Notes of Numerical Simulation of Summer Rainfall in China with a Regional Climate Model REMO

Regional climate models are major tools for regional climate simulation and their output are mostly used for climate impact studies. Notes are reported from a series of numerical simulations of summer rainfall in China with a regional climate model. Domain sizes and running modes are major foci. The results reveal that the model in forecast mode driven by "perfect" boundaries could reasonably represent the inter-annual differences: heavy rainfall along the Yangtze River in 1998 and dry conditions in 1997. Model simulation in climate mode differs to a greater extent from observation than that in forecast mode. This may be due to the fact that in climate mode it departs further from the driving fields and relies more on internal model dynamical processes. A smaller domain in climate mode outperforms a larger one. Further development of model parameterizations including dynamic vegetation are encouraged in future studies.     

Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.     

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961–2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.     

Regional model simulation of summer rainfall over the Philippines: Effect of choice of driving fields and ocean flux schemes

Summary The latest version of the Abdus Salam International Centre for Theoretical Physics (ICTP) regional model RegCM is used to investigate summer monsoon precipitation over the Philippine archipelago and surrounding ocean waters, a region where regional climate models have not been applied before. The sensitivity of simulated precipitation to driving lateral boundary conditions (NCEP and ERA40 reanalyses) and ocean surface flux scheme (BATS and Zeng) is assessed for 5 monsoon seasons. The ability of the RegCM to simulate the spatial patterns and magnitude of monsoon precipitation is demonstrated, both in response to the prominent large scale circulations over the region and to the local forcing by the physiographical features of the Philippine islands. This provides encouraging indications concerning the development of a regional climate modeling system for the Philippine region. On the other hand, the model shows a substantial sensitivity to the analysis fields used for lateral boundary conditions as well as the ocean surface flux schemes. The use of ERA40 lateral boundary fields consistently yields greater precipitation amounts compared to the use of NCEP fields. Similarly, the BATS scheme consistently produces more precipitation compared to the Zeng scheme. As a result, different combinations of lateral boundary fields and surface ocean flux schemes provide a good simulation of precipitation amounts and spatial structure over the region. The response of simulated precipitation to using different forcing analysis fields is of the same order of magnitude as the response to using different surface flux parameterizations in the model. As a result it is difficult to unambiguously establish which of the model configurations is best performing.     

Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region

In the context of the EU-Project BALANCE () the regional climate model REMO was used for extensive calculations of the Barents Sea climate to investigate the vulnerability of this region to climate change. The regional climate model REMO simulated the climate change of the Barents Sea Region between 1961 and 2100 (Control and Climate Change run, CCC-Run). REMO on ~50 km horizontal resolution was driven by the transient ECHAM4/OPYC3 IPCC SRES B2 scenario. The output of the CCC-Run was applied to drive the dynamic vegetation model LPJ-GUESS. The results of the vegetation model were used to repeat the CCC-Run with dynamic vegetation fields. The feedback effect of the modified vegetation on the climate change signal is investigated and discussed with focus on precipitation, temperature and snow cover. The effect of the offline coupled vegetation feedback run is much lower than the greenhouse gas effect.     

A high-resolution 43-year atmospheric hindcast for South America generated with the MPI regional model

An evaluation of the present-day climate in South America simulated by the MPI atmospheric limited area model, REMO, is made. The model dataset was generated by dynamical downscaling from the ECMWF-ERA40 reanalysis and compared to in-situ observations. The model is able to reproduce the low-level summer monsoon circulation but it has some deficiencies in representing the South American Low-Level Jet structure. At upper levels, summer circulation features like the Bolivian High and the associated subtropical jet are well simulated by the model. Sea-level pressure fields are in general well represented by REMO. The model exhibits reasonable skill in representing the general features of the mean seasonal cycle of precipitation. Nevertheless, there is a systematic overestimation of precipitation in both tropical and subtropical regions. Differences between observed and modeled temperature are smaller than 1.5°C over most of the continent, excepting during spring when those differences are quite large. Results also show that the dynamical downscaling performed using REMO introduces some enhancement of the global reanalysis especially in temperature at the tropical regions during the warm season and in precipitation in both the subtropics and extratropics. It is then concluded that REMO can be a useful tool for regional downscaling of global simulations of present and future climates.     

Long-term simulation of Indonesian rainfall with the MPI regional model

Simulations of the Indonesian rainfall variability using the Max Planck Institute regional climate model REMO have been performed using three different lateral boundary forcings: Reanalyses from the European Centre for Medium-Range Weather Forecasts (ERA15), the National Centers for Environmental Prediction and National Center for Atmospheric Research (NRA) as well as from ECHAM4 climate model simulation. The result of those simulations are compared to station data. REMO simulations were performed at 0.5° horizontal resolution for the whole archipelago and at 1/6° for Sulawesi Island. In general the REMO model, reproduces the spatial pattern of monthly and seasonal rainfall well over land, but overestimates the rainfall over sea. Superiority of REMO performance over land is due to a high-resolution orography, while over sea, REMO suffers from erroneously low surface fluxes. REMO reproduces variability during El Niño-Southern Oscillations years well but fails to show a good (wet and dry) monsoon contrast. Despite strong influences of the lateral boundary fields, REMO shows a realistic improvement of a local phenomenon over Molucca. Significant improvement for the step from the relatively high global 1.125° to 0.5° resolution is noticeable, but not from 0.5° into 1/6°. The REMO simulation driven by ERA15 has the best quality, followed by NRA and ECHAM4 driven simulations. The quality of ERA15 is the main factor determining the quality of REMO simulations. A predictability study shows small internal variability among ensemble members. However, there are systematic intrinsic climatological errors as shown in the predictability analysis. These intrinsic errors have monthly, seasonal and regional dependencies and the one over Java is significantly large. The intrinsic error study suggests the presence of the spring predictability barrier and a high level of predictability in summer.     

A note to the simulation of the annual and inter-annual variability of the water budget over the Baltic Sea drainage basin

Summary The annual and inter-annual variability of the water budget over the Baltic Sea area has been studied using the global climate model ECHAM4/T106 and the regional climate model REMO for three experiments covering a time period of 10 years each. To address the capability of REMO to simulate realistically the water budget over the Baltic Sea re-analyses data (so-called perfect boundaries) were applied as lateral boundary conditions. The validation against observations shows that the results agree rather well. However not all components of the hydrological cycle are observed, therefore only some of them could be compared to the simulation results. A clear dependence of the annual cycle of precipitation from the horizontal resolution was found in the experiments. Until now it is still unclear which processes are responsible for this. Further research will help to identify the sensitive physical processes involved in the water budget and their interactions. Received September 8, 2000 Revised April 3, 2001     

Simulation of the atmospheric circulation in the Weddell Sea region using the limited-area model REMO

Summary ?To analyse the applicability of a limited-area atmosphere model to the Southern Ocean, a one-year simulation for 1985 is performed using the REgional MOdel REMO at 55-km horizontal grid-spacing implemented for the Antarctic regions of the Weddell, Bellingshausen and Amundsen Seas. To evaluate the performance of REMO, a comparison of model results to observations and to reanalysis/analysis data sets is carried out. REMO is initialized and driven at the lateral and lower boundaries by data of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA15). Overall, REMO is an appropriate tool for further climate studies in Antarctic regions. It reproduces reasonably well basic spatial patterns and the seasonal cycle of the atmospheric circulation. However, the simulated mean sea level pressure (MSLP) is predominantly lower than the MSLP provided by observations and by ERA. Considerable temperature differences in the lower troposphere over sea ice in winter cause discrepancies between the REMO and ERA pressure fields in the mid-troposphere too. The precipitation rate P of the REMO simulation agrees qualitatively well with main features of the observed climatological spatial distribution described in literature. The seasonal cycle of P in the inner Weddell Sea reflects the Antarctic semi-annual oscillation. Concerning the forcing fields, the ERA sea ice surface temperatures in winter are generally higher than satellite derived surface temperatures. Although the differences are 10 to 15 K in the southern Weddell Sea, this deficiency of the ERA data hardly influences the mean large-scale circulation. Received October 10, 2001; revised April 22, 2002; accepted May 12, 2002     

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     

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

Summary A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an observation space version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.The analysis and forecast fields derived from the assimilation system are objectively evaluated through comparisons with parallel runs based on the current Optimum Interpolation based operational analysis and on the European Centre for Medium Range Weather Forecast (ECMWF) analyzed fields. Objective comparisons with RAOB and conventional surface observations are also presented.The main result of these studies is that, despite its relative simplicity, the new system is capable of adequately capturing the information content of the available observations, while the efficient parallel implementation of the objective analysis algorithm makes it suitable for operational use even in small operational environments.     

区域气候模式REMO对东亚季风季节变化的模拟研究

将欧洲区域气候模式REMO首次应用于东亚区域,利用该模式对1980年和1990年东亚季风季节变化进行了模拟研究,并将模拟结果与NCEP再分析资料进行比较,以检验该模式对东亚季风的模拟能力.研究表明,区域气候模式REMO能够较好地模拟出东亚地区高、低空的大气环流特征,模拟的高度场、流场和温度场与NCEP再分析资料场都比较一致.模拟结果显示了东亚季风的月变化和季节转换特征.模拟的降水场与GPCC降水资料的对比结果表明,REMO能较为成功地模拟出东亚地区降水的空间分布,并能较好地反映降水的季节变化及主要降水趋势,夏季降水模拟偏大,整个区域平均的降水量偏差约为18%左右.     

Hydrological issues in lateral boundary conditions for regional climate modeling: simulation of east asian summer monsoon in 1998

The atmospheric branch of the hydrological cycle associated with the East Asian summer monsoon is intricate due to its distinct land-sea configurations: the highest mountains are to its west, the oceans are to its south and east, and mid-latitude influences come from its north. Here we use the weather research and forecast (WRF) model to demonstrate that using two different large-scale driving fields, derived from the NCEP/DOE R2 and ERA40 reanalysis data and the same model configuration yielded remarkable differences. We found that the differences are primarily caused by uncertainties in the water vapor influx across the lateral boundaries in the reanalyses. The summer-mean water vapor convergence into the model domain computed from the ERA40 reanalysis is 47% higher than that from the R2 reanalysis. The largest uncertainties in moisture transport are found in the regions of the Philippine Sea and the Bay of Bengal, where the moisture transport has the most significant impacts on the East Asian summer monsoon rainfall distribution. The sensitivity test results suggest that the biases in the seasonal mean, seasonal march of the rain band, and individual rainfall events may be reduced by using an “ensemble” average of R2 and ERA40 as lateral boundary forcing. While the large-scale forcing field does not conserve water vapor, the WRF simulation conserves water vapor in the inner model domain. The regional model simulation has corrected the biases in the total amount and the month-to-month distribution of precipitation in the large-scale driving field. However, RCM’s daily precipitation is poorer than that in the reanalysis filed. Since the RCM solutions may sensitively depend on the reanalysis forcing, intercomparison of models’ performance based on a single set of the reanalysis may not be reliable. This calls for attention to reshape our strategy for validation of RCMs.     

Climate and Forecast Mode Simulations for Antarctica: Implications for Temperature and Wind

Climate and forecast mode simulations with the regional climate model HIRlam-ECHAM(HIRHAM) are evaluated over a pan-Antarctic domain. The ability of the model to simulate temperature and wind profiles in the troposphere is quantified by comparing its results with radiosonde data acquired from the Davis station for January and July 2007. Compared to the climate mode, the forecast mode was found to deliver improved results for temperature and wind simulations at the near surface and in the lower troposphere. The main remaining model bias found was the under-representation of low-level wind jets. Based on ensemble simulations, it is shown that a distinct internal variability is inherent in the climate mode simulations, and associated areas of reduced predictability over Antarctica are identified.     

气候模式-农业气象模式集成系统的小麦灌溉管理新途径

首次采用区域数值预报模式与农业气象模型结合的技术途径, 构成一个气候模式-土壤水分模式-灌溉模式的系统模型。模型的数值天气预报部分采用大气过程与陆面过程耦合的区域气候模式; 农业气象模型采用适用于冬小麦区的土壤水分和灌溉管理预报模型。研究表明, 本模型较农业气象模型中一般用气候平均作为环境背景场的方法其预测能力有显著提高, 并提供覆盖整个小麦生长期的区域土壤水分定量预报和灌溉管理服务, 具有很好的使用和推广前景。     

Analysis of high-resolution simulations for the Black Forest region from a point of view of tourism climatology �C a comparison between two regional climate models (REMO and CLM)

An analysis of climate simulations from a point of view of tourism climatology based on two regional climate models, namely REMO and CLM, was performed for a regional domain in the southwest of Germany, the Black Forest region, for two time frames, 1971?C2000 that represents the twentieth century climate and 2021?C2050 that represents the future climate. In that context, the Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and B1 are used. The analysis focuses on human-biometeorological and applied climatologic issues, especially for tourism purposes ?C that means parameters belonging to thermal (physiologically equivalent temperature, PET), physical (precipitation, snow, wind), and aesthetic (fog, cloud cover) facets of climate in tourism. In general, both models reveal similar trends, but differ in their extent. The trend of thermal comfort is contradicting: it tends to decrease in REMO, while it shows a slight increase in CLM. Moreover, REMO reveals a wider range of future climate trends than CLM, especially for sunshine, dry days, and heat stress. Both models are driven by the same global coupled atmosphere?Cocean model ECHAM5/MPI-OM. Because both models are not able to resolve meso- and micro-scale processes such as cloud microphysics, differences between model results and discrepancies in the development of even those parameters (e.g., cloud formation and cover) are due to different model parameterization and formulation. Climatic changes expected by 2050 are small compared to 2100, but may have major impacts on tourism as for example, snow cover and its duration are highly vulnerable to a warmer climate directly affecting tourism in winter. Beyond indirect impacts are of high relevance as they influence tourism as well. Thus, changes in climate, natural environment, demography, tourists?? demands, among other things affect economy in general. The analysis of the CLM results and its comparison with the REMO results complete the analysis performed within the project Climate Trends and Sustainable Development of Tourism in Coastal and Low Mountain Range Regions (CAST) funded by the German Federal Ministry of Education and Research (BMBF).     

RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.     

RegCM3对中国区域气候模拟的敏感性试验

为使区域气候模式RegCM3在中国区域气候的模拟中取得更好的模拟效果,针对RegCM3进行了初始场、模式水平分辨率、侧边界方案及积云对流方案的敏感性试验.结果表明:①从冬季开始的积分,模拟结果对初始场的依赖性较小;②模式水平分辨率的提高不一定会带来模拟效果的显著改善,高分辨率的嵌套模拟会对模拟效果有一定程度的改善;③选...     

Change in North American Atmospheric Conditions Associated with Deep Convection and Severe Weather using CRCM4 Climate Projections

Severe weather has important social and economic impacts. Some studies have indicated that its intensity may increase over this century as a consequence of climate change induced by greenhouse gases. This study aims to investigate the possibility of a future increase in deep convective events over North America resulting from the evolution of favourable atmospheric conditions. Our analysis is based on an ensemble of projections performed using the Canadian Regional Climate Model (CRCM) at 45?km resolution, driven by different Global Climate Models (GCMs) and reanalyses. We concentrate our study on Convective Available Potential Energy (CAPE), vertical wind shear, and convective precipitation. Based on two different approaches to linking atmospheric conditions and severe weather, we find that the number of extreme weather events is expected to increase during the twenty-first century. In agreement with other studies on this subject, we find that CAPE is expected to increase, whereas wind shear is expected to decrease slightly. Through the analysis of the CRCM's convective precipitation outputs, we show that severe convective liquid precipitation events may become both more frequent and slightly more intense. Sensitivity experiments show that results depend on the driving GCM although they confirm the general conclusions. Additional experiments conducted with reduced humidity input at the lateral boundaries show the significant role that the humidity level of the driving GCMs has on simulated extreme regional events. At the regional level results are, in general, consistent with those found at the continental scale, but large inter-regional variations exist.