• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Performance of Convective Parameterization Schemes in Asia Using RegCM: Simulations in Three Typical Regions for the Period 1998–2002

    2015-02-24 06:22:05ShaukatALIDANLiFUCongbinandYANGYang
    Advances in Atmospheric Sciences 2015年5期

    Shaukat ALIDAN LiFU Congbinand YANG Yang

    1START Temperate East Asia Regional Center and Key Laboratory of Regional Climate-Environment for Temperate East Asia,

    Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing100029

    2University of Chinese Academy of Sciences,Beijing100049

    3Global Change Impact Studies Centre,Ministry of Climate Change,Islamabad,Pakistan

    Performance of Convective Parameterization Schemes in Asia Using RegCM: Simulations in Three Typical Regions for the Period 1998–2002

    Shaukat ALI1,2,3,DAN Li?1,FU Congbin1,and YANG Yang2

    1START Temperate East Asia Regional Center and Key Laboratory of Regional Climate-Environment for Temperate East Asia,

    Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing100029

    2University of Chinese Academy of Sciences,Beijing100049

    3Global Change Impact Studies Centre,Ministry of Climate Change,Islamabad,Pakistan

    This study discusses the sensitivity of convective parameterization schemes(CPSs)in the Regional Climate Model(version 4.3)(RegCM4.3)over East/South Asia.The simulations using different CPSs in RegCM are compared to discover a suitable scheme for this region,as the performance of different schemes is greatly in fl uenced by region and seasonality.Over SoutheastChinaandtheBayofBengal,theGrellschemeexhibitsthelowestRMSEsofsummerprecipitationcomparedtoobserved data.Moreover,the Emanuel over land and Grell over ocean(ELGO)scheme enhances the simulation,in comparison with any single CPS(Grell/Emanuel)over Western Ghats,Sri Lanka,and Southeast India.Over the Huang–Huai–Hai Plain (3H)and Tibetan Plateau(TP)regions of China,the Tiedtke scheme simulates the more reasonable summer precipitation with high correlation coef fi cient and comparable amplitude.Especially,it reproduces a minimum convective precipitation bias of 8 mm d-1and the lowest RMSEs throughout the year over East/South Asia.Furthermore,for seasonal variation of precipitation,the Tiedtke scheme results are closer to the observed data over the 3H and TP regions.However,none of the CPSs is able to simulate the seasonal variation over North Pakistan(NP).In comparison with previous research,the results of this study support the Grell scheme over South Asia.However,the Tiedtke scheme shows superiority for the 3H,TP and NP regions.The thicker PBL,less surface latent heat fl ux,the unique ability of deep convection and the entrainment process in the Tiedtke scheme are responsible for reducing the wet bias.

    regional climate models(RCM),RegCM4,Tiedtke scheme,convective parameterization scheme(CPS),topography,seasonality

    1. Introduction

    Efforts have been made in recent decades to develop and improve regional climate models(RCMs),but many problems remain;for example,the lateral boundary conditions (Liang et al.,2001;Wu et al.,2005),horizontal resolution, size match of a region(Vannitsem and Chom′e,2005;Xue et al.,2007;Liu et al.,2010),and the parameterization schemes of unique physical processes(Cha et al.,2008;Yhang and Hong,2008).Moreover,the selection of an appropriate convective parameterization scheme(CPS)in RCMs is a major source of error and has signi fi cant impact on regional climate model predictions(Pal et al.,2007).The Regional Climate Model Intercomparison Project(RMIP)for Asia concluded that the simulations of RCMs are highly sensitive to CPSchoices(Fu et al.,2005).Generally,no single CPS can perform well universally for all atmospheric systems because, for instance,the processes of convection in the tropics can be signi fi cantly different from those in the midlatitudes(Wang and Seaman,1997;Singh et al.,2006;Chow and Chan, 2010).Manystudieshavebeenconductedindifferentregions to validate the sensitivity of CPSs,e.g.,America(Gochis et al.,2002;Liang et al.,2007),Europe(Wang and Seaman, 1997;Zanis et al.,2009),Africa(Davis et al.,2009;Segele et al.,2009;Tchotchou and Kamga,2010),the Caribbean region(Mart′?nez-Castro et al.,2013),the Maritime Continent (Gianotti et al.,2012),and South and East Asia(Dash et al., 2006;Chow and Chan,2010;Singh et al.,2011;Sinha et al., 2014).

    Wang and Seaman(1997)reported inconclusive results when they compared four CPSs,with no single scheme emerging as the best.The Regional Climate Model(RegCM) with a horizontal resolution of 55 km was used by Dash et al.(2006)for a four-year simulation(1993–96),and the results showed that the Grell scheme performed better for simulating the summer precipitation over India.Using the Anthes–KuoschemeinRegCMproducedcomparableresultsforareaaveraged precipitation over the Caribbean(Mart′?nez-Castro et al.,2013).Singh et al.(2006)statistically analyzed the climate over East Asia.Their results indicated that the Emanuel and Grell schemes minimize the biases and performs well over this region,especially Korea,but that issues of overestimation still remain.Liang et al.(2007)simulated the summer precipitation over the U.S.and Mexico using an ensemble of the Grell and Kain–Fritschl cumulus schemes.This approach produced far superior performance and considerable improvement was achieved compared to each individual scheme over the entire study domain.RegCM was customized with the Emanuel scheme for precipitation simulation by Davis et al.(2009).This model con fi guration predicted the rainfall over eastern Africa and the tropical Indian Ocean more realistically,but overestimation of precipitation also occurred.Segele et al.(2009)concluded that the Emanuel scheme performs better when selecting 1984 as a dry year and 1996 as a wet year.Octaviani and Manomaiphiboon(2011)demonstratedthattheEmanuelschemeperforms well,followed by the Anthes–Kuo scheme,when a doublenested 60 and 20 km resolution domain is used.According to Basit et al.(2012),the Grell scheme captures well the monsoon phenomenon,especially for the mountainous regions of North Pakistan,with the Arakawa–Schubert(AS) and Fritsch–Chappell(FC)closures both performing satisfactorily.Huang et al.(2013)simulated the diurnal variation of rainfall over Southeast China during 1998–2002,and reported better results when using the Grell scheme;whereas, the simulation of summer mean rainfall over East Asia was more realistically simulated using the Emanuel scheme.The CPSs play an important role in the simulation of summer precipitation in monsoon regions and the performances of CPSs have numerous uncertainties(Lee et al.,2008;Bao,2013).

    Table 1 provides a list of recent RegCM recent studies on CPSs over East,South,and Southeast Asia.Most of the studieswerebasedonmodelsimulationsof1–5years(Dashetal., 2006;Singh et al.,2006;Im et al.,2008a;Basit et al.,2012), but with some based on 10 years or more(Cao et al.,2007; Im et al.,2008b).Horizontal resolutions of 50 km or more have been used in several studies(Dash et al.,2006;Rahman et al.,2007a,2007b;Liu and Ding,2007;Chow and Chan, 2010;Huang et al.,2013;Bao,2013).However,few studies have also used a resolution of less than 50 km(Singh et al., 2006;Gianotti et al.,2012)in a nested domain setup(Im et al.,2008a;Octaviani and Manomaiphiboon,2011).Studies show that CPSs present good results with a smaller model domain over East Asia,but they are unable to model tropical cyclones and extreme events(Zhong,2006).Convective precipitation derived from different convection parameterizations is a major contributor to the performance of some models in the summer season(Im et al.,2008a).In simulating the Asian summermonsoon,the dualscheme approach enhances model performance(Chow and Chan,2010).Errors in models persist irrespective of the choice of CPS or land surface scheme and lateral boundary conditions(Gianotti et al.,2012).The performances of CPSs improve with a smaller horizontal resolution;for example,Sinha et al.(2013)reported results that were better when using 30 km rather than 90 km.Overall,the previous results summarized in Table 1 suggest that the Grell scheme is best for South Asia,the Emanuel scheme for East Asia,while both are suitable for Southeast Asia.

    2. The convective parameterization schemes

    2.1.Grell scheme

    Grell(1993)represents cloud and environment as two steady-state circulations(an updraft and a downdraft that are undiluted,i.e.,no entrainment or detrainment occurs along the cloud edges such that the mass fl ux is constant with height)in the Grell scheme.The scheme can be used when a lifted parcel reaches moist convection level,and the mixing of cloud,air,and the environment occurs only at the top and bottom.This scheme is very simple in nature and focuses on the statistical equilibrium between large-scale processes and convection.The minimum and maximum levels of moist static energy indicate the initiating levels of the downdraft and updraft.The Grell scheme activates when a lifted parcel of air reaches the condensation and moist convection level in the updraft,and is calculated by a saturated parcel.Mddenotes the downdraft mass fl ux andMurepresent the updraft mass fl ux.Hence,the scheme can be shown in the form of an equation:

    ThenormalizedupdraftcondensationisdenotedbyI1,the normalized downdraft evaporation isI2,andβis the fraction of updraft condensation that re-evaporates during the downdraft and depends on the change in the wind direction and speed that typically changes between 0.3 and 0.5.Hence,wehave the equation

    wherePis precipitation.The detrainment and mass fl uxes at the top and bottom of the cloud regulate the moistening and heating in the Grell scheme with the cooling effect during the downdrafts.The Grell scheme is fl exible to apply with different assumptions[i.e.Arakawa-Schubert(AS)and Fritsch-Chappell(FC)].

    2.2.Emanuel scheme

    The Emanuel scheme assumes that mixing in clouds is highly inhomogeneous and episodic.Modeling of convective fl uxes is based on an idealized condition of sub-cloud-scale downdrafts and updrafts.The process of convection is initiated if the level of neutral buoyancy is greater than the cloud base level.Air is lifted between these two levels and a fraction of the condensed vapor forms precipitation,whereas the residual forms the cloud(Elguindi et al.,2013).It is assumed that the cloud is mixed with the air from the environment permitting to the range of mixtures that descend or ascend to particular levels of neutral buoyancy.The mixing detrainment and entrainment rates are the functions of the vertical gradients of buoyancy in clouds.The fraction of the total cloud base mass fl ux that combines with the environment at all levels is proportional to the rate of change of buoyancy with altitude.The upward mass fl ux at the cloud base decreases towards the sub-cloud layer quasi equilibrium.The Emanuel scheme is designed in such a way that it provides several advantages regarding convection options.It consists of a technique that converts the cloud water into precipitation in cumulus clouds.The ice processes are temperature-dependent, allowing the auto-conversion threshold water content to be used.The precipitation is included in hydrostatic,unsaturated,and a single downdraft that carries water and heat.The Emanuel scheme also considers the carrying of passive tracers.

    2.3.Tiedtke scheme

    The Tiedtke scheme was originally developed for application on the global scale.This scheme is dependent on the mass fl ux and moisture convergence.The triggering mechanism is based on convection,i.e.if the temperature of the parcel exceeds the temperature of the environment by a fi xed temperature threshold,it creates conditional instability.It has shallow and deep convection,determining the cloud base mass fl ux from the PBL equilibrium and mass fl ux closure from CAPE,respectively.In deep convection,the reduction of CAPE is the integrated effect of the convective heating, and the middle level exists if there is large-scale ascent with mass fl ux closure.In the Tiedtke parameterization,updraft is sensitive to entrained air from the free troposphere(Hourdin et al.,2006).Thus,the convection can be reduced by the dry, free troposphere.The convective cloud cover and cloud water content sources are described as functions of the detrainment of mass from the speci fi c content of cloud water in the updrafts,convective updrafts,and the density of cloudy air.An updraft air parcel is assumed to detrain into existing cloud as well as into cloud-free air,making sure the real limits of zero cloud cover and full cloud cover.Zero cloud cover is considered in which updraft air detrains only into clear air and full cloud cover is considered where all updraft air detrains into existing clouds.The mass for detrainment is acquired from the cumulus parameterization for the updraft mass fl ux (Tiedtke,1993).Cumulus clouds can occur if a deep layer of conditional instability and large-scale moisture convergence exist.Within the lower half of the troposphere,an increase in vertical mass fl ux is connected to the moisture convergence in the column of the atmosphere.Hence,deep convection occurs as the undiluted parcel of air rises adiabatically with the dry adiabatic lapse rate that positively regulates the buoyancy until it touches the LCL and becomes saturated.The precipitation will occur due to turbulent eddies and stronger large-scale moisture convergence(Tiedtke,1989).

    3. Methods

    3.1.Model

    The model used in this study is version 4.3 of RegCM. The fi rst version of RegCM was developed in the late 1980s (Giorgi and Bates,1989;Dickinson et al.,1989).Since then, it has been continuously upgraded to RegCM2(Giorgi et al.,1993),RegCM3(Pal et al.,2000,2007)and RegCM4 (Giorgi et al.,2012).Earth System Physics(ESP),Abdul Salam International Center for Theoretical Physics(ICTP), Italy,maintains the latest version,i.e.,RegCM4.The model’s latest versions are more user-friendly, fl exible,and portable, having important updates made to the source code.The dynamic core of RegCM4 is similar to RegCM3,which was based on the hydrostatic version of the National Center for Atmospheric Research(NCAR)/Penn State mesoscale model(MM5)(Grell et al.,1994).The PBL computations are parameterized by the scheme of Holtslag et al.(1990); the land surface model is the Biosphere–Atmosphere Transfer Scheme(BATS)(Dickinson et al.,1989);the radiation scheme is the modi fi ed NCAR Community Climate Model version 3(CCM3)(Kiehl et al.,1998);and the resolvablescale precipitation is signi fi ed by the system of subgrid explicit moisture scheme(SUBEX)(Pal et al.,2000).

    3.2.Experiments and data

    The model domain covers Southeast Asia over the area (4°–56°N,49°–138°E).The climatology of this region is mainly affected by the monsoon season.Over most parts of the Southeast Asian region,rainfall occurs during the months of June to September,also known as the summer monsoon, depending on the seasonal direction of the prevailing surface wind.High rainfall associated with regional orography occurs parallel to India,the west coast of the Indochina peninsula,South China,and the South China Sea.There is a wide zone of around 20°N extending towards the northeast from the north part of the Bay of Bengal(BoB)that receives substantial rainfall.Southeast Asian summer monsoon rainfallis linked with the variability of rainfall in this monsoon zone (Wang and Wu,1997).The rainfall over monsoon zone is associated with the synoptic-scale convective systems produced over the warm oceans surrounded by the subcontinent that transport moisture to the northeast.Partly overlapping disturbances are also generated over this zone due to active spells of the monsoon.The summer monsoon even in fl uences the global climate through energy exchange and hydrological processes,as well as the regional climate(Lau and Weng, 2001).

    Three sub-regions are selected from the model domain for detailed analysis(Fig.1):North Pakistan[NP:(34.5°–37°N,71°–78°E)];Tibetan Plateau[TP:(30°–37°N,80°–95°E)];and Huang-Huai-Hai Plain[3H:(31°–41°N,112°–121°E)].The selected sub-regions consist of two mountain areas(NP and TP)and one irrigated plain(3H)region(Dan et al.,2012)in China.3H is occupied by 425 million people and provides 50%of China’s grain,where the crop production is greatly dependent on irrigation from groundwater and surface runoff.NP and TP consist of the Himalaya,Hindu Kush,andKarakoram,withtheworld’sthird-largesticestore. The domain contains 336 grid points in the latitudinal direction and 280 grid points in the longitudinal direction,with a central point of(32°N,94°E)and 18 vertical sigma levels. This domain is quite large for the development of internal model mesoscale circulations and regional forcing(Jones et al.,1995;Singh et al.,2006).

    RCMs are usually run at high resolution when the output of RCMs is used for impact studies.In this study,RegCM4 is run at 20 km at its maximum fi ner resolution because the hydrostatic engine of RegCM does not allow a resolution fi ner than 20 km(Elguindi et al.,2013).Five simulations with fi ve different CPSs are carried out for the period 1997–2002.The fi rst year,1997,is used as model spin-up,and so the analysis is considered from 1998 to 2002.The lateral and initial boundary conditions are taken from ERA-interim data(Simmons et al.,2007;Uppala et al.,2008),available since 1979 to the present day with 1.5°horizontal resolution.The ERA-interim dataset is a realistic state-of-the-art and widely used model solution.It has good coverage of upper-air measurements over the whole globe and is regarded as relatively more reliable than other reanalysis datasets(Lin et al.,2014),especially over the Northern Hemisphere.It also assimilates more advanced and observational data(Dee et al.,2011).

    The SST data are acquired by optimum interpolation(OI) processing,i.e.,the weighted monthly mean of the given set of data on the basis of the observed Reynolds SST fi eld where the variance of the estimate is kept to the minimum. The OI SST analysis is produced weekly on a 1°grid.The analysis usesin situand satellite SSTs,plus SSTs simulated by sea-ice cover.Before the analysis is computed, the satellite data are adjusted for biases using the method of Reynolds(1988)and Reynolds and Marsico(1993).Topographic and vegetation cover datasets was taken from 30-arcsecond(GTOPO30),aggregated to 10 arc minutes and global land cover characterization(GLCC)respectively.To validate the model results,three observational datasets are used for precipitation and temperature including:monthly-mean and 3-hourly datasets available from 0.25°×0.25°products from the Tropical Rainfall Measurement Mission(TRMM 3B42, Huffman et al.,2007),over the range 50°N–50°S since January 1998 to the present day.TRMM 3A25 data with distinct convective and stratiform rainfall are used to validate the convective precipitation.The monthly mean temperature and precipitation data for the period 1901–2000 over the global land area at regular intervals of 0.5°are from the Climate Research Unit(CRU)TS2.1 dataset(Mitchell and Jones,2005).The gridded precipitation data for the period 1957–2007arefromtheAsianPrecipitationHighly-Resolved Observational Data Integration Towards Evaluation of water resources(APHRODITE)dataset(Yatagai et al.,2012),provided by the Meteorological Research Institute of the Japan Meteorological Agency(MRI/JMA)and the Research Institute for Humanity and Nature(RIHN)at 0.25°resolution.

    4. Results

    The effects of different CPSs on average temperature, precipitation,and winds at 850 hPa during a fi ve-year period (1998–2002)are presented in this section.First,we describe the simulation results over the whole of the East/South Asia domain for the four seasons de fi ned as:spring(March–May; MAM);summer(June–August;JJA);autumn(September–November;SON);and winter(December–February;DJF). And second,we analyze the statistical results,including correlation coef fi cient,normalized standard deviation,and RMSE values,over the three sub-regions(3H,NP,and TP).

    4.1.Atmospheric simulation using the fi ve CPSs

    The seasonal and annual means of precipitation and wind are examined to understand the moisture fl ow from one region to another(Fig.2).It can be seen that RegCM4.3 is able to properly reproduce the circulation for the East/South Asian monsoon.During MAM–JJA,atmospheric pressure decreases over the Asian landmass due to intense surface heating,and at the same time surface pressure remains relatively high over the cool sea to the south.Moist air from the equator moves northward under this seasonally developed pressure gradient carrying water vapor from the BoB and Arabian Sea.South/southwestward wind patterns develop due to the Coriolis force and prevail over South/Southeast Asia during the summer monsoon from May to September. During SON–DJF,north/northeast winds move from northern high latitudes affected by the Siberian high,carrying cold air from northern land to most parts of East/South Asia and causing winter precipitation.The annual means of precipitation and circulation are more affected by MAM–JJA,whereas SON–DJF has less impact.The annual mean and MAM–JJA circulation patterns are more similar in Fig.2,which clearly indicates that MAM–JJA is dominant in terms of the annual mean of circulation and precipitation.

    The results of RegCM4.3-simulated precipitation and winds are compared with TRMM and ERA-Interim data(Fig. 3)separately.It is clear that the Grell simulations produce more rainfall over the Arabian Sea and BoB throughout the year,whereas other schemes show a dry bias.In summer, the Emanuel and Tiedtke schemes underestimate the precipitation over the Indian Peninsula,whereas the Grell scheme overestimates precipitation by 6 mm d-1over south India due to the local cyclone for air convergence.Furthermore, over southwest China,the Indochina peninsula,and Northeast China,the Emanuel scheme produces more precipitation and the Tiedtke scheme produces less precipitation over South China,probably due to less surface latent heat fl ux (Fig.4)and entrained air from the troposphere.In winter, all the schemes produce less biased results of precipitation as compared to summer due to less convective activity.Table 2 lists the seasonal RMSEs of precipitation for the fi ve schemes over the whole domain.The Grell scheme shows a small RMSE value for precipitation of 3.41 mm d-1for the summer season(JJA),whereas the Emanuel scheme shows a high RMSE of 5.20 mm d-1,followed by GLEO(4.57 mm d-1).During MAM,the Tiedtke scheme shows the lowest RMSE values in comparison to the other CPSs.In winter, the Emanuel and Tiedtke schemes have low RMSE values for precipitation(~1.7 mm d-1).RMSE values are higher during summer precipitation than in other seasons.Table 3 lists the precipitation RMSE values on a seasonal basis overthe southeast China(SEC),BoB,the Western Ghats(WG), and Sri Lanka/southeast India(SLSEI).For SEC,the Grell scheme performs effectively compared to the other schemes during JJA,SON,and DJF,while the Tiedtke scheme performs better for MAM.Over the BoB,the Grell scheme shows effective results for JJA and SON,while GLEO and the Tiedtke scheme improve their outcomes for MAM and DJF,respectively.Over WG,the Grell scheme shows enhanced performance during MAM,SON,and DJF.However, the ELGO scheme produces considerable results over WG and SLSEI compared to each standalone scheme(i.e.Grell and Emanuel)during JJA,indicating that in regions that containbothlandandocean,thecombinationoftheGrellscheme over the ocean and the Emanuel scheme over land produces suitable results.

    The amount of convective precipitation is very sensitive and directly in fl uenced by the choice of convection scheme (Wang and Seaman,1997).Figure 5 illustrates the differences of seasonal mean convective precipitation between RegCM4.3 and TRMM 3A25 data.It is clear that in JJA the Tiedtke scheme produces the least biased convective precipitation.However,it overestimates rainfall by 4–6 mm d-1over southern China and adjoining areas,and underestimates precipitation over some parts of India and NP.Figure 5 also indicates that the Grell,Emanuel,GLEO and ELGO schemes overestimate precipitation by 4–12 mm d-1over the Indianpeninsula,SEC,and adjoining areas.The Emanuel scheme shows a precipitation bias of 4–6 mm d-1over India and the BoB,while over SEC and the Indochina peninsula it generates more convective precipitation and the bias exceeds 12 mm d-1.The ELGO scheme reduces the wet bias over India and the Indochina peninsula,and produces the secondsmallest wet bias over Southwest China.The GLEO scheme produces a small dry bias over the BoB,close to that of the Emanuel scheme,but over India and the Indochina peninsula it shows a large wet bias.In comparison with TRMM data, theTiedtkeschemereproduceswell-distributedseasonalvariability and intensity of convective precipitation,with the smaller bias probably due to less convection in the scheme. The Tiedtke scheme also produces minimum RMSE values for all the seasons with TRMM(Table 4).

    Table 3.Seasonal RMSE for precipitation over Southeast China, Bay of Bengal,Western Ghats near the Arabian Sea,and Sri Lanka/Southeast India(bold values indicate the lowest RMSE for each season).

    Table 4.Seasonal RMSE for convective precipitation for the entire East/South Asian domain of our study(bold values indicate the lowest RMSE for each season).

    The seasonal mean temperatures at the height of 2 m in the fi ve schemes along with CRU data are shown in Fig. 6.Overall,the simulated surface air temperatures with the fi ve CPSs agree closely with CRU data throughout the year. The results show that RegCM4.3 is able to capture the mean state and seasonal cycle of the surface air temperature over East/South Asia.

    In order to study the inter-model differences in temperature at the height of 2 m,the differences between RegCM4.3 when using the fi ve CPSs and CRU data are shown in Fig. 7.Also shown are the differences between ERA-Interim and CRU data(Figs.7u–x).In general,surface air temperature bias patterns are similar in RegCM4.3 with the different CPSs.All the schemes result in a similar cold bias throughout the year over the west of the TP and NP.The possible reasons for this cold bias are:(1)the difference in the representation of elevation in the model and actual station values;(2)the rapid variation in the topography of mountainous regions,e.g.,the problem of accommodating and processing orographic lifting is very signi fi cant in the NP;and (3)the actual height of the Himalaya is more than prescribed in RegCM(Sinha et al.,2014).The Tiedtke scheme shows a relatively smaller cold bias among the fi ve CPSs in summer.For surface air temperature during summer,the Tiedtke scheme even shows a warm bias(more heating)because of more radiation in the surrounding regions and a high rate of evaporation and convection,which later transports moisture towards the northeast.Increased heating makes the atmosphere warmer over most parts of the domain when compared to other schemes that show cold bias.The Tiedtke scheme results show a thick PBL over India and most parts of China(not shown)with less precipitation.Since convection is primarily initiated within the PBL region that responds to surface turbulent heat fl uxes driven by incoming solar radiation after relatively short time scales,convective activity affects large-scale atmospheric dynamics by vertical transport of heat and moisture and adiabatic heating.It is also in fl uenced by the interaction of cumulus clouds with radiation.The resilient contact of cumulus clouds with longwave andshortwaveradiationcausesatmosphericmotion,moisture convergence and dispersion over the surface as well as in the atmosphere.This moisture is carried to the northeast,leaving most parts of India and China relatively drier.In winter,all the schemes produce a cold bias over SEC and the Indochina peninsula,with a center over Thailand,west of the TP,and Southwest China.The temperature bias patterns in RegCM are similar in different CPSs.The Grell,Emanuel,ELGO and GLEO schemes exhibit RMSE values between 2.09 and 2.47°C during summer(JJA)(Table 2),whereas the Tiedtke scheme shows the highest RMSE value of 3.11°C and produces worse results than the other schemes.In winter,the Tiedtke and Grell schemes show smaller RMSEs.It is also clear that the RMSE values for temperature are larger in winter than in other seasons.

    4.2.Simulation over the three sub-regions

    The results of seasonal variation of precipitation over the three sub-regions(3H,TP and NP)(Fig.1)are presented in Fig.8.TRMM and APHRODITE data show more precipitation in the region of 3H but less in TP and NP.The model resultsinFig.8forJJAalsoshowsimilarresults.Overthe3H region,precipitation reaches the maximum,i.e.,around 4mm d-1in July and the minimum in December.The Grell and GLEO schemes show that precipitation in summer exceeds 6 mm d-1,while in the Emanuel and ELGO scheme results its amplitude reaches double that of the APHRODITE data.The seasonal variation of the Tiedtke scheme produces simulation results closer to TRMM and APHRODITE data.The results over the TP are similar to the 3H region,with all CPSs showing more precipitation throughout the year except the Tiedtkescheme,which shows a dry bias in summer.Small variations in precipitation are shown according to APHRODITE and TRMM data for the NP.APHRODITE produces maximum precipitation in April,whereas TRMM produces maximum precipitation in July.The seasonal variation of simulated precipitation shows larger differences in winter than summerifwecomparewithTRMMandAPHRODITE.None of the CPSs generate results that re fl ect the observed amplitude variation(high and low)of rainfall in February and August.Overall,in the three sub-regions,the simulation results of the Grell(Emanuel)and GLEO(ELGO)schemes are quite similar,which share the same CPS over land,and are therefore in fl uenced directly by the CPS over land rather than over the ocean.

    Vertical pro fi les of summer temperature and water vapor mixing ratio are compared with ERA-interim data(Fig.9). Over the 3H region,the Tiedtke scheme shows warmer temperatures near the surface up to 500 hPa associated with the maximum temperature at the height of 2 m for the same region(Fig.7).Above 500 hPa,the temperature differences become very small.Over the TP and NP,the warmer temperature in the Tiedtke scheme reaches up to the height of 200 hPa,and the differences between RegCM4.3 and ERAInterim show warmer temperatures at this level compared to the lower troposphere.The warm difference(RegCM minus ERA-Interim)decreases as the altitude increases up to 600 hPa,and even turns to cold differences in the middle troposphere by the Grell and GLEO schemes above 600 hPa.This temperature decrease is due to frequent convective activities in the Grell scheme.Furthermore,the differences in temperature increase and attain maximum values of around 12°C at 150 hPa.The Grell and GLEO schemes show more unstable atmospheric conditions when the altitude increases up to 600 hPa.In the Tiedtke scheme the slow convective process decreases the ascending motion of the air before the condensation level and creates a more stable structure with less precipitation,possibly due to less surface latent heat fl ux and entrainment.This reduces the wet bias of convective precipitation in the Tiedtke scheme(Fig.5).The Tiedtke scheme retains more water vapor in the troposphere but shows a reduced precipitation difference(Fig.3b).The underestimation of precipitation in the Tiedtke scheme was also reported by Kaspar and Cubasch(2008),Wang et al.(2011),and Mart′?nez-Castro et al.(2013).The atmosphere is drier in the Tiedtke scheme at 400–700 hPa,as shown in Fig.9e,and at 850 hPa in Fig.9f.The Emanuel scheme is more active in transporting humid air from low levels to high levels,generating more precipitation.

    Figures 10a and b show the correlation coef fi cient and normalized standard deviation results for summer surface air temperature and precipitation,respectively,with the fi ve CPSs over the 3H,TP and NP sub-regions.For surface air temperature,the simulations of the different CPSs are closer to each other and the correlation ranges from 0.72 to 0.97 compared with CRU data.Over the 3H,the Emanuel and ELGO schemes show strong correlation and standard deviation of temperature which is approximately 1,while over the NP and TP,the Grell scheme shows strong correlation and a normalized standard deviation ratio of closer to 1.For precipitation,the correlation is weaker than for temperature over the three sub-regions,and the correlation and standard deviation show large differences in different schemes.Over the 3H region,the correlation of the Grell and Tiedtke schemes with TRMM data is about 0.6,which is double that for the Emanuel scheme(0.3).Over the TP,the Tiedtke scheme produces strong positive correlation(0.8)and standard deviation closer to 1 in simulating summer precipitation.Over the NP, all the CPSs show very weak correlation,i.e.,less than 0.3, and low standard deviation for summer precipitation.

    Table 5.Seasonal RMSE for precipitation and temperature over the 3H region,North Pakistan and Tibetan Plateau(bold values indicate the lowest RMSE for each season).

    RMSEvaluesarecalculatedforallschemesoverthethree sub-regions for precipitation and temperature(Table 5).The Tiedtke scheme performs better in simulating precipitation over the 3H region all year round,especially in MAM and JJA.For temperature in the 3H region,ELGO produces better results for JJA,SON,and DJF.Over the NP,the Tiedtke scheme produces good approximations of precipitation except for JJA.The ELGO scheme produces better results for JJA compared to the Tiedtke scheme. Over the TP,the Tiedtke scheme produces appropriate results throughout the year for precipitation and temperature.

    5. Conclusion

    RegCM4.3 successfully simulates the characteristics of East/South Asia summer monsoon circulation at 850 hPa. The performance of all CPSs is strongly dependent on spatial and seasonal variation of a region.Over SEC and the BoB, the Grell scheme performs more effectively than the other schemes.However,all the schemes tend to show a dry bias over the Arabian Sea and BoB throughout the year,except the Grell scheme which produces surplus rainfall.Over WG,the Grell scheme shows better performance throughout the year except in JJA,when the ELGO scheme produces reasonable results.The Tiedtke scheme improves the simulation of convective precipitation in both spatial distribution and magnitude for all the seasons with minimum RMSE values.In the case of surface air temperature,all the CPSs produce almost the same cold bias(0–10°C)over the west of the TP and NP throughout the year.

    Generally,the Tiedtke scheme shows close agreement withTRMMandAPHRODITEdataforprecipitationoverthe three sub-regions.The annual cycle of precipitation shows that the model simulations with the different schemes areclose to the observed data over the 3H and TP regions,except over NP,where no scheme produces the seasonal variation because the actual height of the Himalaya is more than prescribed in RegCM.The simulations are processed with 20 km horizontal resolution,and hence the problem of a leeward sudden change in orography exists.The model is unable to process the issues of orography,and thus some balancing parameters in the model are needed to overcome the simulation problems in this region.In the vertical pro fi les of temperature and water vapor mixing ratio,the atmosphere in the Tiedtke scheme is warmer and drier over the TP and NP compared to the other CPSs,which generates a precipitation difference. The Tiedtke scheme produces the dry conditions over the 3H region,and hence less precipitation due to less surface latent heat fl ux.This result is supported by the Tiedtke scheme’s mechanism of moisture transportation and precipitation towards the northeast.For precipitation,the CPSs differ distinctly from one another.Among all the schemes,the Tiedtke scheme shows a strong correlation and standard deviation of precipitation and temperature.However,the correlation and standard deviation is very weak in NP in the results of all the schemes.

    Overall,the Tiedtke scheme yields better results for precipitation and temperature as compared to observed data, with the lowest RMSE values over the three sub-regions.Previous studies have recommended the Grell scheme for South Asia,the Emanuel scheme for East Asia,and both schemes (GrellandEmanuel)withequalweightingforSoutheastAsia. This study agrees with previous results that the Grell scheme is best for South Asia;however,over most parts of China and the three sub-regions,our results are quite different from previous studies and suggest the Tiedtke scheme to be superior. We believe that the reason for this fi nding is the unique characteristics of deep convection and entrainment in the Tiedtke scheme,which reduces the wet bias of precipitation.

    Acknowledgements.We thank Graziano GIULIANI and Erika COPPOLA,ICTP,for providing support and data for this research.This study was fi nancially supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(KZCX2-EW-QN208),a project of the National Natural Science Foundation of China(Grant No.41275082),the National Basic Research Program of China(Grant Nos.2010CB428502 and 2011CB952003), and the R&D Special Fund for Public Welfare Industry(meteorology)of the Ministry of Finance and the Ministry of Science and Technology(GYHY201006014-04).

    REFERENCES

    Bao,Y.,2013:Simulations of summer monsoon climate over East Asia with a Regional Climate Model(RegCM)using Tiedtke convective parameterization scheme(CPS).Atmos.Res.,134, 35–44.

    Bao,Y.,2013:Simulations of summer monsoon climate over East Asia with a Regional Climate Model(RegCM)using Tiedtke convective parameterization scheme(CPS).Atmos.Res.,134, 35–44.

    Basit,A.,S.R.Shoaib,N.Irfan,and R.Avila,2012:Simulation of monsoon precipitation over South-Asia using RegCM3.ISRN Meteor.,12,754902,doi:10.5402/2012/754902.

    Cao,J.,X.N.Zhang,Y.L.You,and R.W.Yang,2007:Applicability of cumulus convective parameter schemes in RegCM3 to the rainfall over the Longitudinal Range-Gorge Region.Chinese Science Bulletin,52(2),115–121.

    Cha,D.H.,D.K.Lee,and S.Y.Hong,2008:Impact of boundary layer processes on seasonal simulation of the East Asian summer monsoon using a regional climate model.Meteorology and.Atmospheric Physics,100(1–4),53–72.

    Chow,K.C.,and J.C.Chan,2010:A dual-scheme approach of cumulus parameterization for simulating the Asian summer monsoon.Meteorological Applications,17(3),287–297.

    Dan,L.,J.Ji,Z.Xie,F.Chen,G.Wen,and J.E.Richey,2012:Hydrological projections of climate change scenarios over the 3H region of China:A VIC model assessment.J.Geophys. Res,117(D11).doi:10.1029/2011JD017131.

    Dash,S.K.,M.S.Shekhar,and G.P.Singh,2006:Simulation of Indian summer monsoon circulation and rainfall using RegCM3.Theor.Appl.Climatol.,86(1–4),161–172.

    Davis,N.,J.Bowden,F.Semazzi,L.Xie,and B.¨Onol,2009: Customization of RegCM3 regional climate model for eastern Africa and a tropical Indian Ocean domain.J.Climate, 22,3595–3616.

    Dee,D.P.,and Coauthors,2011:The ERA-Interim reanalysis: Con fi guration and performance of the data assimilation system.Quart.J.Roy.Meteor.Soc.,137,553–597.

    Dickinson,R.E.,R.M.Errico,F.Giorgi,and G.T.Bates,1989: A regional climate model for the western United States.Climatic Change,15(3),383–422.

    Elguindi,N.,X.Bi,F.Giorgi,B.Nagarajan,J.Pal,F.Solmon, and G.Giuliani,2013:Regional Climate Model RegCM User Manual Version 4.4.The Abdus Salam International Centre for Theoretical Physics,Strada Costiera,Trieste,Italy October 21,2013,54 pp.

    Emanuel,K.A.,and M.ˇZivkovic-Rothman,1999:Development andevaluationofaconvectionschemeforuseinclimatemodels.J.Atmos.Sci.,56(11),1766–1782.

    Fu,C.,S.Wang,Z.Xiong,W.J.Gutowski,D.K.Lee,J.L.Mc-Gregor,and M.S.Suh,2005:Regional climate model intercomparison project for Asia.Bull.Amer.Meteor.Soc.,86(2), 257–266.

    Gianotti,R.L.,D.Zhang,and E.A.Eltahir,2012:Assessment of the regional climate model version 3 over the maritime continent using different cumulus parameterization and land surface schemes.J.Climate,25(2),638–656.

    Giorgi,F.,and G.T.Bates,1989:The climatological skill of a regional model over complex terrain.Mon.Wea.Rev.,117(11), 2325–2347.

    Giorgi,F.,M.R.Marinucci,and G.T.Bates,1993:Development of a second generation regional climate model(RegCM2).I. Boundary layer and radiative transfer processes.Mon.Wea. Rev.,121,2794–2813.

    Giorgi,F.,and Coauthors,2012:RegCM4:Model description and preliminary tests over multiple CORDEX domains.Climate Res.,52,7–29.

    Gochis,D.J.,W.J.Shuttleworth,and Z.-L.Yang,2002:Sensitivity of the modeled North American monsoon regional climate to convective parameterization.Mon.Wea.Rev.,130,1282–1298.

    Grell,G.A.,1993:Prognostic evaluation of assumptions usedby cumulus parameterizations.Mon.Wea.Rev.,121(3),764–787.

    Grell,G.A.,J.Dudhia,and D.R.Stauffer,1994:A description of the fi fth-generation Penn State/NCAR mesoscale model (MM5).NCAR Technical Note NCAR/TN-398+STR,doi: 10.5065/D60Z716B.

    Holtslag,A.A.M.,E.I.F.De Bruijn,and H.L.Pan,1990:A high resolution air mass transformation model for short-range weather forecasting.Mon.Wea.Rev.,118(8),1561–1575.

    Hourdin,F.,and Coauthors,2006:The LMDZ4 general circulation model:Climate performance and sensitivity to parameterized physics with emphasis on tropical convection.Climate Dyn., 27(7–8),787–813.

    Huang,W.R.,J.C.L.Chan,and A.Y.M.Au-Yeung,2013:Regional climate simulations of summer diurnal rainfall variations over East Asia and Southeast China.Climate Dyn., 40(7–8),1625–1642.

    Huffman,G.J.,D.T.Bolvin,E.J.Nelkin,D.B.Wolff,R.F. Adler,G.Gu,and E.F.Stocker,2007:The TRMM Multisatellite Precipitation Analysis(TMPA):Quasi-global,multiyear,combined-sensor precipitation estimates at fi ne scales.Journal of Hydrometeorology,8(1),38–55.

    Im,E.S.,J.B.Ahn,A.R.Remedio,and W.T.Kwon,2008a:Sensitivity of the regional climate of East/Southeast Asia to convective parameterizations in the RegCM3 modelling system. Part 1:Focus on the Korean peninsula.International Journal of Climatology,28(14),1861–1877.

    Im,E.S.,W.J.Gutowski,and F.Giorgi,2008b:Consistent changes in twenty- fi rst century daily precipitation from regional climate simulations for Korea using two convection parameterizations.Geophys.Res.Lett.,35,doi:10.1029/2008 GL034126.

    Jones,R.G.,J.M.Murphy,and M.Noguer,1995:Simulation of climate change over Europe using a nested regional climate model.Part I:Assessment of control climate,including sensitivity to location of lateral boundaries.Quart.J.Roy.Meteor. Soc.,121,1413–1449.

    Kaspar,F.,and U.Cubasch,2008:Simulation of East African precipitation patterns with the regional climate model CLM.Meteorologische Zeitschrift,17(4),511–517.

    Kiehl,J.T.,J.J.Hack,G.B.Bonan,B.A.Boville,D.L. Williamson,and P.J.Rasch,1998:The national center for atmospheric research community climate model:CCM3.J. Climate,11(6),1131–1149.

    Lau,K.M.,and H.Weng,2001:Coherent modes of global SST and summer rainfall over China:An assessment of the regional impacts of the 1997–98 El Nino.J.Climate,14(6), 1294–1308.

    Lee,D.Y.,C.Y.Tam,and C.K.Park,2008:Effects of multicumulus convective ensemble on East Asian summer monsoon rainfall simulation.J.Geophys.Res.,113(D24),doi:10.1029/ 2008JD009847.

    Liang,X.Z.,K.E.Kunkel,and A.N.Samel,2001:Development of a regional climate model for US Midwest applications.Part I:Sensitivity to buffer zone treatment.J.Climate, 14(23),4363–4378.

    Liang,X.Z.,M.Xu,K.E.Kunkel,G.A.Grell,and J.S.Kain, 2007:Regional climate model simulation of U.S.-Mexico summer precipitation using the optimal ensemble of two cumulus parameterizations.J.Climate,20(20),5201–5207.

    Lin,R.,T.Zhou,and Y.Qian,2014:Evaluation of global monsoon precipitation changes based on fi ve reanalysis datasets.J.Climate,27(3),1271–1289.

    Liu,Y.,and Y.Ding,2007:Sensitivity study of the South China Sea summer monsoon in 1998 to different cumulus parameterization schemes.Adv.Atmos.Sci.,24,360–376,doi: 10.1007/s00376-007-0360-y.

    Liu,Y.,and Y.Ding,2007:Sensitivity study of the South China Sea summer monsoon in 1998 to different cumulus parameterization schemes.Adv.Atmos.Sci.,24,360–376,doi: 10.1007/s00376-007-0360-y.

    Liu,H.,D.L.Zhang,and B.Wang,2010:Impact of horizontal resolution on the regional climate simulations of the summer 1998 extreme rainfall along the Yangtze River Basin.J.Geophys.Res.,115(D12),doi:10.1029/2009JD012746.

    Mamgain,A.,L.Mariotti,E.Coppola,F.Giorgi,and S.K.Dash, 2013:Sensitivity of RegCM4.3 two convection schemes on Indian summer monsoon for the South Asia CORDEX domain.EGU General Assembly Conference Abstracts,Vol.15, 4812.

    Mart′?nez-Castro,D.,A.Vichot-Llano,A.Bezanilla-Morlot,and A.Centella-Artola,2013:Sensitivity study on convection schemes in regCM4.3,in the simulation of air temperature and precipitation fi elds in Central America and the Caribbean.InternationalConferenceonRegionalClimateCORDEX,4–7 November 2013,Brussels,Belgium.

    Mitchell,T.D.,and P.D.Jones,,2005:An improved method of constructing a database of monthly climate observations and associated high-resolution grids.International Journal of Climatology,25(6),693–712.

    Octaviani,M.,and K.Manomaiphiboon,2011:Performance of regional climate model RegCM3 over Thailand.Climate Research,47(3),171–186.

    Pal,J.S.,E.E.Small,and E.A.Eltahir,2000:Simulation of regional-scale water and energy budgets:Representation of subgrid cloud and precipitation processes within RegCM.J. Geophys.Res..,105(D24),29 579–29 594.

    Pal,J.S.,F.Giorgi,X.Bi,N.Elguindi,F.Solmon,S.A.Rauscher, and A.L.Steiner,2007:Regional climate modeling for the developing world:The ICTP RegCM3 and RegCNET.Bull. Amer.Meteor.Soc.,88(9),1395–1409.

    Rahman,M.M.,M.N.Islam,A.U.Ahmed,and R.Afroz,2007a: Comparison of RegCM3 simulated meteorological parameters in Bangladesh:Part I—Preliminary result for rainfall.Sri Lankan Journal of Physics,8,1–9.

    Rahman,M.M.,M.N.Islam,A.U.Ahmed,and R.Afroz,2007b: Comparison of RegCM3 simulated meteorological parameters in Bangladesh:Part II—Preliminary result for temperature.Sri Lankan Journal of Physics,8,11–19.

    Reynolds,R.W.,1988:A real-time global sea surface temperature analysis.J.Climate,1,75–86.

    Reynolds,R.W.,and D.C.Marsico,1993:An improved real-time global sea surface temperature analysis.J.Climate,6,114–119.

    Segele,Z.T.,L.M.Leslie,and P.J.Lamb,2009:Evaluation and adaptation of a regional climate model for the Horn of Africa: Rainfallclimatologyandinterannualvariability.International Journal of Climatology,29(1),47–65.

    Simmons,A.,C.Uppala,D.Dee,and S.Kobayashi,2007:ERAInterim:New ECMWF reanalysis products from 1989 onwards.ECMWF Newsletter,No.110,25–35.

    Singh,A.P.,R.P.Singh,P.V.S.Raju,and R.Bhatla,2011:The impact of three different cumulus parameterization schemes on the Indian summer monsoon circulation.The InternationalJournal of Ocean and Climate Systems,2,27–44.

    Singh,G.P.,J.H.Oh,J.Y.Kim,and O.Y.Kim,2006:Sensitivity of summer monsoon precipitation over East Asia to convective parameterization schemes in RegCM3.Sola,2,29–32.

    Sinha,P.,U.C.Mohanty,S.C.Kar,S.K.Dash,and S.Kumari,2013:Sensitivity of the GCM driven summer monsoon simulations to cumulus parameterization schemes in nested RegCM3.Theor.Appl.Climatol.,112(1–2),285–306.

    Sinha,P.,U.C.Mohanty,S.C.Kar,and S.Kumari,2014:Role of the Himalayan orography in simulation of the Indian summer monsoon using RegCM3.Pure and Applied Geophysics,171, 1385–1407,doi:10.1007/s00024-013-0675-9.

    Tiedtke,M.,1993:Representation of clouds in large-scale models.Mon.Wea.Rev.,121,3040–3061.

    Tiedtke,M.,1989:A comprehensive mass fl ux scheme for cumulus parameterization in large-scale models.Mon.Wea.Rev, 117(8),1779–1800.

    Tchotchou,L.A.D.,and M.Kamga,2010:Sensitivity of the simulated African monsoon of summers 1993 and 1999 to convective parameterization schemes in RegCM3.Theor.Appl. Climatol.,100,207–220.

    Uppala,S.,D.Dee,S.Kobayashi,P.Berrisford,and A.Simmons, 2008:Towards a climate data assimilation system:Status update of ERA-Interim.European Centre for Medium-Range Weather Forecasts(ECMWF)Newsletter,No.115,12–18.

    Vannitsem,S.,and F.Chom′e,2005:One-way nested regional climate simulations and domain size.J.Climate,18(1),229–233.

    Wang,W.,and N.L.Seaman,1997:A comparison study of convectiveparameterizationschemesinamesoscalemodel.Mon. Wea.Rev.,125(2),252–278.

    Wang,B.,and R.Wu,1997:Peculiar temporal structure of the South China Sea summer monsoon.Adv.Atmos.Sci.,14(2), 177–194,doi:10.1007/s00376-997-0018-9.

    Wang,X.,Q.Bao,K.Liu,G.Wu,and Y.Liu,2011:Features of rainfall and latent heating structure simulated by two convectiveparameterizationschemes.ScienceChinaEarthSciences, 54(11),1779–1788.

    Wu,W.,A.H.Lynch,and A.Rivers,2005:Estimating the uncertainty in a regional climate model related to initial and lateral boundary conditions.J.Climate,18(7),917–933.

    Xue,Y.,R.Vasic,Z.Janjic,F.Mesinger,and K.E.Mitchell,2007: Assessment of dynamic downscaling of the continental US regional climate using the Eta/SSiB regional climate model.J.Climate,20(16),4172–4193.

    Yatagai,A.,K.Kamiguchi,O.Arakawa,A.Hamada,N.Yasutomi,and A.Kitoh,2012:APHRODITE:Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges.Bull.Amer.Meteor.Soc., 93(9),1401–1415.

    Yhang,Y.B.,and S.Y.Hong,2008:Improved physical processes in a regional climate model and their impact on the simulated summer monsoon circulations over East Asia.J.Climate,21(5),963–979.

    Zanis,P.,C.Douvis,I.Kapsomenakis,I.Kioutsioukis,D.Melas, and J.S.Pal,2009:A sensitivity study of the Regional ClimateModel(RegCM3)totheconvectiveschemewithemphasis in central eastern and southeastern Europe.Theor.Appl. Climatol.,97(3–4),327–337.

    Zhong,Z.,2006:A possible cause of a regional climate model’s failure in simulating the East Asian summer monsoon.Geophys.Res.Lett.,33,L24707,doi:10.1029/2006GL027654.

    :Ali,S.,L.Dan,C.B.Fu,and Y.Yang,2015:Performance of convective parameterization schemes in Asia using RegCM:Simulations in three typical regions for the period 1998–2002.Adv.Atmos.Sci.,32(5),715–730,

    10.1007/s00376-014-4158-4.

    (Received 11 July 2014;revised 20 September 2014;accepted 26 September 2014)

    ?Corresponding author:DAN Li

    Email:danli@tea.ac.cn

    a级毛片免费高清观看在线播放| 日韩精品中文字幕看吧| 国产欧美日韩一区二区精品| 日韩高清综合在线| 美女黄网站色视频| 亚洲综合色惰| 变态另类丝袜制服| 自拍偷自拍亚洲精品老妇| 欧美+日韩+精品| 一个人看视频在线观看www免费| 91狼人影院| 亚洲专区国产一区二区| 国产真实伦视频高清在线观看 | 日韩精品中文字幕看吧| 亚洲片人在线观看| 俄罗斯特黄特色一大片| 国产视频内射| 91在线观看av| 欧美又色又爽又黄视频| 淫秽高清视频在线观看| 热99re8久久精品国产| 最近最新中文字幕大全电影3| 真人做人爱边吃奶动态| 国产精品久久久久久亚洲av鲁大| 国产黄a三级三级三级人| 欧美一区二区国产精品久久精品| 午夜激情欧美在线| 国产在视频线在精品| 十八禁国产超污无遮挡网站| 国产一区二区激情短视频| 色精品久久人妻99蜜桃| 亚洲精品日韩av片在线观看| 男女床上黄色一级片免费看| 岛国在线免费视频观看| 啪啪无遮挡十八禁网站| 在线观看午夜福利视频| 久久久久久大精品| 亚洲狠狠婷婷综合久久图片| 国产高清有码在线观看视频| 亚洲av电影在线进入| 欧美成人性av电影在线观看| 男人舔女人下体高潮全视频| 国产精品一区二区免费欧美| 色视频www国产| 午夜福利在线观看吧| 欧美性猛交╳xxx乱大交人| 日韩中字成人| 国产一区二区在线观看日韩| av天堂在线播放| 日韩精品中文字幕看吧| 色综合婷婷激情| 高潮久久久久久久久久久不卡| 乱码一卡2卡4卡精品| 成人国产综合亚洲| 久久精品国产清高在天天线| 免费观看的影片在线观看| 欧美日韩亚洲国产一区二区在线观看| 亚洲无线观看免费| 一级a爱片免费观看的视频| 俄罗斯特黄特色一大片| 免费黄网站久久成人精品 | 亚洲av电影在线进入| 最近最新免费中文字幕在线| bbb黄色大片| 嫁个100分男人电影在线观看| 欧美精品国产亚洲| 久久人人爽人人爽人人片va | 久久精品国产亚洲av天美| www.熟女人妻精品国产| 观看免费一级毛片| 欧美日韩亚洲国产一区二区在线观看| 久久久国产成人免费| 久久久久久久精品吃奶| 俄罗斯特黄特色一大片| or卡值多少钱| 国产爱豆传媒在线观看| 日韩中文字幕欧美一区二区| 欧美不卡视频在线免费观看| 亚洲av电影不卡..在线观看| 国产成人a区在线观看| 亚洲不卡免费看| 国产单亲对白刺激| 首页视频小说图片口味搜索| 日韩有码中文字幕| 久久草成人影院| 丁香六月欧美| 午夜福利18| 丰满乱子伦码专区| 国产亚洲欧美98| 日日摸夜夜添夜夜添av毛片 | 床上黄色一级片| 三级毛片av免费| 18+在线观看网站| av天堂在线播放| 制服丝袜大香蕉在线| 男人狂女人下面高潮的视频| 亚洲最大成人中文| 免费电影在线观看免费观看| 熟女人妻精品中文字幕| 在线国产一区二区在线| 久久精品国产自在天天线| 女人十人毛片免费观看3o分钟| 精品日产1卡2卡| 757午夜福利合集在线观看| 男女下面进入的视频免费午夜| 亚洲国产精品成人综合色| 亚洲av电影不卡..在线观看| 日本黄大片高清| 99在线人妻在线中文字幕| 亚洲人成电影免费在线| 赤兔流量卡办理| 日本五十路高清| 免费大片18禁| 一卡2卡三卡四卡精品乱码亚洲| 伦理电影大哥的女人| 久久婷婷人人爽人人干人人爱| 成人无遮挡网站| 国产综合懂色| 老熟妇仑乱视频hdxx| 一个人免费在线观看的高清视频| 老司机福利观看| 国产成+人综合+亚洲专区| 亚洲成人中文字幕在线播放| 十八禁人妻一区二区| 高清在线国产一区| 一区二区三区高清视频在线| 少妇裸体淫交视频免费看高清| 国产v大片淫在线免费观看| 亚洲国产精品合色在线| 国内揄拍国产精品人妻在线| 18美女黄网站色大片免费观看| 日韩欧美国产在线观看| 久久精品人妻少妇| 日韩av在线大香蕉| 久久久久久久亚洲中文字幕 | 久久精品国产99精品国产亚洲性色| 天堂av国产一区二区熟女人妻| 日韩欧美国产一区二区入口| 国产伦人伦偷精品视频| 老女人水多毛片| 午夜福利高清视频| 亚洲第一欧美日韩一区二区三区| 日韩大尺度精品在线看网址| 老熟妇仑乱视频hdxx| 日韩欧美免费精品| 久久久久精品国产欧美久久久| 1000部很黄的大片| 女人十人毛片免费观看3o分钟| 国产综合懂色| 午夜福利18| 一区二区三区免费毛片| 欧美最黄视频在线播放免费| 精华霜和精华液先用哪个| 中国美女看黄片| 久久人妻av系列| 99久久九九国产精品国产免费| eeuss影院久久| 噜噜噜噜噜久久久久久91| 狂野欧美白嫩少妇大欣赏| 日日夜夜操网爽| 女同久久另类99精品国产91| 美女黄网站色视频| 亚洲最大成人手机在线| 亚洲在线观看片| 免费在线观看影片大全网站| 在线免费观看的www视频| 国产精品1区2区在线观看.| 亚洲精品亚洲一区二区| 亚洲av免费在线观看| 嫩草影院入口| 最新在线观看一区二区三区| 国产激情偷乱视频一区二区| 日本黄色视频三级网站网址| www日本黄色视频网| 极品教师在线免费播放| 国产亚洲欧美98| 亚洲一区二区三区不卡视频| 国产精品影院久久| 亚州av有码| 国产主播在线观看一区二区| 久久精品国产清高在天天线| 香蕉av资源在线| 国产高清视频在线观看网站| 色在线成人网| 9191精品国产免费久久| 夜夜躁狠狠躁天天躁| 中文资源天堂在线| 观看免费一级毛片| 久久久久久久亚洲中文字幕 | avwww免费| 99久久精品热视频| 97碰自拍视频| 国产黄a三级三级三级人| 最近在线观看免费完整版| 午夜日韩欧美国产| 国产蜜桃级精品一区二区三区| 成人性生交大片免费视频hd| 又黄又爽又免费观看的视频| 亚洲av成人av| 日本在线视频免费播放| 一区二区三区高清视频在线| 最后的刺客免费高清国语| 在线国产一区二区在线| 天堂动漫精品| 色av中文字幕| 欧美又色又爽又黄视频| 亚洲欧美日韩高清专用| 一级黄色大片毛片| 成年女人永久免费观看视频| 最近最新中文字幕大全电影3| 日本免费一区二区三区高清不卡| 国产一区二区激情短视频| 夜夜夜夜夜久久久久| 欧美一级a爱片免费观看看| 99久久久亚洲精品蜜臀av| av欧美777| 免费av毛片视频| 91av网一区二区| 热99在线观看视频| 欧美精品国产亚洲| 一区二区三区四区激情视频 | 亚洲美女搞黄在线观看 | av在线天堂中文字幕| 欧美zozozo另类| 美女 人体艺术 gogo| 在线观看舔阴道视频| 黄片小视频在线播放| 很黄的视频免费| 在线观看免费视频日本深夜| 岛国在线免费视频观看| 免费一级毛片在线播放高清视频| 色噜噜av男人的天堂激情| 18美女黄网站色大片免费观看| 国产亚洲精品av在线| 97超视频在线观看视频| 国产69精品久久久久777片| av福利片在线观看| 一区二区三区四区激情视频 | 国产伦人伦偷精品视频| 日韩大尺度精品在线看网址| 宅男免费午夜| 国产精品久久电影中文字幕| 在线观看av片永久免费下载| 99riav亚洲国产免费| 看黄色毛片网站| 国产私拍福利视频在线观看| 国产成人aa在线观看| 久久久久久久久久成人| 国产一区二区亚洲精品在线观看| 直男gayav资源| 自拍偷自拍亚洲精品老妇| 一本一本综合久久| 全区人妻精品视频| 嫩草影院入口| 国产毛片a区久久久久| 国产av不卡久久| 国产成人啪精品午夜网站| 我的老师免费观看完整版| 午夜亚洲福利在线播放| 韩国av一区二区三区四区| 精品午夜福利在线看| 如何舔出高潮| 精品久久久久久,| 亚洲国产色片| 在线观看免费视频日本深夜| 毛片一级片免费看久久久久 | 成年版毛片免费区| а√天堂www在线а√下载| 99久久成人亚洲精品观看| 亚洲欧美日韩无卡精品| 亚洲成a人片在线一区二区| aaaaa片日本免费| 99视频精品全部免费 在线| 我要搜黄色片| 欧美日本视频| 国产一区二区在线av高清观看| 亚洲人成网站在线播| 日本五十路高清| 精品一区二区三区视频在线| 亚洲中文字幕一区二区三区有码在线看| 俄罗斯特黄特色一大片| 日日夜夜操网爽| 他把我摸到了高潮在线观看| 午夜福利成人在线免费观看| 久久国产乱子免费精品| 欧美丝袜亚洲另类 | 成人国产一区最新在线观看| 给我免费播放毛片高清在线观看| 午夜两性在线视频| 免费观看人在逋| 高潮久久久久久久久久久不卡| 国产三级在线视频| 两人在一起打扑克的视频| 日本黄色视频三级网站网址| 99riav亚洲国产免费| 国产免费男女视频| 成人毛片a级毛片在线播放| 丰满人妻一区二区三区视频av| 欧美色视频一区免费| 又爽又黄a免费视频| 黄色配什么色好看| netflix在线观看网站| 国内精品久久久久精免费| 好看av亚洲va欧美ⅴa在| 三级男女做爰猛烈吃奶摸视频| 欧美日本亚洲视频在线播放| 97超视频在线观看视频| 狠狠狠狠99中文字幕| 精品人妻一区二区三区麻豆 | 五月玫瑰六月丁香| 最近中文字幕高清免费大全6 | 深夜精品福利| 99国产精品一区二区蜜桃av| 午夜老司机福利剧场| 亚洲第一欧美日韩一区二区三区| 人妻制服诱惑在线中文字幕| av中文乱码字幕在线| 久久久久久久午夜电影| 一卡2卡三卡四卡精品乱码亚洲| 久久国产精品影院| 免费电影在线观看免费观看| 很黄的视频免费| 九九在线视频观看精品| 国产精品自产拍在线观看55亚洲| 91麻豆av在线| 欧美区成人在线视频| 亚洲av成人av| 久久久色成人| 欧美最黄视频在线播放免费| 久久香蕉精品热| 亚洲欧美日韩无卡精品| 亚洲av电影在线进入| 亚洲欧美激情综合另类| 亚洲无线观看免费| 热99在线观看视频| 国模一区二区三区四区视频| 国产单亲对白刺激| 亚洲国产高清在线一区二区三| 丰满乱子伦码专区| 国产69精品久久久久777片| 草草在线视频免费看| 免费看a级黄色片| 性色avwww在线观看| 国产av麻豆久久久久久久| 亚洲经典国产精华液单 | 在线观看午夜福利视频| 老女人水多毛片| 特级一级黄色大片| 日本五十路高清| 精品久久国产蜜桃| 亚洲欧美清纯卡通| 观看免费一级毛片| 悠悠久久av| 88av欧美| 三级毛片av免费| 午夜视频国产福利| 午夜福利高清视频| 长腿黑丝高跟| 国产成人欧美在线观看| 在线观看免费视频日本深夜| 嫁个100分男人电影在线观看| 亚洲无线观看免费| 国产精品一区二区三区四区久久| 极品教师在线视频| 日本免费一区二区三区高清不卡| 极品教师在线免费播放| 欧美日韩亚洲国产一区二区在线观看| 18+在线观看网站| 欧美日韩黄片免| or卡值多少钱| 亚洲成a人片在线一区二区| 成人永久免费在线观看视频| 91av网一区二区| 一边摸一边抽搐一进一小说| 国产成人欧美在线观看| 成人高潮视频无遮挡免费网站| 精品人妻视频免费看| 亚洲熟妇熟女久久| 日本撒尿小便嘘嘘汇集6| 午夜日韩欧美国产| 少妇被粗大猛烈的视频| 亚洲av熟女| 九色国产91popny在线| 91麻豆精品激情在线观看国产| 欧洲精品卡2卡3卡4卡5卡区| 国产精品一及| 久久人妻av系列| 美女高潮喷水抽搐中文字幕| 国产av一区在线观看免费| 国产高清激情床上av| 亚洲第一电影网av| 深夜精品福利| 99久久精品一区二区三区| 长腿黑丝高跟| 国产亚洲精品综合一区在线观看| 免费观看人在逋| 亚洲va日本ⅴa欧美va伊人久久| а√天堂www在线а√下载| 日韩精品中文字幕看吧| 午夜福利在线观看吧| 精品福利观看| 99久久无色码亚洲精品果冻| 国产视频一区二区在线看| 久久久久九九精品影院| 国产高潮美女av| 51国产日韩欧美| 又粗又爽又猛毛片免费看| x7x7x7水蜜桃| 婷婷色综合大香蕉| 级片在线观看| 变态另类丝袜制服| 国产熟女xx| 亚洲av一区综合| 99riav亚洲国产免费| 午夜日韩欧美国产| 亚洲av美国av| 国产精品亚洲av一区麻豆| 国产精品98久久久久久宅男小说| 成人特级av手机在线观看| 欧美丝袜亚洲另类 | 亚洲男人的天堂狠狠| 免费看光身美女| 亚洲av.av天堂| 日韩欧美精品免费久久 | 亚洲av免费在线观看| 男人狂女人下面高潮的视频| 中文亚洲av片在线观看爽| 亚洲性夜色夜夜综合| 久久精品国产亚洲av天美| 亚洲成人久久性| 欧美日韩中文字幕国产精品一区二区三区| 一区二区三区四区激情视频 | 长腿黑丝高跟| 中文资源天堂在线| 啪啪无遮挡十八禁网站| 永久网站在线| 亚洲人成伊人成综合网2020| 国产一区二区在线观看日韩| 真实男女啪啪啪动态图| 成人特级av手机在线观看| 成人永久免费在线观看视频| 性插视频无遮挡在线免费观看| 亚洲成人免费电影在线观看| 成年人黄色毛片网站| 在线观看av片永久免费下载| 亚洲精品456在线播放app | 99国产综合亚洲精品| 99久久99久久久精品蜜桃| АⅤ资源中文在线天堂| 精品日产1卡2卡| 日韩成人在线观看一区二区三区| 中文字幕精品亚洲无线码一区| 又紧又爽又黄一区二区| 搡老妇女老女人老熟妇| 亚洲人成网站高清观看| 欧美精品啪啪一区二区三区| 3wmmmm亚洲av在线观看| 黄色视频,在线免费观看| 看片在线看免费视频| 天堂动漫精品| 久久久久精品国产欧美久久久| 最新中文字幕久久久久| 亚洲人成网站在线播| 欧美黄色片欧美黄色片| 亚洲成av人片在线播放无| 午夜亚洲福利在线播放| 精品不卡国产一区二区三区| 一级作爱视频免费观看| 亚洲精品日韩av片在线观看| 国产又黄又爽又无遮挡在线| 天堂√8在线中文| 亚洲国产日韩欧美精品在线观看| 亚洲七黄色美女视频| 熟女电影av网| 日韩 亚洲 欧美在线| 97人妻精品一区二区三区麻豆| 99久久成人亚洲精品观看| 变态另类丝袜制服| 亚洲va日本ⅴa欧美va伊人久久| 欧美xxxx黑人xx丫x性爽| 夜夜看夜夜爽夜夜摸| 午夜激情欧美在线| av欧美777| 国内精品久久久久精免费| 欧美性猛交╳xxx乱大交人| 亚洲色图av天堂| 好男人在线观看高清免费视频| 亚洲精品亚洲一区二区| 蜜桃久久精品国产亚洲av| 欧美精品国产亚洲| 国产精品99久久久久久久久| 最近最新免费中文字幕在线| 国内少妇人妻偷人精品xxx网站| 老司机午夜十八禁免费视频| 一区福利在线观看| 国产色婷婷99| 国产一区二区三区在线臀色熟女| 国产精品1区2区在线观看.| 成人av在线播放网站| 欧美日本亚洲视频在线播放| 亚洲天堂国产精品一区在线| 久久久久久久午夜电影| 国产乱人伦免费视频| av女优亚洲男人天堂| 在线观看av片永久免费下载| 亚洲avbb在线观看| 国产黄a三级三级三级人| 欧美乱色亚洲激情| 亚洲精华国产精华精| 久久久久久九九精品二区国产| 日本黄色片子视频| 欧美午夜高清在线| 91在线观看av| 一个人观看的视频www高清免费观看| 国内精品美女久久久久久| 在线免费观看不下载黄p国产 | 国产野战对白在线观看| 99热这里只有是精品在线观看 | 亚洲成a人片在线一区二区| av中文乱码字幕在线| 99热这里只有是精品在线观看 | 97超级碰碰碰精品色视频在线观看| 波多野结衣高清无吗| 国产麻豆成人av免费视频| 欧美一区二区精品小视频在线| 久99久视频精品免费| 国产高清视频在线播放一区| 最近在线观看免费完整版| 日韩免费av在线播放| 51国产日韩欧美| 99国产极品粉嫩在线观看| 麻豆av噜噜一区二区三区| 少妇人妻一区二区三区视频| 亚洲一区高清亚洲精品| 成人毛片a级毛片在线播放| 亚洲精品影视一区二区三区av| 久久久久免费精品人妻一区二区| 我要搜黄色片| 人妻制服诱惑在线中文字幕| 国产伦人伦偷精品视频| 黄色配什么色好看| 久久天躁狠狠躁夜夜2o2o| 国产黄片美女视频| 久久国产精品影院| 免费观看人在逋| 亚洲国产精品合色在线| 老鸭窝网址在线观看| 夜夜看夜夜爽夜夜摸| 一边摸一边抽搐一进一小说| 精品国产亚洲在线| 日韩有码中文字幕| 日韩人妻高清精品专区| x7x7x7水蜜桃| 美女大奶头视频| 丰满人妻熟妇乱又伦精品不卡| 最新中文字幕久久久久| 久久草成人影院| 3wmmmm亚洲av在线观看| 日本三级黄在线观看| 亚洲片人在线观看| 99热这里只有精品一区| 成人毛片a级毛片在线播放| 中文字幕精品亚洲无线码一区| 麻豆久久精品国产亚洲av| 午夜老司机福利剧场| 色哟哟哟哟哟哟| 国产成人aa在线观看| av中文乱码字幕在线| 欧美黄色淫秽网站| www日本黄色视频网| 欧美高清性xxxxhd video| 久久中文看片网| 99热精品在线国产| 90打野战视频偷拍视频| 免费看光身美女| 最近最新免费中文字幕在线| 午夜福利在线观看免费完整高清在 | 国产三级中文精品| 在线免费观看不下载黄p国产 | av欧美777| 乱码一卡2卡4卡精品| 国产国拍精品亚洲av在线观看| av专区在线播放| 欧美激情在线99| 麻豆成人av在线观看| 精品熟女少妇八av免费久了| 2021天堂中文幕一二区在线观| 观看免费一级毛片| 91在线精品国自产拍蜜月| 大型黄色视频在线免费观看| 乱码一卡2卡4卡精品| 51午夜福利影视在线观看| 悠悠久久av| 久久伊人香网站| 一级毛片久久久久久久久女| 成人av一区二区三区在线看| 少妇人妻精品综合一区二区 | 成人午夜高清在线视频| 在线a可以看的网站| 久久九九热精品免费| 欧美+亚洲+日韩+国产| 午夜福利成人在线免费观看| 亚洲av.av天堂| 中文字幕高清在线视频| 亚洲国产精品成人综合色| 三级国产精品欧美在线观看| 美女高潮的动态| 久久久久久久久大av| 99久久99久久久精品蜜桃| 97热精品久久久久久| 国产高清视频在线播放一区| 两人在一起打扑克的视频| 国产精品免费一区二区三区在线| 久久久久免费精品人妻一区二区| 高清毛片免费观看视频网站|