Paper Info
Title
A Preliminary Assessment Of The Impact Of Smap Soil Moisture On Numerical Weather Forecasts From Gfs And Nuwrf Models
Abstract
NASA Soil Moisture Active/Passive (SMAP) satellite was launched on January 31 st, 2015 and has been providing global soil moisture (SM) data products since April 2015. One of the primary justifications of the mission was to improve numerical weather predictions. With the SMAP SM data becoming available, it is anxiously expected that SMAP SM data could be demonstrated to significantly improve weather forecasts from numerical weather prediction (NWP) models. In this study, the NOAA Global Forecast System (GFS) and NASA Unified Weather Research and Forecast (NUWRF) model coupled with NASA Land Information System are used to carry out the demonstration. A hardwired Ensemble Kalman filter is implemented within GFS to assimilate surface SM observations. For assimilating SM data into NUWRF model, NASA Land Information System (LIS) is coupled with the NUWRF model. In this paper preliminary results of SMAP soil moisture impact on GFS and NUWRF forecasts are presented after the assimilation algorithms and system designs are introduced. Plans for more comprehensive assessment of the satellite soil moisture data impact on NWP models will be discussed.
Year
DOI
Venue
2016
10.1109/IGARSS.2016.7730362
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
Keywords
Field
DocType
SMAP, soil moisture, GFS, NUWRF, NWP
Meteorology,Data modeling,Satellite,Global Forecast System,Computer science,Remote sensing,Weather Research and Forecasting Model,Data assimilation,Ensemble Kalman filter,Weather forecasting,Numerical weather prediction
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
2
7
Name
Order
Citations
PageRank
Xiwu Zhan18315.33
Weizhong Zheng223.30
Li Fang310.72
Jicheng Liu411.37
christopher r hain51411.36
Jifu Yin600.68
Michael Ek731.21