0360677 - ÚFA 2012 RIV GB eng J - Journal Article
Mahfouf, J. - F. - Bližňák, Vojtěch
Combined assimilation of screen-level observations and radar-derived precipitation for soil moisture analysis.
Quarterly Journal of the Royal Meteorological Society. Roč. 137, č. 656 (2011), s. 709-722. ISSN 0035-9009. E-ISSN 1477-870X
Institutional research plan: CEZ:AV0Z30420517
Keywords : data assimilation * weather prediction * land surface schemes
Subject RIV: DG - Athmosphere Sciences, Meteorology
Impact factor: 2.907, year: 2011
http://onlinelibrary.wiley.com/doi/10.1002/qj.791/abstract

A methodology is proposed in order to combine information from radar precipitation with other observations (e.g. screen-level temperature and relative humidity) in a soil analysis scheme based on an extended Kalman filter. The study is performed over the Czech Republic for one month in July 2008 using three-hour rainfall accumulations derived from two radars and a land-surface scheme. The Jacobian matrix of the observation operator is examined to make optimal choices for the estimation of the Kalman gain matrix. Too small values lead to unphysical negative elements whereas too large values reduce the spatial variability considerably. After a log-transform of the precipitation field, the errors are more compatible with the Gaussian hypothesis of the Kalman filter. Two methods for combining the assimilation of screen-level observations with radar precipitation are compared. An evaluation shows more accurate soil analyses when both sources of information are considered to correct soil moisture contents.
Permanent Link: http://hdl.handle.net/11104/0198175