The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006

The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.     

TRMM-retrieved Cloud Structure and Evolution of MCSs over the Northern South China Sea and Impacts of CAPE and Vertical Wind Shear

Cloud structure and evolution of Mesoscale Convective Systems(MCSs) retrieved from the Tropical Rainfall Measuring Mission Microwave Imager(TRMM TMI) and Precipitation Radar(PR) were investigated and compared with some pioneer studies based on soundings and models over the northern South China Sea(SCS).The impacts of Convective Available Potential Energy(CAPE) and environmental vertical wind shear on MCSs were also explored.The main features of MCSs over the SCS were captured well by both TRMM PR and TMI.However,the PR-retrieved surface rainfall in May was less than that in June,and the reverse for TMI.TRMM-retrieved rainfall amounts were generally consistent with those estimated from sounding and models.However,rainfall amounts from sounding-based and PR-based estimates were relatively higher than those retrieved from TRMM-TMI data.The Weather Research and Forecasting(WRF) modeling simulation underestimated the maximum rain rate by 22% compared to that derived from TRMM-PR,and underestimated mean rainfall by 10.4% compared to the TRMM-TMI estimate,and by 12.5% compared to the sounding-based estimate.The warm microphysical processes modeled from both the WRF and the Goddard Cumulus Ensemble(GCE) models were quite close to those based on TMI,but the ice water contents in the models were relatively less compared to that derived from TMI.The CAPE and wind shear induced by the monsoon circulation were found to play critical roles in maintaining and developing the intense convective clouds over SCS.The latent heating rate increased more than twofold during the monsoon period and provided favorable conditions for the upward transportation of energy from the ocean,giving rise to the possibility of inducing large-scale interactions.     

珠江三角洲城市群对夏季降雨影响的初步研究

利用TRMM 2A25卫星降水数据和CMORPH同化数据对珠三角洲地区的降水分布特征进行了探讨,观测表明：珠三角城市群区域总体处于降水的低值中心,且对流降雨的低值中心尤为明显;同时近10 a珠三角核心城市区域降雨有减少的趋势,这种降水减少的趋势可能与珠三角城市化效应有关。本文进一步利用WRF模式模拟分析了珠三角城市群发展对夏季降雨的影响,结果表明珠三角城市化使得该区域降雨减少,其原因为城市化使得地表的蒸发减弱及其大气中的水分供应减少,同时也抬升了珠三角区域边界层高度相应增强了低层大气水汽垂直混合。     

全球灾害系统(GHS)在地质灾害预测预报中的简介

洪水和滑坡是两种典型的地质灾害。针对这两种地质灾害的预报预测,本文简介了全球灾害系统(GHS)及一些应用。基于遥感和预测模型集成的全球洪水和滑坡灾害的解决思路,笔者采用美国宇航局(NASA)集成的准实时卫星降雨的洪水模型和滑坡模型,初步开发成全球灾害系统(GHS)对相关地区进行研究。通过在洪都拉斯、印度尼西亚、中国汶川等实例研究,表明GHS在在大型洪水的时间和强度上具有较好的预测能力,同时,能较精确地预报出滑坡发生的时间和范围。最后本文提出该系统在福建省应用的展望。     

基于TRMM数据的鄱阳湖流域降雨时空分布特征及其精度评价

基于1998-2007 年热带测雨卫星(TRMM) 3B42 V6 降雨数据分析鄱阳湖流域降雨时空分布特征, 并利用40个气象站观测日降雨数据对TRMM数据在不同子流域、不同降雨强度及不同季节里的精度进行了对比分析, 弥补了以往只评价整体精度的不足。结果显示:鄱阳湖流域北部地区修水、饶河子流域较易出现暴雨, 导致雷达信号衰减, 使TRMM对大雨强降雨的探测出现较大偏差;流域内降雨以10~50 mm为主, 其雨量占到总雨量的60%;流域降雨在年内1-3 月中旬为干旱少雨期, 3 月下旬-9 月初为湿润多雨期, 9-12 月再次进入干旱少雨期;而空间分布呈东、西部大, 中部小的格局;同时发现, 在赣南山区TRMM降雨较观测雨量低300~400 mm, 这可能受高程和坡度的影响, 使TRMM对山区降雨的探测精度也出现较大偏差。     

利用TRMM/TMI资料反演青藏高原中部土壤湿度

用辐射传输理论提出的地表微波辐射极化指数PI的定义,分别指出了PI对土壤湿度、地面粗糙度、植被层和大气层的影响。用热带降水测量(TRMM—Tropical Rainfall Measuring Mission)卫星上携带的微波辐射仪(TMI—TRMM Microwave Imager)的1B11的6年亮温数据,统计得到青藏高原中部地区PI值月平均分布。并用归一化距平,反演得到了该区域年、季以及干湿季土壤湿度变化的空间图像。结果表明,PI距平分布图可以很好地表征土壤湿度的变化,从而为大尺度评估高原土壤湿度变化提供了理论依据。另外,在同一时间段内,在已知区域平均PI值与平均土壤湿度的条件下,用归一化距平的方法可以定量反演该区域的土壤湿度。     

Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

反演寿县TMI微波频率的地表比辐射率

利用一个微波辐射传输模式，晴天下的大气探测廓线，地面的部分观测资料以及卫星观测的亮温，计算了淮河流域能量和水循环实验(HUBEx)中，寿县地区的热带降雨观测卫星微波成像仪(TRMM／TMI)微波频率的地表比辐射率。通过比较所计算的微波地表比辐射率随地表状况的改变，发现地表微波比辐射率随地表状况的变化存在敏感性，并且其变化是合理的。本中，地表肤温设定等于地表空气温度，并且仅计算了寿县的地表比辐射率，在HUBEx区域上的地表比辐射率的计算需要更多的观测资料。     

TRMM星载测雨雷达和地基雷达反射率因子数据的三维融合

TRMM卫星上的测雨雷达(TRMMPR)探测资料分布均匀且具有很高的垂直分辨率,但灵敏度较低;地基雷达(GR)水平分辨率较高且具有较高的灵敏度,但其垂直分辨率低。通过将TRMM PR与GR反射率因子数据的三维数据融合,得到了更优的反射率因子图像。测雨雷达与地基雷达三维数据融合主要分为以下几步:测雨雷达与地基雷达数据预处理——如去杂波、衰减校正;测雨雷达与地基雷达时空匹配;选取和应用合适的三维图像融合算法;对融合后的图像进行效果评估。试验结果表明:融合后的图像不仅增大了信息量,更好地检测弱降水,还提高了空间三维(3D)分辨率,能更好地反映降水区域细节,且使得数据总体上具有更高的完整性和可靠性。此外,还将基于雷达资料估测的降水数据与地面雨量计数据进行对比,估计反射率因子数据融合在降水测量上的有效性。      

中国区域逐日融合降水数据集与国际降水产品的对比评估

中国国家气象信息中心基于2400多个国家级台站观测日降水量和CMORPH卫星反演降水产品,采用概率密度匹配和最优插值相结合的两步数据融合方法,研制了中国区域1998年以来的0.25°×0.25°分辨率的逐日融合降水产品(CMPA_Daily)。通过该数据集与广泛应用于中国天气气候领域的两种国际上降水融合产品TRMM 3B42(Tropical Rainfall Measuring Mission, 3B42)和GPCP(Global Precipitation Climatology Project, 1 degree daily)的对比评估,考察CMPA_Daily产品的质量,评价其能否合理体现中国降水的天气气候特征。首先利用2008—2010年5—9月独立检验数据定量对比了CMPA_Daily、TRMM 3B42和GPCP 三种降水产品的误差,结果表明,在误差的时间变化和空间分布上,CMPA_Daily均具有最高的相关系数和最小的平均偏差及均方根误差,TRMM 3B42其次,GPCP的误差相对较大。CMPA_Daily只低估了大暴雨,TRMM 3B42低估了大雨以上量级的降水,而GPCP低估了除小雨以外的所有降水。CMPA_Daily产品因融入了更多的站点观测信息,不论在中国东部沿海,还是中西部地形复杂区,其精度均优于TRMM 3B42和GPCP产品,即使在站点稀疏的青藏高原地区,CMPA_Daily降水量也更加接近站点观测,呈现明显的高相关。CMPA_Daily与独立检验数据的高相关在地形起伏时效果也较稳定,TRMM和GPCP的相关系数则随着地形变化幅度陡变而非常明显地降低。进一步通过对比分析各降水产品1998—2012年的气候平均降水特征表明,3种资料对中国区域气候平均降水量、降水强度、频率分布以及年际变化的总体描述基本一致,因有效融入了更多的中国站点观测信息,不论降水空间分布还是降水量,CMPA_Daily与地面观测均最为接近,在中国的中东部大部分地区对降水的估计精度明显更高,而在站点分布较稀疏的青藏高原地区,CMPA_Daily的降水分布型与TRMM、GPCP卫星融合资料类似,较地面站点插值产品更能体现出合理的降水分布。对中国强降水事件监测对比表明,CMPA_Daily产品可以更加准确地描述降水的强度变化,细致刻画降水空间分布,在把握降水小尺度特征上具有明显的优势,体现出高分辨率、高精度降水产品的特点。