Asian Summer Monsoon Onset in Simulations and CMIP5 Projections Using Four Chinese Climate Models

The reproducibility and future changes of the onset of the Asian summer monsoon were analyzed based on the simulations and projections under the Representative Concentration Pathways （RCP） scenario in which anthropogenic emissions continue to rise throughout the 21 st century （i.e. RCP8.5） by all realizations from four Chinese models that participated in the Coupled Model Intercomparison Project Phase 5 （CMIP5）. Delayed onset of the monsoon over the Arabian Sea was evident in all simulations for present-day climate, which was associated with a too weak simulation of the low-level Somali jet in May. A consistent advanced onset of the monsoon was found only over the Arabian Sea in the projections, where the advanced onset of the monsoon was accompanied by an increase of rainfall and an anomalous anticyclone over the northern Indian Ocean. In all the models except FGOALS-g2, the enhanced low-level Somali jet transported more water vapor to the Arabian Sea, whereas in FGOALS-g2 the enhanced rainfall was determined more by the increased wind convergence. Furthermore, and again in all models except FGOALS-g2, the equatorial SST warming, with maximum increase over the eastern Pacific, enhanced convection in the central West Pacific and reduced convection over the eastern Indian Ocean and Maritime Continent region, which drove the anomalous anticyclonic circulation over the western Indian Ocean. In contrast, in FGOALS-g2, there was minimal （near-zero） warming of projected SST in the central equatorial Pacific, with decreased convection in the central West Pacific and enhanced convection over the Maritime Continent. The broader-scale differences among the models across the Pacific were related to both the differences in the projected SST pattern and in the present-day simulations.

Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models

The Southern Ocean is covered by a large amount of clouds with high cloud albedo.However,as reported by previous climate model intercomparison projects,underestimated cloudiness and overestimated absorption of solar radiation(ASR)over the Southern Ocean lead to substantial biases in climate sensitivity.The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models.We employ 10-year satellite observations to evaluate cloud radiative effect(CRE)and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud,radiation,and aerosol.The simulated longwave,shortwave,and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations.Total cloud fraction(CF)is also reasonably simulated in CMIP6,but the comparison of liquid cloud fraction(LCF)reveals marked biases in spatial pattern and seasonal variations.The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macroand micro-physical properties,including liquid water path(LWP),cloud optical depth(COD),and cloud effective radius,as well as aerosol optical depth(AOD).However,the large underestimation of both LWP and cloud effective radius(regional means~20%and 11%,respectively)results in relatively smaller bias in COD,and the impacts of the biases in COD and LCF also cancel out with each other,leaving CRE and ASR reasonably predicted in CMIP6.An error estimation framework is employed,and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE.Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations,while the modeled CRE is too sensitive to LWP and COD.The relationships between cloud effective radius,LWP,and COD are also analyzed to explore the possible uncertainty sources in different models.Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.

Projections of Wind Changes for 21st Century in China by Three Regional Climate Models

This paper examines the capability of three regional climate models (RCMs), i.e., RegCM3 (the International Centre for Theoretical Physics Regional Climate Model), PRECIS (Providing Regional Climates for Impacts Studies) and CMM5 (the fifth-generation Pennsylvania State University-the National Center for Atmospheric Research of USA, NCAR Mesoscale Model) to simulate the near-surface-layer winds (10 m above surface) all over China in the late 20th century. Results suggest that like global climate models (GCMs), these RCMs have the certain capability of imitating the distribution of mean wind speed and fail to simulate the greatly weakening wind trends for the past 50 years in the country. However, RCMs especially RegCM3 have the better capability than that of GCMs to simulate the distribution and change feature of mean wind speed. In view of their merits, these RCMs were used to project the variability of near-surface-layer winds over China for the 21st century. The results show that 1) summer mean wind speed for 2020-2029 will be lower compared to those in 1990-1999 in most area of China; 2) annual and winter mean wind speed for 2081-2100 will be lower than those of 1971-1990 in the whole China; and 3) the changes of summer mean wind speed for 2081-2100 are uncertain. As a result, although climate models are absolutely necessary for projecting climate change to come, there are great uncertainties in projections, especially for wind speed, and these issues need to be further explored.

Coupling methods of global climate models and regional climate models

The future climate dynamical downscaling method is that output of general circulation models( GCMs) is employed to provide initial conditions,lateral boundary conditions,sea surface temperatures,and initial land surface conditions to regional climate models( RCMs). There are two methods of downscaling: offline coupling and online coupling. The two kinds of coupling methods are described in detail by coupling the Weather Research and Forecasting model( WRF) with the Institute of Atmospheric Physics of Chinese Academy of Sciences Atmospheric General Circulation Model Version 4. 0( IAP AGCM4. 0) in the study. And the extreme precipitation event over Beijing on July 212012 is simulated by using the two coupling methods. Results show that online coupling method is of great value in improving the model simulation. Furthermore,the data exchange frequency of online coupling has some effect on simulation result.

Advance in Application of Regional Climate Models in China

Regional climate models have become the powerful tools for simulating regional climate and its change process and have been widely used in China. Using regional climate models, some research results have been obtained on the following aspects： 1） the numerical simulation of East Asian monsoon climate, including exceptional monsoon precipitation, summer precipitation distribution, East Asian circulation, multi-year climate average condition, summer rain belt and so on; 2） the simulation of arid climate of the western China, including thermal effect of the Qinghal-Tibet Plateau, the plateau precipitation in the Qilian Mountains; and the impacts of greenhouse effects （CO2 doubling） upon climate in the western China; and 3） the simulation of the climate effect of underlying surface changes, including the effect of soil on climate formation, the influence of terrain on precipitation, the effect of regional soil degradation on regional climate, the effect of various underlying surfaces on regional climate, the effect of land-sea contrast on the climate formulation, the influence of snow cover over the plateau regions on the regional climate, the effect of vegetation changes on the regional climate, etc. In the process of application of regional climate models, the preferences of the models are improved so that better simulation results are gotten. At last, some suggestions are made about the application of regional climate models in regional climate research in the future.

FUTURE CHANGE OF PRECIPITATION EXTREMES OVER THE PEARL RIVER BASIN FROM REGIONAL CLIMATE MODELS

Based on RegCM4,a climate model system,we simulated the distribution of the present climate(1961-1990)and the future climate(2010-2099),under emission scenarios of RCPs over the whole Pearl River Basin.From the climate parameters,a set of mean precipitation,wet day frequency,and mean wet day intensity and several precipitation percentiles are used to assess the expected changes in daily precipitation characteristics for the 21 st century.Meanwhile the return values of precipitation intensity with an average return of 5,10,20,and 50 years are also used to assess the expected changes in precipitation extremes events in this study.The structure of the change across the precipitation distribution is very coherent between RCP4.5 and RCP8.5.The annual,spring and winter average precipitation decreases while the summer and autumn average precipitation increases.The basic diagnostics of precipitation show that the frequency of precipitation is projected to decrease but the intensity is projected to increase.The wet day percentiles(q90 and q95) also increase,indicating that precipitation extremes intensity will increase in the future.Meanwhile,the5-year return value tends to increase by 30%-45%in the basins of Liujiang River,Red Water River,Guihe River and Pearl River Delta region,where the 5-year return value of future climate corresponds to the 8-to 10-year return value of the present climate,and the 50-year return value corresponds to the 100-year return value of the present climate over the Pearl River Delta region in the 2080 s under RCP8.5,which indicates that the warming environment will give rise to changes in the intensity and frequency of extreme precipitation events.

An Alternative Means of Assessing Climate Models

The authors compared two different sets of assessment of the abilities of contemporary climate models. One group is made of experts, and their results are provided in two expert reports, while the other is the subjective assessment made by ＂physical climate scientists＂ in general, sampled in a series of three survey questionnaires. The expert group is considerably more optimistic than the general group; the former suggesting progress, while the perception of the latter group is more or less stationary.

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)

In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources.

Toward a Learnable Climate Model in the Artificial Intelligence Era

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

Global Well-Posedness of the Fractional Tropical Climate Model

In this paper, we consider the Cauchy problem of 3-dimensional tropical climate model. This model reflects the interaction and coupling among the barotropic mode u, the first baroclinic mode v of the velocity and the temperature θ. The systems with fractional dissipation studied here may arise in the modeling of geophysical circumstances. Mathematically these systems allow simultaneous examination of a family of systems with various levels of regularization. The aim here is the global strong solution with the least dissipation. By energy estimate and delicate analysis, we prove the existence of global solution under three different cases: first, with the help of damping terms, the global strong solution of the system with Λ2au, Λ2βv and Λ2γ θ for;and second, the global strong solution of the system for with damping terms;finally, the global strong solution of the system for without any damping terms, which improve the known existence theory for this system.

Projection of IPCC AR4 Coupled Climate Models for Multitimescale Temperature Variation in Yunnan: A Case Study on Southwest Yunnan from 1960 to 2050

Based on daily mean temperature records from 1961 to 2007 at 20 meteorological sites in Southwest Yunnan, and the surface temperature simulated by IPCC AR4 Climate Models, a quantitative examination was undertaken into the characteristics of multi-timescale temperature （AMT, DMT and WMT） variation in Southwest Yunnan. The simulation abilities of the models were also evaluated with the normalized root mean square error （NRMSE） and Mann-Kendal test statistic methods. Temperatures show remarkable increasing trend from 1961 to 2007, with the Mann-Kendall test statistic passing 95% confidence verification. The result of the NRMSE analysis shows that the simulated temperature anomaly variations are more similar to observed ones especially for AMT and DMT, and the projected result （anomalies） of IPCC AR4 climate models can be used for predicting the trends in multi-timescale temperature variation in Southwest Yunnan in the next 40 years under the three emission scenarios, which has better simulating effect on AMT and DMT than WMT. Over the next 40 years the temperature will continue to rise, with annual mean temperature showing a more remarkable rising trend than that of the dry and wet seasons. Temperature anomalies exhibit different increasing rates under different emission scenarios： During the 2020s the rising rates of multi-timescale temperature anomalies in a high greenhouse gases emissions scenario （SRESA2） are smaller than those under a low emission scenario （SRESB1）. Except that, the rate of increase in temperature anomalies are the highest in the intermediate emissions scenario （SRESA1B）, followed by those in SRESA2, and those in low emissions scenario （SRESB1） are the lowest. The reason of different simulating effects on WMT from AMT and DMT was also discussed.

Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon

We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6,respectively)in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period 1979–2005.All 92 models are able to simulate the geographical distribution of the above variables reasonably well.Compared with earlier CMIP5 models,current CMIP6 models have nationally weaker cold biases,a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient,a comparable overestimation of the spatial variability of the interannual variability,and a similar underestimation of the strength of winter monsoon over northern Asia.Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon.The ability of models relates to their horizontal resolutions in certain aspects.Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.

Attribution analysis for the failure of CMIP5 climate models to simulate the recent global warming hiatus

The Coupled Model Inter-comparison Project Phase 5 （CMIP5） contains a group of state-of-the-art climate models and represents the highest level of climate simulation thus far. However, these models significantly overestimated global mean surface temperature （GMST） during 2006-2014. Based on the ensemble empirical mode decomposition （EEMD） method, the long term change of the observed GMST time series of HadCRUT4 records during 1850-2014 was analyzed, then the simulated GMST by 33 CMIP5 climate models was assessed. The possible reason that climate models failed to project the recent global warming hiatus was revealed. Results show that during 1850-2014 the GMST on a centennial timescale rose with fluctuation, dominated by the secular trend and the multi-decadal variability （MDV）. The secular trend was relatively steady beginning in the early 20th century, with an average warming rate of 0.0883℃/decade over the last 50 years. While the MDV （with a -65-year cycle） showed 2.5 multi-decadal waves during 1850-2014, which deepened and steepened with time, the alarming warming over the last quarter of the 20th century was a result of the concurrence of the secular wanning trend and the warming phase of the MDV, both of which accounted one third of the temperature increase during 1975-1998. Recently the slowdown of global warming emerged as the MDV approached its third peak, leading to a reduction in the warming rate. A comparative analysis between the GMST time series derived from HadCRUT4 records and 33 CMIP5 model outputs reveals that the GMSTs during the historical simulation period of 1850-2005 can be reproduced well by models, especially on the accelerated global warming over the last quarter of 20th century. However, the projected GMSTs and their linear trends during 2006-2014 under the RCP4.5 scenario were significantly higher than observed. This is because the CMIP5 models confused the MDV with secular trend underlying the GMST time series, which results in a fast secular trend and an improper MDV with irregular phases and small amplitudes. This implies that the role of atmospheric CO2 in global warming may be overestimated, while the MDV which is an interior oscillation of the climate system may be underestimated, which should be related to insufficient understanding of key climatic internal dynamic processes. Our study puts forward an important criterion for the new generation of climate models： they should be able to simulate both the secular trend and the MDV of GMST.

An Assessment on the Performance of IPCC AR4 Climate Models in Simulating Interdecadal Variations of the East Asian Summer Monsoon

Observations from several data centers together with a categorization method are used to evaluate the IPCC AR4 （Intergovernmental Panel on Climate Change, the Fourth Assessment Report） climate models＇ performance in simulating the interdecadal variations of summer precipitation and monsoon circulation in East Asia. Out of 19 models under examination, 9 models can relatively well reproduce the 1979-1999 mean June-July-August （JJA） precipitation in East Asia, but only 3 models （Category-1 models） can capture the interdecadal variation of precipitation in East Asia. These 3 models are： GFDL-CM2.0, MIROC3.2 （hires）, and MIROC3.2 （medres）, among which the GFDL-CM2.0 gives the best performance. The reason for the poor performance of most models in simulating the East Asian summer monsoon interdecadal variation lies in that the key dynamic and thermal-dynamic mechanisms behind the East Asian monsoon change are missed by the models, e.g., the large-scale tropospheric cooling and drying over East Asia. In contrast, the Category-1 models relatively well reproduce the variations in vertical velocity and water vapor over East Asia and thus show a better agreement with observations in simulating the pattern of ＂wet south and dry north＂ in China in the past 20 years. It is assessed that a single model＇s performance in simulating a particular variable has great impacts on the ensemble results. More realistic outputs can be obtained when the multi-model ensemble is carried out using a suite of well-performing models for a specific variable, rather than using all available models. This indicates that although a multi-model ensemble is in general better than a single model, the best ensemble mean cannot be achieved without looking into each member model＇s performance.

Could CMIP6 climate models reproduce the early-2000s global warming slowdown?

The unexpected global warming slowdown during 1998–2013 challenges the existing scientific understanding of global temperature change mechanisms,and thus the simulation and prediction ability of state-of-the-art climate models since most models participating in phase 5 of the Coupled Model Intercomparison Project(CMIP5)cannot simulate it.Here,we examine whether the new-generation climate models in CMIP6 can reproduce the recent global warming slowdown,and further evaluate their capacities for simulating key-scale natural variabilities which are the most likely causes of the slowdown.The results show that although the CMIP6 models present some encouraging improvements when compared with CMIP5,most of them still fail to reproduce the warming slowdown.They considerably overestimate the warming rate observed in 1998–2013,exhibiting an obvious warming acceleration rather than the observed deceleration.This is probably associated with their deficiencies in simulating the distinct temperature change signals from the human-induced long-term warming trend and/or the three crucial natural variabilities at interannual,interdecadal,and multidecadal scales.In contrast,the 4 models that can successfully reproduce the slowdown show relatively high skills in simulating the long-term warming trend and the three keyscale natural variabilities.Our work may provide important insight for the simulation and prediction of near-term climate changes.

Asymmetry of Surface Climate Change under RCP2.6 Projections from the CMIP5 Models

The multi-model ensemble （MME） of 20 models from the Coupled Model Intercomparison Project Phase Five （CMIP5） was used to analyze surface climate change in the 21st century under the representative con- centration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature （SAT） is 1.86℃ relative to the pre-industrial level, achieving the target to limit the global warming to 2℃. Associated with the ＂increase-peak-decline＂ greenhouse gases （GHGs） concentration path- way of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods： warming during 2006-55 and cooling during 2056-2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cool- ing period. The warming during 2006-55 is distributed globally, while the cooling during 2056-2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.

High-Resolution Projections of Mean and Extreme Precipitation over China by Two Regional Climate Models

In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.

Response of the North Pacific Oscillation to global warming in the models of the Intergovernmental Panel on Climate Change Fourth Assessment Report

Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation(NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario(the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.

Future meteorological drought conditions in southwestern Iran based on the NEX-GDDP climate dataset

Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts.Therefore,studying the future meteorological drought conditions at a local scale is vital.In this study,we assessed the efficiency of seven downscaled Global Climate Models(GCMs)provided by the NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP),and investigated the impacts of climate change on future meteorological drought using Standard Precipitation Index(SPI)in the Karoun River Basin(KRB)of southwestern Iran under two Representative Concentration Pathway(RCP)emission scenarios,i.e.,RCP4.5 and RCP8.5.The results demonstrated that SPI estimated based on the Meteorological Research Institute Coupled Global Climate Model version 3(MRI-CGCM3)is consistent with the one estimated by synoptic stations during the historical period(1990-2005).The root mean square error(RMSE)value is less than 0.75 in 77%of the synoptic stations.GCMs have high uncertainty in most synoptic stations except those located in the plain.Using the average of a few GCMs to improve performance and reduce uncertainty is suggested by the results.The results revealed that with the areas affected by wetness decreasing in the KRB,drought frequency in the North KRB is likely to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios.At the seasonal scale,the decreasing trend for SPI in spring,summer,and winter shows a drought tendency in this region.The climate-induced drought hazard can have vast consequences,especially in agriculture and rural livelihoods.Accordingly,an increasing trend in drought during the growing seasons under RCP scenarios is vital for water managers and farmers to adopt strategies to reduce the damages.The results of this study are of great value for formulating sustainable water resources management plans affected by climate change.