EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

被引：32

作者：

Berges, J. C. ^{[1
]}

Jobard, I. ^{[2
,3
]}

Chopin, F. ^{[2
]}

Roca, R. ^{[2
]}

机构：

[1] Univ Paris 01, PRODIG, F-75005 Paris, France

[2] Ecole Polytech, CNRS, IPSL, LMD, F-91128 Palaiseau, France

[3] Univ Paris Sud, F-92296 Chatenay Malabry, France

来源：

ANNALES GEOPHYSICAE | 2010年 / 28卷 / 01期

关键词：

Meteorology and atmospheric dynamics; Precipitation; Tropical meteorology; Instruments and techniques; ARTIFICIAL NEURAL-NETWORKS; PASSIVE MICROWAVE SENSORS; SMALL-SCALE RAINFALL; GLOBAL PRECIPITATION; PROFILING ALGORITHM; CONVECTIVE RAINFALL; CLOUD; RETRIEVAL; IMAGERY; AFRICA;

D O I：

10.5194/angeo-28-289-2010

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey) indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

引用

页码：289 / 308

页数：20

共 67 条

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