NOAA RFE 2.0在西藏高原的验证

随着卫星探测技术的不断提高和资料处理方法的不断改进,出现了许多卫星遥感降水估算产品。每种产品都有优点及不足,且卫星间接式降水估算方法的精度也有限,但对地形复杂常规气象站台站稀少且分布极不均匀的大面积地区如西藏高原来说,卫星遥感不失为估算区域降水的有效方法之一。鉴于卫星遥感降水估算精度的局限性,每种产品需要利用地面观测数据来定量化降水估算误差,分析和评价这些资料的可用性。利用NOAA气候预测中心(CPC)研发的RFE 2.0降水估算产品,从西藏高原东南部到西北部不同气候区选取11个典型气象站2005—2006年6—9月的日降水量观测资料,验证了RFE 2.0降水估算产品在西藏高原的应用效果。结果表明,西藏高原的主要气候区RFE 2.0估算值与地面观测值之间的相关系数在0.45～0.86,平均为0.74;RFE 2.0估算的正确率POD (Probability Of Detection)一般大于73%,而空报率FAR(False Alarm Rate)为2%～12%;仅在喜马拉雅南麓地区估算精度相对较差。      

多部雷达联合估算淮河流域降水

以淮河流域内6部CINRAD雷达基数据资料以及高密度自动雨量站观测资料为源,在应用多种方法进行降水估算和校准,并采用主成分集成方法进行集成应用的基础上,采用"先估算降水再拼图"和"重叠区域选取最大值"的方法来进行整个流域的降水估算结果拼图,从而实现了整个淮河流域的降水估算。从2007年7月初降水过程应用结果来看,经过校准以后估算误差在45%以下,并且能够反映出缺少地面雨量观测站的区域的降水分布,是一种切实可行的淮河流域降水估算的方法。     

乌鲁木齐市地理地形因素对降水空间分布的影响

提供了一个描述乌鲁木齐市年、季降水空间分布的估算模型.利用中国气象局整编的气象站点信息资料和位于研究区域的3个站点(乌鲁木齐、达坂城、蔡家湖)从建站到2000年的多年降水资料,采用多元逐步回归方法,分析和估算了3个地理、地形影响因子(即经度、纬度、海拔高度)对乌鲁木齐市降水空间分布的影响,并对回归方程和影响因子进行了显著性检验,得出了一些定性、定量的结果.本文模型估算的降水能够较好地再现该区的实际降水分布,具有一定的适用价值.     

Comparison of satellite-estimated and model-forecasted rainfall data during a deadly debris-flow event in Zhouqu,Northwest China

本文比较了三种卫星遥感资料和三层嵌套WRF模式预报降水在舟曲泥石流事件前后相对观测降水的准确度、误差等。结果表明,卫星遥感资料能从降水分布型、降水量值等方面反映出实际的降水特征,尤其是CMORPH和TRMM,更是基本接近实际降水的情况。PERSIANN资料虽然有相对大一些的误差,但区域降水总量、降水区分布型以及最大降水的时空再现已经比较精确。数值预报降水对区域总降水以及降水的分布形态能比较好的预报,高分辨率的模式甚至能较好地预报降水极值的时间和位置,因此在灾害预警方面有较高的应用价值。     

区域降水指数的分析

讨论了如何利用单站降水记录计算区域降水指数的方法。该指数能够比较客观地反映区域降水的分布情况，从而得到较好的区域降水序列，便于进行气候分析与预报。     

利用气象卫星资料定量测量黄河流域汛期降水

根据 Ｇ Ｍ Ｓ－ ５ 静止气象卫星数字化卫星云图的灰度分布,计算灰度共生矩阵,抽取云的纹理特征量,组成云自动分类方程,进而滤去地表和非降水云信息,实现云的自动分类,然后针对黄河流域不同类型云建立云顶温度与地面实测降水关系曲线,并选取订正因子,建立地面降水估算方程进行降水估算。使用结果表明,该方法对黄河流域汛期降水估算效果较好。     

低纬高原地区多元信息综合变分分析试验

利用高分辨率雷达、卫星降水反演数据和地面降水观测资料,建立联合降水估算场并对其进行变分订正,得到0.1°×0.1°细网格降水同化场。同化资料包括2008年6～8月逐日4次FY-2卫星和CINRAD/CC雷达降水估算资料、地面自动站降水观测资料,试验结果表明,采用变分方法对卫星及雷达联合降水估算场进行同化后,所得结果既较真实地反映了地面观测网天气尺度信息,也对低纬高原地区降水离散性分布特征的描述有较大的改善。     

基于最大互相关的对流云预测

传统上利用卫星云图做降水都是根据已知的卫星云图中的通道信息来进行降水量的估算。因此,利用卫星云图仅仅做到了降水量的估算。本文利用图像的最大互相关以及线性外推对未来的卫星云图进行预测,并取得较好的结果,从而能够利用云图进行降水量的预报。     

利用卫星和雷达估计大暴雨

利用合肥、武汉和长沙雷达、云顶亮温TBB等观测资料,对2003年7月8日发生的大暴雨天气过程进行了联合估计。结果表明:联合估算降水很好地再现了这次降水过程;卫星估算降水很大程度上弥补了雷达估算降水在空间分布上的不足,但对特大暴雨在强度上估计不足,对中等强度的降水估计偏大;引入雷达对卫星估算降水进行联合估算,能很好地反映暴雨云团的中尺度结构特征,反演的降水场能很好揭示强降水过程的时空变化特征。     

基于图像熵的卫星云图分类方法

介绍一种基于图像熵和自动分割技术的卫星云图阂值分类方法,重点解决普通阈值法中阈值不确定性的问题。采用自动分割方法进行云图的划分,结合图像纹理特征信息,通过统计分析来确定具体的阈值。将该方法应用于2007年7月上旬淮河流域的暴雨过程,并与美国GOES卫星分层阈值进行类比,分析了两种阈值与地面实况降水间的关系。结果表明,该方法能够在卫星估算降水过程中增强对不同类型降水的识别能力,是一种有效的卫星云图分类方法。     

中国东部夏季降水与东亚垂直环流结构及其预测试验

本文在分析中国东部夏季降水的时空分布特征基础上, 从东亚高、中、低层大尺度环流异常着手, 选取对中国东部夏季降水异常有显著影响的大气环流预报因子, 分别应用逐步回归和最优子集回归法两种统计降尺度方法, 以动力气候模式CAM3.1预报输出的大气环流预报因子为基础, 以中国东部夏季降水的典型空间分布型为预报对象, 建立动力与统计相结合的中国东部夏季降水预测模型, 并对1981～2000年的中国东部夏季降水进行回报试验。结果表明: 中国东部夏季降水具有4类典型的空间分布型式, 且具有显著的准2年和年代际尺度振荡周期; 东亚高、中、低层大气环流异常的特定配置, 对东部夏季降水的空间分布型有显著影响; 使用两种降尺度方案建立的动力与统计相结合的预测模型对中国东部夏季降水异常具有一定的预报技巧, 可以在一定程度上提高动力模式对中国东部夏季降水的预报效果。     

A new method to compare hourly rainfall between station observations and satellite products over central-eastern China

This study employs a newly defined regional-rainfall-event (RRE) concept to compare the hourly characteristics of warm-season (May-September) rainfall among rain gauge observations, China merged hourly precipitation analysis (CMPA-Hourly), and two commonly used satellite products (TRMM 3B42 and CMORPH). By considering the rainfall characteristics in a given limited area rather than a single point or grid, this method largely eliminates the differences in rainfall characteristics among different observations or measurements over central-eastern China. The results show that the spatial distribution and diurnal variation of RRE frequency and intensity are quite consistent among different datasets, and the performance of CMPA-Hourly is better than the satellite products when compared with station observations. A regional rainfall coefficient (RRC), which can be used to classify local rain and regional rain, is employed to represent the spatial spread of rainfall in the limited region defining the RRE. It is found that rainfall spread in the selected grid box is more uniform during the nocturnal to morning hours over central-eastern China. The RRC tends to reach its diurnal maximum several hours after the RRE intensity peaks, implying an intermediate transition stage from convective to stratiform rainfall. In the afternoon, the RRC reaches its minimum, implying the dominance of local convections on small spatial scale in those hours, which could cause large differences in rain gauge and satellite observations. Since the RRE method reflects the overall features of rainfall in a limited region rather than at a fixed point or in a single grid, the widely recognized overestimation of afternoon rainfall in satellite products is not obvious, and thus the satellite estimates are more reliable in representing sub-daily variation of rainfall from the RRE perspective. This study proposes a reasonable method to compare satellite products with rain gauge observations on the sub-daily scale, which also has great potential to be used in evaluating the spatiotemporal variation of cloud and rainfall in numerical models.     

西藏地区汛期雨型划分与全国夏季雨带的关系

利用西藏地区1961～2000年汛期（5～9月）降水资料,采用EOF分析方法并结合降水距平百分率,分析全区汛期降水的空间分布特征,确定了西藏地区汛期的主要雨型,与全国夏季雨带进行对比,发现两者之间存在特定的关系.     

概率密度匹配法对中国区域卫星降水资料的改进

为考察概率密度匹配法 (PDF方法) 对中国区域卫星反演降水产品系统误差订正的适用性,基于逐日和逐时我国地面观测降水量资料,引入PDF方法,分别对逐日0.25°×0.25°水平分辨率和逐时0.1°×0.1°水平分辨率的CMORPH (Climate Prediction Center Morphing Technique) 卫星降水产品的系统误差进行订正。在分析CMORPH卫星降水产品误差特征的基础上,根据两种资料不同的时空分辨率和误差特点,调整概率密度匹配时选取样本的时间和空间范围,设计相应的订正方案。评估结果表明: PDF方法订正后, 两种分辨率卫星降水资料在中国区域系统误差均显著减小,达到了理想的订正效果。在我国站点稀疏的西部地区,订正后的CMORPH卫星降水产品仍保持卫星观测的降水空间分布,降水量也明显接近于地面观测降水量。可见,PDF方法是中国区域卫星反演降水产品系统误差订正的一种有效方法。     

华南春季降水纬向非均匀分布及异常年大气环流特征分析

对1951—2007年华南地区18站春季（3—5月）降水进行EOF分析,发现华南春季降水的空间分布具有全区一致性、东西反位相、南北反位相及东北—西南反位相等特点。第二特征向量主要反映了华南春季降水的纬向非均匀分布特征,据此将华南春季降水型分为西涝东旱型和西旱东涝型,并利用NCEP再分析资料对春季降水的纬向分布异常年的大气环流背景特征进行了研究。结果发现：在西涝东旱年,华南西北部存在海平面气压场和高度场的正异常中心,有利于冷空气的南下,而该正异常中心的南部出现负异常,华南东部及其东部海面上呈现范围较大的气压场和高度场正异常,华南西部盛行东南风异常,华南东部存在东北风距平,风场和水汽输送场在华南西部表现为异常辐合,在华南东部表现为异常辐散,因此造成了华南西部降水的偏多和东部降水的偏少。同时,850 hPa涡度场、200 hPa散度场、850 hPa垂直速度场和1000 hPa温度场也均呈现出有利于华南西部降水增多和东部降水减少的环流形势。在西旱东涝年,情况基本相反。     

20世纪我国东部地区的降水及极端旱涝事件变化规律

根据我国东部地区（110°E以东）160个观测站100多a的降水资料对我国东部地区包括华北地区、长江流域和华南地区等100多a的降水变化趋势和降水极端偏多和极端偏少年份的分布进行了分析;并通过计算z指数,实现旱涝面积转化,分析我国东部100多a来的旱、涝范围变化和极端旱、涝年份的分布。结果表明：我国东部地区100多a的降水极端偏多年份随时间分布比较均匀,其间隔在20～40a间。降水极端偏少年份在减少。降水量的变化存在着大约40—50a的震荡周期。夏季降水增加明显,秋季降水下降明显。长江流域的年降水量和我国东部年降水量趋势保持较好的一致性,说明长江流域的降水对我国东部降水的贡献显著,华南区域的降水起次要作用。我国东部近100a来雨涝范围和干旱范围都没有表现出明显的增、减趋势,但存在着明显的年际和年代际振动。我国东部干旱覆盖面积最大的时间主要集中在1930年代以前,1969年以后变化趋势不明显。东北和华北极端干旱年份大都出现在1940年以前,长江流域和华南的极端干旱年份则随时间分布比较均匀。     

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman’s correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d^-1). A strong relationship between GPM rainfall and error was found from heavy (~35 mm d^-1) to violent rain (160 mm d^-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.     

Convective and Stratiform Cloud Rainfall Estimation from Geostationary Satellite Data

The Bayes Decision (BD) method was used to distinguish the corrective and stratiform components of cloud sys-tems from GMS-4 satellite data. A technique originally developed by Adler and Negri (1988, hereafter abbreviated AN) was improved for estimating the convective and stratiform cloud precipitation areas and rates of cloud systems from GMS satellite imagery. It has been applied to a tropical cyclonic cloud cluster observed over east coast area of China on September 23, 1992, which brought about flood disaster in that region. Overlaid 6-hour surface rainfall ob-servations show that the rainfall areas and amounts match with results from improved AN technique. The successful application of the Adler and Negri’s technique to convective and stratiform clouds provides encouragement for the use of this method over large region of mid-latitude China where radar data are not fully covered.     

Simulation of weather systems over Indian region using mesoscale models

Summary Simulation studies have been carried out for two weather systems namely; a pre-monsoon thunderstorm over east coast of India and a weak cyclonic circulation associated with feeble low pressure area over south peninsular India. Two sets of forecast results are obtained: one using Advanced Regional Prediction System Model and other using Weather Research and Forecasting Model. The model performances are compared by examining the predicted parameters like mean sea level pressure, wind, moisture fields and rainfall. The rainfall prediction is assessed qualitatively by comparing the spatial distribution with satellite cloud images and quantitatively by comparing rainfall rates with Tropical Rainfall Measuring Mission products and/or the observed station values reported in Indian Daily Weather Reports. It is found that in case of idealized simulation of thunderstorm, Advanced Regional Prediction System Model has well predicted the spatial distribution of rainfall which is consistent with the clouding in satellite cloud images. It also has simulated the diverging winds at lower levels associated with downdraft during mature/dissipation stage of thunderstorm. Weather Research and Forecasting Model failed to predict these features. In case of a weak cyclonic circulation simulation experiment, Advanced Regional Prediction System model is able to simulate the rainy area better compared to those produced by Weather Research and Forecasting Model. Both models failed to produce observed heavy precipitation rates.