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。     

Statistical downscaling in the arid central Andes: uncertainty analysis of multi-model simulated temperature and precipitation

Statistical downscaling is a technique widely used to overcome the spatial resolution problem of General Circulation Models (GCMs). Nevertheless, the evaluation of uncertainties linked with downscaled temperature and precipitation variables is essential to climate impact studies. This paper shows the potential of a statistical downscaling technique (in this case SDSM) using predictors from three different GCMs (GCGM3, GFDL and MRI) over a highly heterogeneous area in the central Andes. Biases in median and variance are estimated for downscaled temperature and precipitation using robust statistical tests, respectively Mann?CWhitney and Brown?CForsythe's tests. In addition, the ability of the downscaled variables to reproduce extreme events is tested using a frequency analysis. Results show that uncertainties in downscaled precipitations are high and that simulated precipitation variables failed to reproduce extreme events accurately. Nevertheless, a greater confidence remains in downscaled temperatures variables for the area. GCMs performed differently for temperature and precipitation as well as for the different test. In general, this study shows that statistical downscaling is able to simulate with accuracy temperature variables. More inhomogeneities are detected for precipitation variables. This first attempt to test uncertainties of statistical downscaling techniques in the heterogeneous arid central Andes contributes therefore to an improvement of the quality of predictions of climate impact studies in this area.     

Evaluation of statistical downscaling in short range precipitation forecasting

The objective of this study is to compare several statistical downscaling methods for the development of an operational short-term forecast of precipitation in the area of Bilbao (Spain). The ability of statistical downscaling methods nested inside numerical simulations run by both coarse and regional model simulations is tested with several selections of predictors and domain sizes. The selection of predictors is performed both in terms of sound physical mechanisms and also by means of “blind” criteria, such as “give the statistical downscaling methods all the information they can process”.Results show that the use of statistical downscaling methods improves the ability of the mesoscale and coarse resolution models to provide quantitative precipitation forecasts. The selection of predictors in terms of sound physical principles does not necessarily improve the ability of the statistical downscaling method to select the most relevant inputs to feed the precipitation forecasting model, due to the fact that the numerical models do not always fulfil conservation laws or because precipitation events do not reflect simple phenomenological laws. Coarse resolution models are able to provide information usable in combination with a statistical downscaling method to achieve a quantitative precipitation forecast skill comparable to that obtained by other systems currently in use.     

Statistical downscaling of summer temperature extremes in northern China

Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downscale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross-validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downscaling to Hadley Centre Coupled Model Version 3 (HadCM3) simulations under the Representative Concentration Pathways 4.5 (RCP 4.5) scenario of the Fifth Coupled Model Inter-comparison Project (CMIP5). The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5℃, and the 10th of daily minimum temperatures will increase by about 2℃ during the period 2011-35 relative to 1980-99.     

Statistical assessment of trends and oscillations in rainfall dynamics: Analysis of long daily Italian series

Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily rainfall series observed in Milan (1835–2001), Genoa (1833–2000), Bologna (1813–2001) and Palermo (1797–1999) are examples of available long rainfall records. These data series can help analyzing the evolution of precipitation. The present paper deals with long term evolution of: (i) annual rainfall amount; (ii) annual number of rainy events; (iii) intensity of rainfall, (iv) inter-annual rainfall partitioning, i.e. the duration of wet and dry periods, and (v) maximum annual values of daily rainfall amount, duration of wet and dry periods. The evolution is studied analyzing the first two order statistics and the 30-year return period quantiles via moving window analysis. Confidence intervals are introduced to check the statistical significance of the estimated statistics and quantiles. The results are compared with those provided by the traditional Mann-Kendall test. The analysis shows how the annual precipitation exhibits a negative trend in the first half of 20th century, with a subsequent positive trend in northern Italy (Genoa, Milan and Bologna). Conversely, the dataset for Palermo (southern Italy) displays only a negative trend. Because the number of precipitation episodes is found to decrease in the investigated period, the average rain rate is significantly increasing especially in northern Italy. This is also associated with shorter duration of rain episodes with an evident effect on rainfall extremes. Dry periods tend to be longer with increasing variability. The Mann-Kendall test and its progressive form have shown to be well suited for monotonic trend, but the confidence interval analysis, introduced here, is more appropriate if oscillations are significant.     

Statistical characteristics of environmental parameters for warm season short-duration heavy rainfall over central and eastern China

Water vapor content,instability,and convergence conditions are the key to short-duration heavy rainfall forecasting.It is necessary to understand the large-scale atmospheric environment characteristics of shortduration heavy rainfall by investigating the distribution of physical parameters for different hourly rainfall intensities.The observed hourly rainfall data in China and the NCEP final analysis（FNL）data during 1May and 30 September from 2002 to 2009 are used.NCEP FNL data are 6-hourly,resulting in sample sizes of 1573370,355346,and 11401 for three categories of hourly rainfall（P）of no precipitation(P<0.1 mm h^-1),ordinary precipitation(0.1≤P<20 mm h^-1),and short-duration heavy rainfall(P≥20.0 mm h^-1),respectively,by adopting a temporal matching method.The results show that the total precipitable water（PWAT）is the best parameter indicating the hourly rainfall intensity.A PWAT of 28 mm is necessary for any short-duration heavy rainfall.The possibility of short-duration heavy rainfall occurrence increases with PWAT,and a PWAT of 59 mm is nearly sufficient.The specific humidity is a better indicator than relative humidity.Both 700-and 850-hPa relative humidity greater than 80%could be used to determine whether or not it is going to rain,but could not be used to estimate the rainfall intensity.Temperature and potential pseudo-equivalent temperature are also reasonable indicators of short-duration heavy rainfall.Among the atmospheric instability parameters,the best lifted index（BLI）performs best on the shortduration rainfall discrimination;the next best is the K index（KI）.The three rainfall categories are not well recognized by total totals（TT）or the temperature difference between 850 and 500 hPa（DT85）.Threequarters of short-duration heavy rainfall occurred with BLI less than-0.9,while no short-duration heavy rainfall occurred when BLI was greater than 2.6.The minimum threshold of KI was 28.1 for short-duration heavy rainfall.The importance of dynamic conditions was well demonstrated by the 925-and 850-hPa divergence.The representativeness of 925-hPa divergence is stronger than that of 850 hPa.Three-quarters of short-duration heavy rainfall occurred under a negative divergence environment.However,both the best convective potential energy（BCAPE）and vertical wind shear were unable to discriminate the hourly rainfall intensities.     

Statistical models for predicting rainfall in the Caribbean

Summary Separate predictive models are created for the Caribbean early wet season (May–June–July) and late wet season (August–September–October). Simple correlations are used to select predictors for a Caribbean rainfall index and predictive equations are formulated using multiple linear regression. The process is repeated after long term trends are removed from the Caribbean rainfall index and the models validated using a number of statistical methods. Four variables are confirmed as predictors for the early season: Caribbean sea surface temperature anomalies, tropical North Atlantic sea level pressure anomalies, vertical shear anomalies in the equatorial Atlantic, and the size of the Atlantic portion of the Western Hemisphere Warm Pool. Only the first two are retained in the late season model. On the interannual time-scale, equatorial Pacific sea surface temperature anomalies become significant in both seasons. The NINO3 index is retained among the predictors for the early season, and zonal gradients of sea surface temperature between the equatorial Pacific and tropical Atlantic are retained for the late season. The results also indicate spatial variation in the importance of the seasonal predictors.     

Future projections of winter rainfall in southeast Australia using a statistical downscaling technique

Much of southeast Australia has experienced rainfall substantially below the long-term average since 1997. This protracted drought is particularly noticeable in those parts of South Australia and Victoria which experience a winter (May through October) rainfall peak. For the most part, the recent meteorological drought has affected the first half of the rainfall season May–June–July (MJJ), while rainfall during the second half August–September–October (ASO) has been much closer to the long term average. The recent multi-year drought is without precedent in the instrumental record, and is qualitatively similar to the abrupt decline in rainfall which was observed in the southwest of Western Australia in the 1960 and 1970s. Using a statistical downscaling technique, the rainfall decline is linked to observed changes in large-scale atmospheric fields (mean sea level pressure and precipitable water). This technique is able to reproduce the statistical properties of rainfall in southeast Australia, including the interannual variability and longer time-scale changes. This has revealed that the rainfall recent decline may be explained by a shift to higher pressures and lower atmospheric precipitable water in the region. To explore the likely future evolution of rainfall in southeast Australia under human induced climate change, the same statistical downscaling technique is applied to five climate models forced with increasing greenhouse gas concentrations. This reveals that average rainfall in the region is likely to decline in the future as greenhouse gas concentrations increase, with the greatest decline occurring during the first half of winter. Projected declines vary amongst models but are generally smaller than the recent early winter rainfall deficits. In contrast, the rainfall decline in late winter–spring is larger in future projections than the recent rainfall deficits have been. We illustrate the consequences of the observed and projected rainfall declines on water supply to the major city of Melbourne, using a simple rainfall run-off relationship. This suggests that the water resources may be dramatically affected by future climate change, with percentage reductions approximately twice as large as corresponding changes in rainfall.     

太行山地形对一次河北暴雨过程影响的数值研究

应用MM5模式对2000年7月5日河北省中南部的暴雨个例进行数值模拟及诊断分析,探讨了太行山脉对于河北省暴雨的影响.结果表明:降水分布在太行山东部迎风坡上,且强降水中心与喇叭口地形相对应,地形雨特征明显.在高分辨率模式模拟中,地形资料越精细,对迎风坡地形暴雨特征模拟能力越好.本次个例中低层东风越大,造成的迎风坡降水越强.近地面层受地形影响,气流表现为局地环流特征,随山脉的起伏,各物理场均有波动的特征.     

A comparison of three multi-site statistical downscaling models for daily rainfall in the North China Plain

Three statistical downscaling methods (conditional resampling statistical downscaling model: CR-SDSM, the generalised linear model for daily climate time series: GLIMCLIM, and the non-homogeneous hidden Markov model: NHMM) for multi-site daily rainfall were evaluated and compared in the North China Plain (NCP). The comparison focused on a range of statistics important for hydrological studies including rainfall amount, extreme rainfall, intra-annual variability, and spatial coherency. The results showed that no single model performed well over all statistics/timescales, suggesting that the user should chose appropriate methods after assessing their advantages and limitations when applying downscaling methods for particular purposes. Specifically, the CR-SDSM provided relatively robust results for annual/monthly statistics and extreme characteristics, but exhibited weakness for some daily statistics, such as daily rainfall amount, dry-spell length, and annual wet/dry days. GLIMCLIM performed well for annual dry/wet days, dry/wet spell length, and spatial coherency, but slightly overestimated the daily rainfall. Additionally, NHMM performed better for daily rainfall and annual wet/dry days, but slightly underestimated dry/wet spell length and overestimated the daily extremes. The results of this study could be applied when investigating climate change impact on hydrology and water availability for the NCP, which suffers from intense water shortages due to climate change and human activities in recent years.     

中国东部夏季极端降水统计特征及其与El Nio的联系

选取中国东部1961—2012年夏季5—9月无缺测429站逐日降水资料,利用广义帕雷托分布(GPD)拟合,研究中国东部52 a以及El Nio发展年和衰减年极端降水的统计特征,并分析其成因。结果表明:1)中国东部降水阈值呈由东南向西北递减的态势,且基本为线性增加趋势。2)华南地区尺度参数最大,出现极端降水的概率大。黄河以南地区尺度参数变化趋势正值较多,出现极端降水的概率增加。3)El Nio发展年夏季,西太平洋上有气旋环流异常,中国东南部受气旋西侧的异常偏北气流影响,多地阈值偏小,只有福建东南部及黑龙江中西部易发生破纪录的极端降水。4)El Nio衰减年夏季,西太平洋上为异常反气旋环流,中国东南部受反气旋西侧的异常偏南气流影响,多地阈值偏大,广东中东部及皖鄂赣交界处发生洪涝灾害的可能性增大。     

华东地区台风暴雨的诊断研究

本文利用一个空间滤波器将物理量分解为天气尺度和次天气尺度,以两个路径相似但环流形势不同的台风暴雨作为例子,对不同尺度的环流及其动能平衡进行诊断研究,结果表明:中、低纬环流系统能否进行相互作用是决定台风暴雨强度和范围的一个重要条件。在8209号台风过程中,这种相互作用是明显的,因而,8209号台风暴雨的强度和范围均显著大于8304号台风。同时,8209号台风暴雨的能量过程突出地反映在次天气尺度的动能场上,相反,在8304号台风过程中,以天气尺度的能量过程为主要的能量特征。本文还特别指出,不能简单地认为登陆台风是一个动能的“准封闭系统”,在8209号台风过程中,台风从中、低层向外输出的次天气尺度动能是造成台风环流之外暴雨的一个重要物理过程。     

降水的统计降尺度预报及其空间相关性和时间连续性重建

利用欧洲中期天气预报中心(ECMWF)、日本气象厅(JMA)、美国国家环境预报中心(NCEP)以及英国气象局(UKMO)四个中心1~7 d日累计降水量集合预报资料,以中国降水融合产品作为"观测值",对我国地面降水量进行统计降尺度预报,并对预报降水的空间相关性和时间连续性进行重建。对降水量进行分级后,建立各个量级的回归方程进行统计降尺度预报。此外,还利用Schaake Shuffle方法重建丢失的空间相关性和时间连续性。结果表明,分级回归比未分级回归后的预报结果相关系数更高,预报误差更小,更接近观测值。Schaake Shuffle方法可以有效地改进降水预报的空间相关性和时间连续性,使之更接近实况观测,集合成员间的相关性也更好。     

Impact of resolution and downscaling technique in simulating recent Atlantic tropical cylone activity

Using the global environmental multiscale (GEM) model, we investigate the impact of increasing model resolution from 2° to 0.3° on Atlantic tropical cyclone activity. There is a clear improvement in the realism of Atlantic storms with increased resolution, in part, linked to a better representation of African easterly waves. The geographical distribution of a Genesis Potential Index, composed of large-scales fields known to impact cyclone formation, coincides closely in the model with areas of high cyclogenesis. The geographical distribution of this index also improves with resolution. We then compare two techniques for achieving local high resolution over the tropical Atlantic: a limited-area model driven at the boundaries by the global 2° GEM simulation and a global variable resolution model (GVAR). The limited-area domain and high-resolution part of the GVAR model coincide geographically, allowing a direct comparison between these two downscaling options. These integrations are further compared with a set of limited-area simulations employing the same domain and resolution, but driven at the boundaries by reanalysis. The limited-area model driven by reanalysis produces the most realistic Atlantic tropical cyclone variability. The GVAR simulation is clearly more accurate than the limited-area version driven by GEM-Global. Degradation in the simulated interannual variability is partly linked to the models failure to accurately reproduce the impact of atmospheric teleconnections from the equatorial Pacific and Sahel on Atlantic cyclogenesis. Through the use of a smaller limited-area grid, driven by GEM-Global 2°, we show that an accurate representation of African Easterly Waves is crucial for simulating Atlantic tropical cyclone variability.     

Abrupt changes in rainfall in the Eastern area of La Pampa Province, Argentina

The eastern area of La Pampa Province, Argentina, lies in a transition zone between the humid temperate climate stretching east and the steppe climate stretching west. The area is thus very sensitive to abrupt changes in rainfall. In order to determine the long-term occurrence of such phenomena, long-term annual precipitation series (1921?C2004) from 17 stations in the study area were analyzed using the Buishand and Pettitt tests. Results showed a sharp increase in annual rainfall at the southern stations in the 1960s and at the northern and central stations in the 1970s. Increased rainfall can be considered one of the reasons for the subsequent expansion in land planted to crops in the region. While a rapid increase in rainfall can be seen as positive, some researchers believe that if an abrupt decrease in rainfall occurred in future and continued for long, the carrying capacity of the environment could be exceeded, leading to decreased production and environmental degradation.