Characterizing Channel Center Frequencies in AMSU-A and MSU Microwave Sounding Instruments

Author:

Lu Qifeng1,Bell William2

Affiliation:

1. National Satellite Meteorological Center, China Meteorological Administration, Beijing, China

2. ECMWF, Reading, United Kingdom

Abstract

Abstract Passive microwave observations from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) have been exploited widely for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies. The treatment of biases in these observations, with respect to models as well as between satellites, has been the focus of much effort in recent years. This study presents evidence that shifts, drifts, and uncertainties in pass band center frequencies are a significant contribution to these biases. Center frequencies for AMSU-A channels 6–14 and MSU channel 3 have been analyzed using NWP fields and radiative transfer models, for a series of operational satellites covering the period 1979–2012. AMSU-A channels 6 (54.40 GHz), 7 (54.94 GHz), and 8 (55.50 GHz) on several satellites exhibit significant shifts and drifts relative to nominal pass band center frequencies. No significant shifts were found for AMSU-A channels 9–14, most probably as a consequence of the active frequency locking of these channels. For MSU channel 3 (54.96 GHz) most satellites exhibit large shifts, the largest for the earliest satellites. For example, for the first MSU on the Television and Infrared Observation Satellite-N (TIROS-N), the analyzed shift is 68 MHz over the lifetime of the satellite. Taking these shifts into account in the radiative transfer modeling significantly improves the fit between model and observations, eliminates the strong seasonal cycle in the model–observation misfit, and significantly improves the bias between NWP models and observations. The study suggests that, for several channels studied, the dominant component of the model–observation bias results from these spectral errors, rather than radiometric bias due to calibration errors.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

Reference26 articles.

1. Adaptive bias correction for satellite data in a numerical weather prediction system;Auligné;Quart. J. Roy. Meteor. Soc.,2007

2. The assimilation of SSMIS radiances in numerical weather prediction models;Bell;IEEE Trans. Geosci. Remote Sens.,2008

3. BIPM, 1998: Evaluation of measurement data—Guide to the expression of uncertainty in measurement. Joint Committee for Guides in Metrology Rep. ISO/IEC GUIDE-2008, 134 pp. [Available online at www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf.]

4. Monitoring the observation impact on the short-range forecasts;Cardinali;Quart. J. Roy. Meteor. Soc.,2009

5. Analysis of the merging procedure for the MSU daily temperature time series;Christy;J. Climate,1998

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