Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

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.     

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.     

Evaluation of the CORDEX regional climate models performance in simulating climate conditions of two catchments in Upper Blue Nile Basin

This study was targeted at evaluating the performance of six Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX). The evaluation is on the bases of how well the RCMs simulate the seasonal mean climatology, interannual variability and annual cycles of rainfall, maximum and minimum temperature over two catchments in western Ethiopia during the period 1990–2008. Observed data obtained from the Ethiopian National Meteorological Agency was used for performance evaluation of the RCMs outputs. All Regional Climate Models (RCMs) have simulated seasonal mean annual cycles of precipitation with a significant bias shown on individual models; however, the ensemble mean exhibited better the magnitude and seasonal rainfall. Despite the highest biases of RCMs in the wet season, the annual cycle showed the prominent features of precipitation in the two catchments. In many aspects, CRCM5 and RACMO22 T simulate rainfall over most stations better than the other models. The highest biases are associated with the highest error in simulating maximum and minimum temperature with the highest biases in high elevation areas. The rainfall interannual variability is less evident in Finchaa with short rainy season experiencing a larger degree of interannual variability. The differences in performance of the Regional Climate Models in the two catchments show that all the available models are not equally good for particular locations and topographies. In this regard, the right regional climate models have to be used for any climate change impact study for local-scale climate projections.     

Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

Regional climate modelling represents an appealing approach to projecting Great Lakes water supplies under a changing climate. In this study, we investigate the response of the Great Lakes Basin to increasing greenhouse gas and aerosols emissions using an ensemble of sixteen climate change simulations generated by three different Regional Climate Models (RCMs): CRCM4, HadRM3 and WRFG. Annual and monthly means of simulated hydro-meteorological variables that affect Great Lakes levels are first compared to observation-based estimates. The climate change signal is then assessed by computing differences between simulated future (2041–2070) and present (1971–1999) climates. Finally, an analysis of the annual minima and maxima of the Net Basin Supply (NBS), derived from the simulated NBS components, is conducted using Generalized Extreme Value distribution. Results reveal notable model differences in simulated water budget components throughout the year, especially for the lake evaporation component. These differences are reflected in the resulting NBS. Although uncertainties in observation-based estimates are quite large, our analysis indicates that all three RCMs tend to underestimate NBS in late summer and fall, which is related to biases in simulated runoff, lake evaporation, and over-lake precipitation. The climate change signal derived from the total ensemble mean indicates no change in future mean annual NBS. However, our analysis suggests an amplification of the NBS annual cycle and an intensification of the annual NBS minima in future climate. This emphasizes the need for an adaptive management of water to minimize potential negative implications associated with more severe and frequent NBS minima.     

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.     

三江源隆宝高寒湿地不同云系降水雨滴谱特征

利用2019年5～10月布设于三江源地区隆宝高寒湿地的激光雨滴谱仪观测资料,分析高原山区夏秋季层状云降水和对流云降水雨滴微物理特征、平均雨滴谱分布、下落速度及Z-R关系.结果表明:三江源隆宝地区夏秋季对流云降水和层状云降水的雨滴微物理特征具有一定程度的相似性,对流云降水雨滴微物理参量略大于层状云降水;层状云降水和对流云...     

中国东部云-降水对应关系的分析与模式评估

为评估和改进模式中不同类型云与降水的对应关系,利用1998—2007年卫星-台站融合降水资料和国际卫星云气候计划的卫星观测云资料,采用诊断方法分析了中国东部季风区冬季层云、夏季对流云、层云与降水的水平分布及季节变化对应关系,并评估了BCC_AGCM模式的T42和T106分辨率版本对云-降水对应关系的模拟能力。观测资料分析结果表明,中国东部冬季云带和雨带都稳定少动,降水主要来自雨层云和高层云,南部沿海层云和层积云也对降水有贡献;夏季,中国东部表现为层积混合云降水特征,对流云带与降水带具有较好的对应关系,并具有一致的移动特征。对流降水主要来自深对流云和卷层云,深对流云云量和降水中心完全吻合,卷层云云带则表现出比深对流云主体和降水带偏北的现象;层云降水主要来自高层云和层积云。模式评估结果表明,中、低分辨率版本的BCC_AGCM模式均模拟出了冬季层云和稳定少动的降水带、夏季深对流云、卷层云和降水带的对应关系及随季风推进的移动特征。与T42模式版本相比,T106模式版本在夏季对流云云量的模拟及其与降水带的对应关系方面有所改善,说明改进的BCC_AGCM积云对流参数化方案与高分辨率模式网格更匹配,但冬季层云云量模拟误差变大,与降水带的对应关系变差,其原因值得进一步分析研究。     

Diurnal cycles of precipitation over subtropical China in IPCC AR5 AMIP simulations

Atmospheric Intercomparison Project simulations of the summertime diurnal cycle of precipitation and low-level winds over subtropical China by Intergovernmental Panel on Climate Change Fifth Assessment Report models were evaluated. By analyzing the diurnal variation of convective and stratiform components, results confirmed that major biases in rainfall diurnal cycles over subtropical China are due to convection parameterization and further pointed to the diurnal variation of convective rainfall being closely related to the closure of the convective scheme. All models captured the early-morning peak of total rainfall over the East China Sea, but most models had problems in simulating diurnal rainfall variations over land areas of subtropical China. When total rainfall was divided into stratiform and convective rainfall, all models successfully simulated the diurnal variation of stratiform rainfall with a maximum in the early morning. The models, overestimating noon-time （nocturnal） total rainfall over land, generally simulated too much convective rainfall, which peaked close to noon （midnight）, sharing some similarities in the closures of their deep convection schemes. The better performance of the Meteorological Research Institute atmospherer. ocean coupled global climate model version 3 （MRI-CGCM3） is attributed to the well captured ratio of the two kinds of rainfall, but not diurnal variations of the two components. Therefore, a proper ratio of convective and stratiform rainfall to total rainfall is also important to improve simulated diurnal rainfall variation.     

Statistical Characteristics of Raindrop Size Distribution in the Tibetan Plateau and Southern China

The characteristics of raindrop size distribution(DSD) over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu and Yangjiang, comprising a total of 9430 and 6366 1-min raindrop spectra, respectively. The raindrop spectra, characteristics of parameter variations with rainfall rate, and the relationships between reflectivity factor(Z) and rainfall rate(R) are analyzed, as well as their DSD changes with precipitation type and rainfall rate. The results show that the average raindrop spectra appear to be one-peak curves, the number concentration for larger drops increase significantly with rainfall rate, and its value over southern China is much higher, especially in convective rain. Standardized Gamma distributions better describe DSD for larger drops, especially for convective rain in southern China. All three Gamma parameters for stratiform precipitation over the Tibetan Plateau are much higher, while its shape parameter(μ) and mass-weighted mean diameter(D_m), for convective precipitation, are less. In terms of parameter variation with rainfall rate, the normalized intercept parameter(N_w) over the Tibetan Plateau for stratiform rain increases with rainfall rate, which is opposite to the situation in convective rain. The μover the Tibetan Plateau for stratiform and convective precipitation types decreases with an increase in rainfall rate, which is opposite to the case for D m variation. In Z–R relationships, like "Z = AR~b", the coefficient A over the Tibetan Plateau is smaller, while its b is higher, when the rain type transfers from stratiform to convective ones. Furthermore, with an increase in rainfall rate, parameters A and b over southern China increase gradually, while A over the Tibetan Plateau decreases substantially, which differs from the findings of previous studies. In terms of geographic location and climate over the Tibetan Plateau and southern China, the precipitation in the pre-flood seasons is dominated by strong convective rain, while weak convective rain occurs frequently in northern Tibet with lower humidity and higher altitude.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

星载测雨雷达探测的夏季亚洲对流与层云降水雨顶高度气候特征

利用热带测雨卫星测雨雷达的10年探测结果,对夏季亚洲对流降水与层云降水雨顶高度分布、雨顶高度与地表降水强度的关系、雨顶高度日变化特征进行了研究。结果表明,青藏高原和中国东部平原的多数(70%以上)对流降水雨顶高度分布在8—12和5—10km,其他地区分布在5—9km;陆面对流降水雨顶平均高度高于洋面。洋面和陆面层云降水雨顶高度没有明显差异,多在5—8km。夏季亚洲浅对流降水比例少,而深厚对流主要出现在中国东部平原、西南、印度次大陆西部至伊朗高原东部地区,比例约40%。洋面和陆面的弱对流降水的雨顶平均高度在7—8km,弱层云降水相应的雨顶平均高度多小于7.5km;陆面约90%的强对流降水雨顶平均高度在9km以上,而强层云降水雨顶的平均高度通常不超过8.5km。夏季亚洲对流降水和层云降水的雨顶平均高度均随着地面平均降水率的增大而升高,两者遵从二次函数关系。对流降水及层云降水频次、强度和雨顶高度的日变化峰值分析表明,陆面这些参量的日变化强于洋面,并且三者的日变化基本同步。     

利用星载测雨雷达探测结果对夏季中国南方对流和层云降水气候特征的分析

本文利用热带测雨卫星(TRMM)上搭载的测雨雷达(PR)十年的探测结果, 对夏季中国南方对流降水和层云降水的气候特征进行了分析。研究结果表明:夏季中国南方层云降水频次较对流降水频次高出两倍以上, 而对流降水强度至少是层云降水强度的4倍; 就整个中国南方而言, 这两种类型的降水对总降水量贡献相当。日变化分析表明夏季中国南方大部分地区的对流降水主要出现在午后, 层云降水出现时间并不集中, 但这两类降水的频次日变化均显示了明显的地域性特征; 对降水廓线日变化的分析结果表明, 对流降水和层云降水廓线的日变化主要表现在“雨顶”高度的日变化, 即对流降水云的厚度有明显的日变化变化特征, 不同地区的降水廓线存在明显的差异。降水率剖面分析结果显示了对流降水的“雨顶” 高度日变化较层云降水剧烈, 降水率的日变化则相反, 且层云降水率的地域性特征更强。     

A STUDY ON THE PRECIPITATION CHARACTERISTICS OVER THE SOUTH CHINA SEA BEFORE AND AFTER THE MONSOON ONSET

This paper presents a study on the temporal and spatial variations of the precipitation over the area of the South China Sea (SCS) during the monsoon onset period. The data used are from the Tropical Rainfall Measuring Mission (TRMM) observations between April and June over the nine years from 1998 to 2006. This study focuses on the central and northern part of South China Sea (110-120°E, 10-20°N). Based on the observations, the 27th pentad is selected as the occurrence time of the SCS monsoon onset. The conclusions are as follows. (1) After the monsoon onset, the specific area, defined as the ratio of the number of pixels with certain type of precipitation to the number of total pixels, extends significantly for both convective and stratiform rain, with the latter having a larger magnitude. The specific rainfall, defined as the ratio of the amount of certain type of precipitation to the total amount of precipitation, decreases for convective rain and increases for stratiform rain. (2) Results also show significant increase in heavy rain and decrease in light rain after the monsoon onset. (3) Changes are also observed in the rainfall horizontal distributions over the SCS before and after the monsoon onset, manifested by the relocation of precipitation minima for both convective and stratiform rain. (4) After the monsoon onset, the variability in characteristics of precipitation vertical structure increases significantly, leading to more latent heat release and consequently deeper convection. Meanwhile, the bright-band altitude of stratiform precipitation is also elevated.     

The influence of synoptic airflow on UK daily precipitation extremes. Part II: regional climate model and E-OBS data validation

We investigate how well the variability of extreme daily precipitation events across the United Kingdom is represented in a set of regional climate models and the E-OBS gridded data set. Instead of simply evaluating the climatologies of extreme precipitation measures, we develop an approach to validate the representation of physical mechanisms controlling extreme precipitation variability. In part I of this study we applied a statistical model to investigate the influence of the synoptic scale atmospheric circulation on extreme precipitation using observational rain gauge data. More specifically, airflow strength, direction and vorticity are used as predictors for the parameters of the generalised extreme value (GEV) distribution of local precipitation extremes. Here we employ this statistical model for our validation study. In a first step, the statistical model is calibrated against a gridded precipitation data set provided by the UK Met Office. In a second step, the same statistical model is calibrated against 14 ERA40 driven 25?km resolution RCMs from the ENSEMBLES project and the E-OBS gridded data set. Validation indices describing relevant physical mechanisms are derived from the statistical models for observations and RCMs and are compared using pattern standard deviation, pattern correlation and centered pattern root mean squared error as validation measures. The results for the different RCMs and E-OBS are visualised using Taylor diagrams. We show that the RCMs adequately simulate moderately extreme precipitation and the influence of airflow strength and vorticity on precipitation extremes, but show deficits in representing the influence of airflow direction. Also very rare extremes are misrepresented, but this result is afflicted with a high uncertainty. E-OBS shows considerable biases, in particular in regions of sparse data. The proposed approach might be used to validate other physical relationships in regional as well as global climate models.     

Comparison of four ensemble methods combining regional climate simulations over Asia

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.     

一次东北冷涡云降水垂直结构特征分析

利用辽宁阜新国家站(121.7458°E,42.0672°N)的毫米波云雷达(8 mm)和微雨雷达(12.5 mm)对2020年8月12-13日东北冷涡影响下的一次降水过程进行了观测,分析了云降水的垂直结构特征并探讨了降水机制。结果表明：本次过程中,云水平方向发展不均匀,以层状云和层积混合云为主,云内有时还嵌有对流泡。云降水阶段性变化明显,先后出现了层状云降水、层积混合云降水和对流云降水。层状云降水和层积混合云降水均表现出明显的亮带特征,但层积混合云降水的雷达回波强度、回波顶高和降水强度明显大于层状云降水。对流云降水的雷达回波会因强降水而产生明显衰减,因此回波顶高不能表示出实际的云顶情况。层状云降水阶段,云雷达反射率随高度降低增长缓慢,雨滴在下落过程中受蒸发和碰并的共同作用,反射率降低。与层状云降水相比,层积混合云降水的碰并效应强,且由于前期降水对近地面的增湿作用,使云下蒸发弱。对流云降水阶段,反射率的增长主要发生在冰水混合层,有利于大滴的产生,拓宽了云滴谱,提高了碰并效率。     

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.     

华北地区秋冬季气溶胶污染与不同类型降水的关系

气溶胶对降水的影响具有很大的不确定性,正确理解和认识气溶胶对不同类型降水的影响对提高天气预报的准确度和全球气候变化具有重要意义。利用GPM-DPR观测资料和MERRA-2再分析资料分析了气溶胶污染与华北地区2014—2020年秋、冬季对流云降水和层状云降水的关系。结果表明:与清洁状况相比,气溶胶污染状况下对流云降水的降水强度有所增强,雨顶高度更高。在污染状态下对流云降水具有粒径小但数浓度高的降水粒子,潜热加热率更高。气溶胶污染与层状云降水的降水强度、雨顶高度等宏观特征不存在明显相关。层状云降水相比对流云降水更容易受到大气水汽条件和垂直上升运动的影响。因此,在气象条件主导降水的情况下,气溶胶污染对华北地区层状云降水的影响很难通过GPM-DPR和MERRA-2数据观测到。      

A new daily weather generator to preserve extremes and low-frequency variability

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series.     

How are seasonal prediction skills related to models’ performance on mean state and annual cycle?

Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated.