Precipitation-Surface Temperature Relationship in the IPCC CMIP5 Models

Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison Project Phase 5 （CMIP5） for the IPCC Assessment Report version 5. Most models performed reasonably well at simulat- ing the large-scale features of the P-T correlation distribution. Based on the pattern correlation of the P-T correlation distribution, the models performed better in November-December-January-February-March （NDJFM） than in May-June-July-August-September （MJJAS） except for the mid-latitudes of the North- ern Hemisphere, and the performance was generally better over the land than over the ocean. Seasonal dependence was more obvious over the land than over the ocean and was more obvious over the mid- and high-latitudes than over the tropics. All of the models appear to have had difficulty capturing the P-T correlation distribution over the mid-latitudes of the Southern Hemisphere in MJJAS. The spatial variabil- ity of the P-T correlation in the models was overestimated compared to observations. This overestimation tended to be larger over the land than over the ocean and larger over the mid- and high-latitudes than over the tropics. Based on analyses of selected model ensemble simulations, the spread of the P-T correlation among the ensemble members appears to have been small. While the performance in the P-T correlation provides a general direction for future improvement of climate models, the specific reasons for the discrep- ancies between models and observations remain to be revealed with detailed and comprehensive evaluations in various aspects.

Sea level rise projection in the South China Sea from CMIP5 models

Future potential sea level change in the South China Sea （SCS） is estimated by using 24 CMIP5 models under different representative concentration pathway （RCP） scenarios. By the end of the 21st century （2081–2100 relative to 1986–2005）, the multimodel ensemble mean dynamic sea level （DSL） is projected to rise 0.9, 1.6, and 1.1 cm under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, resulting in a total sea level rise （SLR） of 40.9, 48.6, and 64.1 cm in the SCS. It indicates that the SCS will experience a substantial SLR over the 21st century, and the rise is only marginal larger than the global mean SLR. During the same period, the steric sea level （SSL） rise is estimated to be 6.7, 10.0, and 15.3 cm under the three scenarios, respectively, which accounts only for 16%, 21% and 24% of the total SLR in this region. The changes of the SSL in the SCS are almost out of phase with those of the DSL for the three scenarios. The central deep basin has a slightly weak DSL rise, but a strong SSL rise during the 21st century, compared with the north and southwest shelves.

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).

Introduction of CMIP5 Experiments Carried out with the Climate System Models of Beijing Climate Center

The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.

Projected change in precipitation forms in the Chinese Tianshan Mountains based on the Back Propagation Neural Network Model

In the context of global warming,precipitation forms are likely to transform from snowfall to rainfall with a more pronounced trend.The change in precipitation forms will inevitably affect the processes of regional runoff generation and confluence as well as the annual distribution of runoff.Most researchers used precipitation data from the CMIP5 model directly to study future precipitation trends without distinguishing between snowfall and rainfall.CMIP5 models have been proven to have better performance in simulating temperature but poorer performance in simulating precipitation.To overcome the above limitations,this paper used a Back Propagation Neural Network(BNN)to predict the rainfall-to-precipitation ratio(RPR)in months experiencing freezing-thawing transitions(FTTs).We utilized the meteorological(air pressure,air temperature,evaporation,relative humidity,wind speed,sunshine hours,surface temperature),topographic(altitude,slope,aspect)and geographic(longitude,latitude)data from 28 meteorological stations in the Chinese Tianshan Mountains region(CTMR)from 1961 to 2018 to calculate the RPR and constructed an index system of impact factors.Based on the BNN,decision-making trial and evaluation laboratory method(BP-DEMATEL),the key factors driving the transformation of the RPR in the CTMR were identified.We found that temperature was the only key factor affecting the transformation of the RPR in the BP-DEMATEL model.Considering the relationship between temperature and the RPR,the future temperature under different representative concentration pathways(RCPs)(RCP2.6/RCP4.5/RCP8.5)provided by 21 CMIP5 models and the meteorological factors from meteorological stations were input into the BNN model to acquire the future RPR from 2011 to 2100.The results showed that under the three scenarios,the RPR in the number of months experiencing FTTs during 2011-2100 will be higher than that in the historical period(1981-2010)in the CTMR.Furthermore,in terms of spatial variation,the RPR values on the south slope will be larger than those on the north slope under the three emission scenarios.Moreover,the RPR values exhibited different variation characteristics under different emission scenarios.Under the low-emission scenario(RCP2.6),as time passed,the RPR values changed slightly at more stations.Under the mediumemission scenario(RCP4.5),the RPR increased in the whole CTMR and stabilized on the north slope by the end of this century.Under the high-emission scenario(RCP8.5),the RPR values increased significantly through the 21 st century in the whole CTMR.This study may help to provide a scientific management basis for agricultural production and hydrology.

Relationship between South China Sea Precipitation Variability and Tropical Indo-Pacific SST Anomalies in IPCC CMIP5 Models during Spring-to-Summer Transition

The present study evaluates the precipitation variability over the South China Sea（SCS） and its relationship to tropical Indo-Pacific SST anomalies during spring-to-summer transition（April–May–June,AMJ） simulated by 23 Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project Phase 5 coupled models.Most of the models have the capacity to capture the AMJ precipitation variability in the SCS.The precipitation and SST anomaly（SSTA） distribution in the SCS,tropical Pacific Ocean（TPO）,and tropical Indian Ocean（TIO） domains is evaluated based on the pattern correlation coefficients between model simulations and observations.The analysis leads to several points of note.First,the performance of the SCS precipitation anomaly pattern in AMJ is model dependent.Second,the SSTA pattern in the TPO and TIO is important for capturing the AMJ SCS precipitation variability.Third,a realistic simulation of the western equatorial Pacific（WEP） and local SST impacts is necessary for reproducing the AMJ SCS precipitation variability in some models.Fourth,the overly strong WEP SST impacts may disrupt the relationship between the SCS precipitation and the TPO–TIO SST.Further work remains to be conducted to unravel the specific reasons for the discrepancies between models and observations in various aspects.

Projections of changes in marine environment in coastal China seas over the 21^st century based on CMIP5 models

The increases of atmospheric carbon dioxide and other greenhouse gases have caused fundamental changes to the physical and biogeochemical properties of the oceans,and it will continue to occur in the foreseeable future.Based on the outputs of nine Earth System Models from the fifth phase of the Coupled Model Intercomparison Project(CMIP5),in this study,we provided a synoptic assessment of future changes in the sea surface temperature(SST),salinity,dissolved oxygen(DO),seawater pH,and marine net primary productivity(NPP)in the coastal China seas over the 21st century.The results show that the mid-high latitude areas of the coastal China seas(East China Seas(ECS),including the Bohai Sea,Yellow Sea,and East China Sea)will be simultaneously exposed to enhanced warming,deoxygenation,acidification,and decreasing NPP as a consequence of increasing greenhouse gas emissions.The magnitudes of the changes will increase as the greenhouse gas concentrations increase.Under the high emission scenario(Representative Concentration Pathway 8.5),the ECS will experience an SST increase of 3.24±1.23℃,a DO concentration decrease of 10.90±3.92μmol/L(decrease of 6.3%),a pH decline of 0.36±0.02,and a NPP reduction of-17.7±6.2 mg/(m2·d)(decrease of 12.9%)relative to the current levels(1980-2005)by the end of this century.The co-occurrence of these changes and their cascade effects are expected to induce considerable biological and ecological responses,thereby making the ECS among the most vulnerable ocean areas to future climate change.Despite high uncertainties,our results have important implications for regional marine assessments.

How Frequently Will the Persistent Heavy Rainfall over the Middle and Lower Yangtze River Basin in Summer 2020 Happen under Global Warming?

The middle and lower Yangtze River basin(MLYRB)suffered persistent heavy rainfall in summer 2020,with nearly continuous rainfall for about six consecutive weeks.How the likelihood of persistent heavy rainfall resembling that which occurred over the MLYRB in summer 2020(hereafter 2020PHR-like event)would change under global warming is investigated.An index that reflects maximum accumulated precipitation during a consecutive five-week period in summer(Rx35day)is introduced.This accumulated precipitation index in summer 2020 is 60%stronger than the climatology,and a statistical analysis further shows that the 2020 event is a 1-in-70-year event.The model projection results derived from the 50-member ensemble of CanESM2 and the multimodel ensemble(MME)of the CMIP5 and CMIP6 models show that the occurrence probability of the 2020PHR-like event will dramatically increase under global warming.Based on the Kolmogorov-Smirnoff test,one-third of the CMIP5 and CMIP6 models that have reasonable performance in reproducing the 2020PHR-like event in their historical simulations are selected for the future projection study.The CMIP5 and CMIP6 MME results show that the occurrence probability of the 2020PHR-like event under the present-day climate will be double under lower-emission scenarios(CMIP5 RCP4.5,CMIP6 SSP1-2.6,and SSP2-4.5)and 3-5 times greater under higher-emission scenarios(3.0 times for CMIP5 RCP8.5,2.9 times for CMIP6 SSP3-7.0,and 4.8 times for CMIP6 SSP5-8.5).The inter-model spread of the probability change is small,lending confidence to the projection results.The results provide a scientific reference for mitigation of and adaptation to future climate change.

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model lntercomparison Project Phase 5 （CMIP5） results, multidecadal variations and trends in annual mean surface air temperature anomalies （SATa） at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways （RCPs） are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere （NH） and of the ocean in the southern hemisphere （SH） are similar to those of the global mean, showing an increase during the 1900-1944 and 1971-2000 periods, and flattening or even cooling during the 1945-1970 and 2001-2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945-1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period （2001-2013）, the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006-2099 period. The selected multi-model ensemble （MME） projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 （RCP8.5） are 0.17 （0.29） ℃, 0.22 （0.36） ℃, and 0.11 （0.23） ℃-decade-1 in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.

Climatology and interannual variability of the annual mean Hadley circulation in CMIP5 models

Using 26 climate models from the Coupled Model Intercomparison Project Phase 5(CMIP5), climatology and the interannual variability of the annual mean Hadley circulation are evaluated. The results show that most of 26 models perform well in simulating the spatial structure of the climatology of the annual mean Hadley circulation, but the results derived from these models are generally weaker than that derived from the reanalysis dataset. Eighteen models can properly simulate well the asymmetric mode and symmetric mode of the annual mean Hadley circulation variability. Two models can only simulate asymmetric mode or symmetric mode and the other two models simulate reversed sequences of asymmetric mode and symmetric mode.The possible reason why some models cannot properly simulate the asymmetric mode and symmetric mode is that these models do not properly simulate the structure of zonal mean sea surface temperature(SST). Especially, not properly simulating variances of symmetric and asymmetric components of the SSTA will lead to reversed sequence of symmetric mode and asymmetric mode. And not properly simulated either symmetric or asymmetric component of the SSTA will lead to inability in simulating symmetric mode or asymmetric mode. On the other hand, some models properly simulate the asymmetric mode and symmetric mode, but do not properly simulate the responses to SST change.These models can not reflect the air sea coupling processes in associated with the Hadley circulation, therefore they should be taken more care when classify the models into groups.

An assessment of the CMIP5 models in simulating the Argo geostrophic meridional transport in the North Pacifi c Ocean

Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5(CMIP5)were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup transports.The analyses show that the simulated North Pacifi c Ocean circulation is essentially in Sverdrup balance in most of the 11 models while the Argo geostrophic meridional transports indicate signifi cant non-Sverdrup gyre circulation in the tropical North Pacifi c Ocean.The climate models overestimated the observed tropical and subtropical volume transports signifi cantly.The non-Sverdrup gyre circulation leads to non-Sverdrup heat and salt transports,the absence of which in the CMIP5 simulations suggests defi ciencies of the CMIP5 model dynamics in simulating the realistic meridional volume,heat,and salt transports of the ocean.

Evaluation of the performance of CMIP5 and CMIP6 models in simulating the South Pacific Quadrupole-ENSO relationship

The South Pacific Quadrupole(SPQ) is the extratropical South Pacific’s second principal sea surface temperature mode.Previous observational studies have shown that the SPQ promotes the onset of the El Nino-Southern Oscillation(ENSO).The present study evaluates and compares simulations of the SPQ-ENSO relationship by 20 climate models from CMIP6 and their corresponding 20 previous models from CMIP5.It is found that 16 of the20 pairs of models are able to consistently reproduce the spatial pattern of the SPQ.In terms of simulating the SPQ-ENSO relationship,9 of the 16 CMIP6 models show significant improvement over their previous CMIP5 models.The multi-model ensemble(MME) of these 16 CMIP6 models simulates the SPQ-ENSO connection more realistically than the CMIP5 MME.Further analysis shows that the performance of the model simulations in reproducing the SPQ-ENSO relationship is strongly dependent on their ability to simulate the SPQ-related surface air-sea coupling processes over the southwestern and southeastern South Pacific,as well as the response of the SPQ-related equatorial subsurface ocean temperature anomalies.The improvement of the CMIP6 models in simulating these two processes is responsible for the improved performance of the CMIP6 models over their CMIP5 counterparts in simulating the SPQ-ENSO relationship.

Climate change impacts on the streamflow of Zarrineh River,Iran

Zarrineh River is located in the northwest of Iran,providing more than 40%of the total inflow into the Lake Urmia that is one of the largest saltwater lakes on the earth.Lake Urmia is a highly endangered ecosystem on the brink of desiccation.This paper studied the impacts of climate change on the streamflow of Zarrineh River.The streamflow was simulated and projected for the period 1992-2050 through seven CMIP5(coupled model intercomparison project phase 5)data series(namely,BCC-CSM1-1,BNU-ESM,CSIRO-Mk3-6-0,GFDL-ESM2G,IPSL-CM5A-LR,MIROC-ESM and MIROC-ESM-CHEM)under RCP2.6(RCP,representative concentration pathways)and RCP8.5.The model data series were statistically downscaled and bias corrected using an artificial neural network(ANN)technique and a Gamma based quantile mapping bias correction method.The best model(CSIRO-Mk3-6-0)was chosen by the TOPSIS(technique for order of preference by similarity to ideal solution)method from seven CMIP5 models based on statistical indices.For simulation of streamflow,a rainfall-runoff model,the hydrologiska byrans vattenavdelning(HBV-Light)model,was utilized.Results on hydro-climatological changes in Zarrineh River basin showed that the mean daily precipitation is expected to decrease from 0.94 and 0.96 mm in 2015 to 0.65 and 0.68 mm in 2050 under RCP2.6 and RCP8.5,respectively.In the case of temperature,the numbers change from 12.33℃ and 12.37℃ in 2015 to 14.28℃ and 14.32℃ in 2050.Corresponding to these climate scenarios,this study projected a decrease of the annual streamflow of Zarrineh River by half from 2015 to 2050 as the results of climatic changes will lead to a decrease in the annual streamflow of Zarrineh River from 59.49 m^(3)/s in 2015 to 22.61 and 23.19 m^(3)/s in 2050.The finding is of important meaning for water resources planning purposes,management programs and strategies of the Lake's endangered ecosystem.

Simulations of dissolved oxygen concentration in CMIP5 Earth system models

The climatologies of dissolved oxygen concentration in the ocean simulated by nine Earth system models(ESMs) from the historical emission driven experiment of CMIP5(Phase 5 of the Climate Model Intercomparison Project) are quantitatively evaluated by comparing the simulated oxygen to the WOA09 observation based on common statistical metrics. At the sea surface, distribution of dissolved oxygen is well simulated by all nine ESMs due to well-simulated sea surface temperature(SST), with both globally-averaged error and root mean square error(RMSE) close to zero, and both correlation coefficients and normalized standard deviation close to 1. However, the model performance differs from each other at the intermediate depth and deep ocean where important water masses exist. At the depth of 500 to 1 000 m where the oxygen minimum zones(OMZs) exist, all ESMs show a maximum of globally-averaged error and RMSE, and a minimum of the spatial correlation coefficient. In the ocean interior, the reason for model biases is complicated, and both the meridional overturning circulation(MOC) and the particulate organic carbon flux contribute to the biases of dissolved oxygen distribution. Analysis results show the physical bias contributes more. Simulation bias of important water masses such as North Atlantic Deep Water(NADW), Antarctic Bottom Water(AABW) and North Pacific Intermediate Water(NPIW) indicated by distributions of MOCs greatly affects the distributions of oxygen in north Atlantic, Southern Ocean and north Pacific, respectively.Although the model simulations of oxygen differ greatly from each other in the ocean interior, the multi-model mean shows a better agreement with the observation.

On the spring stratospheric final warming in CMIP5 and CMIP6 models

This study evaluates the performance in simulating the stratospheric final warming events(SFWs)that lead to the final collapse of the stratospheric polar vortex in spring in both Southern and Northern Hemispheres(SH and NH,respectively)based on the historical simulations provided by the Coupled Model Intercomparison Project Phases 5 and 6(CMIP5 and CMIP6,respectively).Overall,CMIP5 and CMIP6 models can reproduce the main characteristics of the occurrence of SFWs.However,the SFW onset date(SFWOD)is 7 and 9 days later than in observations in the SH and NH,respectively.Moreover,the intensity of SFWs in models is 50%to 70%of that in observations.Compared with CMIP5 models,CMIP6 models have an ameliorated capability to simulate NH SFWs.However,this improvement does not manifest as significantly earlier SFW onset,but as more intense stratospheric planetary wave activities before the SFWand as a larger interannual variability of the SFWOD.By contrast,in the SH,the capability of CMIP6 models is roughly unchanged,even deteriorated in the simulation of SFWOD and stratospheric planetary wave activities before the SFW onset.The performance of CMIP6 high-top models is better than that of lowtop models.Specifically,in the NH,high-top models are considerably improved in terms of intensity of circumpolar zonal wind around the SFWOD and stratospheric planetary wave activities before the SFW onset.In the SH,high-top models show fairly earlier SFWOD by 11 days,which is closer to observations.

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.

Contributions of anthropogenic and external natural forcings to climate changes over China based on CMIP5 model simulations

Based on observations and historical simulations from the fifth phase of the Coupled Model Intercomparison Project(CMIP5) archive, the contributions of human activities(including greenhouse gases(GHGs), anthropogenic aerosols(AAs), and land use(LU)) and external natural forcings(Nat) to climate changes in China over the past 50 years were quantified. Both anthropogenic and external natural forcings account for 95%–99% of the observed temperature change from 1951–1975 to 1981–2005. In particular, the temperature changes induced by GHGs are approximately 2–3 times stronger than the observed changes, and AAs impose a significant cooling effect. The total external forcings can explain 65%–78% of the observed precipitation changes over the past 50 years, in which AAs and GHGs are the primary external forcings leading to the precipitation changes; in particular, AAs dominate the main spatial features of precipitation changes in eastern China. Human activities also dominate the long-term non-linear trends in observed temperature during the past several decades, and, in particular, GHGs, the primary warming contributor, have produced significant warming since the 1960 s. Compared to the long-term non-linear trends in observed precipitation, GHGs have largely caused the wetting changes in the arid-semiarid region since the 1970 s, whereas AAs have led to the drying changes in the humid-semihumid region; both LU and Nat can impose certain impacts on the long-term non-linear trends in precipitation. Using the optimal fingerprinting detection approach, the effects of human activities on the temperature changes can be detected and attributed in China, and the effect of GHGs can be clearly detected from the observations in humid-semihumid areas. However, the anthropogenic effects cannot be detected in the observed precipitation changes, which may be due to the uncertainties in the model simulations and to other issues. Although some results in this paper still need improvement due to uncertainties in the coupled models, this study is expected to provide the background and scientific basis for climate changes to conduct vulnerability and risk assessments of the ecological systems and water resources in the arid-semiarid region of China.

CMIP5模式对长江和黄河流域极端气温指标的模拟与预估

为研究长江和黄河流域极端气温的变化特征,对耦合模式比较计划第5阶段22个大气环流模式数据进行精度评估、Delta降尺度并计算16个极端气温指标,采用可靠性集合平均方法对两流域历史和未来的极端气温进行预估.结果表明:除四川盆地外,两流域的观测值与REA(ensemble reliability average)值在空间上具有较好一致性;未来三个时期(2020s、2050s、2080s),典型浓度路径(Representative Concentration Pathways,RCP)4.5情景下指标变化趋势依次递减,RCP8.5情景下变化趋势逐渐递增;RCP4.5和RCP8.5情景下指标年际变化在21世纪40年代之前是相似的,但之后变化趋势差异增加;两流域的大多数指标呈现上升趋势,冬季趋势相较于其他季节更显著;两流域之间冷极端指标的差异大于暖极端指标.总的来说,两流域的暖极端事件将更加严重.

Evaluation of CMIP5 Earth System Models in Reproducing Leaf Area Index and Vegetation Cover over the Tibetan Plateau

The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.

Future Changes in the Impact of North Pacific Midlatitude Oceanic Frontal Intensity on the Wintertime Storm Track in CMIP5 Models

The storm track and oceanic front play an important role in the midlatitude air–sea interaction.In this study,future changes in the impact of the North Pacific midlatitude oceanic frontal intensity on the wintertime storm track are projected based on climate model outputs from the Coupled Model Intercomparison Project Phase 5(CMIP5).The performance of 13 CMIP5 models is evaluated,and it is found that a majority of these models are capable of reproducing the northward intensification of the storm track in response to the strengthened oceanic front.The ensemble means of outputs from six best models under three Representative Concentration Pathway(RCP)scenarios(RCP2.6,RCP4.5,and RCP8.5)are compared with the results of the historical simulation,and future changes are projected.It is found that the impact of the oceanic frontal intensity on the storm track tends to get stronger and extends further westward in a warming climate,and the largest increase appears in the RCP8.5 run.Further analysis reveals that the stronger impact of the oceanic front on the storm track in the future may be partially attributed to the greater oceanic frontal impact on the near-surface baroclinicity,which is mainly related to the intensified oceanic frontal impact on the meridional potential temperature gradient under the climate change scenario.However,this process can hardly explain the increasing impact of the oceanic front on the upstream of the storm track.