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.

The Cloud Model for Climate Change

In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO2 was only 0.04%, making it too minuscule to measure reliably.

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

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.

Climate-change habitat shifts for the vulnerable endemic oak species(Quercus arkansana Sarg.)

Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near future is high,yet knowledge of its predicted effects is limited.Our study utilized the biomod2 R package to develop habi-tat suitability ensemble models based on bioclimatic and topographic environmental variables and the known loca-tions of current distribution of Q.arkansana.We predicted suitable habitats across three climate change scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)for 2050,2070,and 2090.Our findings reveal that the current suitable habitat for Q.arkansana is approximately 127,881 km^(2) across seven states(Texas,Arkansas,Alabama,Louisiana,Mississippi,Georgia,and Florida);approximately 9.5%is encompassed within state and federally managed protected areas.Our models predict that all current suitable habitats will disap-pear by 2050 due to climate change,resulting in a northward shift into new regions such as Tennessee and Kentucky.The large extent of suitable habitat outside protected areas sug-gests that a species-specific action plan incorporating pro-tected areas and other areas may be crucial for its conserva-tion.Moreover,protection of Q.arkansana habitat against climate change may require locally and regionally focused conservation policies,adaptive management strategies,and educational outreach among local people.

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model （DGVM） in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land Model- DGVM （CLM3.0-DGVM） with a submodel for temperate and boreal shrubs, as well as other revisions such as the ＂two-leaf＂ scheme for photosynthesis and the definition of fractional coverage of plant functional types （PFTs）. Results show that the revised model may correctly reproduce the global distribution of temperate and boreal shrubs, and improves the model performance with more realistic distribution of di？erent vege- tation types. The revised model also correctly reproduces the zonal distributions of vegetation types. In reproducing the dependence of the vegetation distribution on climate conditions, the model shows that the dominant regions for trees, grasses, shrubs, and bare soil are clearly separated by a climate index derived from mean annual precipitation and temperature, in good agreement with the CLM4 surface data. The dominant plant functional type mapping to a two dimensional parameter space of mean annual temperature and precipitation also qualitatively agrees with the results from observations and theoretical ecology studies.

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.

Multi-model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part I: Precipitation

Potential changes in precipitation extremes in July–August over China in response to CO 2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and the 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. Evaluation of the models’ performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50%. The spread among the models over the Tibetan Plateau is ～2–3 times larger than that over the other areas. Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the 1pctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China, which follows the Clausius–Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.

Multi-Model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part II: Temperature

This is the second part of the authors’ analysis on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. The study focuses on the potential changes of July–August temperature extremes over China. The pattern correlation coefficients of the simulated temperature with the observations are 0.6–0.9, which are higher than the results for precipitation. However, most models have cold bias compared to observation, with a larger cold bias over western China （5°C） than over eastern China （2°C）. The multi-model ensemble （MME） exhibits a significant increase of temperature under the 1pctto2x scenario. The amplitude of the MME warming shows a northwest–southeast decreasing gradient. The warming spread among the models （～1°C– 2°C） is less than MME warming （～2°C–4°C）, indicating a relatively robust temperature change under CO 2 doubling. Further analysis of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） simulations suggests that the warming pattern may be related to heat transport by summer monsoons. The contrast of cloud effects also has contributions. The different vertical structures of warming over northwestern China and southeastern China may be attributed to the different natures of vertical circulations. The deep, moist convection over southeastern China is an effective mechanism for ＂transporting＂ the warming upward, leading to more upper-level warming. In northwestern China, the warming is more surface-orientated, possibly due to the shallow, dry convection.

Global pattern and change of cropland soil organic carbon during 1901-2010: Roles of climate, atmospheric chemistry, land use and management

Soil organic carbon(SOC)in croplands is a key property of soil quality for ensuring food security and agricultural sustainability,and also plays a central role in the global carbon(C)budget.When managed sustainably,soils may play a critical role in mitigating climate change by sequestering C and decreasing greenhouse gas emissions into the atmosphere.However,the magnitude and spatio-temporal patterns of global cropland SOC are far from well constrained due to high land surface heterogeneity,complicated mechanisms,and multiple influencing factors.Here,we use a process-based agroecosystem model(DLEM-Ag)in combination with diverse spatially-explicit gridded environmental data to quantify the long-term trend of SOC storage in global cropland area during 1901-2010 and identify the relative impacts of climate change,elevated CO2,nitrogen deposition,land cover change,and land management practices such as nitrogen fertilizer use and irrigation.Model results show that the total SOC and SOC density in the 2000s increased by 125%and 48.8%,respectively,compared to the early 20th century.This SOC increase was primarily attributed to cropland expansion and nitrogen fertilizer use.Factorial analysis suggests that climate change reduced approximately 3.2%(or 2,166 Tg C)of the total SOC over the past 110 years.Our results indicate that croplands have a large potential to sequester C through implementing better land use management practices,which may partially offset SOC loss caused by climate change.

Assessing the Impacts of Eurasian Snow Conditions on Climate Predictability with a Global Climate Model

On the basis of two ensemble experiments conducted by a general atmospheric circulation model(Institute of Atmospheric Physics nine-level atmospheric general circulation model coupled with land surface model,hereinafter referred to as IAP9L_CoLM),the impacts of realistic Eurasian snow conditions on summer climate predictability were investigated.The predictive skill of sea level pressures(SLP)and middle and upper tropospheric geopotential heights at mid-high latitudes of Eurasia was enhanced when improved Eurasian snow conditions were introduced into the model.Furthermore,the model skill in reproducing the interannual variation and spatial distribution of the surface air temperature(SAT)anomalies over China was improved by applying realistic(prescribed)Eurasian snow conditions.The predictive skill of the summer precipitation in China was low;however,when realistic snow conditions were employed,the predictability increased,illustrating the effectiveness of the application of realistic Eurasian snow conditions.Overall,the results of the present study suggested that Eurasian snow conditions have a significant effect on dynamical seasonal prediction in China.When Eurasian snow conditions in the global climate model(GCM)can be more realistically represented,the predictability of summer climate over China increases.

Unrealistic treatment of detrained water substance in FGOALS-s2 and its influence on the model's climate sensitivity

Based on a series of aqua-planet and air–sea coupled experiments,the influence of unrealistic treatment of water substance in the Flexible Global Ocean–Atmosphere–Land System Model,spectral version 2（FGOALS-s2）,on the model＇s climate sensitivity is investigated in this paper.Because the model does not adopt an explicit microphysics scheme,the detrained water substance from the convection scheme is converted back to the humidity.This procedure could lead to an additional increase of water vapor in the atmosphere,which could strengthen the model＇s climate sensitivity.Further sensitivity experiments confirm this deduction.After removing the water vapor converted from the detrained water substance,the water vapor reduced significantly in the upper troposphere and the high clouds also reduced.Quantitative calculations show that the water vapor reduced almost 10% of the total water vapor,and 50% at 150 h Pa,when the detrained water substance was removed,contributing to the 30% atmospheric surface temperature increase.This study calls for an explicit microphysics scheme to be introduced into the model in order to handle the detrained water vapor and thus improve the model＇s simulation skill.

Economic Implications of Avoiding Dangerous Climate Change： An Analysis Using the AIM/CGE [Global] Model

The purpose of this study is to analyze economic impacts of reducing greenhouse gases emissions significantly. A large amount of emissions reductions are required throughout this century to avoid dangerous climate change, and understanding the economic consequences under such situations is important and meaningful. The AIM/CGE [Global] model, a recursive dynamic computable general equilibrium model on a global scale, is applied to analyze carbon prices and changes in GDP when implementing five policy scenarios represented by emissions pathways, respectively. As a result of the analysis, higher carbon prices and larger decreases in GDP compared to the baseline emissions scenario are observed when emissions are reduced more deeply. However, such GDP losses are rather small and insignificant compared to the GDP growth observed throughout the century. These results suggest that although it is challenging to reduce emissions until the level to avoid dangerous climate change, there is a sufficient possibility to achieve it from economic perspectives.

Evaluating effects of atmospheric CO_2 on stability of global climate:a cell-to-cell mapping approach

Atmospheric carbon dioxide concentration [CO2],incoming solar radiation and sea ice coverage are among the most important factors that control the global climate.By applying the simple cell-to-cell mapping technique to a simplified atmosphere-ocean-sea ice feedback climate model,effects of these factors on the stability of the climatic system are studied.The current climatic system is found to be stable but highly nonlinear.The resiliency of stability increases with [CO2] to a summit when [CO2] reaches 290 μL/L which is comparable to the pre-industrial level,suggesting carbon dioxide is essential to the stability of the global climate.With [CO2] rising further,the global climate stability decreases,the mean ocean temperature goes up and the sea ice coverage shrinks in the polar region.When the incoming solar radiation is intensified,the ice coverage gradually diminishes,but the mean ocean temperature remains relatively constant.Overall,our analysis suggests that at the current levels of three external factors the stability of global climate is highly resilient.However,there exists a possibility of extreme states of climate,such as a snow-ball earth and an ice-free earth.

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation(NPP) to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model(CanESM2) of the Canadian Centre for Climate Modelling and Analysis(CCCma), which are part of the phase 5 of the Coupled Model Intercomparison Project(CMIP5). The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m–2 yr–1 and –0.14 gC m–2 yr–2, respectively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at –1.79 gC m–2 yr–2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m–2 yr–1 and 0.84 gC m–2 yr–2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m–2 yr–1 and 0.83 gC m–2 yr–2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of –0.39 kg m–2 yr–1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration(experiment M2), and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-0.16 gC m-2 yr-2.

Climate Projections and Uncertainties over South America from MRI/JMA Global Model Experiments

This paper analyses the climate change projected for the near and distant future in South America using MRI/JMA (Japanese Meteorological Agency) global model simulations with resolutions of 20 and 60 km. Changes in mean climate, as well as in the annual cycles and interannual variability of temperature and precipitation are discussed. An analysis is also made of the uncertainties of the 60 km resolution model experiments. For the near and distant future, both, the 20 km and 60 km resolution MRI/JMA models project that temperature changes will be positive in all seasons. The greatest values of change are over the Andes and over tropical and subtropical latitudes of the study region. In all the subregions analysed, the 20 km model projects greater changes in the annual cycle of mean temperature than the 60 km model. Changes in summer precipitation are positive over most of the continent, except for southern Chile. Autumn precipitation is projected to increase over northern Argentina and north-western South America and to decrease over central Chile in winter, which might be due to the southward shift of the Pacific storm-track. The most significant positive change in Southeastern South America (SESA) is projected to occur in spring precipitation. In general, projected changes in the annual cycle are greater in the rainy seasons of each subregion. No significant changes are expected in the interannual variability of temperature and precipitation. La Plata basin is projected to experience increased runoff, which would indicate that the projected rise in precipitation would have stronger effect than projected warming. The analysis of climate projection uncertainties revealed that temperature projections are more reliable than precipitation projections;and that uncertainty in near future simulations is greater than in simulations of the end of the century.

Climate Change in La Plata Basin as Seen by a High-Resolution Global Model

This paper analyses the climate change in La Plata Basin, one of the most important regions in South America due to its economy and population. For this work it has been used the Meteorological Research Institute (MRI) and the Japanese Meteorological Agency (JMA) atmospheric global model. For both near and far future, the projected changes for temperature over the entire basin were positive, although they were only statistically significant at the end of the XXI century. Changes in the annual cycle of mean temperature were also positive in all subregions of the basin. Regarding precipitation, there were no changes in the near future that were statistically significant. The summer (winter) is the only season where both models project positive (negative) changes for both periods of the future. In the transitional seasons these changes vary depending on the spatial resolution model and the area of study. The annual cycle showed that the largest changes in precipitation (positive or negative) coincide with the rainy season of each subregion. Regarding the interannual variability of temperature, it was found that the 20 km. model pro-jected a decrease of this variability for both near and far future, especially in summer and autumn. On the other hand, the 60 km. ensemble model showed a decreased of year-to-year variability for summer and an increase in winter and spring. It was also found that both models project an increase in precipitation variability for winter and summer, while in other seasons, only the 60 km. ensemble model presents the mentioned behavior.

Prediction of Climate Change in the 21^(st) Century in Dalian Area under the Various Emission Scenarios

By using the simulative results of more than 20 climate system models which were provided by the fourth assessment report of the Intergovernmental Panel on Climate Change(IPCC),the climate change in Dalian area in the 21st century under the different scenarios(SRES A2,SRES A1B and SRES B1) were analyzed and predicted with the multi-model's aggregative simulative results via the interpolation downscaling calculation.The results showed that the climate in Dalian would have the obvious warming and wetting tendency in the 21st century as a whole.The annual average warming tendency of air temperature would be 2.45-3.46 ℃/100 years,and the annual precipitation increase trend would be 5.8%-16.3% per 100 years.The warming in winter would be the most obvious,and the precipitation increase would be comparatively obvious in winter and spring.The precipitation decrease would be comparatively obvious in autumn in the previous period of 21st century.In A2,A1B and B1 scenarios,the air temperatures in the late period of 21st century would respectively be 3.46,3.44 and 2.45 ℃ higher than in the ordinary years,and the annual precipitation would respectively be 16.3%,11.8% and 5.79% more than in the ordinary years.

1979-2022年北极海冰变化及影响因素分析

海冰是海洋-大气交互系统的重要组成部分,是全球气候变化的指示器。深入分析海冰演变规律,探索全球气候变化与海冰范围之间的关联,对应对和减缓全球气候变化具有重要的理论意义。本文以北极海冰为研究对象,深入分析了1979-2022年北极海冰范围的季节、年际和年代际变化特征,并构建向量自回归模型(Vector AutoRegressive Model,VAR)检验全球平均气温、大气CO_(2)浓度与北极海冰范围之间的因果关系,并分析影响程度。结果表明:(1)北极海冰范围季节变化特征明显,一般在3月达到最大,9月达到最小,这主要与太阳辐射的年变化周期相关;(2)1979-2022年,北极海冰范围总体呈减小趋势,年变化量为5.3万km^(2);(3)北极海冰范围在年代际尺度上逐渐减小,2000-2009年,北极海冰范围较上一个十年减小最多(减少67万km^(2));(4)全球平均气温和大气CO_(2)浓度均对北极海冰范围变化造成了显著影响;(5)全球平均气温和大气CO_(2)浓度与北极海冰范围均有显著负相关关系,相关系数分别为-0.92和-0.95。

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.