Open AccessThe Land Surface Analysis in the NCEP Climate Forecast System Reanalysis
Author(s) -
Jesse Meng,
Rongqian Yang,
Helin Wei,
Michael Ek,
George Gayno,
Pingping Xie,
Kenneth E. Mitchell
Publication year - 2012
Publication title -
journal of hydrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.733
H-Index - 123
eISSN - 1525-755X
pISSN - 1525-7541
DOI - 10.1175/jhm-d-11-090.1
Subject(s) - climate forecast system , environmental science , climatology , data assimilation , forcing (mathematics) , snow , precipitation , meteorology , geology , geography
The NCEP Climate Forecast System Reanalysis (CFSR) uses the NASA Land Information System (LIS) to create its land surface analysis: the NCEP Global Land Data Assimilation System (GLDAS). Comparing to the previous two generations of NCEP global reanalyses, this is the first time a coupled land–atmosphere data assimilation system is included in a global reanalysis. Global observed precipitation is used as direct forcing to drive the land surface analysis, rather than the typical reanalysis approach of using precipitation assimilating from a background atmospheric model simulation. Global observed snow cover and snow depth fields are used to constrain the simulated snow variables. This paper describes 1) the design and implementation of GLDAS/LIS in CFSR, 2) the forcing of the observed global precipitation and snow fields, and 3) preliminary results of global and regional soil moisture content and land surface energy and water budgets closure. With special attention made during the design of CFSR GLDAS/LIS, all the source and sink terms in the CFSR land surface energy and water budgets can be assessed and the total budgets are balanced. This is one of many aspects indicating improvements in CFSR from the previous NCEP reanalyses.