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Advanced Microwave Sounding Unit (advance + microwave_sounding_unit)

Distribution by Scientific Domains

Earth and Environmental Science	100%

Selected Abstracts

Precipitation analysis using the Advanced Microwave Sounding Unit in support of nowcasting applications

METEOROLOGICAL APPLICATIONS, Issue 2 2002
Ralf Bennartz
We describe a method to remotely sense precipitation and classify its intensity over water, coasts and land surfaces. This method is intended to be used in an operational nowcasting environment. It is based on data obtained from the Advanced Microwave Sounding Unit (AMSU) onboard NOAA-15. Each observation is assigned a probability of belonging to four classes: precipitation-free, risk of precipitation, precipitation between 0.5 and 5 mm/h, and precipitation higher than 5 mm/h. Since the method is designed to work over different surface types, it relies mainly on the scattering signal of precipitation-sized ice particles received at high frequencies. For the calibration and validation of the method we use an eight-month dataset of combined weather radar and AMSU data obtained over the Baltic area. We compare results for the AMSU-B channels at 89 GHz and 150 GHz and find that the high frequency channel at 150 GHz allows for a much better discrimination of different types of precipitation than the 89 GHz channel. While precipitation-free areas, as well as heavily precipitating areas (>5 mm/h), can be identified to high accuracy, the intermediate classes are more ambiguous. This stems from the ambiguity of the passive microwave observations as well as from the non-perfect matching of the different data sources and sub-optimal radar adjustment. In addition to a statistical assessment of the method's accuracy, we present case studies to demonstrate its capabilities to classify different types of precipitation and to work over highly structured, inhomogeneous surfaces. Copyright © 2002 Royal Meteorological Society [source]

Estimates of spatial and interchannel observation-error characteristics for current sounder radiances for numerical weather prediction.

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 649 2010
I: Methods, application to ATOVS data
Abstract This is the first part of a two-part article that uses three methods to estimate observation errors and their correlations for clear-sky sounder radiances used in the European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation system. The analysis is based on covariances derived from pairs of first-guess and analysis departures. The methods used are the so-called Hollingsworth/Lönnberg method, a method based on subtracting a scaled version of mapped assumed background errors from first-guess departure covariances and the Desroziers diagnostic. The present article reports the results for the three Advanced TIROS Operational Vertical Sounder (ATOVS) instruments: the Advanced Microwave Sounding Unit (AMSU)-A, High-Resolution Infrared Radiation Sounder (HIRS) and Microwave Humidity Sounder (MHS). The findings suggest that all AMSU-A sounding channels show little or no interchannel or spatial observation-error correlations, except for surface-sensitive channels over land. Estimates for the observation error are mostly close to the instrument noise. In contrast, HIRS temperature-sounding channels exhibit some interchannel error correlations, and these are stronger for surface-sensitive channels. There are also indications for stronger spatial-error correlations for the HIRS short-wave channels. There is good agreement between the estimates from the three methods for temperature-sounding channels. Estimating observation errors for humidity-sounding channels of MHS and HIRS appears more difficult. A considerable proportion of the observation error for humidity-sounding channels appears correlated spatially for short separation distances, as well as between channels. Observation error estimates for humidity channels are generally considerably larger than the instrument noise. Observation error estimates from this study are consistently lower than those assumed in the ECMWF assimilation system. As error correlations are small for AMSU-A, the study suggests that the current use of AMSU-A data in the ECMWF system in terms of observation-error or thinning-scale choices is fairly conservative. Copyright © 2010 Royal Meteorological Society [source]

Toward a consistent reanalysis of the upper stratosphere based on radiance measurements from SSU and AMSU-A

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 645 2009
Shinya Kobayashi
Abstract Radiance measurements from the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit (AMSU-A) are the primary source of information for stratospheric temperature in reanalyses of the satellite era. To improve the time consistency of the reanalyses, radiance biases need to be properly understood and accounted for in the assimilation system. The investigation of intersatellite differences between SSU and AMSU-A radiance observations shows that these differences are not accurately reproduced by the operational version of the radiative transfer model for the TIROS Operational Vertical Sounder (RTTOV-8). We found that this deficiency in RTTOV was mainly due to the treatment of the Zeeman effect (splitting of the oxygen absorption lines at 60 GHz) and to changes in the spectral response function of the SSU instrument that are not represented in RTTOV. On this basis we present a revised version of RTTOV that can reproduce SSU and AMSU-A intersatellite radiance differences more accurately. Assimilation experiments performed with the revised version of RTTOV in a four-dimensional variational analysis system (4D-Var) show some improvements in the stratospheric temperature analysis. However, significant jumps in the stratospheric temperature analysis still occur when switching satellites, which is due to the fact that systematic errors in the forecast model are only partially constrained by observations. Using a one-dimensional retrieval equation, we show that both the extent and vertical structure of the partial bias corrections must inevitably change when the nature of the radiance measurement changes with the transition from SSU to AMSU-A. Copyright © 2009 Royal Meteorological Society [source]