A subgrid parameterization of orographic precipitation

Summary Estimates of the impact of global climate change on land surface hydrology require climate information on spatial scales far smaller than those explicitly resolved by global climate models of today and the foreseeable future. To bridge the gap between what is required and what is resolved, we propose a subgrid-scale parameterization of the influence of topography on clouds, precipitation, and land surface hydrology. The parameterization represents subgrid variations in surface elevation in terms of probability distributions of discrete elevation classes. Separate cloud, radiative, and surface processes are calculated for each elevation class. Rainshadow effects are not treated by the parameterization; they have to be explicitly resolved by the host model. The simulated surface temperature, precipitation, and snow cover for each elevation class are distributed to different geographical locations according to the spatial distribution of surface elevation within each grid cell.The subgrid parameterization has been implemented in the Pacific Northwest Laboratory's climate version of the Penn State/NCAR Mesoscale Model. The scheme is evaluated by driving the regional climate model with observed lateral boundary conditions for the Pacific Northwest and comparing simulated fields with surface observations. The method yields more realistic spatial distributions of precipitation and snow cover in mountainous areas and is considerably more computationally efficient than achieving high resolution by the use of nesting in the regional climate model.With 17 Figures     

Parameterization of the thermal impacts of sub-grid orography on numerical modeling of the surface energy budget over East Asia

Summary A parameterization scheme for the thermal effects of subgrid scale orography is incorporated into a regional climate model (developed at Nanjing University) and its impact on modeling of the surface energy budget over East Asia is evaluated. This scheme includes the effect of terrain slope and orientation on the computation of solar and infrared radiation fluxes at the surface, as well as the surface sensible and latent heat fluxes. Calculations show that subgrid terrain parameters alter the diurnal cycle and horizontal distributions of surface energy budget components. This effect becomes more significant with increased terrain slope, especially in winter. Due to the inclusion of the subgrid topography, the surface area of a model grid box changes over complex terrain areas. Numerical experiments, with and without the subgrid scale topography scheme, show that the parameterization scheme of subgrid scale topography modifies the distribution of the surface energy budget and surface temperature around the Tibetan Plateau. Comparisons with observations indicate that the subgrid topography scheme, implemented in the climate model, reproduces the observed detailed spatial temperature structures at the eastern edge of the Tibetan Plateau and reduces the tendency to overestimate precipitation along the southern coastal areas of China in summer.     

Impact of subgrid scale scheme on topography and landuse for better regional scale simulation of meteorological variables over the western Himalayas

An attempt is made to integrate subgrid scale scheme on the work of Dimri and Ganju (Pure Appl Geophys 167:1–24, 2007) to understand the overall nature of surface heterogeneity and landuse variability along with resolvable finescale micro/meso scale circulation over the Himalayan region, which is having different altitudes and orientations causing prevailing weather conditions to be complex. This region receives large amount of precipitation due to eastward moving low-pressure synoptic weather systems, called western disturbances, during winter season (December, January, February—DJF). Surface heterogeneity and landuse variability of the Himalayan region gives rise to numerous micro/meso scale circulation along with prevailing weather. Therefore, in the present work, a mosaic type parameterization of subgrid scale topography and landuse within a framework of a regional climate model (RegCM3) is extended to study interseasonal variability of surface climate during a winter season (October 1999–March 2000) of the work of Dimri and Ganju (Pure Appl Geophys 167:1–24, 2007). In this scheme, meteorological variables are disaggregated from the coarse grid to the fine grid, land surface calculations are then performed separately for each subgrid cell, and surface fluxes are calculated and reaggregated onto the coarse grid cell for input to the atmospheric model. By doing so, resolvable finescale structures due to surface heterogeneity and landuse variability at coarse grid are subjected to parameterize at regular finescale surface subgrid. Model simulations show that implementation of subgrid scheme presents more realistic simulation of precipitation and surface air temperature. Influence of topographic elevation and valleys is better represented in the scheme. Overall, RegCM3 with subgrid scheme provides more accurate representation of resolvable finescale atmospheric/surface circulations that results in explaining mean variability in a better way.     

Added value of convection permitting seasonal simulations

In this study the added value of a ensemble of convection permitting climate simulations (CPCSs) compared to coarser gridded simulations is investigated. The ensemble consists of three non hydrostatic regional climate models providing five simulations with ~10 and ~3 km (CPCS) horizontal grid spacing each. The simulated temperature, precipitation, relative humidity, and global radiation fields are evaluated within two seasons (JJA 2007 and DJF 2007–2008) in the eastern part of the European Alps. Spatial variability, diurnal cycles, temporal correlations, and distributions with focus on extreme events are analyzed and specific methods (FSS and SAL) are used for in-depth analysis of precipitation fields. The most important added value of CPCSs are found in the diurnal cycle improved timing of summer convective precipitation, the intensity of most extreme precipitation, and the size and shape of precipitation objects. These improvements are not caused by the higher resolved orography but by the explicit treatment of deep convection and the more realistic model dynamics. In contrary improvements in summer temperature fields can be fully attributed to the higher resolved orography. Generally, added value of CPCSs is predominantly found in summer, in complex terrain, on small spatial and temporal scales, and for high precipitation intensities.     

U.S. Climate Sensitivity Simulated with the NCEP Regional Spectral Model

10-year continuous U.S. climate simulations were conducted with the Regional Spectral Model (RSM) using boundary conditions from the National Centers for Environmental Prediction/Dept. of Energy reanalyses and the global PCM (Parallel Climate Model) simulations for present day (1986–1996) andfuture (2040–2050) CO₂ concentrations (about a 36% increasedCO₂). In order to examine the influence of physical parameterization differences as well as grid-resolution, fine resolution RSM simulations (50 km) were compared to coarse resolution (180 and 250 km) RSM simulations, which had resolutions comparable to the T62 reanalysis and PCM simulations. During the winter, the fine resolution RSM simulations provided more realistic detail over the western mountains. During the summer, large differences between the RSM and driving PCM simulations were found. Our results with presentCO₂ suggest that most of the differences between the regionalclimate model simulations and the climate simulations driven by the global model used to drive the regional climate model were not due to the finer resolution of the regional climate model but to the different treatment of the physical processes in the two models, especially when the subgrid scale physics was important, like during summer. Compared to the coarse resolution RSM simulation results, on the other hand, the fine resolution RSM simulations did show improved simulation skills especially when a good boundary condition such as the reanalysis was used to drive the RSM. Under increased CO₂, the driving PCM and downscaled RSM simulations exhibitedwarming over all vertical layers and all regions. Both the RSM and PCM had increased precipitation during the winter, but during the summer, the PCM simulation had an overall precipitation increase mainly due to increased subgrid scale convective activity, whereas the RSM simulations exhibited precipitation decreases and the resulting RSM soil moisture became dryer, especially in the U.S. Southwest. Most of differences in the simulated climate change signals were produced by the distinct model physics rather than by differences in grid resolution.     

The sensitivity of the tropical circulation and Maritime Continent precipitation to climate model resolution

The dependence of the annual mean tropical precipitation on horizontal resolution is investigated in the atmospheric version of the Hadley Centre General Environment Model. Reducing the grid spacing from about 350 km to about 110 km improves the precipitation distribution in most of the tropics. In particular, characteristic dry biases over South and Southeast Asia including the Maritime Continent as well as wet biases over the western tropical oceans are reduced. The annual-mean precipitation bias is reduced by about one third over the Maritime Continent and the neighbouring ocean basins associated with it via the Walker circulation. Sensitivity experiments show that much of the improvement with resolution in the Maritime Continent region is due to the specification of better resolved surface boundary conditions (land fraction, soil and vegetation parameters) at the higher resolution. It is shown that in particular the formulation of the coastal tiling scheme may cause resolution sensitivity of the mean simulated climate. The improvement in the tropical mean precipitation in this region is not primarily associated with the better representation of orography at the higher resolution, nor with changes in the eddy transport of moisture. Sizeable sensitivity to changes in the surface fields may be one of the reasons for the large variation of the mean tropical precipitation distribution seen across climate models.     

Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations

In this study it is shown that the availability of a very high resolution dataset of land surface characteristics leads to the improvement of a surface runoff parameterization scheme. The improved parameterization scheme was developed for application in global and regional climate models and is a further development of the Arno scheme that is widely used in climate models. Here, surface runoff is computed as infiltration excess from a "bucket" type reservoir which takes the subgrid variability of soil saturation within a model gridbox into account. Instead of prescribing a distribution of subgrid scale soil water capacities as in the original Arno scheme, the array of high resolution soil water capacities taken from a global 1 km dataset of land surface parameters is used to obtain individual fractional saturation curves for each model gridbox. From each saturation curve, the three parameters (a shape parameter describing the shape of the subgrid distribution of soil water capacities, subgrid minimum and maximum soil water capacity) required in the modified formulation of the scheme are derived via optimization. As in the original Arno scheme applied in the ECHAM general circulation model and the REMO regional climate model, topography variations will influence the distribution of saturated subgrid areas within a model gridbox. At most gridboxes the net effect of these changes is such that more runoff is produced for high soil water contents and less runoff for low soil water contents. A validation of simulated discharge computed with a simplified land surface scheme applied to reanalysis data of the European Centre for Medium-Range Weather Forecasts and a hydrological discharge model has shown that these changes lead to a more realistic simulation of the annual cycle of discharge for several catchments. In particular this could be shown for the Yangtze Kiang and Amur catchments where adequate input data are available.     

A simple soil moisture scheme for regional climate simulations in the tropics

Summary A regional climate model (RCM) is described which incorporates an improved scheme for soil moisture availability (SMA) compared to an earlier version. The improvement introduces a sensitivity of SMA to soil type, vegetation cover and ground albedo, making the model more adaptable to divers regions. In addition, the interactive SMA depends on past precipitation, ground temperature and terrain relief. Six RCM simulations of the monthly mean climate over southern Africa are performed at 0.5° grid spacing. Improvements in the RCM climate simulations compared to control runs are attributed to the newer SMA scheme. Only a slight improvement in skill results from driving the RCM with observational analyses as opposed to GCM “predicted” lateral boundary conditions. The high spatial resolution of the RCM provides a distinct advantage in the simulated spatial distribution of precipitation compared with a global model run at an effective grid spacing of 2.8°. The mesoscale precipitation signal in the RCM simulations is more dominant during the rather dry December 1982 than during December 1988. The improved SMA scheme contributed to a realistic partition between latent and sensible heat fluxes at the ground-atmosphere boundary and consequently a realistic diurnal cycle of ground temperature. Simulated differences in the spatial distribution of rainfall between December 1982 and December 1988 are more realistic with the improved scheme. Received June 28, 2001 Revised August 27, 2001     

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada. II: Basin-Scale Results

We evaluate the capacity of a regional climate model to simulate the statistics of extreme events, and also examine the effect of differing horizontal resolution, at the scale of individual hydrological basins in the topographically complex province of British Columbia, Canada. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by global reanalysis over the period 1973–1995. The simulations were evaluated with ANUSPLIN, a daily observational gridded surface temperature and precipitation product and with meteorological data recorded at 28 stations within the upper Peace, Nechako, and upper Columbia River basins. In this work, we focus largely on a comparison of the skill of each model configuration in simulating the 90th percentile of daily precipitation (PR90). The companion paper describes the results for a wider range of temperature and precipitation extremes over the entire WCan domain.

Over all three watersheds, both simulations exhibit cold biases compared with observations, with the bias exacerbated at higher resolution. Although both simulations generally display wet biases in median precipitation, CRCM15 features a reduced bias in PR90 in all three basins in summer and throughout the year in the upper Columbia River basin. However, the higher resolution model is inferior to CRCM45 with respect to rarer heavy precipitation events and also displays high spatial variability and lower spatial correlations with ANUSPLIN compared with the coarser resolution model. A reduction in the range of PR90 biases over the upper Columbia basin is noted when the 15?km results are averaged to the 45?km grid. This improvement is partly attributable to the averaging of errors between different elevation data used in the gridded observations and CRCM, but the sensitivity of CRCM15 to resolved topography is also clear from spatial maps of seasonal extremes. At the station scale, modest but systematic reductions in the bias of PR90 relative to ANUSPLIN are again found when the CRCM15 results are averaged to the 45?km grid. Furthermore, the annual cycle of inter-station spatial variance in the upper Columbia River basin is well reproduced by CRCM15 but not by ANUSPLIN or CRCM45. The former result highlights the beneficial effect of spatial averaging of small-scale climate variability, whereas the latter is evidently a demonstration of the added value at high resolution vis-à-vis the improved simulation of precipitation at the resolution limit of the model.     

Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States

To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (20 years) and three future(2040–2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper describes the regional simulations and focuses on the hydroclimate conditions in the Columbia River Basin (CRB) and Sacramento-San Joaquin River (SSJ) Basin. Results based on global and regional simulations show that by mid-century, the average regional warming of 1 to 2.5 °C strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack was about70% as indicated by the regional simulations. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation increased by 5 to 15 mm/day (15–20%) along theCascades and the Sierra. The warming resulted in increased rainfall at the expense of reduced snowfall, and reduced snow accumulation (or earlier snowmelt) during the cold season. In the CRB, these changes were accompanied by more frequent rain-on-snow events. Overall, they induced higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Changes in surface water and energy budgets in the CRB and SSJ basin were affected mainly by changes in surface temperature, which were statistically significant at the 0.95 confidence level. Changes in precipitation, while spatially incoherent, were not statistically significant except for the drying trend during summer. Because snow and runoff are highly sensitive tospatial distributions of temperature and precipitation, this study shows that (1) downscaling provides more realistic estimates of hydrologic impacts in mountainous regions such as the western U.S., and (2) despite relatively small changes in temperature and precipitation, changes in snowpack and runoff can be much larger on monthly to seasonal time scales because the effects of temperature and precipitation are integrated over time and space through various surface hydrological and land-atmosphere feedback processes. Although the results reported in this study were derived from an ensemble of regional climate simulations driven by a global climate model that displays low climate sensitivity compared with most other models, climate change was found to significantly affect water resources in the western U.S. by the mid twenty-first century.     

Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model

Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1°) has been downscaled to a horizontal resolution of 30 and 10?km for the period of 1961?C1990. This model setup includes the whole North Atlantic in the 30?km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10?km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies.     

The 15‐km version of the Canadian regional forecast system

Abstract

A new mesoscale version of the regional forecast system became operational at the Canadian Meteorological Centre on 18 May 2004. The main changes to the regional modelling system include an increase in both the horizontal and vertical resolutions (15‐km horizontal resolution and 58 vertical levels instead of 24‐km resolution and 28 levels) as well as major upgrades to the physics package. The latter consist of a new condensation package, with an improved formulation of the cloudy boundary layer, a new shallow convection scheme based on a Kuo‐type closure, and the Kain and Fritsch deep convection scheme, together with a subgrid‐scale orography parametrization scheme to represent gravity wave drag and low‐level blocking effects. The new forecast system also includes a few changes to the regional data assimilation such as additional radiance data from satellites.

Objective verifications using a series of cases and parallel runs, along with subjective evaluations by CMC meteorologists, indicate significantly improved performance using the new 15‐km resolution forecast system. We can conclude from these verifications that the model exhibits a marked reduction in errors, improved predictability by about 12 hours, better forecasts of precipitation, a significant reduction in the spin‐up time, and a different implicit‐explicit partitioning of precipitation. A number of other features include: sharper precipitation patterns, better representation of trace precipitation, and general improvements of deepening lows and hurricanes. In mountainous regions, several aspects are better represented due to combined higher‐resolution orography and the low‐level blocking term.     

Impact of horizontal diffusion, radiation and cloudiness parameterization schemes on fog forecasting in valleys

Fog and low stratus forecasting experiments have been carried out with the numerical weather prediction model ALADIN on a case of long lasting fog. The model has been used with different radiation, cloud diagnosing and horizontal diffusion schemes, different representation of orography, increased vertical resolution and with or without prognostic condensates and turbulent kinetic energy (TKE). Some of the numerical set-ups are able to reproduce the fog (low stratus) field as seen in the satellite images as well as the measured 2m temperature and relative humidity diurnal cycles. The results show that cloud diagnosing schemes and overlap assumptions play a more important role than a more sophisticated radiation scheme, or introduction of prognostic cloud water, ice, rain, snow or TKE. More realistic orography representation and a more physical horizontal diffusion scheme significantly improve the modelled low stratus and 2m temperature in the areas with variable orography.     

Influence of the orographic roughness of glacier valleys across the Transantarctic Mountains in an atmospheric regional model

Glacier valleys across the Transantarctic Mountains are not properly taken into account in climate models, because of their coarse resolution. Nonetheless, glacier valleys control katabatic winds in this region, and the latter are thought to affect the climate of the Ross Sea sector, frsater formation to snow mass balance. The purpose of this paper is to investigate the role of the production of turbulent kinetic energy by the subgrid-scale orography in the Transantarctic Mountains using a 20-km atmospheric regional model. A classical orographic roughness length parametrization is modified to produce either smooth or rough valleys. A one-year simulation shows that katabatic winds in the Transantarctic Mountains are strongly improved using smooth valleys rather than rough valleys. Pressure and temperature fields are affected by the representation of the orographic roughness, specifically in the Transantarctic Mountains and over the Ross Ice Shelf. A smooth representation of escarpment regions shows better agreement with automatic weather station observations than a rough representation. This work stresses the need to improve the representation of subgrid-scale orography to simulate realistic katabatic flows. This paper also provides a way of improving surface winds in an atmospheric model without increasing its resolution.     

中国西部陆面过程次网格地形参数化的改进对区域气温和降水模拟的影响研究

地表作为大气模块的下垫面,为大气模块提供边界条件,地形对于模式结果的准确性起到至关重要的作用。现有的陆面过程模式在陆面同一网格内的次网格单元采用相同的大气强迫量,没有考虑次网格地形对网格内大气强迫量的影响,这关系到模式对气象要素和陆气交换量的模拟水平。本文在陆面模式NOAH处理次网格单元的同时,将输入的大气强迫量根据其与地形高度的关系进行修订,提出新的次网格地形的参数化方案,并引入到WRF（Weather Research and Forecasting）模式中进行数值试验,通过3组数值模拟试验,与未改进的方案和细网格方案分析比较,探讨新参数化方案对WRF 模式模拟结果的影响。结果表明:地形越复杂区域,次网格地形的影响越大。本文引入的新陆面次网格地形方案对天山山脉和昆仑山脉以及青藏高原南部的地表气温的模拟有较大改善,模拟的地表气温在大范围区域内都更贴近细网格方案。虽然新陆面次网格地形方案和细网格试验都对温度的模拟结果都有改善,但新陆面次网格地形方案对降水的模拟改善甚微,而细网格试验对降水模拟却有改进,这是由于细网格试验在陆面和大气网格都进行了细化,而新陆面次网格地形方案只考虑了陆面次网格的影响。具体来说,新陆面次网格地形方案对温度的模拟结果改进是通过改变地表向上长波和地表感热实现的。而细网格试验由于同时细化了大气和陆面的空间网格,对降水和温模拟的改进是通过综合改变地表能量平衡实现的。     

The impact of implementing the bare essentials of surface transfer land surface scheme into the BMRC GCM

This study describes the first order impacts of incorporating a complex land-surface scheme, the bare essentials of surface transfer (BEST), into the Australian Bureau of Meteorology Research Centre (BMRC) global atmospheric general circulation model (GCM). Land seasonal climatologies averaged over the last six years of integrations after equilibrium from the GCM with BEST and without BEST (the control) are compared. The modeled results are evaluated with comprehensive sources of data, including the layer-cloud climatologies from the international satellite cloud climatology project (ISCCP) data from 1983 to 1991 and the surface-observed global data of Warren et al., a five-year climatology of surface albedo estimated from earth radiation budget experiment (ERBE) top-of-the-atmosphere (TOA) radiatioe fluxes, global grid point datasets of precipitation, and the climatological analyses of surface evaporation and albedo. Emphasis is placed on the surface evaluation of simulations of landsurface conditions such as surface roughness, surface albedo and the surface wetness factor, and on their effects on surface evaporation, precipitation, layer-cloud and surface temperature. The improvements due to the inclusion of BEST are: a realistic geographical distribution of surface roughness, a decrease in surface albedo over areas with seasonal snow cover, and an increase in surface albedo over snow-free land. The simulated reduction in surface evaporation due, in part, to the biophysical control of vegetation, is also consistent with the previous studies. Since the control climate has a dry bias, the overall simulations from the GCM with BEST are degraded, except for significant improvements for the northern winter hemisphere because of the realistic vegetation-masking effects. The implications of our results for synergistic developments of other aspects of model parameterization schemes such as boundary layer dynamics, clouds, convection and rainfall are discussed.     

Global validation of the ISBA sub-grid hydrology

Over recent years, many numerical studies have suggested that the land surface hydrology contributes to atmospheric variability and predictability on a wide range of scales. Conversely, land surface models (LSMs) have been also used to study the hydrological impacts of seasonal climate anomalies and of global warming. Validating these models at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. The present study is aimed at validating a new land surface hydrology within the ISBA LSM. Global simulations are conducted at a 1° by 1° horizontal resolution using 3-hourly atmospheric forcings provided by the Global Soil Wetness Project. Compared to the original scheme, the new hydrology includes a comprehensive and consistent set of sub-grid parametrizations in order to account for spatial heterogeneities of topography, vegetation, and precipitation within each grid cell. The simulated runoff is converted into river discharge using the total runoff integrating pathways (TRIP) river routing model (RRM), and compared with available monthly observations at 80 gauging stations distributed over the world’s largest river basins. The simulated discharges are also compared with parallel global simulations from five alternative LSMs. Globally, the new sub-grid hydrology performs better than the original ISBA scheme. Nevertheless, the improvement is not so clear in the high-latitude river basins (i.e. Ob, MacKenzie), which can be explained by a too late snow melt in the ISBA model. Over specific basins (i.e. Parana, Niger), the quality of the simulated discharge is also limited by the TRIP RRM, which does not account for the occurrence of seasonal floodplains and for their significant impact on the basin-scale water budget.     

GRAPES-MESO模式浅对流参数化的改进与试验

参考Berg 等2005、2013年提出的扰动对流触发函数方法,对GRAPES-Meso模式积云对流参数化方案(KF eta)中的浅对流激发进行改进设计和试验,将单一的温、湿度触发改为对近地层进行一组温度、湿度扰动后的触发,并且用与该组扰动相关的边界层温、湿度分布确定的联合概率密度函数(JPDF)来表征浅对流云的特征参量及计算浅对流的强度。 着重分析了改进方案的浅对流激发、浅对流对环境场的反馈、模式地面降水和2 m气温的相关响应等,并与原方案和相关观测比较,验证了改进方案的合理性。 结果显示,改进方案比原方案能较早地激发出浅对流,且浅对流的激发频次高,浅对流激发的增加致使在模式低层距地数百米至2—3 km的垂直层内对环境温、湿度场和云雨水反馈增大,对GRAPES-Meso浅对流激发偏弱有改进作用,并对格点尺度与次网格尺度降水分配比不协调有改进。 对连续两个月批量试验的检验表明,浅对流激发的改进,可对GRAPES-Meso的24 h降水预报技巧的提高和2 m气温偏差的减小等产生不同程度的正影响。     

High-Resolution Non-Hydrostatic Simulations of Flash-Flood Episodes with Grid-Nesting and Ice-Phase Parameterization

Summary ?Simulations of two heavy rainfall events south of the Alps have been conducted with a non-hydrostatic model at horizontal resolutions ranging from 40 to 2.5 km. Emphasis is placed on the assessment of two recent model developments: a detailed explicit mixed phase microphysical scheme and a two-way interactive grid nesting method. In the high-resolution simulations, the impact of the ice phase was found to be quite substantial, accelerating the propagation of the surface front and modifying the spatial distribution of the rainfall. Simulations carried out with two-way interactive grid nesting yielded more realistic overall precipitation patterns, particularly at the finest horizontal resolution. Received March 22, 1999/Revised June 28, 1999     

Climate and climate change in western canada as simulated by the Canadian regional climate model

Abstract

A þrst climate simulation performed with the novel Canadian Regional Climate Model (CRCM) is presented. The CRCM is based on fully elastic non‐hydrostatic þeld equations, which are solved with an efþcient semi‐implicit semi‐Lagrangian (SISL) marching algorithm, and on the parametrization package of subgrid‐scale physical effects of the second‐generation Canadian Global Climate Model (GCMII). Two 5‐year integrations of the CRCM nested with GCMII simulated data as lateral boundary conditions are made for conditions corresponding to current and doubled CO₂ scenarios. For these simulations the CRCM used a grid size of 45 km on a polar‐stereographic projection, 20 scaled‐height levels and a time step of 15 min; the nesting GCMII has a spectral truncation of T32, 10 hybrid‐pressure levels and a time step of 20 min. These simulations serve to document: (1) the suitability of the SISL numerical scheme for regional climate modelling, (2) the use of GCMII physics at much higher resolution than in the nesting model, (3) the ability of the CRCM to add realistic regional‐scale climate information to global model simulations, and (4) the climate of the CRCM compared to that of GCMII under two greenhouse gases (GHG) scenarios.