AN IMPROVED LAND-SURFACE PROCESS MODEL AND ITS SIMULATION EXPERIMENT——PART I:LAND-SURFACE PROCESS MODEL AND ITS“OFF-LINE”TESTS AND PERFORMANCE ANALYSES

Based on the existing land-surface schemes and models,an improved Land-surface ProcessModel(LPM-ZD)has been developed.It has the following major characteristics:(1)Thecombination of physical equations and empirical analytical formulae are used to construct thegoverning equations of soil temperature and moisture.Higher resolution of model level andphysical equations are adopted for the upper soil layers,and for the lower soil layers,lowerresolution of model level is adopted and empirical analytical formulae are used.(2)In land surfacehydrological process,the sub-grid distribution of rainfall and its effects are taken into account.(3)A simple snow cover submodel has been used,which includes effects of snow cover on soilthermodynamics and hydrology,as well as albedo.By use of this model and three groups of point observation data,a series of“off-line”testshave been carried out.The simulation results indicate that land-surface process model has goodperformance and can well simulate diurnal and seasonal variation of land surface processes for manykinds of land surface covers(forest,grass,crops and desert)in different climate zone.The resultssimulated by the model are consistent with the observations.Later,by use of one group ofobservation data and the model,a series of sensitivity experiments have been done.It is shownthat the model is much sensitive to some parameters,such as initial soil moisture,vegetationphysical parameters as well as the proportion of the grid covered with rain.Therefore it is muchimportant for land-surface process model to define these parameters as accurately as possible.     

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.     

The cloud processes of a simulated moderate snowfall event in North China

The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event in North China that occurred during 20–21 December 2002. Thirteen experiments are performed to test the sensitivity of the simulation to the cloud physics with different cumulus parameterization schemes and different options for the Goddard cloud microphysics parameterization schemes. It is shown that the cumulus parameterization scheme has little to do with the simulation result. The results also show that there are only four classes of water substances, namely the cloud water, cloud ice, snow, and vapor, in the simulation of the moderate snowfall event. The analysis of the cloud microphysics budgets in the explicit experiment shows that the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow, and the Bergeron process of cloud ice are the dominant cloud microphysical processes in the simulation. The accretion of cloud water by snow and the deposition growth of the snow are equally important in the development of the snow.     

Numerical Simulation of the Evolution of Snow Cover and Its Sensitivity Experiments

By using Comprehensive Land Surface Model (CLSM), three snow cases, i.e., France Col de Porte 1993/1994, 1994/1995 and BOREAS SSA-OJP 1994/1995, were simulated. The simulated results were compared with the observations to examine the capability of the model to describe the evolutions of snow cover under two different land cover conditions. Several sensitivity experiments were performed to investigate the effects of the parameterization schemes of some snow cover internal processes and vegetation on the model results. Results suggest that the CLSM simulates the basic processes of snow cover accurately and describes the features of snow cover evolutions reasonably, indicating that the model has the potential to model the processes related to the snow cover evolution. It is also found that the different parameterization schemes of the snowfall density and snow water holding capacity have significant effects on the simulation of snow cover. The estimation of snowfall density mainly impacts the simulated snow depth, and the underestimation (overestimation) of the snowfall density increases (decreases) the snow depth simulated significantly but with little effect on the simulated snow water equivalent (SWE). The parameterization of the snow water holding capacity plays a crucial role in the evolution of snow cover, especially in the ablation of snow cover. Larger snow water holding capacity usually leads to larger snow density and heat capacity by storing more liquid water in the snow layer, and makes the temperature of snow cover and the snow ablation vary more slowly. To a smaller snow water holding capacity, contrary is the case. The results also show that the physical processes related to the snow cover variation are different, which are dependent on the vegetation existed. Vegetation plays an important role in the evolution of soil-snow system by changing the energy balance at the snow-soil surface. The existence of vegetation is favorable to the maintenance of snow cover and delays the increase of underlying soil temperature.     

IMPROVEMENTS OF A DISTRIBUTED HYDROLOGY MODEL DHSVM AND ITS CLIMATOLOGICAL-HYDROLOGICAL OFF-LINE SIMULATIONAL EXPERIMENTS

The advanced distributed hydrology-soil-vegetation model DHSVM,developed by Wigmostaet al.(1994)is introduced from US Pacific Northwest National Laboratory.To apply DHSVM inChina for the first time some improvements have been made in terms of the basin characteristics:1)to change evapotranspiration model,using the improved Penman-Monteith approach in place ofthe original one;2)to change the model structure,inserting datasets from 4 stations to grid cellsfor each river basin,instead of datasets from one or two stations;3)to develop new hydrology,vegetation and soil parameterization schemes for improving the simulated results,with focus oncalculation and adjustment of 11 parameters,such as soil porosity (?),field capacity θ_(fc),leaf areaindex LAI,stochastic resistance γ_s,among the total 33 parameters.Then the improved DHSVM isdriven by observed datasets for Luanhe River Basin and Sanggan River Basin,respectively.Thesimulated evapotranspiration(ET),runoff,snow water equivalent,water table,soil moisture andpercolation are then gained as DHSVM outputs.The simulated ET shows that the highest peakappears in May or June instead of July or August.This is consistent with the real situations,owing to the improvement of ET model.The simulated runoff process and flood peak are quiteconsistent with the observed ones.The model efficiency values for Luanhe River and SangganRiver Basins are 0.89 and 0.82,respectively,which shows high simulating ability of the modelsystem for both relatively humid and dry basins.     

A NUMERICAL STUDY OF TROPICAL DEEP CONVECTION USING WRF MODEL

The Weather Research Forecast model (WRF) configured with high resolution and NCEP 1°×1° reanalysis data were used to simulate the development of a tropical deep convection over the Tiwi Islands,northern Australia,and to investigate the sensitivity of model results to model configuration and parameterization schemes of microphysical processes.The simulation results were compared with available measurements.The results show that the model can reproduce most of the important characteristics of the observed diurnal evolution of the convection,including the initiation of convection along the sea-breeze front,which is then reinforced by downdraft outflows,merging of cells and the formation of a deep convective system.However,further improvement is needed to simulate more accurately the location and the time for initiation of the deep convective system.Sensitivity tests show that double-nesting schemes are more accurate than the non-nesting schemes in predicting the distribution and intensity of precipitation as far as this particular case is concerned.Additionally,microphysical schemes also have an effect on the simulated amount of precipitation.It is shown that the best agreement is reached between the simulation results and observations when the Purdue Lin scheme is used.     

Aerosol-Cloud-Precipitation Interactions in WRF Model: Sensitivity to Autoconversion Parameterization

Cloud-to-rain autoconversion process is an important player in aerosol loading, cloud morphology, and precipitation variations because it can modulate cloud microphysical characteristics depending on the participation of aerosols, and affects the spatio-temporal distribution and total amount of precipitation. By applying the Kessler, the Khairoutdinov-Kogan(KK), and the Dispersion autoconversion parameterization schemes in a set of sensitivity experiments, the indirect effects of aerosols on clouds and precipitation are investigated for a deep convective cloud system in Beijing under various aerosol concentration backgrounds from 50 to 10000 cm-3. Numerical experiments show that aerosol-induced precipitation change is strongly dependent on autoconversion parameterization schemes. For the Kessler scheme, the average cumulative precipitation is enhanced slightly with increasing aerosols, whereas surface precipitation is reduced significantly with increasing aerosols for the KK scheme. Moreover, precipitation varies non-monotonically for the Dispersion scheme, increasing with aerosols at lower concentrations and decreasing at higher concentrations.These different trends of aerosol-induced precipitation change are mainly ascribed to differences in rain water content under these three autoconversion parameterization schemes. Therefore, this study suggests that accurate parameterization of cloud microphysical processes, particularly the cloud-to-rain autoconversion process, is needed for improving the scientific understanding of aerosol-cloud-precipitation interactions.     

Development of a model for water and heat exchange between the atmosphere and a water body

A model for studying the heat and mass exchange between the atmosphere and a water body is developed, in which the phase change process of water freezing in winter and melting in summer and the function of the convective mixing process are taken into consideration. The model uses enthalpy rather than temperature as the predictive variable. It helps to set up governing equations more concisely, to deal with the phase change process more easily, and make the numerical scheme simpler. The model is verified by observed data from Lake Kinneret for a non-frozen lake in summer time, and Lake Lower Two Medicine for a frozen lake in winter time. Reasonably good agreements between the model simulations and observed data indicate that the model can serve as a component for a water body in a land surface model. In order to more efficiently apply the scheme in a climate system model, a sensitivity study of various division schemes with less layers in the vertical direction in the water body is conducted. The results of the study show that the division with around 10 vertical layers could produce a prediction accuracy that is comparable to the fine division with around 40 layers.     

EXPERIMENTAL STUDIES WITH AN OPERATIONAL NUMERICAL MODEL FOR PREDICTION OF TYPHOON TRACKS OVER THE SOUTH CHINA SEA REGION

Experiments for short range forecasting of typhoon tracks over the South China Sea Region were carried out using limited-area numerical model recently developed by the authors.Due to the shortage of sounding data over the sea, typhoon circulations are usually obtained incompletely from objective analysis, or with significant deviation of the centre from reality.Therefore a set of schemes for typhoon initialization are proposed here to construct a bogus typhoon with the circulation being consistent with the physical processes included in the limited-area model.Based on the schemes bogus data over the model grids are created and analysed together with conventional observational data.Then the normal model initialization scheme is issued to further modulate the model typhoon with the numeriCal modeel.Some experiments of sensitivity in various aspects are conducted for further improvement of typhoon track predictions.The experimental results for a number of typhoon landing in southern China in 1993 and 1994 shows that the limited-area model is capable of predicting typhoon tracks in the southern China region.     

A model for retrieval of dual linear polarization radar fields from model simulation outputs

An algorithm for retrieving polarimetric variables from numerical model fields is developed. By using this technique, radar reflectivity at horizontal polarization~ differential reflectivity, specific differential phase shift and correlation coefficients between the horizontal and vertical polarization signals at zero lag can be derived from rain, snow and hail contents of numerical model outputs. Effects of environmental temperature and the melting process on polarimetric variables are considered in the algorithm. The algorithm is applied to the Advanced Regional Prediction System （ARPS） model simulation results for a hail storm. The spatial distributions of the derived parameters are reasonable when compared with observational knowledge. This work provides a forward model for assimilation of dual linear polarization radar data into a mesoscale model.     

用于气候研究的雪盖模型参数化方案敏感性研究

为了得到一个适用于气候研究简化的季节性雪盖模式最佳方案,必须对雪盖内部的重要物理过程、其与上大气相互作用、相应模型的参数化方案和有关的参数选取以及模型的分层结构进行深入研究.利用作者的雪盖模型(SAST),对其中的一些关键性过程的有关参数化方案(如压实、相变、融化雪水流动及分层方案考虑等)及关键的参数(如雪面反照率、有效热传导系数及持水能力等)进行了分析和敏感性试验,得到若干有意义的结论,为雪盖模式改进提供有用的结论.     

An Intercomparison Among Four Models Of Blowing Snow

Four one-dimensional, time-dependent blowing snow models areintercompared. These include three spectral models, PIEKTUK-T,WINDBLAST, SNOWSTORM, and the bulk version of PIEKTUK-T,PIEKTUK-B. Although the four models are based on common physicalconcepts, they have been developed by different research groups. Thestructure of the models, numerical methods, meteorological field treatmentand the parameterization schemes may be different. Under an agreed standardcondition, the four models generally give similar results for the thermodynamic effects of blowing snow sublimation on the atmospheric boundary layer, including an increase of relative humidity and a decrease of the ambient temperature due to blowing snow sublimation. Relative humidity predicted by SNOWSTORM is lower than the predictions of the other models, which leads to a larger sublimation rate in SNOWSTORM. All four models demonstrate that sublimation rates in a column of blowing snow have a single maximum in time, illustrating self-limitation of the sublimation process of blowing snow. However, estimation of the eddy diffusioncoefficient for momentum (K_m), and thereby the diffusion coefficients for moisture (K_w) and for heat (K_h), has a significant influence on the process. Sensitivitytests with PIEKTUK-T show that the sublimation rate can be approximately constant with time after an initial phase, if K_m is a linear function with height. In order to match the model results with blowing snow observations, some parameters in the standard run, such as settling velocity of blowing snow particles in these models, may need to be changed to more practical values.     

Improvement of a Snow Albedo Parameterization in the Snow–Atmosphere–Soil Transfer Model:Evaluation of Impacts of Aerosol on Seasonal Snow Cover

The presence of light-absorbing aerosols(LAA) in snow profoundly influence the surface energy balance and water budget.However,most snow-process schemes in land-surface and climate models currently do not take this into consideration.To better represent the snow process and to evaluate the impacts of LAA on snow,this study presents an improved snow albedo parameterization in the Snow–Atmosphere–Soil Transfer(SAST) model,which includes the impacts of LAA on snow.Specifically,the Snow,Ice and Aerosol Radiation(SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme.The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot(SASP),Colorado,USA.Results show that the snow albedo and snow depth are better reproduced than those in the original SAST,particularly during the period of snow ablation.Furthermore,the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack,with or without LAA.The LAA particles directly absorb extra solar radiation,which accelerates the growth rate of the snow grain size.Meanwhile,these larger snow particles favor more radiative absorption.The average total radiative forcing of the LAA at the SASP is 47.5Wm~(-2).This extra radiative absorption enhances the snowmelt rate.As a result,the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier,respectively,which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.     

青海高原牧区雪灾综合预警评估模型研究

应用灾害学的理论和观点，以青海牧区为研究对象，对造成青藏高原雪灾的致灾因子、孕灾环境和承灾体等要素综合分析。建立从降水、积雪、成灾、灾情评价的综合判识模型，在地理信息背景数据库的支持下，从产生降水之后，进行快速监测，并对不同地区的雪灾发展趋势做动态预测，最后实施灾情评估。结果表明：在青藏高原的雪灾形成过程中，除积雪的直接致灾作用之外，孕灾环境的脆弱性和承灾体的敏感性也起着重要的作用。提出保护草场、加强草原畜牧业配套设施建设等措施，可以发挥人类抗灾的能动性，降低雪灾级别。最后应用综合预警模型，对发生在青海境内的雪灾过程进行了预测，效果较好，模型具有业务应用潜力。     

基于GIS的雪灾风险区划

依据巴彦淖尔地区冬春季节降水少、年变率大的气候特点和易形成雪灾的量级指标进行雪灾风险区划。选取1971—2010年11月到次年3月,日降雪量大于等于3mm,并出现积雪和结冰现象为研究对象,分析了降雪量大于等于3mm的降雪日数和积雪深度大于等于5cm的积雪日数年代际变化,结合民政部门历史灾情记载、实地调查、农牧业现状以及各种基础资料数据与GIS技术,从致灾因子、脆弱性评估分析方面,在NOAA卫星遥感雪覆盖监测图像上,利用加权综合与层次分析法,构建雪灾判别模型,得出巴彦淖尔地区雪灾风险区划:雪灾最严重的地区为五原县大部、乌前旗南部和东北部部分区域、乌中旗东南和西南两区域、乌后旗的海力素附近大片区域。     

不同积雪深度下地面温度与雪面温度的相关

基于新疆昌吉州5个国家气象站2008—2010年积雪深度大于等于0 cm的实测地面温度与雪面温度,对0 cm地面温度（含最高、最低）、雪面温度（含最高、最低）及云量、日照时数、雪深进行统计分析,找出不同积雪深度下地面温度与雪面温度的关系,并以阜康市天池气象站2011年所有积雪日数据对关系模型作检验。结果显示：地面温度与雪面温度的关系有3个雪深分层：5 cm以下、6~40 cm和40 cm以上,积雪深度为0~5 cm时,地面温度与雪面温度差值很小,受雪深及天气条件影响明显,雪深6~40 cm,主要受雪深影响,雪深超过40 cm,地面温度趋于定值。     

一个简单的雪晶辐射参数化方案及雪晶辐射对中尺度降水的影响

文章提出一个简单的雪晶辐射性质参数化方案, 并利用1998年6月8日华南暴雨资料研究了雪晶的辐射性质对于中尺度降水的影响。结果表明:雪晶的辐射性质对中尺度降水的影响是不可忽略的, 白天尤为显著; 它能够明显地改变中尺度降水的局部特征, 特别是降水中心的强度和位置, 而对降水的分布影响不大。因此, 建立独立的雪晶辐射参数化对提高中尺度模式对中尺度降水的预报能力是必要的。     

Snow contribution to springtime atmospheric predictability over the second half of the twentieth century

A set of global atmospheric simulations has been performed with the ARPEGE-Climat model in order to quantify the contribution of realistic snow conditions to seasonal atmospheric predictability in addition to that of a perfect sea surface temperature (SST) forcing. The focus is on the springtime boreal hemisphere where the combination of a significant snow cover variability and an increasing solar radiation favour the potential snow influence on the surface energy budget. The study covers the whole 1950?C2000 period through the use of an original snow mass reanalysis based on an off-line land surface model and possibly constrained by satellite snow cover observations. Two ensembles of 10-member AMIP-type experiments have been first performed with relaxed versus free snow boundary conditions. The nudging towards the monthly snow mass reanalysis significantly improves both potential and actual predictability of springtime surface air temperature over Central Europe and North America. Yet, the impact is confined to the lower troposphere and there is no clear improvement in the predictability of the large-scale atmospheric circulation. Further constraining the prescribed snow boundary conditions with satellite observations does not change much the results. Finally, using the snow reanalysis only for initializing the model on March 1st also leads to a positive impact on predicted low-level temperatures but with a weaker amplitude and persistence. A conditional skill approach as well as some selected case studies provide some guidelines for interpreting these results and suggest that an underestimated snow cover variability and a misrepresentation of ENSO teleconnections may hamper the benefit of an improved snow initialization in the ARPEGE-Climat model.     

基于MODIS资料的西藏遥感积雪监测业务化方法

雪灾是西藏地区藏北一线、南部边缘地区对牧业生产影响最严重的灾害之一,利用卫星遥感资料开展积雪监测,提供监测信息产品具有重要的现实意义.利用拉萨接收站接收的中分辨率成像光谱仪(MODIS)卫星遥感资料对西藏高原积雪的监测方法进行了探讨,找出适合该地区的积雪判别模式,建立MODIS资料为基础的积雪监测系统.基于MODIS数据计算得出的归一化差分积雪指数(NDSI)和归一化植被指数(NDVI)与1、2、4、6通道等相结合,建立积雪监测模型是可行的;得出的积雪判识方法对于西藏地区有较高的适用性,如结合地表土地利用类型数据将有林区和非森林区分开计算,能较好地消除藏东南地区因地势复杂、森林茂密对NDSI的影响.