an improvement compared to standard methods. Projected daily climate was obtained employing CORDEX data under the RCP8.5 scenario for the central region of the country. Overall, the changes in climate estimated by the end of the 21st century agree with coarser‐scale projections. Finally, projected climate extremes indices were calculated and rendered further details on the intensity of future CC by the end of the century. [ABSTRACT FROM AUTHOR]

Gridded meteorological systems greatly facilitate the analysis of the impacts of climate on crop development and productivity. Comparisons of these data with actual ground data validate this data source for various analyses in agricultural areas. The impact of the use of these grid data is an important evaluation for the temporal and spatial simulation of soil‐water availability for crops. We seek to verify how meteorological (ECMWF) data represents the surface water balance for Minas Gerais state. Monthly data for air temperature (T) and precipitation (P) from ECMWF were compared with the data from 771 ground stations (National Meteorological Institute, INMET) in the state of Minas Gerais in southeastern Brazil for 1979–2017. Potential evapotranspiration was estimated by Thornthwaite method (1948), and water balance was estimated by the method proposed by Thornthwaite and Mather (1955), with an available water capacity of 100 mm. We temporally and spatially compared the two data sources, and the comparisons were evaluated for accuracy using mean absolute percentage error (MAPE) root mean square error (RMSE) and for precision using the adjusted coefficient of determination (R2adj). ECMWF T and P tended to be temporally and spatially similar to the INMET data. The largest deviation between INMET T and ECMWF T was 2.81°C, mainly in the southwest of the state (the Minas Gerais triangle) and part of the central region during winter and spring, and the smallest deviation was −0.19°C in the northeast. The largest deviation between INMET P and ECMWF P was 75 mm·mo−1 in the summer, mainly between January and February in the central region of Minas Gerais. ECMWF T and ECMWF P allowed an accurate estimation of the components of the water balance. For example, the lowest MAPEs were 1.21% for ECMWF water‐storage capacity (southern Minas Gerais), 9.16% for ECMWF water deficiency (Vale do Jequitinhonha e Mucurí), and 8.69% for ECMWF excess water (Vale do Jequitinhonha e Mucurí). ECMWF can be used to estimate WB to represent surface stations, provided they are calibrated according to the region and seasons. [ABSTRACT FROM AUTHOR]

Analogue forecasting is a method with a long history in weather and climate prediction. Recently, model‐based analogue forecasting (MAF) was developed and applied in Indo‐Pacific sea surface temperature (SST) with the long‐term (>1,000 years) run of the coupled general circulation model as the prediction library dataset. Here, we use the MAF method for Indo‐Pacific SST prediction with a 1,600‐year uninitialized control run of ICMv2 as the library datasets to select the analogues. In the improved analogue strategy, subsurface thermal conditions are valid predictors besides the surface conditions. The anomaly of SST, subsurface temperature at 5‐ and 105‐m depth as the best‐performing predictors can better simulate the overall thermal conditions of the ocean. In addition, by increasing the length of the model library dataset, the number of selected analogue cases for the ensemble, using root‐mean‐square and pattern correlation combined analogue metric and subtracting the long‐term trend, the improved MAF can produce a skillful SST prediction in the tropical Indian Ocean, southwest and northwest Pacific Ocean across 1‐ to 9‐month lead times. The ACC of the improved MAF prediction in these regions significantly increases by more than 0.18 relatively to the SST‐initialized hindcast of ICMv2 with considerable savings in terms of computational resource. [ABSTRACT FROM AUTHOR]

The simulation of the intra‐seasonal variability (ISV), especially the fidelity of monsoon intra‐seasonal oscillations (MISO) over the South Asian summer monsoon (SASM), has been evaluated in Atmospheric Model Intercomparison Project run of three Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric general circulation models (AGCM), participating in Coupled Model Intercomparison Project phase 5. Two of the models, namely, "GFDL‐HIRAM‐C180" and "GFDL‐HIRAM‐C360" are global high‐resolution atmospheric models (HIRAMs), which are same but at different horizontal resolutions. Third model "GFDL‐CM3" is at moderate horizontal resolution, whose atmospheric component differs from HIRAMs. Results have led to the conclusion that simulation of ISV over SASM remains poor in GFDL AGCMs at higher horizontal resolution, except northwards propagation of 30–60‐day mode of MISO by HIRAMs. Our diagnostics revealed resemblance in key characteristics of ISV simulated in two HIRAMs, except spectral peak at lower frequencies (30–60 day), which is captured only by "GFDL‐HIRAM‐C180" over equatorial Indian Ocean. Based on these results, it is conjectured that although high horizontal resolution is crucial for AGCMs to reproduce observed northwards propagation of 30–60‐day mode of MISO, the simulation of nature of ISV over SASM is not influenced by the difference of horizontal resolution in two HIRAMs. Analysis implicates that a reasonable representation of meridional migration of horizontal moisture advection, the meridional gradient of low‐level specific humidity over Indian longitudes and precipitation–SST relationship over north Indian Ocean, the northwestern tropical Pacific Ocean and tropical Indian Ocean assures the northwards propagation of 30–60‐day mode of MISO in HIRAMs. [ABSTRACT FROM AUTHOR]

The selection of general circulation models (GCMs) with high capability to represent the past and likely future climate for a specific geographical location is a crucial step to assess impacts of climate change on different sectors. This study included pool of 105 and 78 GCMs for representative concentration pathways (RCPs) 4.5 and 8.5, respectively, from Coupled Model Intercomparison Project—Phase 5, applied an advanced envelope‐based selection approach to select representative GCMs for the Koshi river basin in China and Nepal at short‐term (2016–2045), mid‐century (2036–2065) and end‐of‐century (2071–2100) periods, and developed range of possible future precipitation and temperature scenarios with high resolution downscaled data (10 × 10 km2), which is the novelty contribution of the study. Considering RCP4.5, average annual precipitation is expected to increase by 0–16%, 4–23% and 4–24% in the short‐term, mid‐century and end‐of‐century periods, respectively. Using RCP8.5, equivalent predictions are 6–20%, 6–36% and 13–49% in the short‐term, mid‐century and end‐of‐century periods, respectively. Average annual temperature is expected to increase, but with higher increases during winter than in the monsoon period. Considering RCP4.5, average annual temperature is expected to increase by 1–1.4°C, 1.3–1.9°C and 1.6–2.8°C in the short‐term, mid‐century and end‐of‐century periods, respectively. Similarly, using RCP8.5, equivalent predictions are 1–1.6°C, 1.8–2.9°C and 3.1–5.6°C in the short‐term, mid‐century and end‐of‐century periods, respectively. The ensemble mean of absolute change in average precipitation and temperature projects that High Himalaya and Tibet regions are more sensitive to climate change considering precipitation and temperature, respectively. The results also suggest that GCMs selection for a catchment varies with climate scenarios and specific future time periods. [ABSTRACT FROM AUTHOR]

Realistic simulation of cloud variability and rainfall by the coupled models still remains a challenge particularly over the Asian Summer Monsoon (ASM). The simulation of the "pool of inhibited cloudiness" (hereafter referred to as PIC) and associated cloud variability have been analysed in the historical run of 26 models which participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and it is shown that the current state of the art general circulation models (GCMs) still have difficulties in properly simulating the PIC. The pool covers an area greater than 1 million km2 between 3°–13°N and 77°–90°E over the southwest Bay of Bengal (BoB); persisting throughout the ASM and interestingly it is surrounded by the deep convective region. The majority of the models could not simulate cloud variability over the ASM. The performance of National Centre for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) version 2.0, which is being used for operational monsoon prediction over the Indian region, is also tested to evaluate its fidelity in capturing PIC. The moist convective process in the default CFSv2 is found to be one of the major sources of uncertainty in its monsoon prediction. In this study, evaluation of the default CFSv2 (CTRL) and suites of modified CFSv2 have been carried out. The default version of CFSv2 has the simplified Arakawa Schubert (SAS) as convection scheme and Zhao and Carr (ZC) as microphysics. In another modification, the SAS is changed to revised simplified Arakawa Schubert (RSAS) keeping the microphysics unchanged. Further, a more physically based cloud scheme (WRF Single Moment 6‐class microphysics—WSM6) is used with SAS and RSAS for comparison of simulation of PIC. Among the CMIP5 models, ACESS‐1‐0, GFDL‐CM3, HadGEM2‐CC, HadGEM2‐ES are able to represent the PIC reasonably well. CFSCR has shown an improved fidelity in comparison to the CTRL, CTRL‐WSM and RSAS and other CMIP5 models. The impact of cloud microphysics in CTRL‐WSM and CFSCR appears to play an important role in the simulation of the PIC. [ABSTRACT FROM AUTHOR]

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

Glaciers are of key importance to freshwater supplies in the Himalayan region. Their growth or decline is among other factors determined by an interaction of 2‐m air temperature (TAS) and precipitation rate (PR) and thereof derived positive degree days (PDD) and snow and ice accumulation (SAC). To investigate determining factors in climate projections, we use a model ensemble consisting of 36 CMIP5 general circulation models (GCMs) and 13 regional climate models (RCMs) of two Asian CORDEX domains for two different representative concentration pathways (RCP4.5 and RCP8.5). First, we downsize the ensemble in respect to the models' ability to correctly reproduce dominant circulation patterns (i.e., the Indian summer monsoon [ISM] and western disturbances [WDs]) as well as elevation‐dependent trend signals in winter. Within this evaluation, a newly produced data set for the Indus, Ganges and Brahmaputra catchments is used as observational data. The reanalyses WFDEI, ERA‐Interim, NCEP/NCAR and JRA‐55 are used to further account for observational uncertainty. In a next step, remaining TAS and PR data are bias corrected applying a new bias adjustment method, scale distribution mapping, and subsequently PDD and SAC computed. Finally, we identify and quantify projected climate change effects. Until the end of the century, the ensemble indicates a rise of PDD, especially during summer and for lower altitudes. Also TAS is rising, though the highest increases are shown for higher altitudes and between December and April (DJFMA). PRs connected to the ISM are projected to robustly increase, while signals for PR changes during DJFMA show a higher level of uncertainty and spatial heterogeneity. However, a robust decline in solid precipitation is projected over our research domain, with the exception of a small area in the high mountain Indus catchment where no clear signal emerges. [ABSTRACT FROM AUTHOR]

Summer monsoon rainfall forecasting in the Yangtze River basin is highly valuable for water resource management and for the control of floods and droughts. However, improving the accuracy of seasonal forecasting remains a challenge. In this study, a statistical model and four dynamical global circulation models (GCMs) are applied to conduct seasonal rainfall forecasts for the Yangtze River basin. The statistical forecasts are achieved by establishing a linear regression relationship between the sea surface temperature (SST) and rainfall. The dynamical forecasts are achieved by downscaling the rainfall predicted by the four GCMs at the monthly and seasonal scales. Historical data of monthly SST and GCM hindcasts from 1982 to 2010 are used to make the forecast. The results show that the SST‐based statistical model generally outperforms the GCM simulations, with higher forecasting accuracy that extends to longer lead times of up to 12 months. The SST statistical model achieves a correlation coefficient up to 0.75 and the lowest mean relative error of 6%. In contrast, the GCMs exhibit a sharply decreasing forecast accuracy with lead times longer than 1 month. Accordingly, the SST statistical model can provide reliable guidance for the seasonal rainfall forecasts in the Yangtze River basin, while the results of GCM simulations could serve as a reference for shorter lead times. Extensive scope exists for further improving the rainfall forecasting accuracy of GCM simulations. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0), which is an indicator of atmospheric evaporation demand over a hypothetical reference surface, is expected to alter along with global climate change. In this study, the changes and driving forces of historical ET0 and its future projections in Xinjiang, China, were comprehensively conducted. The trend analysis revealed that regional ET0 decreased significantly at a rate of −4.1 mm/year2 during 1961–1993 and increased at a rate of 3.4 mm/year2 during 1994–2010. To explore the possible causes, the contributions of major climatic variables to the ET0 trends were derived based on the differential equation method. During 1961–1993, the decreasing trend of ET0 was primarily ascribed to the wind speed. The integrated negative effect from the decrease in wind speed (U) and increase in relative humidity (RH) was more significant than the positive effect from the increase in air temperature (T), resulting in the decrease in ET0. During 1994–2010, combined with increasing T and decreasing RH, the increase in U offset the effect of the net radiation (Rn) decrease and led to an increase in ET0. Future ET0 projections over three periods (2010–2039, 2040–2069, and 2070–2099, which are named as 2020s, 2050s, and 2080s, respectively) were conducted based on the general circulation models under two representative concentration pathways scenarios (RCP4.5 and RCP8.5). A continuous increasing trend in ET0 was demonstrated in the 21st century. The increase in ET0 will increase the irrigated water resource consumption and bring new challenge to water resource management in this area. [ABSTRACT FROM AUTHOR]

The South Asian high (SAH) and the North Pacific subtropical high (NPSH) are two crucial systems affecting the summer rainfall over East Asia. Features of the relative vorticity of the SAH and its dynamic effect on zonal extension of the western NPSH (WNPSH) are investigated on interannual timescales using data diagnosis and numerical model experiments. Results show that two climatological centres of negative relative vorticity are observed along the northern flank of the SAH over the Tibetan Plateau and northern West Asia at 200 hPa during boreal summer. The relatively more intense centre over the Tibetan Plateau (TPV) shows a pronounced southeast‐northwest (SE‐NW) variation, indicating a SE‐NW shift of the SAH. When the SAH shifts southeastward, an anomalous anticyclone occurs over eastern China at 200 hPa. In the middle troposphere, this anomalous anticyclone is located over southern China and the northern South China Sea, leading to a westward extension of the WNPSH. A diagnostic analysis of the vorticity equation indicates that the negative relative vorticity anomalies at 500 hPa are mainly caused by the downward advection of the mean relative vorticity by anomalous sinking motions. When the SAH extends southeastward, intense convergence on the southeastern flank of the anomalous upper‐level anticyclone induces descending motions that cause downward advection of mean negative vorticity. Consequently, negative vorticity anomaly is formed at 500 hPa, leading to a westward extension of the WNPSH. Results from the experiments using an idealized anomalous atmospheric general circulation model further demonstrate that the upper‐level anomalous anticyclone associated with a southeastward extension of the SAH triggers an anomalous anticyclone at the middle level, causing a westward extension of the WNPSH. [ABSTRACT FROM AUTHOR]

By using the observation, reanalysis data and numerical simulation, the inter‐decadal variations in El Niño–Southern Oscillation (ENSO) impacts on the eastern China (EC) precipitation during its developing autumn in the past 65 years have been investigated. Results show that ENSO is related to the significant dipole precipitation anomalies in EC in the early decades (1951–1981); El Niño/La Niña introduces more/less precipitation in the southern EC, but less/more in the northern EC. However, the significant dipole pattern disappears in the recent decades (1985–2015), mainly owing to loss of the significant positive influences of La Niña on the northern EC precipitation. Comparison of the atmospheric circulation anomalies in East Asia related to La Niña in the two periods shows that there are anticyclonic circulation anomalies in the northeastern Asia near Japan in the first period, while they shift to Mongolia in the second period. Hence, in the first period, the northern EC is under the influences of anomalous southwesterlies along the southwestern flank of the anticyclonic circulation anomalies that advect more moisture from the south to the northern EC and lead to more precipitation there. In contrast, in the second period, the northern EC is under the influences of anomalous northeasterlies along the southeastern edge of the anticyclonic circulation anomalies near Mongolia that impede the northwards transport of moisture and are not conducive to surplus precipitation. The westwards shift of the anticyclonic circulation anomalies may be closely related to the higher SST and thus convective anomalies related to La Niña in the tropical western North Pacific (WNP) east of the Philippines in the second than the first periods. The sensitivity experiment forced by the positive SST anomalies in the tropical WNP comparable to the observed in an atmospheric general circulation model can successfully simulate the anticyclonic circulation anomalies around Mongolia. [ABSTRACT FROM AUTHOR]

The 50‐year pentad mean simulation outputs of an atmosphere–ocean coupled general circulation model, the Scale INTeraction EXperiment (SINTEX)‐the Frontier Research Center for Global Change (FRCGC) model (SINTEX‐F model), are used to understand processes of the northward‐propagation of intraseasonal oscillations (ISOs) over the South China Sea (SCS) during the pre‐monsoon season. A quite different mean state is found in the SCS before the monsoon onset relative to that of summertime, which is consistent with the observations. Then, 18‐year SCS ISOs, with a relatively larger strength and significant northward component, are selected, and the composite and lead–lag correlation analyses are conducted to explore a possible mechanism for the northward propagation of ISOs in the pre‐monsoon period. Two mechanisms contribute to the northward propagation of the SCS ISOs. One is the vorticity advection by the barotropic southerly mean flow. First, a barotropic vorticity is induced by vertical advection inside the convection centre. During the pre‐monsoon period, the west sides of the upper tropospheric high and the western Pacific subtropical high cover the SCS, thus, there are southerly flows both in the upper and lower troposphere over the SCS. Then the barotropic vorticity induced inside the convection centre shifts to the north because of the advection by the barotropic southerly mean flow. The other is the planetary boundary layer (PBL) moisture advection by the mean flow that lead to a meridional phase leading of the ISO humidity. The northward shift of the PBL moisture promotes a convective instability ahead of the convection centre and leads to the northward propagation of ISOs over the SCS. [ABSTRACT FROM AUTHOR]

Climate change is known as one of the key challenges of the 21st century for sustainable agricultural development over Southwest Asia. However, not much is known about the way that climate changes might affect precipitation, temperature, and climate zones as their consequence over Southwest Asia. Here we have analysed probable changes in modified Thornthwaite climate zones by using monthly temperature and precipitation data from 320 meteorological stations during the historical period of 1971–2015, as well as the future projections of 17 GCMs (General Circulation Models) outputs under the RCP4.5 and RCP8.5 scenarios in two future periods, 2041–2070 and 2071–2100. The CMIP5 climate projections were bias corrected using the correction factors derived in the historical period and applied to simulate future climatic conditions over Southwest Asia. Results derived from multi model ensemble projections of precipitation and temperature indicated that the regional mean annual temperature by the future period of 2071–2100 is expected to increase by 2.4 and 3.8°C, under RCP4.5 and RCP8.5, respectively. Also, except for the southern and eastern parts of the Arabian Peninsula, by 2071–2100, the mean annual precipitation would significantly decrease by on average 6.2 and 7.5%, under RCP4.5 and RCP8.5, respectively. Computing climate types based on averages from three climatic periods (1971–2015, 2041–2070, and 2071–2100) showed that Southwest Asia tends to become warmer and dryer. For example, by the end of the 21st century, the percentage of the area occupied by the torrid‐arid climate type (which already covers 13.8% of the total area) would be 29.3 and 36.4% under RCP4.5 and RCP8.5, respectively. These changes are important because they would definitely have profound ecological, hydrologic, and social consequences and may affect the basic components of sustainable agricultural systems like crop and livestock productions. [ABSTRACT FROM AUTHOR]

Future changes in wave climate will influence the marine ecosystem, coastal erosion, design of coastal defences, operation of near‐ and off‐shore structures, and coastal zone management policies and may further add to the potential vulnerabilities of coastal regions to projected sea level rise. Many studies have reported changes in the global wave characteristics under climate change scenarios, but it is important to project future changes in local/regional wave climate for smooth implementation of policies and preventing severe coastal erosion and flooding. In this study the regional wave climate along the Indian coast for two time slices, 2011–2040 and 2041–2070, is reported using an ensemble of near‐surface winds generated by four different CMIP5 general circulation models (GCMs), under RCP4.5 scenario. Comparison of the wave climate for the two time slices shows an increase in wave heights and periods along much of the Indian coast, with the maximum wave heights increasing by more than 30% in some locations. An important finding is that at most locations along the east coast, wave periods are expected to increase by almost 20%, whereas along the west coast an increase of around 10% is expected. This will alter the distribution of wave energy at the shoreline through changes in wave refraction and diffraction, with potential implications for the performance and design of coastal structures and swash‐aligned beaches. Furthermore, the computations show material changes in the directional distribution of waves. This is particularly important in determining the longshore transport of sediments and can lead to realignment of drift‐aligned beaches, manifesting itself as erosion and/or siltation problems. This study is a preliminary contribution towards regional climate projections for the Indian Ocean region which are needed to plan and mitigate the impacts of future climate change. [ABSTRACT FROM AUTHOR]