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1.
This study illustrates the sensitivity of regional climate change projections to the model physics. A single-model (MM5) multi-physics ensemble of regional climate simulations over the Iberian Peninsula for present (1970–1999) and future (2070–2099 under the A2 scenario) periods is assessed. The ensemble comprises eight members resulting from the combination of two options of parameterization schemes for the planetary boundary layer, cumulus and microphysics. All the considered combinations were previously evaluated by comparing hindcasted simulations to observations, none of them providing clearly outlying climates. Thus, the differences among the various ensemble members (spread) in the future projections could be considered as a matter of uncertainty in the change signals (as similarly assumed in multi-model studies). The results highlight the great dependence of the spread on the synoptic conditions driving the regional model. In particular, the spread generally amplifies under the future scenario leading to a large spread accompanying the mean change signals, as large as the magnitude of the mean projected changes and analogous to the spread obtained in multi-model ensembles. Moreover, the sign of the projected change varies depending on the choice of the model physics in many cases. This, together with the fact that the key mechanisms identified for the simulation of the climatology of a given period (either present or future) and those introducing the largest spread in the projected changes differ significantly, make further claims for efforts to better understand and model the parameterized subgrid processes.  相似文献   

2.
This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature.  相似文献   

3.
We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.  相似文献   

4.
基于多模式短期集合预报技术的热带气旋降水预报试验   总被引:3,自引:1,他引:2  
利用中尺度AREM和WRF模式为试验模式,由对降水预报结果影响颇大的积云和边界层参数化方案构成的10个集合预报成员,开展有限区域多模式短期集合预报在热带气旋降水预报中的应用与研究.分别研究了单个模式集合预报和多模式集合预报在热带气旋"天鹅"(0907)降水预报中的应用.试验结果表明:(1) WRF模式集合预报效果整体上...  相似文献   

5.
In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated “Newy”). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ~10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.  相似文献   

6.
不同参数化方案对长江中游汛期降水模式预报试验   总被引:2,自引:2,他引:0  
李俊  王斌  王志斌  沈铁元 《气象科技》2008,36(2):134-138
利用中尺度模式多个物理过程组合成不同预报方案,对长江中游汛期降水预报进行了对比试验.试验结果表明,使用不同物理过程参数化方案对长江中游汛期降水的预报效果存在差异,这种差异随降水预报量级的提高而愈加明显;而就试验而言,Grell积云对流参数化方案与Blackadar边界层参数化方案的组合预报效果相对较好;就单个降水个例而言,预报效果相对好的参数化方案存在不确定性,集合平均预报相对稳定且优于大多数方案,其对降水评分的改进尤其体现在暴雨以下量级的预报中.  相似文献   

7.
The use of high resolution atmosphere–ocean coupled regional climate models to study possible future climate changes in the Mediterranean Sea requires an accurate simulation of the atmospheric component of the water budget (i.e., evaporation, precipitation and runoff). A specific configuration of the version 3.1 of the weather research and forecasting (WRF) regional climate model was shown to systematically overestimate the Mediterranean Sea water budget mainly due to an excess of evaporation (~1,450 mm yr?1) compared with observed estimations (~1,150 mm yr?1). In this article, a 70-member multi-physics ensemble is used to try to understand the relative importance of various sub-grid scale processes in the Mediterranean Sea water budget and to evaluate its representation by comparing simulated results with observed-based estimates. The physics ensemble was constructed by performing 70 1-year long simulations using version 3.3 of the WRF model by combining six cumulus, four surface/planetary boundary layer and three radiation schemes. Results show that evaporation variability across the multi-physics ensemble (~10 % of the mean evaporation) is dominated by the choice of the surface layer scheme that explains more than ~70 % of the total variance and that the overestimation of evaporation in WRF simulations is generally related with an overestimation of surface exchange coefficients due to too large values of the surface roughness parameter and/or the simulation of too unstable surface conditions. Although the influence of radiation schemes on evaporation variability is small (~13 % of the total variance), radiation schemes strongly influence exchange coefficients and vertical humidity gradients near the surface due to modifications of temperature lapse rates. The precipitation variability across the physics ensemble (~35 % of the mean precipitation) is dominated by the choice of both cumulus (~55 % of the total variance) and planetary boundary layer (~32 % of the total variance) schemes with a strong regional dependence. Most members of the ensemble underestimate total precipitation amounts with biases as large as 250 mm yr?1 over the whole Mediterranean Sea compared with ERA Interim reanalysis mainly due to an underestimation of the number of wet days. The larger number of dry days in simulations is associated with a deficit in the activation of cumulus schemes. Both radiation and planetary boundary layer schemes influence precipitation through modifications on the available water vapor in the boundary layer generally tied with changes in evaporation.  相似文献   

8.
This study evaluated the ability of Weather Research and Forecasting (WRF) multi-physics ensembles to simulate storm systems known as East Coast Lows (ECLs). ECLs are intense low-pressure systems that develop off the eastern coast of Australia. These systems can cause significant damage to the region. On the other hand, the systems are also beneficial as they generate the majority of high inflow to coastal reservoirs. It is the common interest of both hazard control and water management to correctly capture the ECL features in modeling, in particular, to reproduce the observed spatial rainfall patterns. We simulated eight ECL events using WRF with 36 model configurations, each comprising physics scheme combinations of two planetary boundary layer (pbl), two cumulus (cu), three microphysics (mp), and three radiation (ra) schemes. The performance of each physics scheme combination and the ensembles of multiple physics scheme combinations were evaluated separately. Results show that using the ensemble average gives higher skill than the median performer within the ensemble. More importantly, choosing a composite average of the better performing pbl and cu schemes can substantially improve the representation of high rainfall both spatially and quantitatively.  相似文献   

9.
A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations.  相似文献   

10.
为评估CWRF模式的降尺度能力和其热带气旋模拟对物理参数化方案的敏感性,本文利用ERI再分析资料驱动CWRF在30km网格上对1982-2016年中国近海热带气旋开展了一次集合模拟.结果表明:CWRF与ERI均能模拟出热带气旋的季节变化和年际变化形势且均存在低估,但相较ERI,CWRF的降尺度技术和集合模拟可以再现更多的热带气旋,显著减少低估.年际变化结果提升最为明显,它对积云方案最为敏感,其次是边界层,陆面和辐射方案,对云和微物理方案较弱.该研究为应用CWRF理解和预报热带气旋提供了参考.  相似文献   

11.
2003年江淮汛期多模式短期集合预报方法研究   总被引:8,自引:3,他引:5  
利用AREM、MM5和WRF模式为试验模式,由对短期天气预报结果影响颇大的积云参数化方案和边界层方案构成15个集合预报成员,开展有限区域多模式短期集合预报在我国汛期时段的应用与研究.分别研究了单个模式集合预报和多模式集合预报在2003年汛期(7月)预报中的应用,预报对象主要包括降水、500 hPa位势高度和700 hPa相对湿度.试验结果表明:(1) 由AREM、MM5和WRF模式构成的多模式集合对以上要素的集合预报总体效果比其任一单个模式的集合预报效果好;(2) 对于降水的集合预报,单个模式的集合平均结果对多模式集合预报效果有影响.且对于不同的降水临界值影响不同;当降水临界值较小时,单模式集合平均结果对多模式集合效果影响较小;当降水临界值较大时,影响较大,甚至可以影响多模式集合的集合平均预报成败;(3) 对于降水、500 hPa位势高度和700 hPa相对湿度,其单个模式以及多模式的48 h集合预报对确定性预报的改善度都比24 h的显著.(4) 对于形势预报和相对湿度预报,多模式集合预报效果明显比同期T213模式的预报水平高.  相似文献   

12.
The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.  相似文献   

13.
Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.  相似文献   

14.
To evaluate the downscaling ability with respect to tropical cyclones (TCs) near China and its sensitivity to the model physics representation, the authors performed a multi-physics ensemble simulation with the regional Climate–Weather Research and Forecasting (CWRF) model at a 30 km resolution driven by ERA-Interim reanalysis data. The ensemble consisted of 28 integrations during 1979–2016 with varying CWRF physics configurations. Both CWRF and ERA-Interim can generally capture the seasonal cycle and interannual variation of the TC number near China, but evidently underestimate them. The CWRF downscaling and its multi-physics ensemble can notably reduce the underestimation and significantly improve the simulation of the TC occurrences. The skill enhancement is especially large in terms of the interannual variation, which is most sensitive to the cumulus scheme, followed by the boundary layer, surface and radiation schemes, but weakly sensitive to the cloud and microphysics schemes. Generally, the Noah surface scheme, CAML(CAM radiation scheme as implemented by Liang together with the diagnostic cloud cover scheme of Xu and Randall(1996)) radiation scheme, prognostic cloud scheme, and Thompson microphysics scheme stand out for their better performance in simulating the interannual variation of TC number. However, the Emanuel cumulus and MYNN boundary layer schemes produce severe interannual biases. Our study provides a valuable reference for CWRF application to improve the understanding and prediction of TC activity.摘要为评估CWRF模式的降尺度能力和其热带气旋模拟对物理参数化方案的敏感性, 本文利用ERI再分析资料驱动CWRF在30km网格上对1982-2016年中国近海热带气旋开展了一次集合模拟.结果表明:CWRF与ERI均能模拟出热带气旋的季节变化和年际变化形势且均存在低估, 但相较ERI, CWRF的降尺度技术和集合模拟可以再现更多的热带气旋, 显著减少低估.年际变化结果提升最为明显, 它对积云方案最为敏感, 其次是边界层, 陆面和辐射方案, 对云和微物理方案较弱.该研究为应用CWRF理解和预报热带气旋提供了参考.  相似文献   

15.
物理过程参数化方案对中尺度暴雨数值模拟影响的研究   总被引:48,自引:5,他引:43  
陈静  薛纪善  颜宏 《气象学报》2003,61(2):203-218
利用中尺度非静力MM 5模式和中国 2 0 0 1年 8月的 4个暴雨个例 ,研究了非绝热物理过程对中国暴雨动力和热力场预报的影响 ,深入分析了对流参数化方案在中尺度暴雨预报中的作用 ,讨论了利用模式扰动方法开展中国暴雨集合预报的可行性。结果表明 ,在短期数值预报中 ,非绝热物理过程对高度场预报影响较小 ,但边界层方案和对流参数化方案对产生暴雨的 3个基本条件即水汽通量散度、垂直速度、不稳定层结的影响很明显。不同对流参数化方案所预报的中尺度热力、动力场离差的结构特征与所预报降水的离差特征相似 ,且主要是在模式积分初期迅速增加 ,其后即趋于稳定。对中国热力场较均匀的暴雨过程 ,可以通过扰动模式的边界层和对流参数化方案 ,构造集合预报模式  相似文献   

16.
By using the Betts-Miller-Janjic, Grell-Devenyi, and Kain-Fritsch cumulus convective parameterization schemes in theWeather Research and Forecasting (WRF) model, long time simulations from 2000 to 2009 are conducted to investigate the impacts of different cumulus convective parameterization schemes on summer monsoon precipitation simulation over China. The results show that all the schemes have the capability to reasonably reproduce the spatial and temporal distributions of summer monsoon precipitation and the corresponding background circulation. The observed north-south shift of monsoon rain belt is also well simulated by the three schemes. Detailed comparison indicates that the Grell-Devenyi scheme gives a better performance than the others. Deficiency in simulated water vapor transport is one possible reason for the precipitation simulation bias.  相似文献   

17.
In the context of non-hydrostatic MM5 version we have explored the impact of convective parameterization schemes on uncertainty in mesoscale numerical prediction of South China heavy rain and mesoscale heavy rainfall short-range ensemble simulation by using two kinds of physics perturbation methods through a heavy rain case occurring on June 8, 1998 in Guangdong and Fujian Provinces. The results show the physical process of impacts of convective schemes on heavy rainfall is that different latent heat of convective condensation produced by different convective schemes can make local temperature perturbation, leading to the difference of local vertical speed by the intrinsic dynamic and thermodynamic processes of atmosphere,and therefore, making difference of the timing, locations and strength of mesh scale and subgrid scale precipitation later. New precipitations become the new source of latent heat and temperature perturbation,which finally make the dynamic and thermodynamic structures different in the simulations. Two kinds of methods are used to construct different model version stochastically. The first one is using different convective parameterization and planetary boundary layer schemes, the second is adjusting different parameters of convective trigger functions in Grell scheme. The results indicate that the first ensemble simulations can provide more uncertainty information of location and strength of heavy rainfall than the second. The single determinate predictions of heavy rain are unstable; physics ensemble predictions can reflect the uncertainty of heavy rain, provide more useful guidance and have higher application value.Physics ensembles suggest that model errors should be taken into consideration in the heavy rainfall ensembles. Although the method of using different parameters in Grell scheme could not produce good results, how to construct the perturbation model or adjust the parameter in one scheme according to the physical meaning of the parameter still needs further investigation. The limitation of the current study is that it is based on a single case and more cases will be addressed in the future researches.  相似文献   

18.
This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble (TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean (BREM) and superensemble (SUP), are compared with the ensemble mean (EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.  相似文献   

19.
短期集合预报技术在梅雨降水预报中的试验研究   总被引:38,自引:6,他引:32       下载免费PDF全文
数值预报的误差来源于初始场和模式的误差,集合预报技术是减小这些误差的有效方法。该文以MM5模式作为试验模式框架,模式的积云参数化方案分别取Anthes-Kuo、Grell、Kain-Fritsch和Betts-Miller方案,边界层参数化方案分别取MRF和Eta方案,通过组合4种积云参数化方案和两种边界层参数化方案产生8个集合成员,对1999年华东地区梅雨期间3个降水个例进行48 h集合预报试验。结果显示不同集合成员的预报结果各不相同,积云参数化方案对降水的影响比边界层参数化方案对降水的影响大;不同集合成员预报降水的偏差也各不相同,大多存在湿偏差,量级小的降水的湿偏差程度比量级大的降水的湿偏差程度小;对于不同个例,各成员中预报效果相对较好的成员是不同的,集合平均后可以得到一个比较稳定的预报结果;从集合预报结果中还能得到客观化和定量化的降水概率预报,它能对可能发生的天气现象发出信号。  相似文献   

20.
The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (PSU-NCAR MM5). The feasibility of physical ensemble and the effect of interior (spectral) nudging are also assessed. The RCM simulations are evaluated against the NCEP/NCAR reanalysis data and NCEP/CPC precipitation data for three summers (JJA) in 1991, 1998, and 2003. The results show that the RCM is highly sensitive to CUPA schemes. Different CUPA schemes cause distinctive characteristics in the modeling of JJA precipitation and the intraseasonal (daily) variability of regional precipitation. The sensitivity of the RCM simulations to the CUPA schemes is reduced by adopting the spectral nudging technique, which enables the RCM to reproduce more realistic large-scale circulations at the upper levels of the atmosphere as well as near the surface, and better precipitation simulation in the selected experiments. The ensemble simulations using different CUPA schemes show higher skills than individual members for both control runs and spectral nudging runs. The physical ensemble adopting the spectral nudging technique shows the highest downscaling skill in capturing the general circulation patterns for all experiments and improved temporal distributions of precipitation in some regions.  相似文献   

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