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.     

Simulating future Caspian sea level changes using regional climate model outputs

We report on simulations of present-day climate (1961–1990) and future climate conditions (2071–2100, Special Report on Emissions Scenario A2) over the Caspian sea basin with a regional climate model (RCM) nested in time-slice general circulation model (GCM) simulations. We also calculate changes (A2 scenario minus present-day) in Caspian sea level (CSL) in response to changes in the simulated hydrologic budget of the basin. For the present-day run, both the GCM and RCM show a good performance in reproducing the water budget of the basin and the magnitude of multi-decadal changes in CSL. Compared to present-day climate, in the A2 scenario experiment we find an increase in cold season precipitation and an increase in temperature and evaporation, both over land and over the Caspian sea. We also find a large decrease of CSL in the A2 scenario run compared to the present-day run. This is due to increased evaporation loss from the basin (particularly over the sea) exceeding increased cold season precipitation over the basin. Our results suggest that the CSL might undergo large changes under future climate change, leading to potentially devastating consequences for the economy and environment of the region.     

东亚区域极端气候事件变化的数值模拟试验

使用ResCM2区域气候模式,嵌套澳大利亚CSIRO R21L9全球海气耦合模式,进行了温室效应（二氧化碳加倍）对东亚（主要是中国区域）极端气候事件影响的数值试验。控制试验的结果表明,区域模式能够较好地模拟中国区域的极端气候事件。对温室效应引起的它们的变化进行了信度检验,分析结果表明,温室效应将引起日最高和最低气温增加,日较差减小;使得高温天气增多,低温日数减少。降水日数和大雨日数在一些地区将增加。同时还会引起影响中国的台风活动的变化。     

Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model

The COSMO-CLM (CCLM) model is applied to perform regional climate simulation over the second phase of CORDEX-East Asia (CORDEX-EA-II) domain in this study. Driven by the ERAInterim reanalysis data, the model was integrated from 1988 to 2010 with a high resolution of 0.22°. The model’s ability to reproduce mean climatology and climatic extremes is evaluated based on various aspects. The CCLM model is capable of capturing the basic features of the East Asia climate, including the seasonal mean patterns, interannual variations, annual cycles and climate extreme indices for both surface air temperature and precipitation. Some biases are evident in certain areas and seasons. Warm and wet biases appear in the arid and semi-arid areas over the northwestern and northern parts of the domain. The simulated climate over the Tibetan Plateau is colder and wetter than the observations, while South China, East China, and India are drier. The model biases may be caused by the simulated anticyclonic and cyclonic biases in low-level circulations, the simulated water vapor content biases, and the inadequate physical parameterizations in the CCLM model. A parallel 0.44° simulation is conducted and the comparison results show some added value introduced by the higher resolution 0.22° simulation. As a result, the CCLM model could be an adequate member for the next stage of the CORDEX-EA project, while further studies should be encouraged.     

Projections of daily mean temperature variability in the future: cross-validation tests with ENSEMBLES regional climate simulations

Because of model biases, projections of future climate need to combine model simulations of recent and future climate with information on observed climate. Here, 10 methods for projecting the distribution of daily mean temperatures are compared, using six regional climate change simulations for Europe. Cross validation between the models is used to assess the potential performance of the methods in projecting future climate. Delta change and bias correction type methods show similar cross-validation performance, with methods based on the quantile mapping approach doing best in both groups due to their apparent ability to reduce the errors in the projected time mean temperature change. However, as no single method performs best under all circumstances, the optimal approach might be to use several well-behaving methods in parallel. When applying the various methods to real-world temperature projection for the late 21st century, the largest intermethod differences are found in the tails of the temperature distribution. Although the intermethod variation of the projections is generally smaller than their intermodel variation, it is not negligible. Therefore, it should be preferably included in uncertainty analysis of temperature projections, particularly in applications where the extremes of the distribution are important.     

Recent past and future patterns of the Etesian winds based on regional scale climate model simulations

The aim of this work is to investigate the recent past and future patterns of the Etesian winds, one of the most persistent localized wind systems in the world, which dominates the wind regime during warm period over the Aegean Sea and eastern Mediterranean. An objective classification method, the Two Step Cluster Analysis (TSCA), is applied on daily data from regional climate model simulations carried out with RegCM3 for the recent past (1961–1990) and future periods (2021–2050 and 2071–2100) constrained at lateral boundaries either by ERA-40 reanalysis fields or the global circulation model (GCM) ECHAM5. Three distinct Etesian patterns are identified by TSCA with the location and strength of the anticyclonic action center dominating the differences among the patterns. In case of the first Etesian pattern there is a ridge located over western and central Europe while for the other two Etesian patterns the location of the ridge moves eastward indicating a strong anticyclonic center over the Balkans. The horizontal and vertical spatial structure of geopotential height and the vertical velocity indicates that in all three Etesian patterns the anticyclonic action center over central Europe or Balkan Peninsula cannot be considered as an extension of the Azores high. The future projections for the late 21st century under SRES A1B scenario indicate a strengthening of the Etesian winds associated with the strengthening of the anticyclonic action center, and the deepening of Asian thermal Low over eastern Mediterranean. Furthermore the future projections indicate a weakening of the subsidence over eastern Mediterranean which is rather controlled by the deepening of the south Asian thermal Low in line with the projected in future weakening of South Asian monsoon and Hadley cell circulations.     

增暖背景下东亚夏季风区降水演变的空间模态及其形成机制

基于CMIP5中全新世(Mid-Holocene,6 ka BP)试验及RCP8.5试验的对比,本文研究了不同增暖情景下东亚夏季风区降水演变的空间模态及其成因.结果表明,两种增暖情景下东亚夏季风区降水演变的空间模态存在显著差异.轨道辐射主导的中全新世暖期期间,东亚夏季风区降水演变的空间模态为经向三极子结构;而大气C...     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Evaluating uncertainties in regional climate simulations over South America at the seasonal scale

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.     

欧洲多个耦合气候模式对东亚冬季气候的预测性能研究

在短期气候预测方法中,多模式集合预测作为一种实用方法得到了广泛的研究。利用DEMETER多模式集合预测系统1980—2001年的回报试验,研究了欧洲7个耦合模式对东亚地区(0°—60°N,70°—140°E)冬季大气环流和气候异常的预测效能。研究的气候要素是冬季500 hPa高度场、850 hPa风场、表面气温场和降水场。集合平均(EM)是最基本的多模式集合构建方法。为了进一步订正模式预测的误差,基于经验正交函数分解进行订正,产生“合成数据集”,并利用该数据集进行合成集合平均或合成超级集合(SEM/SSE)。研究表明,东亚地区冬季气候异常的模式预测效能热带高于中高纬度地区,海洋高于内陆。多模式集合平均和合成集合平均或合成超级集合均从整体上对东亚地区冬季气候异常的预测效能有一定程度的提高,体现了其相对于7个单一模式的优势。两类不同的多模式集合方法对预测结果也有一定的影响,其中,合成集合平均或合成超级集合对冬季500 hPa高度场、850 hPa风场和降水场异常的预测效能优于集合平均;但是对于冬季表面气温场异常的预测,集合平均优于合成集合平均或合成超级集合。     

嵌套域大小对区域气候模式模拟效果的影响

This paper presents a numerical study on the 1998 summer rainfall over the Yangtze River valley in central and eastern China, addressing effect of a nested area size on simulations in terms of the technique of nesting a regional climate model (RCM) upon a general circulation model (GCM). Evidence suggests that the size exerts greater impacts upon regional climate of the country, revealing that a larger nested size is su perior to a small one for simulation in mitigating errors of GCM-provided lateral boundary forcing. Also,simulations show that the RCM should incorporate regions of climate systems of great importance into study and a low-resolution GCM yields more pronounced errors as a rule when used in the research of the Tibetan Plateau, and, in contrast, our PσRCM can do a good job in describing the plateau′s role in a more realistic and accurate way. It is for this reason that the tableland should be included in the nested area when the RCM is employed to investigate the regional climate. Our PσRCM nesting upon a GCM reaches morerealistic results compared to a single GCM used.     

Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme

This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23?years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates that the proposed weighting factors reflect well all five attributes and the performances of weighted averaged references are better than that of the best single model. This study also found that the improvement of WARs’ performance is due to the reliability (accuracy) of RCMs rather than the ensemble size.     

Probabilistic multimodel ensemble prediction of decadal variability of East Asian surface air temperature based on IPCC-AR5 near-term climate simulations

Based on near-term climate simulations for IPCC-AR5 (The Fifth Assessment Report), probabilistic multimodel ensemble prediction (PMME) of decadal variability of surface air temperature in East Asia (20°-50 °N, 100°-145°E) was conducted using the multivariate Gaussian ensemble kernel dressing (GED) methodology. The ensemble system exhibited high performance in hindcasting the decadal (1981-2010) mean and trend of temperature anomalies with respect to 1961-90, with a RPS of 0.94 and 0.88 respectively. The interpretation of PMME for future decades (2006-35) over East Asia was made on the basis of the bivariate probability density of the mean and trend. The results showed that, under the RCP4.5 (Representative Concentration Pathway 4.5 W m-2 ) scenario, the annual mean temperature increases on average by about 1.1-1.2 K and the temperature trend reaches 0.6-0.7 K (30 yr)-1 . The pattern for both quantities was found to be that the temperature increase will be less intense in the south. While the temperature increase in terms of the 30-yr mean was found to be virtually certain, the results for the 30-yr trend showed an almost 25% chance of a negative value. This indicated that, using a multimodel ensemble system, even if a longer-term warming exists for 2006-35 over East Asia, the trend for temperature may produce a negative value. Temperature was found to be more affected by seasonal variability, with the increase in temperature over East Asia more intense in autumn (mainly), faster in summer to the west of 115°E, and faster still in autumn to the east of 115°E.     

Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC） Part Ⅱ： The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center (NCC) since 2001. The NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM (CGCM) provides the boundary and initial conditions for driving the regional climate model (RegCM NCC). The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme (TKE) and an improved land process model (LPM). The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part I. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model’s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast (1991–2000) for summer (June–August), the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient (ACC) are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM NCC were made. The results are basically reasonable compared with the observations.     

Impact of the Atlantic multidecadal variability on East Asian summer climate in idealized simulations

本文利用基于地球系统模式CESM1开展的北大西洋多年代际振荡理想化数值试验,研究了北大西洋多年代际振荡对东亚夏季气候的影响.结果显示,北大西洋多年代际振荡可以通过中纬度罗斯贝波以及热带开尔文波的传播两种途■影响东亚夏季气候.当北大西洋多年代际振荡处于正位相时,一方面,偏暖的北大西洋通过激发一条从北大西洋向下游传播的中纬度大气罗斯贝波列导致东亚陆地气压降低而西北太平洋气压升高,使得东亚-西北太平洋之间的海陆气压差增强;另一方面,偏暖的北大西洋激发赤道开尔文波东传,激发西北太平洋对流层低层出现反气旋式环流异常.通过以上两种途■,正位相的北大西洋多年代际振荡最终导致东亚夏季风增强,东亚地区夏季出现北湿南干和偏暖的气候.     

High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions

To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections.