Litterfall production modeling based on climatic variables and nutrient return from stands of Eucalyptus grandis Hill ex Maiden and Pinus taeda L.

Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.

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.

Hydrological Modelling of the Casamance River in Its Upstream Section (Basin at Kolda Level) to Predict Its Future States as a Function of Different Stresses

Flow records for stations in the Casamance basin are incomplete. Several gaps were noted over the 1980-2021 study period, making this study tedious. The aim of this study is to assess the potential impact of climate change on the flow of the Casamance watershed at Kolda. To this end, hydrological series are simulated and then extended using the GR2M rainfall-runoff model, with a monthly time step. Projected climate data are derived from a multi-model ensemble under scenarios SSP2-4.5 (scenario with additional radiative forcing of 4.5 W/m2 by 2099) and SSP5-8.5 (scenario with additional radiative forcing of 8.5 W/m2 by 2099). An analysis of the homogeneity of the rainfall data series from the Kolda station was carried out using KhronoStat software. The Casamance watershed was then delimited using ArcGIS to determine the morphometric parameters of the basin, which will be decisive for the rest of the work. Next, monthly evapotranspiration was calculated using the formula proposed by Oudin et al. This, together with rainfall and runoff, forms the input data for the model. The GR2M model was then calibrated and cross-validated using various simulations to assess its performance and robustness in the Casamance watershed. The version of the model with the calibrated parameters will make it possible to extend Casamance river flows to 2099. This simulation of future flows with GR2M shows a decrease in the flow of the Casamance at Kolda with the two scenarios SSP2-4.5 and SSP5-8.5 during the rainy period, and almost zero flows during the dry season from the period 2040-2059.

Nucleation of Supercooled Water by Neutrons: Latitude Dependence and Implications for Cloud Modelling

It has recently been shown that incident particles, neutrons, can initiate the freezing in a supercooled water volume. This new finding may have ramifications for the interpretation of both experimental data on the nucleation of laboratory samples of supercooled water and perhaps more importantly on the interpretation of ice nucleation involved in cloud physics. For example, if some fraction of the cloud nucleation previously attributed to dust, soot, or aerosols has been caused by cosmogenic neutrons, fresh consideration is required in the context of climate models. Moreover, as cosmogenic neutrons, most being muon-induced, have much greater flux at high latitudes, estimates of ice nucleates in these regions may be larger than required to accurately model cloud and condensation properties. This discrepancy has been pointed out in IPCC reports. Our paper discusses the connection between the new concept of neutrons nucleating supercooled water and the need for a new source of nucleation in high latitude clouds, ideally causing others to review current data, or to analyse future data with this idea in mind. .

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.

Numerical Modelings of the Climatic Effects of the Land-Sea Distribution and Topography

The effects of the land-sea contrast and the topography on the climatic properties are simulated rn this paper by use of a p- a incorporated coordinate system mode! in a zonal domain.In this paper we firstly discuss the statistical features of the model and find that the capability of the model is stable,with the same land-sea distribution and topography seven monthly mean climate states are close to one another,their variance is even less than the initial one.Secondly,we focally discuss the effects of the land-sea contrast and the topography on the modeled climate fields.It is pointed out that the land-sea contrast and the topography influence the atmosphere mainly through the heating ef-fect and the former has larger influences on the simulated large scale climate fields than the latter.

Antarctic Sea Ice Concentration in the Brazilian Earth System Model Simulations

Sea ice is an important and complex component of the Earth’s system, acting as both an indicator and an amplifier of climate change. Here, we investigated the ability of the Brazilian Earth System Model (BESM-OA2.5) and four state-of-the-art climate models participating in the fifth phase of the Coupled Model Intercomparison Project, Version 5 (CMIP5) to represent the Antarctic Sea Ice Concentration (SIC) seasonal cycle. We validated the sea ice model’s performance using satellite data from 1980 to 2005 and calculated the skill and RMSE of each model. BESM-OA2.5 results for melt-freeze transitions in the Southern Ocean are consistent with CMIP5 models and satellite data. In February, when the sea ice reaches its annual minimum, the BESM-OA2.5 has the best fit among the models. However, in September, when the Antarctic sea ice reaches its annual maximum, the SIC simulated by BESM-OA2.5 indicated the largest area covered by ice compared to satellite, particularly on the Polar Front. Similar results were found in the CMIP5 models evaluated here. We suggest that the large bias simulated in the Polar Front is related to the inability of the sea ice model to represent the complex ocean-atmosphere-sea ice interactions. The subject is considered a hot topic in climate change studies and lacks conclusive answers.

Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau(TP)cause considerable damage to local society and natural ecosystems.In this study,the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model,RegCM4.The model is driven by five CMIP5 global climate models at a grid spacing of 25 km,under the RCP4.5 and RCP8.5 pathways.Four modified ETCCDI extreme indices-namely,SNOWTOT,S1mm,S10mm,and Sx5day-are employed to characterize the extreme snowfall events.RegCM4 generally reproduces the spatial distribution of the indices over the region,although with a tendency of overestimation.For the projected changes,a general decrease in SNOWTOT is found over most of the TP,with greater magnitude and better cross-simulation agreement over the eastern part.All the simulations project an overall decrease in S1mm,ranging from a 25%decrease in the west and to a 50%decrease in the east of the TP.Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP.Notably,S10mm shows a marked increase(more than double)with high cross-simulation agreement over the central TP.Significant increases in all four indices are found over the Tarim and Qaidam basins,and northwestern China north of the TP.The projected changes show topographic dependence over the TP in the latitudinal direction,and tend to decrease/increase in low-/high-altitude areas.

The Decade-Scale Climatic Forecasting in China

Described is a new technique of decade-scale climatic forecasting, presented by a combination of wavelet analysis and stochastic dynamics. The technique is also applied to diagnosing and forecasting the duration time of dry and wet climates in the decadal hierarchy of different areas in China. Results show that in the decadal hierarchy, the north, southwest, and southeast of China are areas where various kinds of frequent climate disasters appear; droughts easily occur in the north and northwest, while floods often occur in South China. Because this modeling technique is based on time series data, it can also be applied in the modeling and forecasting of such time series as hydrology, earthquakes and ecology.

Historical and Future Climatic Change Scenarios for Temperature and Rainfall for Iraq

The world is facing a big challenge of climatic change, mainly due to increasing concentrations of GHGs （greenhouse gases） in the atmosphere. Many researches indicated that the climate change occurred disproportionately on developing countries such as MENA （Middle East and North Africa） countries. The climatic model CGCM3.1 （T47） 2 is used in this research to explain the changes in average temperatures and the rainfall on the MENA region with special emphases on Iraq. Historical records （1900-2009） and future （2020-2099） were studied and compared; each period was divided to four sub-periods of thirty years. The results showed that the average monthly temperature for the four historical periods fluctuated between the lowest and highest value as follows： 9.2-32.9, 10.3-32.7, 9.3-32.8 and 8.6-33.9 （℃）. The rainfall for historical periods kept on the same distribution during the past 109 years, and fluctuated between the lowest and highest value of 21.3 mm and 37.6 mm with an average that reached up to 26.51 mm. For the future period, the maximum average monthly temperature reached up to 37.41 （℃） during June and minimum average monthly temperature reached up to 4.24 （℃） during January. The average monthly temperature fluctuated giving a clear impression that the future portends a higher temperature. The average monthly rainfall, for the future period, fluctuated between the lowest and highest value of 12.91 mm and 20.63 mm with an average that reached 16.84 mm which represent a reduction percentage of about 36.47% relative to the historical record of rainfall for the sanae months.

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

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.

Control of the Dust Vertical Distribution over Western Africa by Convection and Scavenging

Saharan dust represents more than 50%of the total desert dust emitted around the globe and its radiative effect significantly affects the atmospheric circulation at a continental scale.Previous studies on dust vertical distribution and the Saharan Air Layer(SAL)showed some shortcomings that could be attributed to imperfect representation of the effects of deep convection and scavenging.The authors investigate here the role of deep convective transport and scavenging on the vertical distribution of mineral dust over Western Africa.Using multi-year(2006-2010)simulations performed with the variable-resolution(zoomed)version of the LMDZ climate model.Simulations are compared with aerosol amounts recorded by the Aerosol Robotic Network(AERONET)and with vertical profiles of the Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP)measurements.LMDZ allows a thorough examination of the respective roles of deep convective transport,convective and stratiform scavenging,boundary layer transport,and advection processes on the vertical mineral dust distribution over Western Africa.The comparison of simulated dust Aerosol Optical Depth(AOD)and distribution with measurements suggest that scavenging in deep convection and subsequent re-evaporation of dusty rainfall in the lower troposphere are critical processes for explaining the vertical distribution of desert dust.These processes play a key role in maintaining a well-defined dust layer with a sharp transition at the top of the SAL and in establishing the seasonal cycle of dust distribution.This vertical distribution is further reshaped offshore in the Inter-Tropical Convergence Zone(ITCZ)over the Atlantic Ocean by marine boundary layer turbulent and convective transport and wet deposition at the surface.

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.

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC). Part Ⅰ: Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC) Part Ⅱ:The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.

Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model

in the latest version of the international Centre for Theoretical Physics＇ regional climate model, RegCM4, CLM was introduced as a new land surface scheme. The performance over China of RegCM4-CLM with different convection schemes is analyzed in this study, based on a series of short- term experiments.The model is driven by ERA-Interim data at a grid spacing of 25 km.The convection schemes employed are： Emanuel; Grell; Emanuel over land and Grell over ocean; Grell over land and Emanuel over ocean; and Tiedtke. The simulated mean surface air temperature and precipitation in December-February-January and June-July-August are compared against observation. In general, better performance of Emanuel is found both for temperature and precipitation, and in both seasons. Thus, the model physics of CLM and Emanuel for the land surface processes and convection, respectively, are recommended for further application of RegCM4 over the China region. The de^ciencies that remain in the model arealso outlined and discussed.

The Interannual Variability of East Asian Monsoon and Its Relationship with SST in a Coupled Atmosphere-Ocean-Land Climate Model

Based on a 200 year simulation and reanalysis data (1980–1996), the general characteristics of East Asian monsoon (EAM) were analyzed in the first part of the paper. It is clear from this re-search that the South Asian monsoon (SAM) defined by Webster and Yang (1992) is geographically and dynamically different from the East Asian monsoon (EAM). The region of the monsoon defined by Webster and Yang (1992) is located in the tropical region of Asia (40–110°E, 10–20°N), including the Indian monsoon and the Southeast Asian monsoon, while the EAM de-fined in this paper is located in the subtropical region of East Asia (110–125°E, 20–40°N). The components and the seasonal variations of the SAM and EAM are different and they characterize the tropical and subtropical Asian monsoon systems respectively. A suitable index (EAMI) for East Asian monsoon was then defined to describe the strength of EAM in this paper. In the second part of the paper, the interannual variability of EAM and its relationship with sea surface temperature (SST) in the 200 year simulation were studied by using the composite method, wavelet transformation, and the moving correlation coefficient method. The summer EAMI is negatively correlated with ENSO (El Nino and Southern Oscillation) cycle represented by the NINO3 sea surface temperature anomaly (SSTA) in the preceding April and January, while the winter EAM is closely correlated with the succeeding spring SST over the Pacific in the coupled model. The general differences of EAM between El Nino and La Nina cases were studied in the model through composite analysis. It was also revealed that the dominating time scales of EAM variability may change in the long-term variation and the strength may also change. The anoma-lous winter EAM may have some correlation with the succeeding summer EAM, but this relation-ship may disappear sometimes in the long-term climate variation. Such time-dependence was found in the relationship between EAM and SST in the long-term climate simulation as well. Key words East Asian monsoon - Interannual variability - Coupled climate model The author wishes to thank Profs. Wu G.X., Zhang X.H., and Dr. Yu Y.Q. for providing the coupled model re-sults. Dr. Yu also kindly provided assistance in using the model output. This work was supported jointly by the Na-tional Natural Science Foundation of China key project ’ The analysis on the seasonal-to-interannual variation of the general circulation’ under contract 49735160 and Chinese Academy of Sciences key project ’ The Interannual Va-riability and Predictability of East Asian Monsoon’.

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.