西藏高原测站降水与TRMM估测降水一致性评估

利用124个测站2011—2012年6—8月逐小时降水资料,分辨率为0.25°×0.25°的TRMM估测降水和DEM 高程数据,采用相关系数、相对误差和准确性指标,分析了西藏高原TRMM估测降水整体表现能力及海拔高度对降水估测影响。结果表明：TRMM估测降水在西藏高原整体趋势较一致,降水量级偏大,次数偏多;平均无降水准确率远高于平均有降水准确率,漏测率低而空测率高,降水量大的测站TRMM估测能力相对强。西藏高原上大部分测站处于相对低洼（河谷）地带,海拔高度差较小的区域TRMM估测降水与测站降水误差小,较大的区域误差则大。     

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。     

雨量计与星载测雨雷达资料结合的降水估算方法

利用华东地区97个气象站点,1998—2012年逐月降水资料和TRMM卫星降水产品,基于卫星结合雨量计降水估算方法,并考虑海拔高度对降水的影响,对华东地区的降水进行估算,得到研究区域降水的时空分布情况。通过误差验证,发现估算值与站点实测值之间具有较好的一致性,并且1、4、10月的估算值要好于7月的估算值。总体而言,该方法能够对华东地区进行较好的降水估算,并且能够反映研究区域的降水空间分布情况。     

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...     

基于光学厚度和有效半径的白天降水云识别方案

基于卫星资料观测和反演降水是当前监测全球尺度降水的主要方式,而其中一大难题就是如何将降水云与非降水云在像素尺度进行有效分离,这也是准确反演地表降水量的基本前提.为建立一套适用于常见星载可见光/红外探测仪器的降水云识别方法,本文利用热带测雨卫星( TRMM)可见光/红外辐射计(VIRS)和测雨雷达(PR)的融合观测资料,...     

High-frequency atmospheric variability over South China Sea as depicted by TRMM and QuikSCAT

By using the TRMM and QuikSCAT datathe characteristics of the 2–8 day high frequency atmospheric variability over the South China Sea are studied in this paper.It’s found that: (1) the 2–8 day high frequency signals are significant not only during the periods of the South China Sea Summer Monsoon (SCSSM),but also after the retreat of the SCSSM.It reaches its peak around July to August;(2) the 2–8 day high frequency signals exhibit strong intermittent features;(3) During El Nino years,the 2–8 day high freque...     

澜沧江及周边流域TRMM3B43数据精度检验

在地形复杂的澜沧江及周边流域,利用相关系数法、散点斜率法,以研究区内35个国家基准与基本站观测数据为“真值”对1998-2009年之间月尺度的TRMM 3B43降水数据精度进行检验,采用泰森多边形法、K-Means聚类法分析了高程与坡度对检验结果的影响,借助主成分法比较了高程与坡度对TRMM 3B43的影响程度.研究表...     

Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments

Abstract

A novel approach is presented for combining spatial and temporal detail from newly available TRMM-based data sets to derive hourly rainfall intensities at 1-km spatial resolution for hydrological modelling applications. Time series of rainfall intensities derived from 3-hourly 0.25° TRMM 3B42 data are merged with a 1-km gridded rainfall climatology based on TRMM 2B31 data to account for the sub-grid spatial distribution of rainfall intensities within coarse-scale 0.25° grid cells. The method is implemented for two dryland catchments in Tunisia and Senegal, and validated against gauge data. The outcomes of the validation show that the spatially disaggregated and intensity corrected TRMM time series more closely approximate ground-based measurements than non-corrected data. The method introduced here enables the generation of rainfall intensity time series with realistic temporal and spatial detail for dynamic modelling of runoff and infiltration processes that are especially important to water resource management in arid regions.

Editor D. Koutsoyiannis

Citation Tarnavsky, E., Mulligan, M. and Husak, G., 2012. Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments. Hydrological Sciences Journal, 57 (2), 248–264.     

Relation between GRACE-derived surface mass variations and precipitation over Australia

Surface mass changes (SMCs) obtained from time-variable gravity observations of the Gravity Recovery and Climate Experiment (GRACE) satellite mission and precipitation data from the Australian Bureau of Metrology and the Tropical Rainfall Measurement Mission are analysed over the Australian continent to determine whether there is a statistically significant correlation between them. The multiple linear regression analysis and the principal-component analysis techniques are applied in order to reveal the spatial and temporal variability of each data set separately as well as their mutual relationships. The study provides results and their statistical significance for the whole of Australia including the Murray Darling Basin in the southeast. The results suggest a significant decrease in water storage in the southeast of Australia and a dominant annual cycle over the majority of the continent for the four year period considered (January 2003 to December 2006), both in the surface mass and rainfall time series. The study revealed a direct relation between the data sets over most parts of Australia as confirmed by visual comparison and correlation analysis. When compared with precipitation data GRACE-derived SMCs exhibit smoother spatial and temporal variations. The latter is better suited to detect long-term trends in the presence of strong annual signals, which can adversely affect long-term trend estimates. Results regarding the magnitude of the annual signal suggest that only about a fourth of the precipitation's water masses remain sufficiently long in an area to be detected as a gravity change. The respective phases of the annual signals show an average time lag of about 40 days between precipitation and SMCs, suggesting that it takes about one to two months until a temporal gravity observation can detect a precipitation event.     

Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998-2015 Based on TRMM Precipitation Data

Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite (TRMM) 3B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool (BFAST) in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km2 per year from 1998 to 2015.