南京雷达数据的一致性分析和订正

运用几何匹配法处理了南京雷达和热带测雨卫星(Tropical Rainfall Measuring Mission,TRMM)上搭载的测雨雷达(Precipitation Radar,PR)的反射率因子探测资料,统计分析了2008—2013年共245个时次的匹配数据。 以TRMM PR工作多年持续稳定特征为参照,揭示了南京雷达6 a的探测资料情况。结果表明,南京雷达和TRMM PR探测降水具有较强的一致性,6 a时间里南京雷达存在一定的运行不稳定情况,南京雷达0℃层以下数据存在“3段特征”:时段Ⅰ2008年1月—2010年3月,时段Ⅱ2010年3月—2013年5月,时段Ⅲ2013年5—10月。3个时段之间整体回波强度有差异,时段Ⅱ整体回波强度比时段Ⅰ、Ⅲ偏小2—3 dB;而3个时段内的回波整体保持相对的稳定,南京雷达与TRMM PR的回波强度差值随回波强度的变化呈线性关系;在中低回波值时TRMM PR比南京雷达大,在中高回波值时南京雷达比TRMM PR大。基于两种雷达回波强度值的拟合关系,对南京雷达的反射率因子进行分段线性订正,有效地改善了南京雷达的一致性:3个时段回波强度的整体差异减小到0.75 dB以内;在245个匹配时次和105894个匹配点上南京雷达和TRMM PR的反射率因子的相关系数增大,南京雷达-TRMM PR值的标准差减小。     

TRMM降水数据在气象干旱监测中的应用研究

针对热带降雨计划卫星(TRMM)的降水数据在气象干旱监测中还未有应用的现状,论文利用TRMM 3843降水数据产品,以2008年10月～2009年2月间我国北方冬麦区气象干旱为监测实例,采用降水距平百分率指数对干旱的空间演变过程进行了监测.监测结果显示:(1)累积降水距平百分率,由于充分考虑了前期降水的累积效应,其气象干旱监测结果与实际情况极为吻合.(2)在2008年10月～2009年2月期间,我国北方冬麦区气象干旱先后经历了一个不断加重到逐渐缓解的过程.其中,2009年1月份的干旱程度最高,干旱核心区主要分布在北京南部,天津、河北中南部,山西大部,陕西北部,山东西部,河南中北部,湖北北部以及安徽北部等广大区域;至2009年2月底,受多次有效降水过程的影响,我国北方冬麦区的抗旱压力则得到极大缓解.(3)TRMM降水数据较地面气象站点观测,具有较好的时空连续性,在全国性及区域性宏观气象干旱监测中具有较好的应用前景.     

Estimating soil moisture using remote sensing data: A machine learning approach

Soil moisture is an integral quantity in hydrology that represents the average conditions in a finite volume of soil. In this paper, a novel regression technique called Support Vector Machine (SVM) is presented and applied to soil moisture estimation using remote sensing data. SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach. SVM has been used to predict a quantity forward in time based on training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. SVM model is applied to 10 sites for soil moisture estimation in the Lower Colorado River Basin (LCRB) in the western United States. The sites comprise low to dense vegetation. Remote sensing data that includes backscatter and incidence angle from Tropical Rainfall Measuring Mission (TRMM), and Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) are used to estimate soil water content (SM). Simulated SM (%) time series for the study sites are available from the Variable Infiltration Capacity Three Layer (VIC) model for top 10 cm layer of soil for the years 1998–2005. SVM model is trained on 5 years of data, i.e. 1998–2002 and tested on 3 years of data, i.e. 2003–2005. Two models are developed to evaluate the strength of SVM modeling in estimating soil moisture. In model I, training and testing are done on six sites, this results in six separate SVM models – one for each site. Model II comprises of two subparts: (a) data from all six sites used in model I is combined and a single SVM model is developed and tested on same sites and (b) a single model is developed using data from six sites (same as model II-A) but this model is tested on four separate sites not used to train the model. Model I shows satisfactory results, and the SM estimates are in good agreement with the estimates from VIC model. The SM estimate correlation coefficients range from 0.34 to 0.77 with RMSE less than 2% at all the selected sites. A probabilistic absolute error between the VIC SM and modeled SM is computed for all models. For model I, the results indicate that 80% of the SM estimates have an absolute error of less than 5%, whereas for model II-A and II-B, 80% and 60% of the SM estimates have an error less than 10% and 15%, respectively. SVM model is also trained and tested for measured soil moisture in the LCRB. Results with RMSE, MAE and R of 2.01, 1.97, and 0.57, respectively show that the SVM model is able to capture the variability in measured soil moisture. Results from the SVM modeling are compared with the estimates obtained from feed forward-back propagation Artificial Neural Network model (ANN) and Multivariate Linear Regression model (MLR); and show that SVM model performs better for soil moisture estimation than ANN and MLR models.     

西太平洋副热带高压下热对流降水结构特征的个例分析

利用热带测雨卫星的测雨雷达和红外辐射计的探测结果,对2003年8月2日15时(北京时)中国东南部副热带高压下发生的热对流降水结构特征、云和降水云之间的关系进行了分析研究。大气背景分析表明,500 hPa副热带高压中心附近的较强上升运动和850 hPa的水汽通量辐合为此次午后热对流降水云团的发生提供了动力和水汽条件。热带测雨卫星的测雨雷达探测结果表明,热对流降水云团的水平尺度多为30~40 km,平均垂直尺度均超过10 km,最高达17.5 km;云团的最大近地面雨强超过50 mm/h。热对流降水云团的平均降水廓线表明,其最大降水率出现在5 km的高度,这一高度比估计的环境大气0℃层高度低1 km。与“98.7.20”中尺度强降水的对流降水廓线比较表明,两者的最大降水率高度相同,但热对流降水云团更深厚;在4 km高度至近地面,热对流的降水率减少速度比“98.7.20”强对流降水的快,表明前者雨滴在下降过程中因气温高而发生强烈蒸发。对降水云团顶部特征与近地面雨强关系的分析结果表明,雨顶高较低时,云顶高度变化范围大;当雨顶越高时,云顶高度与雨顶高度越相近;平均而言,给定地面降水率,云顶高度比雨顶高度高出1~4 km;当近地面雨强越大,则云顶高度和雨顶高度越高、且越相近。结果还表明,非降水云面积约占86%,晴空面积仅占2%,而降雨云面积约为云面积的1/8。     

A Geo‐spatial study for analysing temporal responses of NDVI to rainfall

Climate change has become a serious concern worldwide owing to its multifaceted impact upon the physical as well as socio‐economic environment (IPCC, 2013). Vulnerability to climate change is much higher in the developing countries like India, where the economy is mainly agro‐based and productivity from the agricultural sector is dependent upon summer monsoon rainfall. Hence, assessing the quantitative relationship between vegetation patterns and climatic influence has become an increasingly important study conducted on regional and global scales. As vegetation cover plays a key role in conserving the natural environment, studying the spatio‐temporal trend of vegetation is crucial in identifying changes in the natural environment. We analysed the spatial responses of SPOT‐VGT NDVI to TRMM based rainfall during a sixteen year period (1998–2013) in the Bundelkhand region of Central India. The Normalized Difference Vegetation Index (NDVI) has proven to be a strong indicator of global vegetation productivity. Among climatic factors, rainfall robustly influences both spatial and temporal outline of NDVI. In this study, we used linear regression for analysing the statistical relationship among NDVI and rainfall and their trends. The study reveals a varying pattern of vegetation dynamics in response to rainfall over the area.     

Rain rate measurements over global oceans from IRS-P4 MSMR

In this paper rain estimation capability of MSMR is explored. MSMR brightness temperature data of six channels corresponding to three frequencies of 10, 18 and 21 GHz are colocated with the TRMM Microwave Imager (TMI) derived rain rates to find a new empirical algorithm for rain rate by multiple regression. Multiple correlation analysis involving various combinations of channels in linear and non-linear forms and rain rate from TMI is carried out, and thus the best possible algorithm for rain rate measurement was identified which involved V and H polarized brightness temperature measurements at 10 and 18 GHz channels. This algorithm explained about 82 per cent correlation (r) with rain rate, and 1.61 mm h^-1 of error of estimation. Further, this algorithm is used for generating global average rain rate map for two contrasting months of August (2000) and January (2001) of northern and southern hemispheric summers, respectively. MSMR derived monthly averaged rain rates are compared with similar estimates from TRMM Precipitation Radar (PR), and it was found that MSMR derived rain rates match well, quantitatively and qualitatively, with that from PR.     

利用TRMM资料分析2002年登陆广东的热带气旋降水分布特征

用2002年3个热带气旋登陆广东的过程中自动站的降水资料, 对TRMM准全球、准实时的3 h降水估测资料进行了检验, 表明该资料与地面3 h降水有很好的相关性, 可以反映出热带气旋3 h降水变化的特征。利用该资料分析了这3个热带气旋登陆过程中不同半径、不同方向降水的时空变化特征, 并分析了不同热带气旋之间降水差异的大尺度环流背景。研究发现, 3个热带气旋登陆过程中心附近降水沿半径方向存在收缩和扩展的变化, 除了低层水汽输送的变化和地形对降水造成影响之外, “北冕”和“黄蜂”都发现热带气旋外围降水加强会导致其中心附近降水减弱, 这与以往的观测及研究成果类似。     

基于TRMM数据的福建省降水时空格局BME插值分析

传统空间插值方法可获得福建省区域内降水的总体分布,但该地区气象站点较稀疏且分布不均,导致该区域内降水的空间插值结果误差较大。为提高插值精度,本文利用TRMM卫星数据以弥补站点数据的不足,尝试将TRMM数据作为"软数据"、台站数据作为"硬数据",两者相结合后采用贝叶斯最大熵(Bayesian Maximum Entropy,BME)方法对福建省降水的时空格局进行分析。以2000-2012年近13年20个气象站点的年降水量和月降水量为基础数据,分别利用普通克里格法(Ordinary Kriging,OK)和TRMM为"软数据"的BME插值法,分析福建省多年降水的时空分布格局,并对2种方法的插值结果进行比较。结果表明:在时空分布上,以TRMM数据为辅助变量的贝叶斯最大熵插值结果能更好地体现降水的局部差异特征;在误差评价上,以TRMM数据为辅助变量的贝叶斯最大熵插值结果的MAE和RMSE较小,表明TRMM数据作为"软数据"参与插值的BME方法可以在一定程度上弥补站点数据的不足,有效降低预测结果的绝对误差。通过对福建省降水插值的时空分布格局分析和误差评价可看出,BME插值法通过对基础台站数据,以及TRMM卫星产品数据的利用,使降水的时空分析结果更加真实客观,同时,为TRMM卫星降水数据的应用提供了一个新思路。     

基于TMI产品资料对数值模式水凝物模拟能力的检验分析

本文利用热带测雨卫星(Tropical Rainfall Measuring Mission,TRMM)搭载微波成像仪(TRMM Microwave Imager,TMI)的探测及反演结果,结合微波辐射传输模式,就2004年17号台风暹芭(Chaba)过程,对AREM(Advanced Regional Eta-coo...     

2000—2007年登陆台风中闪电活动与降水特征

利用TRMM卫星LIS, PR和TMI资料,对2000—2007年41个登陆我国的台风中闪电活动和降水特征进行分析。结果表明:台风中的闪电活动整体较弱,相对而言,外雨带中的闪电活动最强,其次是眼壁,内雨带最弱,而眼壁的闪电密度最大。闪电活动沿台风径向有两个明显的高值区,主峰出现在距台风眼375 km的外雨带,次峰出现在距台风眼55 km的眼壁和内雨带相交的边界附近。台风中对流云降水面积远小于层云降水面积,其中外雨带中的对流云降水面积最大,其次是眼壁,内雨带最小;但对流降水对总降水量的贡献与层云相当。眼壁和内雨带中的对流云和层云的降水回波平均高度都小于外雨带。分析表明:TMI观测到的85.5 GHz极化修正亮温 (T_PC85.5) 越低,闪电发生概率越大,外雨带具有最低的T_PC85.5。有、无闪电发生区域的平均6 km高度雷达反射率因子和T_PC85.5差异明显。台风区域内,闪电活动位置对应的平均6 km雷达回波强度普遍大于20 dBZ,而无闪电发生位置普遍低于30 dBZ。