Evaluation of Mediterranean Sea water and heat budgets simulated by an ensemble of high resolution regional climate models

Air-sea heat and freshwater water fluxes in the Mediterranean Sea play a crucial role in dense water formation. Here, we compare estimates of Mediterranean Sea heat and water budgets from a range of observational datasets and discuss the main differences between them. Taking into account the closure hypothesis at the Gibraltar Strait, we have built several observational estimates of water and heat budgets by combination of their different observational components. We provide then three estimates for water budget and one for heat budget that satisfy the closure hypothesis. We then use these observational estimates to assess the ability of an ensemble of ERA40-driven high resolution (25 km) Regional Climate Models (RCMs) from the FP6-EU ENSEMBLES database, to simulate the various components, and net values, of the water and heat budgets. Most of the RCM Mediterranean basin means are within the range spanned by the observational estimates of the different budget components, though in some cases the RCMs have a tendency to overestimate the latent heat flux (or evaporation) with respect to observations. The RCMs do not show significant improvements of the total water budget estimates comparing to ERA40. Moreover, given the large spread found in observational estimates of precipitation over the sea, it is difficult to draw conclusions on the performance of RCM for the freshwater budget and this underlines the need for better precipitation observations. The original ERA40 value for the basin mean net heat flux is ?15 W/m² which is 10 W/m² less than the value of ?5 W/m² inferred from the transport measurements at Gibraltar Strait. The ensemble of heat budget values estimated from the models show that most of RCMs do not achieve heat budget closure. However, the ensemble mean value for the net heat flux is ?7 ± 21 W/m², which is close to the Gibraltar value, although the spread between the RCMs is large. Since the RCMs are forced by the same boundary conditions (ERA40 and sea surface temperatures) and have the same horizontal resolution and spatial domain, the reason for the large spread must reside in the physical parameterizations. To conclude, improvements are urgently required to physical parameterizations in state-of-the-art regional climate models, to reduce the large spread found in our analysis and to obtain better water and heat budget estimates over the Mediterranean Sea.     

Statistical bias correction for daily precipitation in regional climate models over Europe

We design, apply, and validate a methodology for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. We refer to this as a statistical bias correction. Validation of the methodology is carried out using daily precipitation fields, defined over Europe, from the ENSEMBLES climate model dataset. The bias correction is calculated using data from 1961 to 1970, without distinguishing between seasons, and applied to seasonal data from 1991 to 2000. This choice of time periods is made to maximize the lag between calibration and validation within the ERA40 reanalysis period. Results show that the method performs unexpectedly well. Not only are the mean and other moments of the intensity distribution improved, as expected, but so are a drought and a heavy precipitation index, which depend on the autocorrelation spectra. Given that the corrections were derived without seasonal distinction and are based solely on intensity distributions, a statistical quantity oblivious of temporal correlations, it is encouraging to find that the improvements are present even when seasons and temporal statistics are considered. This encourages the application of this method to multi-decadal climate projections.     

Performance of ENSEMBLES regional climate models over Central Europe using various metrics

We show the evaluation of ENSEMBLES regional climate models (RCMs) driven by reanalysis ERA40 over a region centered at the Czech Republic. Attention is paid especially to the model ALADIN-CLIMATE/CZ, being used as the basis of the new climate change scenarios simulation for the Czech Republic. The validation criteria used here are based on monthly or seasonal mean air temperature and precipitation. We concentrate not only on spatiotemporal mean values but also on temporal standard deviation, inter-annual variability, the mean annual cycle, and the skill of the models to represent the observed spatial patterns of these quantities. Model ALADIN-CLIMATE/CZ performs quite well in comparison to the other RCMs; we find its performance satisfactory for further use for impact studies. However, it is also shown that the results of evaluation of the RCMs’ skill in simulating observed climate strongly depend on the criteria incorporated for the evaluation.     

Evaluation of CORDEX regional climate models in simulating temperature and precipitation over the Tibetan Plateau

区域气候模式对研究地形复杂的青藏高原地区气候具有高分辨率的优势。以前的相关研究主要基于单个区域模式,我们评估了CORDEX多区域气候模式对青藏高原气候的模拟能力。结果显示:(1)5个区域气候模式一致模拟出了相似的气温、降水空间模态,但产生了冷偏差和湿偏差。所有区域气候模式未能再现观测的气温、降水趋势空间模态,并且平均高估了气温趋势、低估了降水趋势。综合考虑模拟的气温、降水趋势,多模式集合的结果最优。就单个模式而言,Reg CM4所得趋势最为合理。(2)各区域气候模式结果之间的差异十分显著,表明青藏高原气候模拟具有很大的模式依赖性。这一结果建议当利用单个区域气候模式开展青藏高原气候变化研究时需要谨慎。(3)多区域模式集合预估显示,相对1986–2005年,到2016–2035年气温(降水)将增加1.38±0.09°C(0.8%±4.0%)(RCP4.5)和1.77±0.28°C(7.3%±2.5%)(RCP8.5)。这些结果从多模式角度提高了我们对运用区域气候模式研究青藏高原气候的认识。     

Twenty-first century changes in snowfall climate in Northern Europe in ENSEMBLES regional climate models

Changes in snowfall in northern Europe (55–71°N, 5–35°E) are analysed from 12 regional model simulations of twenty-first century climate under the Special Report on Emissions Scenarios A1B scenario. As an ensemble mean, the models suggest a decrease in the winter total snowfall in nearly all of northern Europe. In the middle of the winter, however, snowfall generally increases in the coldest areas. The borderline between increasing and decreasing snowfall broadly coincides with the ?11 °C isotherm in baseline (1980–2010) monthly mean temperature, although with variation between models and grid boxes. High extremes of daily snowfall remain nearly unchanged, except for decreases in the mildest areas, where snowfall as a whole becomes much less common. A smaller fraction of the snow in the simulated late twenty-first century climate falls on severely cold days and a larger fraction on days with near-zero temperatures. Not only do days with low temperatures become less common, but they also typically have more positive anomalies of sea level pressure and less snowfall for the same temperature than in the present-day climate.     

An inter-comparison of regional climate models for Europe: model performance in present-day climate

The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.     

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs.     

Sources of systematic errors in the climatology of a regional climate model over Europe

 Two ten-year simulations made with a European regional climate model (RCM) are compared. They are driven by the same observed sea surface temperatures but use different lateral boundary forcing. For one simulation, RCM AMIP, this forcing is obtained from a standard integration of a global general circulation model (GCM AMIP), whereas for the other simulation, RCM ASSIM, it is derived from a time series of operational analyses. The archive of analysis fields (surface pressure plus winds and temperatures on various pressure levels) is not sufficiently comprehensive to provide directly the full set of driving fields required for the RCM (in particular, no moisture fields are present), so these are obtained via a GCM integration, GCM ASSIM, in which the model is continuously relaxed towards the analysis fields using a data assimilation technique. Errors in RCM AMIP can arise either from the internal RCM physics or from errors in the lateral boundary forcing inherited from GCM AMIP. Errors in RCM ASSIM can arise from the internal RCM physics or the boundary moisture forcing but not from the driving circulation. Although previous studies have considered RCM integrations driven either by output from standard GCM integrations or operational analyses, our study is the first to compare parallel integrations of each type. This allows the total systematic error in an RCM integration driven by standard GCM output to be partitioned into components arising from the driving circulation and the internal RCM physics. These components indicate the scope for reducing regional simulation biases by improving either the driving GCM or the RCM itself. The results relate mainly to elements of surface climate likely to be influenced by both the driving circulation and regional physical processes operating in the RCM. For cloud cover, errors are found to arise largely from the internal RCM physics. Values are too low despite a positive relative humidity bias, indicating shortcomings in the parametrisation scheme used to calculate cloud cover. In summer, surface temperature and precipitation errors are also explained principally by regional processes. For example excessive solar heating leads to anomalously high surface temperatures over southern Europe and excessive drying of the soil reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing also exerts some influence, mainly via a tropospheric cold bias which partially offsets the warming over southern Europe and also increases precipitation. In other seasons the lateral boundary forcing and the regional physics both contribute significantly to the errors in surface temperature and precipitation. In winter the boundary forcing (apart from moisture) is responsible for about 60% of the total error variance for temperature and about 40% for precipitation, due to the cold bias and circulation errors such as a southward shift in the storm track. The remaining errors arise from the regional physics, although for precipitation an excessive supply of moisture from the lateral boundaries also contributes. The skill of the mesoscale component of the surface temperature and precipitation distributions exceeds previous estimates, due to more realistic observed climatology. The mesoscale patterns are very similar in the two RCM simulations indicating that errors in the simulation of fine scale detail arise mainly from inadequate representations of local forcings rather than errors in the large-scale circulation. Circulation errors in RCM AMIP (e.g. cold bias, southward shift of storm track) are also present in GCM AMIP, but are largely absent in RCM ASSIM except in summer. This confirms evidence from previous work that the key to reducing most circulation errors in the RCM lies in improving the driving GCM. Regional processes only make a major contribution to circulation errors in summer, when reduced advection from the boundaries allows errors in surface temperature to be transmitted more effectively into the troposphere. Finally, we find evidence of error balances in the GCM which act to minimise biases in important climatological variables. This reflects tuning of the model physics at GCM resolution. In order to achieve simultaneous optimisation of the RCM and GCM at widely differing resolutions it may be necessary to introduce explicit scale dependences into some aspects of the physics. Received: 17 September 1997/Accepted: 10 March 1998     

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.     

Projected evolution of circulation types and their temperatures over Central Europe in climate models

The study deals with changes in large-scale atmospheric circulation (represented by circulation types) and associated surface air temperatures as projected in an ensemble of regional climate models (RCMs) from the ENSEMBLES project. We examine changes of circulation type frequencies and means of daily maximum and minimum temperatures within circulation types in individual seasons for two time slices of transient runs under the SRES A1B scenario (2021–2050 and 2071–2100) with respect to the control period (1961–1990). To study the influence of driving data, simulations of the driving general circulation models (GCMs) also are evaluated. We find that all models project changes of atmospheric circulation that are statistically significant for both future time slices. The models tend to project strengthening of the westerly circulation in winter and its weakening in summer. We show that increases of daily maximum and minimum temperatures in all seasons differ for individual circulation types. There are, however, only few features of the projected changes in the future circulation–temperature links that are common among the models, in particular relatively smaller warming for westerly types. Only in winter, projected changes in circulation types tend to contribute to the projected overall warming. This effect is negligible and mostly opposite in the other seasons. We also detect a strong influence of driving data on RCMs’ simulation of atmospheric circulation and temperature changes.     

Future changes in cyclone climatology over Europe as inferred from a regional climate simulation

This study analyzes the cyclone climatology in regional climate model simulations of present day (1961–1990) and future (2071–2100, A2 and B2 emission scenarios) european climate conditions. The model domain covers the area from Scandinavia to Northern Africa and from the Eastern Atlantic to Russia at a horizontal grid spacing of 50 km. Compared to present day, in the A2 and B2 scenario conditions the annual average storm track intensity increases over the North-East Atlantic and decreases over Russia and the Eastern Mediterranean region. This overall change pattern is larger in the A2 than in the B2 simulations. However, the cyclone climatology change signal shows a large intermonthly variability and important differences across European regions. The largest changes are found over the North-East Atlantic, where the storm track intensity increases in winter and decreases in summer. A significant reduction of storm track intensity is found during late summer and autumn over the Mediterranean region, and from October to January over Russia. The number of cyclones decreases in future conditions throughout Europe, except over the Central Europe and Mediterranean regions in summer (where it increases). The frequency of intense cyclones and the depth of extreme cyclones increase over the North-East Atlantic, decrease over Russia and show an irregular response over the rest of the domain.

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基于全球及区域气候模式的江苏省降水变化趋势预估

利用气象观测资料,8个全球耦合气候系统模式的集合平均以及区域气候模式(RegCM4)的结果,通过方差分析、相关分析、趋势分析、扰动法等方法对模式性能进行了评估,并对江苏省在未来RCP8.5高端排放情景下降水的变化趋势进行了预估。结果表明,在RCP8.5情景下,至2020、2030和2050年,全球模式模拟的江苏省年平均降水在未来有逐渐增加的趋势,线性增加率约为7 mm/(10 a)。至2050年,江苏省年平均降水量将增加2%左右;区域模式模拟的年平均降水在未来线性增加率为1.5 mm/(10 a),变化不显著。区域模式模拟的夏季降水在未来有所增加,最多可增加20%～30%,但增幅随时间逐渐减小;全球模式模拟的夏季降水比现在有所减少,至2050年,减少了大约10%。区域模式模拟的冬季降水在未来不同时间段均比现在有所减少,同现在相比,最多可减少30%～40%;而全球模式模拟的冬季降水在未来则是先减少,后增加,至2050年,比现在大约增加10%。对于不同季节,总体而言,南部地区降水量的变化较北部地区显著。对于极端降水事件来说,江苏省未来小雨日数将减少,而暴雨日数则微弱增加。但由于全球模式本身的性能、区域模式对全球模式的依赖性以及温室气体排放的不确定性使上述预估结果仍具有不确定性。     

Error characteristics of high resolution regional climate models over the Alpine area

This study describes typical error ranges of high resolution regional climate models operated over complex orography and investigates the scale-dependence of these error ranges. The results are valid primarily for the European Alpine region, but to some extent they can also be transferred to other orographically complex regions of the world. We investigate the model errors by evaluating a set of 62 one-year hindcast experiments for the year 1999 with four different regional climate models. The analysis is conducted for the parameters mean sea level pressure, air temperature (mean, minimum and maximum) and precipitation (mean, frequency and intensity), both as an area average over the whole modeled domain (the “Greater Alpine Region”, GAR) and in six subregions. The subregional seasonal error ranges, defined as the interval between the 2.5th percentile and the 97.5th percentile, lie between ?3.2 and +2.0 K for temperature and between ?2.0 and +3.1 mm/day (?45.7 and +94.7%) for precipitation, respectively. While the temperature error ranges are hardly broadened at smaller scales, the precipitation error ranges increase by 28%. These results demonstrate that high resolution RCMs are applicable in relatively small scale climate impact studies with a comparable quality as on well investigated larger scales as far as temperature is concerned. For precipitation, which is a much more demanding parameter, the quality is moderately degraded on smaller scales.     

Potential climate change impact on wind energy resources in northern Europe: analyses using a regional climate model

There is considerable interest in the potential impact of climate change on the feasibility and predictability of renewable energy sources including wind energy. This paper presents dynamically downscaled near-surface wind fields and examines the impact of climate change on near-surface flow and hence wind energy density across northern Europe. It is shown that: Simulated wind fields from the Rossby Centre coupled Regional Climate Model (RCM) (RCAO) with boundary conditions derived from ECHAM4/OPYC3 AOGCM and the HadAM3H atmosphere-only GCM exhibit reasonable and realistic features as documented in reanalysis data products during the control period (1961–1990). The near-surface wind speeds calculated for a climate change projection period of 2071–2100 are higher than during the control run for two IPCC emission scenarios (A2, B2) for simulations conducted using boundary conditions from ECHAM4/OPYC3. The RCAO simulations conducted using boundary conditions from ECHAM4/OPYC3 indicate evidence for a small increase in the annual wind energy resource over northern Europe between the control run and climate change projection period and for more substantial increases in energy density during the winter season. However, the differences between the RCAO simulations for the climate projection period and the control run are of similar magnitude to differences between the RCAO fields in the control period and the NCEP/NCAR reanalysis data. Additionally, the simulations show a high degree of sensitivity to the boundary conditions, and simulations conducted using boundary conditions from HadAM3H exhibit evidence of slight declines or no change in wind speed and energy density between 1961–1990 and 2071–2100. Hence, the uncertainty of the projected wind changes is relatively high.     

基于多区域模式集合的中国西部干旱区极端温度未来预估

利用CORDEX-EA计划11个区域模式模拟结果,集合预估了中国西部干旱区16个极端温度指数未来的变化趋势及空间分布。结果表明:1)区域模式基本上能够再现近30 a西部干旱区极端温度的空间分布。2)多模式集合预估的西部干旱区21世纪中期霜冻日数(FD)和冰封日数(ID)呈现显著的下降趋势,而热夜日数(TR)和夏季日数(SU)则呈现明显的上升趋势。3)未来异常暖昼持续指数(WSDI)和生长期(GSL)呈现增加趋势,异常冷昼持续指数(CSDI)和日较差(DTR)则呈现下降趋势。4)未来气候增温导致冷昼日数(TX90p)、暖夜日数(TN90p)增加,而暖昼日数(TX10p)和冷夜日数(TN10p)减少。5)未来月最高温度极大值(TXx)、月最低温度极大值(TNx)、月最高温度极小值(TXn)和月最低温度极小值(TNn)都呈现增加的趋势。因此,西部干旱区未来发生极端低温事件的概率减小,发生极端高温事件的概率则会增大,但不同的极端温度指数变化的空间分布并不均一,存在明显的区域差异。     

Intercomparison of precipitation simulated by regional climate models over East Asia in 1997 and 1998

Regional climate simulations in Asia from May 1997 to August 1998 were performed using the Seoul National University regional climate model （SNURCM） and Iowa State University regional climate model （ALT.MM5/LSM）, which were developed by coupling the NCAR/Land Surface Model （LSM） and the Mesoscale Model （MM5）. However, for physical processes of precipitation, the SNURCM used the Grell scheme for the convective parameterization scheme （CPS） and the simple ice scheme for the explicit moisture scheme （EMS）, while the ALT.MM5/LSM used the Betts-Miller scheme for CPS and the mixed phase scheme for EMS.
The simulated precipitation patterns and amounts over East Asia for the extreme climatic summer in 1997 （relative drought conditions） and 1998 （relative flood conditions） were especially focused upon. The ALT.MM5/LSM simulated more precipitation than was observed in 1997 due to more moisture and cloud water in the lower levels, despite weak upward motion. In the SNURCM, strong upward motion resulted in more precipitation than that was observed in 1998, with more moisture and cloud water in the middle levels. In the ALT.MM5/LSM, weak upward motion, unchanged moisture in the lower troposphere, and the decrease in latent heat flux at the surface increased convective precipitation only by 3% for the 1998 summer event. In the SNURCM, strong upward motion, the increase in moisture in the lower troposphere, and the increase in latent heat flux at the surface increased convective precipitation by 48% for the summer of 1998. The main differences between both simulations were moisture availability and horizontal momentum transport in the lower troposphere, which were also strongly influenced by large-scale forcing.