Seasonal climate prediction for South America with FSU Multi-model Synthetic Superensemble algorithm

Summary Objective combination schemes of predictions from different models have been applied to seasonal climate forecasts. These schemes are successful in producing a deterministic forecast superior to individual member models and better than the multi-model ensemble mean forecast. Recently, a variant of the conventional superensemble formulation was created to improve skills for seasonal climate forecasts, the Florida State University (FSU) Synthetic Superensemble. The idea of the synthetic algorithm is to generate a new data set from the predicted multimodel datasets for multiple linear regression. The synthetic data is created from the original dataset by finding a consistent spatial pattern between the observed analysis and the forecast data set. This procedure is a multiple linear regression problem in EOF space. The main contribution this paper is to discuss the feasibility of seasonal prediction based on the synthetic superensemble approach and to demonstrate that the use of this method in coupled models dataset can reduce the errors of seasonal climate forecasts over South America. In this study, a suite of FSU coupled atmospheric oceanic models was used. In evaluation the results from the FSU synthetic superensemble demonstrate greater skill for most of the variables tested here. The forecast produced by the proposed method out performs other conventional forecasts. These results suggest that the methodology and database employed are able to improve seasonal climate prediction over South America when compared to the use of single climate models or from the conventional ensemble averaging. The results show that anomalous conditions simulated over South America are reasonably realistic. The negative (positive) precipitation anomalies for the summer monsoon season of 1997/98 (2001/02) were predicted by Synthetic Superensemble formulation quite well. In summary, the forecast produced by the Synthetic Superensemble approach outperforms the other conventional forecasts.     

Improving multimodel weather forecast of monsoon rain over China using FSU superensemble

In this paper we present the current capabilities for numerical weather prediction of precipitation over China using a suite of ten multimodels and our superensemble based forecasts. Our suite of models includes the operational suite selected by NCARs TIGGE archives for the THORPEX Program. These are: ECMWF, UKMO, JMA, NCEP, CMA, CMC, BOM, MF, KMA and the CPTEC models. The superensemble strategy includes a training and a forecasts phase, for these the periods chosen for this study include the months February through September for the years 2007 and 2008. This paper addresses precipitation forecasts for the medium range i.e. Days 1 to 3 and extending out to Day 10 of forecasts using this suite of global models. For training and forecasts validations we have made use of an advanced TRMM satellite based rainfall product. We make use of standard metrics for forecast validations that include the RMS errors, spatial correlations and the equitable threat scores. The results of skill forecasts of precipitation clearly demonstrate that it is possible to obtain higher skills for precipitation forecasts for Days 1 through 3 of forecasts from the use of the multimodel superensemble as compared to the best model of this suite. Between Days 4 to 10 it is possible to have very high skills from the multimodel superensemble for the RMS error of precipitation. Those skills are shown for a global belt and especially over China. Phenomenologically this product was also found very useful for precipitation forecasts for the Onset of the South China Sea monsoon, the life cycle of the mei-yu rains and post typhoon landfall heavy rains and flood events. The higher skills of the multimodel superensemble make it a very useful product for such real time events.     

基于BCC_CSM模式的中国东部夏季降水预测检验及订正

基于国家气候中心第二代季节预测模式的历史回报试验数据,检验了模式对我国东部夏季降水的预测能力,探讨了预测误差形成的可能原因,并应用降尺度方法提高了模式的降水预测技巧。分析表明:（1）模式能在一定程度上把握我国东部夏季降水时空变率的两个主要模态（偶极子型模态和全区一致型模态）,但是不同超前时间的预测在刻画模态方差贡献、异常空间分布特征、时间系数的年际变化等方面存在明显误差;（2）模式能够合理预测大尺度环流和海表温度（SST）的变化特征,但是对中国东部夏季降水的总体预测技巧有限,这与模式不能准确刻画西太平洋副热带高压、大陆高压、中高纬阻塞高压等环流系统以及热带太平洋、印度洋SST变率对中国东部降水模态的影响有关;（3）针对1991~2003年回报试验数据中的500 hPa位势高度、850 hPa纬向风和经向风、SST变量,在全球范围内寻找并定位与中国东部站点降水关系最密切的预报因子,进而建立针对降水预测的单因子线性回归、多因子逐步和多元回归模型。采用2004~2013年回报试验对所建立的降水预测模型进行了独立检验,结果表明:所建立的降尺度预测模型能显著提高中国东部地区夏季降水的预报技巧。以6月1日起报试验为例,预测的第一模态（第二模态）与观测的空间相关系数由原始的0.12（0.48）提高到了0.58（0.80）,时间相关系数则从0.47（0.15）提高到0.80（0.67）;其它超前时间的预测试验中,降尺度预测模型的降水预测技巧相比模式原始预测技巧也同样明显提高。     

Multimodel based superensemble forecasts for short and medium range NWP over various regions of Africa

Summary This study examines the predictability of weather over several regions in Africa using a multimodel superensemble technique developed at the Florida State University, which is an objective means of combining daily forecasts from multilevel global models. It is referred to as FSUSE and up to 7 different models are used to construct the superensemble. The benchmark reanalysis fields used are the precipitation data sets from CMORPH and all other global fields from ECMWF daily operational analysis. The FSUSE works by using multiple linear regression to derive weights from a comparison of each member model forecast to the benchmark analysis during a training period of the most recent 120 days, and these weights are passed to the forecast phase. This procedure removes the bias of each model and allows for an optimal linear combination of the individual model forecasts by taking account of the relative skill of each model to give a consensus forecast that is superior to the ensemble mean and all the members. Results show that bad models and poor analysis fields used during the training phase degrade the skill of the FSUSE. In the forecasts of rainfall events over all regions of Africa, the FSUSE root-mean-square (R M S) error, equitable threat skill score (E T S), and bias on the daily forecasts of rainfall were invariably superior to the best member model. The skills deteriorate as the forecast lead time in days increases, with the degradation being most significant beyond day 3. In all cases, the bias score of the FSUSE was approximately 1, while the anomaly correlation scores were to the order of 0.9. These scores indicate the robustness of the FSUSE forecasts. Over East Africa, the FSUSE forecasts were consistent with the spatial-temporal pattern of the Intertropical Convergence Zone (ITCZ), the main rain bearing synoptic mechanism across tropical Africa. Thus, in addition to superior forecasts, the use of FSUSE based data sets may provide a better understanding of the dynamical processes within the ITCZ over the region. These results could be further improved if the daily series of operational analysis had included gauge data and if the resolution were higher. It is hardly possible to get uniformly consistent and continuous daily observations over these diverse regions of Africa. However, given the availability of the satellite based estimates of daily rainfall, such as CMORPH and global analysis that are exchanged very fast nowadays, the FSUSE scheme for numerical weather predictions (N W P) provides useful medium range weather forecasts in real-time.     

Predictability of winter rainfall in South China as demonstrated by the coupled models of ENSEMBLES

Winter rainfall over South China shows strong interannual variability,which accounts for about half of the total winter rainfall over South China.This study investigated the predictability of winter （December-January-February; DJF） rainfall over South China using the retrospective forecasts of five state-of-the-art coupled models included in the ENSEMBLES project for the period 1961-2006.It was found that the ENSEMBLES models predicted the interannual variation of rainfall over South China well,with the correlation coefficient between the observed/station-averaged rainfall and predicted/areaaveraged rainfall being 0.46.In particular,above-normal South China rainfall was better predicted,and the correlation coefficient between the predicted and observed anomalies was 0.64 for these wetter winters.In addition,the models captured well the main features of SST and atmospheric circulation anomalies related to South China rainfall variation in the observation.It was further found that South China rainfall,when predicted according to predicted DJF Nifio3.4 index and the ENSO-South China rainfall relationship,shows a prediction skill almost as high as that directly predicted,indicating that ENSO is the source for the predictability of South China rainfall.     

江苏—南黄海地区M≥6强震有序网络结构及其预测研究

基于TIGGE（THORPEX Interactive Grand Global Ensemble,全球交互式大集合）资料中欧洲中期天气预报中心（European Centre for Medium-Range Weather,ECMWF）、日本气象厅（Japan Meteorological Agency,JMA）、美国国家环境预报中心（National Centers for Environmental Prediction,NCEP）和英国气象局（United Kingdom Met Office,UKMO）4个中心的北半球地面2m气温集合平均预报资料,利用插值技术与回归分析,并引入了消除偏差集合平均（bias-removed ensemble mean,BREM）和多模式超级集合（superensemble,SUP）方法进行统计降尺度预报研究.结果表明,在2007年夏季3个月中,4个单中心的降尺度预报明显地改善了预报效果.引入SUP和BREM两种集成预报方法后,预报误差得到进一步减小.对比综合表现最好的单中心ECMWF的预报,1～7d的降尺度预报误差改进率均达20％以上.研究还发现,引入SUP方法的降尺度预报效果优于引入BREM方法的降尺度预报,利用双线性插值方法在上述两方案中的预报效果优于其他3种插值方法.     

基于TIGGE资料的北半球地面气温预报的统计降尺度研究

基于TIGGE(THORPEX Interactive Grand Global Ensemble,全球交互式大集合)资料中欧洲中期天气预报中心(European Centre for Medium-Range Weather,ECMWF)、日本气象厅(Japan Meteorological Agency,JMA)、美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)和英国气象局(United Kingdom Met Office,UKMO)4个中心的北半球地面2 m气温集合平均预报资料,利用插值技术与回归分析,并引入了消除偏差集合平均(bias-removed ensemble mean,BREM)和多模式超级集合(superensemble,SUP)方法进行统计降尺度预报研究。结果表明,在2007年夏季3个月中,4个单中心的降尺度预报明显地改善了预报效果。引入SUP和BREM两种集成预报方法后,预报误差得到进一步减小。对比综合表现最好的单中心ECMWF的预报,1~7 d的降尺度预报误差改进率均达20%以上。研究还发现,引入SUP方法的降尺度预报效果优于引入BREM方法的降尺度预报,利用双线性插值方法在上述两方案中的预报效果优于其他3种插值方法。     

Influence of the Madden Julian Oscillation on precipitation and surface air temperature in South America

The regional influence of the Madden–Julian oscillation (MJO) on South America is described. Maps of probability of weekly-averaged rainfall exceeding the upper tercile were computed for all seasons and related statistically with the phase of the MJO as characterized by the Wheeler–Hendon real-time multivariate MJO (RMM) index and with the OLR MJO Index. The accompanying surface air temperature and circulation anomalies were also calculated. The influence of the MJO on regional scales along with their marked seasonal variations was documented. During December–February when the South American monsoon system is active, chances of enhanced rainfall are observed in southeastern South America (SESA) region mainly during RMM phases 3 and 4, accompanied by cold anomalies in the extratropics, while enhanced rainfall in the South Atlantic Convergence Zone (SACZ) region is observed in phases 8 and 1. The SESA (SACZ) signal is characterized by upper-level convergence (divergence) over tropical South America and a cyclonic (anticyclonic) anomaly near the southern tip of the continent. Impacts during March–May are similar, but attenuated in the extratropics. Conversely, in June–November, reduced rainfall and cold anomalies are observed near the coast of the SACZ region during phases 4 and 5, favored by upper-level convergence over tropical South America and an anticyclonic anomaly over southern South America. In September–November, enhanced rainfall and upper-level divergence are observed in the SACZ region during phases 7 and 8. These signals are generated primarily through the propagation of Rossby wave energy generated in the region of anomalous heating associated with the MJO.     

Skill of synthetic superensemble hurricane forecasts for the Canadian maritime provinces

Summary From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or about 42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters its area of forecast responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer use vortex bogussing to carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the Florida State University (FSU) hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble, which is similar to the operational version of the multi-model superensemble that is used at FSU. The synthetic superensemble differs in that is has a larger set of member models consisting of regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The track forecasts from this method have generally less error than those of the member models, the operational superensemble, and the ensemble mean. This study shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting.     

基于TIGGE资料的地面气温多模式超级集合预报

基于TIGGE资料, 采用均方根误差分别对欧洲中期天气预报中心、日本气象厅、美国国家环境预报中心和英国气象局4个中心集合预报的地面气温场集合平均结果进行检验评估, 比较各中心地面气温的预报效果。并利用超级集合、多模式集合平均和消除偏差集合平均3种方法对4个中心的地面气温预报进行集成, 同时对预报结果进行分析。结果表明: 2007年夏季日本气象厅与欧洲中期天气预报中心在北半球大部分地区预报效果最好, 各中心在不同地区预报效果不同。超级集合与消除偏差集合平均降低了预报误差, 预报效果优于最好的单个中心预报和多模式集合平均。对于较长的预报时效, 消除偏差集合平均表现出了更好的预报性能。     

Transient simulations,empirical reconstructions and forcing mechanisms for the Mid-holocene hydrological climate in southern Patagonia

This study investigates the atmospheric circulation in transient climate simulations with a coupled atmosphere–ocean general circulation model (GCM) for the mid-Holocene (MH) period 7–4.5 ka BP driven with combinations of orbital, solar and greenhouse gas forcings. The focus is on southern South America. Statistical downscaling models are derived from observational data and applied to the simulations to estimate precipitation in south-eastern Patagonia during the MH. These estimates are compared with lake level estimates for Laguna Potrok Aike (LPA) from sediments. Relative to pre-industrial conditions (i.e. 1550–1850), which show extraordinarily high lake levels, the proxy-based reconstructed lake levels during the MH are lower. The downscaled simulated circulation differences indicate higher LPA precipitation during the MH from March to August, higher annual means, and reduced precipitation from September to February. Thus the reconstructed lower LPA lake levels can not be explained solely by the simulated precipitation changes. Possible reasons for this discrepancy are discussed. Based on proxy data from southern South America hypotheses have also been proposed on the latitudinal position of the southern hemispheric westerlies (SHWs). In agreement with some of these hypotheses our simulations show an increased seasonal cycle of the latitudinal position of the SHWs during the MH, which can be explained by the orbital forcing. The simulations also show stronger SHWs over southern Patagonia during austral summer and weaker SHWs during winter. The downscaling model associates weaker SHWs with increased precipitation in the LPA region. However, this relationship is only moderate, and therefore the downscaling model does not support the assumption of a strong link between mean SHWs and precipitation over south-eastern Patagonia, which is the basis of many proxy-based hypotheses about the SHWs.     

中国南方降水及其极端事件的动力-统计相结合延伸期预报

延伸期预报是无缝隙预测系统中的薄弱环节,如何提高灾害天气过程的延伸期预报技巧是国际热点及前沿问题。本研究基于2005年12月—2014年8月的观测/再分析资料,通过奇异值分解方法,揭示了与中国南方低频降水变化高度耦合的热带对流和中纬度波列信号。利用中国气象局参加国际次季节至季节预报计划模式（BCC-CPS-S2Sv2模式,简称BCC S2S模式）的回报数据,对中国南方低频降水异常场进行统计降尺度,构建了一套动力-统计相结合的延伸期降水预测模型。独立预测时段（2014年12月—2019年8月）的结果表明,BCC S2S模式可以提前10—15 d预报中国南方大部分区域的异常降水;提前15—20 d以上预报时,动力-统计结合预报模型对冬季（夏季）华南沿海地区（长江以北地区）的降水时间演变、降水空间分布及极端强降水事件的预报技巧均优于BCC S2S模式。文中提出的思路和方法可广泛应用于其他区域气象要素和极端天气事件的延伸期预报。     

Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter

Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal forecast system in predicting two main types of El Niño-Southern Oscillation (ENSO), namely canonical (or cold tongue) and Modoki ENSO, and their regional climate impacts is assessed for boreal winter. The APCC MME is constructed by simple composite of ensemble forecasts from five independent coupled ocean-atmosphere climate models. Based on a hindcast set targeting boreal winter prediction for the period 1982–2004, we show that the MME can predict and discern the important differences in the patterns of tropical Pacific sea surface temperature anomaly between the canonical and Modoki ENSO one and four month ahead. Importantly, the four month lead MME beats the persistent forecast. The MME reasonably predicts the distinct impacts of the canonical ENSO, including the strong winter monsoon rainfall over East Asia, the below normal rainfall and above normal temperature over Australia, the anomalously wet conditions across the south and cold conditions over the whole area of USA, and the anomalously dry conditions over South America. However, there are some limitations in capturing its regional impacts, especially, over Australasia and tropical South America at a lead time of one and four months. Nonetheless, forecast skills for rainfall and temperature over East Asia and North America during ENSO Modoki are comparable to or slightly higher than those during canonical ENSO events.     

Climate impacts of recent multidecadal changes in Atlantic Ocean Sea Surface Temperature: a multimodel comparison

During the twentieth century sea surface temperatures in the Atlantic Ocean exhibited prominent multidecadal variations. The source of such variations has yet to be rigorously established—but the question of their impact on climate can be investigated. Here we report on a set of multimodel experiments to examine the impact of patterns of warming in the North Atlantic, and cooling in the South Atlantic, derived from observations, that is characteristic of the positive phase of the Atlantic Multidecadal Oscillation (AMO). The experiments were carried out with six atmospheric General Circulation Models (including two versions of one model), and a major goal was to assess the extent to which key climate impacts are consistent between the different models. The major climate impacts are found over North and South America, with the strongest impacts over land found over the United States and northern parts of South America. These responses appear to be driven by a combination of an off-equatorial Gill response to diabatic heating over the Caribbean due to increased rainfall within the region and a Northward shift in the Inter Tropical Convergence Zone (ITCZ) due to the anomalous cross-equatorial SST gradient. The majority of the models show warmer US land temperatures and reduced Mean Sea Level Pressure during summer (JJA) in response to a warmer North Atlantic and a cooler South Atlantic, in line with observations. However the majority of models show no significant impact on US rainfall during summer. Over northern South America, all models show reduced rainfall in southern hemisphere winter (JJA), whilst in Summer (DJF) there is a generally an increase in rainfall. However, there is a large spread amongst the models in the magnitude of the rainfall anomalies over land. Away from the Americas, there are no consistent significant modelled responses. In particular there are no significant changes in the North Atlantic Oscillation (NAO) over the North Atlantic and Europe in Winter (DJF). Additionally, the observed Sahel drying signal in African rainfall is not seen in the modelled responses. Suggesting that, in contrast to some studies, the Atlantic Multidecadal Oscillation was not the primary driver of recent reductions in Sahel rainfall.     

A review on aspects of climate simulation assessment

This paper reviews some aspects of evaluation of climate simulation, including the ITCZ, the surface air temperature (SAT), and the monsoon. A brief introduction of some recently proposed approaches in weather forecast verification is followed by a discussion on their possible application to evaluation of climate simulation. The authors suggest five strategies to extend the forecast verification methods to climate simulation evaluation regardless significant differences between the forecasts and climate simulations. It is argued that resolution, convection scheme, stratocumulus cloud cover, among other processes in the atmospheric general circulation model (AGCM) and the ocean-atmosphere feedback are the potential causes for the double ITCZ problem in coupled models and AGCM simulations, based on the system- and component-level evaluations as well as the downscaling strategies in some recent research. Evaluations of simulated SAT and monsoons suggest that both coupled models and AGCMs show good performance in representing the SAT evolution and its variability over the past century in terms of correlation and wavelet analysis but poor at reproducing rainfall, and in addition, the AGCM alone is not suitable for monsoon regions due to the lack of air-sea interactions.     

我国地面降水的分级回归统计降尺度预报研究

利用TIGGE资料中欧洲中期天气预报中心(ECMWF,the European Centre for Medium-Range Weather Forecasts)、日本气象厅(JMA,the Japan Meteorological Agency)、美国国家环境预报中心(NCEP,the National Centers for Environmental Prediction)以及英国气象局(UKMO,the UK Met Office)4个中心1~7 d预报的日降水量集合预报资料,并以中国降水融合产品作为"观测值",对我国地面降水量预报进行统计降尺度处理。采用空间滑动窗口增加中雨和大雨雨量样本,建立分级雨量的回归方程,并与未分级雨量的统计降尺度预报进行对比。结果表明,对于不同模式、不同预报时效以及不同降水量级,统计降尺度的预报技巧改进程度不尽相同。统计降尺度的预报技巧依赖于模式本身的预报效果。相比雨量未分级回归,雨量分级回归的统计降尺度预报与观测值的距平相关系数更高,均方根误差更小,不同量级降水的ETS评分明显提高。对雨量分级回归统计降尺度预报结果进行二次订正,可大大减少小雨的空报。     

SST variability in the South Indian Ocean and associated circulation and rainfall patterns over Southern Africa

Summary A general circulation model is used to study the response of the atmosphere to an idealised sea surface temperature (SST) anomaly pattern (warm throughout the southern midlatitudes, cool in the tropics) in the South Indian Ocean region. The anomaly imposed on monthly SST climatology captures the essence of patterns observed in the South Indian Ocean during both ENSO events and multidecadal epochs, and facilitates diagnosis of the model response. A previous study with this anomaly imposed in the model examined differences in the response between that on the seasonal scale (favours enhancement of the original SST anomaly) and that on the decadal scale (favours damping of the anomaly). The current study extends that work firstly by comparing the response on the intraseasonal, seasonal and interannual scales, and secondly, by assessing the changes in the circulation and rainfall over the adjoining African landmass.It is found that the atmospheric response is favourable for enhancement of the original SST anomaly on scales up to, and including, annual. However, as the scale becomes interannual (i.e., 15–21 months after imposition of the anomaly), the model response suggests that damping of the original SST anomaly becomes likely. Compared to the shorter scale response, the perturbation pressure and wind distribution on the interannual scale is shifted poleward, and is more reminiscent of the decadal response. Winds are now stronger over the warm anomaly in the southern midlatitudes suggesting enhanced surface fluxes, upper ocean mixing, and consequently, a damping of the anomaly.Examination of the circulation and rainfall patterns indicates that there are significant anomalies over large parts of southern Africa during the spring, summer and autumn seasons for both short (intraseasonal to interannual) and decadal scales. It appears that rainfall anomalies are associated with changes in the advection of moist tropical air from the Indian Ocean and its related convergence over southern Africa. Over eastern equatorial Africa, the austral autumn season (the main wet season) showed rainfall increases on all time scales, while parts of central to eastern subtropical southern Africa were dry. The signals during summer were more varied. Spring showed generally dry conditions over the eastern half of southern Africa on both short and decadal time scales, with wet areas confined to the west. In all cases, the magnitude of the rainfall anomalies accumulated over a 90 day season were of the order of 90–180 mm, and therefore represent a significant fraction of the annual total of many areas. It appears that relatively modest SST anomalies in the South Indian Ocean can lead to sizeable rainfall anomalies in the model. Although precipitation in general circulation models tends to be less accurately simulated than many other variables, the model results, together with previous observational work, emphasize the need for ongoing monitoring of SST in this region.With 14 Figures     

Identification of the principal patterns of summer moisture transport in South America and their representation by WCRP/CMIP3 global climate models

The goal of this study is to assess the ability of a set of global climate models (GCMs) to represent the main regional spatial patterns of austral summer moisture transport in South America in order to evaluate if one of the possible causes of GCMs misestimating summer precipitation in this region could be associated with an erroneous representation of these patterns. For this purpose, NCEP/NCAR reanalysis and 20 GCMs from the WCRP/CMIP3 multi-model dataset for the period 1960–1999 were considered. Extreme cases of moisture transport patterns were selected to assess their association with rainfall anomalies. Results obtained indicate that only some aspects of water vapor transport and convergence in South America as well as the associated precipitation anomalies can be reproduced adequately by GCMs. Finally, a case study is presented showing that one of the moisture transport patterns identified was observed during December 2008–February 2009.     

Downscaling large-scale NCEP CFS to resolve fine-scale seasonal precipitation and extremes for the crop growing seasons over the southeastern United States

Seasonally predicted precipitation at a resolution of 2.5° was statistically downscaled to a fine spatial scale of ~20 km over the southeastern United States. The downscaling was conducted for spring and summer, when the fine-scale prediction of precipitation is typically very challenging in this region. We obtained the global model precipitation for downscaling from the National Center for Environmental Prediction/Climate Forecast System (NCEP/CFS) retrospective forecasts. Ten member integration data with time-lagged initial conditions centered on mid- or late February each year were used for downscaling, covering the period from 1987 to 2005. The primary techniques involved in downscaling are Cyclostationary Empirical Orthogonal Function (CSEOF) analysis, multiple regression, and stochastic time series generation. Trained with observations and CFS data, CSEOF and multiple regression facilitated the identification of the statistical relationship between coarse-scale and fine-scale climate variability, leading to improved prediction of climate at a fine resolution. Downscaled precipitation produced seasonal and annual patterns that closely resemble the fine resolution observations. Prediction of long-term variation within two decades was improved by the downscaling in terms of variance, root mean square error, and correlation. Relative to the coarsely resolved unskillful CFS forecasts, the proposed downscaling drove a significant reduction in wet biases, and correlation increased by 0.1–0.5. Categorical predictability of seasonal precipitation and extremes (frequency of heavy rainfall days), measured with the Heidke skill score (HSS), was also improved by the downscaling. For instance, domain averaged HSS for two category predictability by the downscaling are at least 0.20, while the scores by the CFS are near zero and never exceed 0.1. On the other hand, prediction of the frequency of subseasonal dry spells showed limited improvement over half of the Georgia and Alabama region.     

MRI-CGCM模式气候预测回报试验在东亚夏季的检验和降尺度订正

应用1979—2010年MRI-CGCM模式回报、NCEP/NCAR再分析数据和中国东部降水观测资料检验了模式对东亚夏季风的模拟能力,并利用模式500 hPa高度场回报资料建立了中国东部夏季降水的奇异值分解（SVD）降尺度模型。模式较好地模拟了亚洲季风区夏季降水的气候态,但模拟的季风环流偏弱、偏南,导致降水偏弱。模拟降水的方差明显偏小,且模拟降水的外部、内部方差比值低,模拟降水受模式初值影响较大。模式对长江雨型的模拟能力最高,华南雨型次之,华北雨型最低。模式对东亚夏季风第1模态的模拟能力明显高于第2模态。对于东亚夏季风第1模态,模式模拟出了西太平洋异常反气旋,但强度偏弱,且未模拟出中高纬度的日本海气旋、鄂霍次克海反气旋,导致长江中下游至日本南部降水偏弱。各时次模拟环流均能反映但低估了ENSO衰减、印度洋偏暖对西太平洋反气旋的增强作用。对于东亚夏季风第2模态,模式对西太平洋的“气旋-反气旋”结构有一定的模拟能力,但未模拟出贝加尔湖异常反气旋和东亚沿海异常气旋,导致中国东部“北少南多”雨型在模拟中完全遗漏。仅超前时间小于4个月的模拟降水能够反映ENSO发展对降水分布的作用。通过交叉检验选取左场时间系数可以提高降尺度模型的预测技巧,SVD降尺度模型在华南、江南、淮河、华北4个区域平均距平相关系数分别为0.20、0.23、0.18、0.02,明显高于模式直接输出。