Zoning Evaluation of Hourly Precipitation in High-resolution Regional Numerical Models over Hainan Island

This study assesses the performance of three high-resolution regional numerical models in predicting hourly rainfall over Hainan Island from April to October for the years from 2020 to 2022.The rainfall amount,frequency,intensity,duration,and diurnal cycle are examined through zoning evaluation.The results show that the China Meteor-ological Administration Guangdong Rapid Update Assimilation Numerical Forecast System(CMA-GD)tends to forecast a higher occurrence of light precipitation.It underestimates the late afternoon precipitation and the occurrence of short-duration events.The China Meteorological Administration Shanghai Numerical Forecast Model System(CMA-SH9)reproduces excessive precipitation at a higher frequency and intensity throughout the island.It overestimates rainfall during the late afternoon and midnight periods.The simulated most frequent peak times of rainfall in CMA-SH9 are 0-1 hour deviations from the observed data.The China Meteorological Administration Mesoscale Weather Numerical Forecasting System(CMA-MESO)displays a similar pattern to rainfall observations but fails to replicate reasonable structure and diurnal variation of frequency-intensity.It underestimates the occurrence of long-duration events and overestimates related rainfall amounts from midnight to early morning.Notably,significant discrepancies are observed in the predictions of the three models for areas with complex terrain,such as the central,southeastern,and southwestern regions of Hainan Island.

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.

Models of Spatial Structures of Regional Multi-element Geochemical Anomalies over Copper-Polymetallic Orefields

Regional stream sediment surveys at a 1:200,000 scale reveal positive andnegative regional multi-element geochemical anomalies over medium to large copper-polymetallicorefields of different genetic types in China. Regional geochemical anomalies of orefield refer tothose geochemical anomalies that are related to metallogenesis of an orefield in a certain area. Theanomaly area is typically 10 to 100 km^2. The regional multi-element anomalies related tomineralization can be divided into three groups, that is, the ore-element anomaly association,indicator element anomaly association, and metallogenic environmental element anomaly association.Their common spatial distributions over ore deposits or orefields possess unique structures. Themodel of spatial structure of regional multi-element geochemical anomalies (RAGSS) of an orefielddelineates structural feature possessed by orderly spatial distributions of different groups ofmulti-element anomaly associations related to orefield metallogenesis. It is used to outline thecommon metallogenetic anomaly visage that is composed of the orderly spatial distribution ofdifferent groups of multi-element anomaly associations. The orderly spatial distribution ofmulti-element anomalies over an orefield reflects element distributions as they are changed from adispersed 'out-of-order' state into a concentrated 'orderly' state during the mineralization of anorefield. Three different patterns of the spatial anomaly structure related to mineralization in anorefield can be concluded: (1) nested pattern; (2) eccentric pattern and; (3) peripheral pattern.There are marked differences between multi-element anomaly patterns related and not related tomineralization. RAGSS models of orefields can be used to better understand and evaluate regionalmulti-element anomalies and identify ore types.

GPS-based regional ionospheric models and their suitability in Antarctica

There are a number of ionospheric models available for research and application, such as the polynomial model, generalized trigonometric series function model, low degree spherical harmonic function model, adjusted spherical harmonic function model, and spherical cap harmonic function analysis. Using observations from more than 40 continuously operating stations across Antarctica in 2010, ifve models are compared with regard to their precision and applicability to polar regions. The results show that all the models perform well in Antarctica with 0.1 TECU of residual mean value and 2 TECU of root mean square error.

Advance in Application of Regional Climate Models in China

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

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

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

A Hybrid Regional Model for Predicting Ground Deformation Induced by Large-Section Tunnel Excavation

Due to the large number of finite element mesh generated,it is difficult to use full-scale model to simulate largesection underground engineering,especially considering the coupling effect.A regional model is attempted to achieve this simulation.A variable boundary condition method for hybrid regional model is proposed to realize the numerical simulation of large-section tunnel construction.Accordingly,the balance of initial ground stress under asymmetric boundary conditions achieves by applying boundary conditions step by step with secondary development ofDynaflowscripts,which is the key issue of variable boundary conditionmethod implementation.In this paper,Gongbei tunnel based on hybrid regional model involvingmulti-field coupling is simulated.Meanwhile,the variable boundary condition method for regional model is verified against model initialization and the ground deformation due to tunnel excavation is predicted via the proposed hybrid regional model.Compared with the monitoring data of actual engineering,the results indicated that the hybrid regional model has a good prediction effect.

Study of the geomagnetic field's regional gradients in Chinese continent using three-dimensional surface Spline model

We combined domestic ground-based and satellite magnetic measurements to create a regional three-dimensional surface Spline(3DSS)gradient model of the main geomagnetic field over the Chinese continent.To improve the precision of the model,we considered the data gap between the ground and satellite data.We compared and analyzed the results of the Taylor polynomial,surface Spline,and CHAOS-6(the CHAMP,?rsted and SAC-C model of Earth’s magnetic field)gradient models.Results showed that the gradients in the south-north and east-west directions of the four models were consistent.The 3DSS model was able to express not only gradients at different altitudes,but also average gradients inside the research area.The two Spline models were able to capture more information on gradient anomalies than were the fitted models.Strong local anomalies were observed in northern Xinjiang,Beijing,and the junction area between Jiangsu and Zhejiang,and the total intensity F decreased whereas the altitude increased.The gradient decreased by 21.69%in the south-north direction and increased by 11.78%in the east-west direction.In addition,the altitude gradient turned from negative to positive while the altitude increased.The Spline model and the two fitted models differed mainly in the field sources they expressed and the modeling theory.

Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

Regional Finite-Fault Source Model for Development of Ground Motion Attenuation Relationship in Sichuan, China

The attenuation relationship of ground motion based on seismology has always been a front subject of engineering earthquake.Among them,the regional finite-fault source model is very important.In view of this point,the general characteristics of regional seism-tectonics,including the dip and depth of the fault plane,are emphasized.According to the statistics of regional seism-tectonics and focal mechanisms in Sichuan,China,and the sensitivity of estimated peak ground acceleration(PGA)attenuation is analyzed,and the dip angle is taken as an average of 70°.Based the statistics of the upper crustal structure and the focal depth of regional earthquakes,the bottom boundary of the sedimentary cover can be used as the upper limit for estimating the depth of upper-edge.The analysis shows that this value is sensitive to PGA.Based on the analysis of geometric relations,the corresponding calculation formula is used,and a set of concepts and steps for building the regional finite-fault source model is proposed.The estimation of source parameters takes into account the uncertainty,the geometric relationship among parameters and the total energy conservation.Meanwhile,a set of reasonable models is developed,which lay a foundation for the further study of regional ground motion attenuation based on seismology.

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.

Identification of thermal front dynamics in the northern Malacca Strait using ROMS 3D-model

The thermal front in the oceanic system is believed to have a significant effect on biological activity.During an era of climate change,changes in heat regulation between the atmosphere and oceanic interior can alter the characteristics of this important feature.Using the simulation results of the 3D Regional Ocean Modelling System(ROMS),we identified the location of thermal fronts and determined their dynamic variability in the area between the southern Andaman Sea and northern Malacca Strait.The Single Image Edge Detection(SIED)algorithm was used to detect the thermal front from model-derived temperature.Results show that a thermal front occurred every year from 2002 to 2012 with the temperature gradient at the location of the front was 0.3°C/km.Compared to the years affected by El Ni?o and negative Indian Ocean Dipole(IOD),the normal years(e.g.,May 2003)show the presence of the thermal front at every selected depth(10,25,50,and 75 m),whereas El Ni?o and negative IOD during 2010 show the presence of the thermal front only at depth of 75 m due to greater warming,leading to the thermocline deepening and enhanced stratification.During May 2003,the thermal front was separated by cooler SST in the southern Andaman Sea and warmer SST in the northern Malacca Strait.The higher SST in the northern Malacca Strait was believed due to the besieged Malacca Strait,which trapped the heat and make it difficult to release while higher chlorophyll a in Malacca Strait is due to the freshwater conduit from nearby rivers(Klang,Langat,Perak,and Selangor).Furthermore,compared to the southern Andaman Sea,the chlorophyll a in the northern Malacca Strait is easier to reach the surface area due to the shallower thermocline,which allows nutrients in the area to reach the surface faster.

Spatiotemporal characteristics of water exchange between the Andaman Sea and the Bay of Bengal

A high-resolution customized numerical model is used to analyze the water transport in the three major water passages between the Andaman Sea(AS)and the Bay of Bengal,i.e.,the Preparis Channel(PC),the Ten Degree Channel(TDC),and the Great Channel(GC),based on the daily averaged simulation results ranging from 2010 to 2019.Spectral analysis and Empirical Orthogonal Function(EOF)methods are employed to investigate the spatiotemporal variability of the water exchange and controlling mechanisms.The results of model simulation indicate that the net average transports of the PC and GC,as well as their linear trend,are opposite to that of the TDC.This indicates that the PC and the GC are the main inflow channels of the AS,while the TDC is the main outflow channel of the AS.The transport variability is most pronounced at surface levels and between 100 m and 200 m depth,likely affected by monsoons and circulation.A 182.4-d semiannual variability is consistently seen in all three channels,which is also evident in their second principal components.Based on sea level anomalies and EOF analysis results,this is primarily due to equatorial winds during the monsoon transition period,causing eastward movement of Kelvin waves along the AS coast,thereby affecting the spatiotemporal characteristics of the flow in the AS.The first EOF of the PC flow field section shows a split at 100 m deep,likely due to topography.The first EOF of the TDC flow field section is steady but has potent seasonal oscillations in its time series.Meanwhile,the first EOF of the GC flow field section indicates a stable surface inflow,probably influenced by the equatorial Indian Ocean’s eastward current.

A regional suspended load yield estimation model for ungauged watersheds

Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.

Seasonal Prediction of Indian Summer Monsoon Using WRF: A Dynamical Downscaling Perspective

Seasonal forecasting of the Indian summer monsoon by dynamically downscaling the CFSv2 output using a high resolution WRF model over the hindcast period of 1982-2008 has been performed in this study. The April start ensemble mean of the CFSv2 has been used to provide the initial and lateral boundary conditions for driving the WRF. The WRF model is integrated from 1st May through 1st October for each monsoon season. The analysis suggests that the WRF exhibits potential skill in improving the rainfall skill as well as the seasonal pattern and minimizes the meteorological errors as compared to the parent CFSv2 model. The rainfall pattern is simulated quite closer to the observation (IMD) in the WRF model over CFSv2 especially over the significant rainfall regions of India such as the Western Ghats and the central India. Probability distributions of the rainfall show that the rainfall is improved with the WRF. However, the WRF simulates copious amounts of rainfall over the eastern coast of India. Surface and upper air meteorological parameters show that the WRF model improves the simulation of the lower level and upper-level winds, MSLP, CAPE and PBL height. The specific humidity profiles show substantial improvement along the vertical column of the atmosphere which can be directly related to the net precipitable water. The CFSv2 underestimates the specific humidity along the vertical which is corrected by the WRF model. Over the Bay of Bengal, the WRF model overestimates the CAPE and specific humidity which may be attributed to the copious amount of rainfall along the eastern coast of India. Residual heating profiles also show that the WRF improves the thermodynamics of the atmosphere over 700 hPa and 400 hPa levels which helps in improving the rainfall simulation. Improvement in the land surface fluxes is also witnessed in the WRF model.

Changes of Extreme Events in Regional Climate Simulations over East Asia

Changes of extreme events due to greenhouse effects (2 × CO2) over East Asia, with a focus on the China region as simulated by a regional climate model (RegCM2), are investigated. The model is nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM). Analysis of the control run of the regional model indicates that it can reproduce well the extreme events in China. Statistically significant changes of the events are analyzed. Results show that both daily maximum and daily minimum temperature increase in 2 × CO2 conditions, while the diurnal temperature range decreases. The number of hot spell days increases while the number of cold spell days decreases. The number of rainy days and heavy rain days increases over some sub-regions of China. The 2 × CO2 conditions also cause some changes in the tropical storms affecting China.

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.

Simulation of Effects of Land Use Change on Climate in China by a Regional Climate Model

Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.

Climate Change due to Greenhouse Effects in China as Simulated by a Regional Climate Model

Impacts of greenhouse effects (2 × CO2) upon climate change over China as simulated by a regional climate model over China (RegCM / China) have been investigated. The model was based on RegCM2 and was nested to a global coupled ocean-atmosphere model (CSIRO R21L9 AOGCM model). Results of the control run (1 × CO2) indicated that simulations of surface air temperature and precipitation in China by RegCM are much better than that by the global coupled model because of a higher resolution. Results of sensitive experiment by RegCM with 2 × CO2 showed that the surface air temperature over China might increase remarkably due to greenhouse effect, especially in winter season and in North China. Precipitation might also increase in most parts of China due to the CO2 doubling. Key words Regional climate model - Greenhouse effect This research was supported by National Key Programme for Developing Basic Sciences (G1998040900 — Part I), Chinese Academy of Sciences Key Program KZCX2-203 and KZ981-B1-108.