Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.     

Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.     

High-resolution simulations for Vietnam - methodology and evaluation of current climate

To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.     

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

使用区域气候模式RegCM4.4,对全球模式CSIRO-Mk3.6.0在RCP4.5情景下的气候变化试验结果（1950-2100年）在东亚地区进行25 km动力降尺度试验,比较了CSIRO-Mk3.6.0和RegCM4.4预估中国地区的21世纪气候变化。结果表明,两个模式预估未来中国地区气温持续升高,升温幅度具有区域性特征,RegCM4.4预估区域平均升温幅度低于CSIRO-Mk3.6.0,但二者年际波动基本一致。两个模式预估未来降水在中国西部以持续增加为主,东部则表现出较大的不一致性,预估区域平均年降水量变化不大,呈现冬季明显增加,夏季微弱减少的特点。此外,为了解区域气候模式对中国降水预估的不确定性,对本研究和以往RegCM3使用相同分辨率模拟得到的未来降水预估进行了对比,两个区域模式预估中国西部大部分地区未来降水一致性增加,东部存在明显不一致（冬季中、高纬除外）。     

Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990)

We present an analysis of a multidecadal simulation of present-day climate (1961–1990) over Europe with the regional climate model RegCM nested within the global atmospheric model HadAMH. Climatic means, interannual variability and trends are examined, with focus on surface air temperature and precipitation. The RegCM driven by HadAMH fields is able to reproduce the basic features of the observed mean surface climate over Europe, its seasonal evolution and the regional detail due to topographic forcing. Surface air temperature biases are mostly less than 1–2 °C and precipitation biases mostly within 10–20%. The RegCM has more intense vertical transport of temperature and water vapor than HadAMH, which results in lower surface air temperatures and greater precipitation than found in the HadAMH simulation. In some cases this is in the direction of greater agreement with observations, while in others it is in the opposite direction. The simulation shows a tendency to overestimate interannual variability of temperature and precipitation compared to observations, particularly during summer and over the Mediterranean regions. It is shown that in DJF, MAM and SON the RegCM interannual variability is primarily determined by the boundary forcing from HadAMH, while in JJA the internal model physics and resolution effects dominate over many subregions of the domain, and the RegCM has higher interannual variability than HadAMH. The precipitation trends simulated by the nested modeling system for the period 1961–1990 capture some features of the observed trends, in particular the cold season drying over the Mediterranean regions. Ensembles of simulations are, however, needed for a more robust assessment of the models capability to simulate climatic trends. Overall, this simulation is of good quality compared with previous nested RegCM experiments and will constitute the basis for the generation of climate change scenarios over the European region to be reported in future work.     

不同区域气候模式对中国地区温度和降水的长期模拟比较

利用亚洲区域模式比较计划RMIP第二阶段五个区域模式和一个变网格全球模式，对中国地区1988年12月～1998年11月十年模拟的平均温度和降水结果，分析比较了不同区域气候模式对中国地区温度和降水的模拟能力。研究结果表明:几乎所有模式都能模拟出中国地区多年平均温度和降水的基本空间分布形态，但模式模拟的温度普遍偏低，在大部分区域，大多数模式模拟的降水偏多，而且不同模式之间存在较大差别。模式能较好地反映出中国地区温度的年际变化，对夏季降水的年际变化模拟较差，对冬季模拟较好。     

基于RegCM4模式的中国区域日尺度降水模拟误差订正

气候模式模拟得到的各气候变量与观测相比,总会存在一定的偏差,所得到的气候变化预估结果难以在影响评估模型中直接应用。本文尝试对一个区域气候模式（RegCM4.4）所模拟的中国区域逐日降水,基于概率分布（分位数映射）方法进行统计误差订正。在订正过程中,以模拟时段1991~2010年中的前半段（1991~2000年）作为参照时段,建立传递函数,对后一时段（2001~2010年）进行订正并检验其效果。首先对使用参数和非参数所建立的6种不同传递函数方法进行对比,发现6种方法均可明显减少降水模拟的误差,其中利用非参数转换建立传递函数的RQUANT方法效果更好。随后进一步分析了采用该方法对模式模拟降水所做订正的效果,结果表明,该方法可以明显改善对平均降水,以及降水年际变率和极端事件的模拟结果。     

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean(CMIP6-MME) can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature, and minimum daily minimum temperature. However, CMIP6-MME has difficulties in reproducing cold nights and warm days, and has large cold biases over the Tibetan Plateau. Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices. Compared to CMIP5, CMIP6 models show improvements in the simulation of climate indices over China. This is particularly true for precipitation indices for both the climatological pattern and the interannual variation, except for the consecutive dry days. The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME) to 79%(CMIP6-MME). The most striking feature is that the dry biases in southern China, very persistent and general in CMIP5-MME, are largely reduced in CMIP6-MME. Stronger ascent together with more abundant moisture can explain this reduction in dry biases. Wet biases for total precipitation, heavy precipitation, and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME, but smaller, compared to CMIP5-MME.     

气候系统模式FGOALS模拟的南亚夏季风：偏差和原因分析

本文通过与观测和再分析资料的对比,评估了LASG/IAP发展的气候系统模式FGOALS的两个版本FGOALS-g2和FGOALS-s2对南亚夏季风的气候态和年际变率的模拟能力,并使用水汽收支方程诊断,研究了造成降水模拟偏差的原因。结果表明,两个模式夏季气候态降水均在陆地季风槽内偏少,印度半岛附近海域偏多,在降水年循环中表现为夏季北侧辐合带北推范围不足。FGOALS-g2中赤道印度洋"东西型"海温偏差导致模拟的东赤道印度洋海上辐合带偏弱,而FGOALS-s2中印度洋"南北型"海温偏差导致模拟的海上辐合带偏向西南。水汽收支分析表明,两个模式中气候态夏季风降水的模拟偏差主要来自于整层积分的水汽通量,尤其是垂直动力平流项的模拟偏差。一方面,夏季阿拉伯海和孟加拉湾的海温偏冷而赤道西印度洋海温偏暖,造成向印度半岛的水汽输送偏少;另一方面,对流层温度偏冷,冷中心位于印度半岛北部对流层上层,同时季风槽内总云量偏少,云长波辐射效应偏弱,对流层经向温度梯度偏弱以及大气湿静力稳定度偏强引起的下沉异常造成陆地季风槽内降水偏少。在年际变率上,观测中南亚夏季风环流和降水指数与Ni?o3.4指数存在负相关关系,但FGOALS两个版本模式均存在较大偏差。两个模式中与ENSO暖事件相关的沃克环流异常下沉支和对应的负降水异常西移至赤道以南的热带中西印度洋,沿赤道非对称的加热异常令两个模式中越赤道环流季风增强,导致印度半岛南部产生正降水异常。ENSO相关的沃克环流异常下沉支及其对应的负降水异常偏西与两个模式对热带南印度洋气候态降水的模拟偏差有关。研究结果表明,若要提高FGOALS两个版本模式对南亚夏季风气候态模拟技巧,需减小耦合模式对印度洋海温、对流层温度及云的模拟偏差;若要提高南亚夏季风和ENSO相关性模拟技巧需要提高模式对热带印度洋气候态降水以及与ENSO相关的环流异常的模拟能力。     

Simulation of the summer circulation over South America by two regional climate models. Part I: Mean climatology

Summary This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model – EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.     

Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971–2000)

We present an analysis of a high resolution multi-decadal simulation of recent climate (1971–2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm/day are simulated only at the high resolution of the double nested domain. (5) The model shows a tendency to overestimate the number of precipitation days and to underestimate the precipitation intensities. (6) A CSEOF analysis reveals that the model captures the strength of the annual cycle and the surface warming trend throughout the simulated period.     

Climate Scenarios for the Southeastern U.S. Based on GCM and Regional Model Simulations

We analyze the control runs and 2 × CO₂ projections (5-yearlengths) of the CSIRO Mk 2 GCM and the RegCM2 regional climate model, which was nested in the CSIRO GCM, over the Southeastern U.S.; and we present the development of climate scenarios for use in an integrated assessment of agriculture. The RegCM exhibits smaller biases in both maximum and minimum temperature compared to the CSIRO. Domain average precipitation biases are generally negative and relatively small in winter, spring, and fall, but both models produce large positive biases in summer, that of the RegCM being the larger. Spatial pattern correlations of the model control runs and observations show that the RegCM reproduces better than the CSIRO the spatial patterns of precipitation, minimum and maximum temperature in all seasons. Under climate change conditions, the most salient feature from the point of view of scenarios for agriculture is the large decreases in summer precipitation, about 20% in the CSIRO and 30% in the RegCM. Increases in springprecipitation are found in both models, about 35% in the CSIRO and 25% in theRegCM. Precipitation decreases of about 20% dominate in winter in the CSIRO,while a more complex pattern of increases and decreases is exhibited by the regional model. Temperature increases by 3 to 5 °C in the CSIRO, the higher values dominating in winter and spring. In the RegCM, temperature increases are much more spatially and temporally variable, ranging from 1 to 7 °C acrossall months and grids. In summer large increases (up to 7 °C) in maximum temperature are found in the northeastern part of the domain where maximum drying occurs.     

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.     

Downscaled simulations of the ECHAM5, CCSM3 and HadCM3 global models for the eastern Mediterranean–Black Sea region: evaluation of the reference period

The outputs of three GCMs, ECHAM5, CCSM3 and HadCM3, are downscaled for the eastern Mediterranean–Black Sea region for the period 1961–1990 using a regional climate model, RegCM3, to assess the capability of these models in simulating the climatology of the region. In addition, the NCEP/NCAR Reanalysis data are also downscaled for the same period to display the performance of the regional climate model for the same region, which constitutes a relatively complex terrain and rich variety of climates. The gridded observational dataset of CRU is primarily used in the evaluation of the models, however, a regional dataset, which is based on a relatively dense gauging network, is also used to see how it affects the performance measures of the models. The reanalysis simulation indicates that RegCM3 is able to simulate the precipitation and surface temperature as well as the upper level fields reasonably well. However, it tends to overestimate the precipitation over the mountainous areas. All three GCM models are found to be highly skilled in simulating the winter precipitation and temperature in the region. The two models, ECHAM5 and HadCM3, are also good at simulating the summer precipitation and temperature, but the CCSM3 simulation generates dryer and warmer conditions than the observations for the whole region, which are most likely a result of the dryness in the upper levels of the original outputs. The use of the regional observational dataset does not necessarily improve the pattern correlations, but it yields better match between the modeled and observed precipitation in terms of variability and root-mean-square difference. It could be said that the outputs of these GCMs can be used in the climate change downscaling and impact assessment studies for the region, given that their strengths and weaknesses that are displayed in the present study are considered.     

Assessment of Temperature Extremes in China Using RegCM4 and WRF

This study assesses the performance of temperature extremes over China in two regional climate models(RCMs),RegCM4 and WRF, driven by the ECMWF's 20 th century reanalysis. Based on the advice of the Expert Team on Climate Change Detection and Indices(ETCCDI), 12 extreme temperature indices(i.e., TXx, TXn, TNx, TNn, TX90 p, TN90 p,TX10 p, TN10 p WSDI, ID, FD, and CSDI) are derived from the simulations of two RCMs and compared with those from the daily station-based observational data for the period 1981–2010. Overall, the two RCMs demonstrate satisfactory capability in representing the spatiotemporal distribution of the extreme indices over most regions. RegCM performs better than WRF in reproducing the mean temperature extremes, especially over the Tibetan Plateau(TP). Moreover, both models capture well the decreasing trends in ID, FD, CSDI, TX10 p, and TN10 p, and the increasing trends in TXx, TXn, TNx, TNn, WSDI, TX90 p,and TN90 p, over China. Compared with observation, RegCM tends to underestimate the trends of temperature extremes,while WRF tends to overestimate them over the TP. For instance, the linear trends of TXx over the TP from observation,RegCM, and WRF are 0.53?C(10 yr)^-1, 0.44?C(10 yr)^-1, and 0.75?C(10 yr)^-1, respectively. However, WRF performs better than RegCM in reproducing the interannual variability of the extreme-temperature indices. Our findings are helpful towards improving our understanding of the physical realism of RCMs in terms of different time scales, thus enabling us in future work to address the sources of model biases.     

The WAMME regional model intercomparison study

Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed.     

Introduction to the Regional Coupled Model WRF4-LICOM: Performance and Model Intercomparison over the Western North Pacific

Regional coupled modeling is one of the frontiers of regional climate modeling, but intercomparison has not been well coordinated. In this study, a community regional climate model, WRF4, with a resolution of 15 km, was coupled with a high-resolution(0.1°) North Pacific Ocean model(LICOM_np). The performance of the regional coupled model,WRF4_LICOM, was compared to that of another regional coupled model, RegCM4_LICOM, which was a coupling of version 4 of the Regional Climate Model(RegCM4) with LICOM_np. The analysis focused on the 2005 western North Pacific summer monsoon rainfall. The results showed that the regional coupled models with either RegCM4 or WRF4 as their atmospheric model component simulated the broad features over the WNP reasonably well. Quantitative intercomparison of the regional coupled simulations exhibited different biases for different climate variables.RegCM4_LICOM exhibited smaller biases in its simulation of the averaged June–July–August SST and rainfall, while WRF4_LICOM better captured the tropical cyclone(TC) intensity, the percentage contributions of rainfall induced by TCs to the total rainfall, and the diurnal cycle of rainfall and stratiform percentages, especially over land areas. The different behaviors in rainfall simulated by the two models were partly ascribed to the behaviors in the simulated western North Pacific subtropical high(WNPSH). The stronger(weaker) WNPSH in WRF4_LICOM(RegCM4_LICOM) was driven by overestimated(underestimated) diabatic heating, which peaked at approximately 450 hPa over the region around the Philippines in association with different condensation–radiation processes. Coupling of WRF4 with LIOCM is a crucial step towards the development of the next generation of regional earth system models at the Chinese Academy of Sciences.     

Performance of RegCM4 over Major River Basins in China

A long-term simulation for the period 1990–2010 is conducted with the latest version of the International Centre for Theoretical Physics' Regional Climate Model(RegCM4), driven by ERA-Interim boundary conditions at a grid spacing of 25 km. The Community Land Model(CLM) is used to describe land surface processes, with updates in the surface parameters,including the land cover and surface emissivity. The simulation is compared against observations to evaluate the model performance in reproducing the present day climatology and interannual variability over the 10 main river basins in China,with focus on surface air temperature and precipitation. Temperature and precipitation from the ERA-Interim reanalysis are also considered in the model assessment. Results show that the model reproduces the present day climatology over China and its main river basins, with better performances in June–July–August compared to December–January–February(DJF).In DJF, we find a warm bias at high latitudes, underestimated precipitation in the south, and overestimated precipitation in the north. The model in general captures the observed interannual variability, with greater skill for temperature. We also find an underestimation of heavy precipitation events in eastern China, and an underestimation of consecutive dry days in northern China and the Tibetan Plateau. Similar biases for both mean climatology and extremes are found in the ERA-Interim reanalysis, indicating the difficulties for climate models in simulating extreme monsoon climate events over East Asia.     

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.     

Multiseason evaluation of the MM5, COAMPS and WRF over southeast United States

Three models, MM5, COAMPS, and WRF, have been applied for the warm season in 2003 and the cool season in 2003?C2004 to evaluate their performances. All models run over the same domain area covering the north Gulf Mexico and southeastern United States (US) region with the same spatial resolution of 27?km. It was found that the temporal variations of the mean error distribution and strength at 24 and 36?h were rather weak for surface temperature, sea level pressure, and surface wind speed for all models. A warm bias in surface temperature forecasts dominated over land during the warm season, whereas a cool bias existed during the cool season. The MM5 and WRF produced negative biases of sea level pressure during the warm season and positive biases during the cool season while the COAMPS yielded a similar distribution of sea level pressure biases during both seasons. During both seasons, similar surface wind speed biases produced by each model included a high wind speed forecast over most areas by MM5 while the COAMPS and WRF yielded weak surface winds over the western Plains and stronger surface winds over the eastern Plains. Root-mean-squared errors revealed that the forecast of surface temperature, sea level pressure, and surface wind speed were degraded with the increase of forecast time. For rainfall evaluation, it was found that the MM5 underpredicted seasonal precipitation while the COAMPS and WRF overpredicted. The bias scores revealed that the MM5 yielded an underprediction of the coverage of precipitation areas, especially for heavier rainfall events. The MM5 presented the lower threat score at lighter rainfall events compared to the COAMPS and WRF. For moderate and heavier thresholds, all models lacked forecast accuracy. The WRF accuracy in predicting precipitation was heavily dependent upon the performance of the selected cumulus parameterization scheme. Use of the Grell?CDevenyi and Bette?CMiller?CJanjic schemes helps suppress precipitation overprediction.