GSTDTAP  > 气候变化
DOI10.1002/2017JD027472
Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms
Mateus, Pedro1; Miranda, Pedro M. A.1; Nico, Giovanni2; Catalao, Joao1; Pinto, Paulo3; Tome, Ricardo1
2018-04-16
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
EISSN2169-8996
出版年2018
卷号123期号:7页码:3341-3355
文章类型Article
语种英语
国家Portugal; Italy
英文摘要

Very high resolution precipitable water vapor maps obtained by the Sentinel-1 A synthetic aperture radar (SAR), using the SAR interferometry (InSAR) technique, are here shown to have a positive impact on the performance of severe weather forecasts. A case study of deep convection which affected the city of Adra, Spain, on 6-7 September 2015, is successfully forecasted by the Weather Research and Forecasting model initialized with InSAR data assimilated by the three-dimensional variational technique, with improved space and time distributions of precipitation, as observed by the local weather radar and rain gauge. This case study is exceptional because it consisted of two severe events 12hr apart, with a timing that allows for the assimilation of both the ascending and descending satellite images, each for the initialization of each event. The same methodology applied to the network of Global Navigation Satellite System observations in Iberia, at the same times, failed to reproduce observed precipitation, although it also improved, in a more modest way, the forecast skill. The impact of precipitable water vapor data is shown to result from a direct increment of convective available potential energy, associated with important adjustments in the low-level wind field, favoring its release in deep convection. It is suggested that InSAR images, complemented by dense Global Navigation Satellite System data, may provide a new source of water vapor data for weather forecasting, since their sampling frequency could reach the subdaily scale by merging different SAR platforms, or when future geosynchronous radar missions become operational.


英文关键词data assimilation SAR interferometry severe weather events atmospheric moisture Weather Research and Forecasting (WRF) precipitation
领域气候变化
收录类别SCI-E
WOS记录号WOS:000430786500002
WOS关键词SAR INTERFEROMETRY ; GPS ; SIMULATIONS ; MODELS ; MM5
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/33827
专题气候变化
作者单位1.Univ Lisbon, Inst Dom Luiz, Fac Ciencias, Lisbon, Portugal;
2.CNR, Ist Applicaz Calcolo, Bari, Italy;
3.IPMA, Lisbon, Portugal
推荐引用方式
GB/T 7714
Mateus, Pedro,Miranda, Pedro M. A.,Nico, Giovanni,et al. Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(7):3341-3355.
APA Mateus, Pedro,Miranda, Pedro M. A.,Nico, Giovanni,Catalao, Joao,Pinto, Paulo,&Tome, Ricardo.(2018).Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(7),3341-3355.
MLA Mateus, Pedro,et al."Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.7(2018):3341-3355.
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