Validation of microwave radiometer geophysical parameters using meteorological model analyses

Abstract

Data measured by microwave radiometers are brightness temperatures, from which, using algorithms, geophysical parameters arc retrieved. Errors in these parameters can be due either to the algorithms or to instrumental deficiencies affecting the brightness temperatures. Only geophysical data can be validated directly since dedicated meteorological experiments cannot be performed frequently enough or in a sufficient number of places during the satellites lifetime. To achieve such a global validation, we propose to use global meteorological model analyses, which contain the information of all routine observations after checking their quality. In this article, we test this approach by comparing Nimbus-7/SMMR geophysical data with ECMWF model analyses. Data from five months in 1979 are examined, and deviations between both data sets are analysed in terms of satellite or model errors. This comparison reveals SMMR problems in SSTand surface wind data, and local model errors in the precipitable water. Therefore, a good knowledge of model behaviour is necessary for using its analyses in satellite data validation, yet it appears as a useful tool, working at scales ranging from regional to global, and in time, from a particular event to a season or more.

Expected improvements in the atmospheric humidity profile retrieval using the Megha‐Tropiques microwave payload

“…Two types of training database are generally used for the design of a retrieval scheme: the atmospheric profiles are either extracted from quality‐controlled radiosoundings (see Wang and Chang, 1990; Cabrera‐Mercadier and Staelin, 1995; among others) or from analyses or reanalyses (NCEP‐NCAR or ECMWF models, e.g. Eymard et al , 1993; Shi, 2001; Zhang et al , 2008; Aires et al , 2012, this issue). Both sources of information are studied, section 4 being dedicated to the selection of the most adapted training dataset for the present problem.…”

Assessment of the AMSR-E soil moisture product over India

“…However, the AMSR-E soil moisture product contains uncertainties due to imperfect instrument calibration and inversion algorithms, geophysical noise, representativeness error, communication breakdowns and other sources (Eymard et al 1993, Zhan et al 2004. Also, the presence of moderate to dense vegetation obscures the soil moisture signals, impeding accurate satellite measurements (Sahoo et al 2008).…”

Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

“…Satellite microwave radiometers have been successfully used to monitor the temporal and spatial variations of sea surface and atmospheric properties on a global scale. This includes the validation of microwave radiometer geophysical parameters using meteorological model analysis (Eymard et al 1993), comparative studies (Varma et al 1998), rainfall, cloud liquid water, surface winds and precipitation related studies (Schluessel and Emery 1990;Schluessel and Luthardt 1991;Chang and Holt 1994;Ledvina and Pfaendtner 1995;Weng et al 1997;Xiao et al 2000 etc. ).…”