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- Author or Editor: Thomas Wilheit x
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Abstract
In preparation for the launch of TRMM, new algorithms must be created that take advantage of the combined data from radar and microwave radiometers that will be on board the satellite. A microwave radiative transfer algorithm with a one-dimensional cloud model is created that incorporates data from radar and radiometers using data obtained from TCM-90 and TOGA COARE flown over the western Pacific in 1990 and 1993, respectively.
A hybrid cloud model (HCM) was developed using observations from TOGA COARE, TCM-90, and other field projects. The HCM is a physically based model that is not “tuned” by limited “ground truth.” Therefore, the HCM incorporated new microphysical data based on observations of clouds. Cloud observations changed the HCM in four ways. First, stratiform clouds with low rain rates were shown to have a low cloud liquid water content (<0.1 g m−3). Second, radar data showed a linear decrease in the logarithm of the backscatter of ice particles above the freezing level. Third, tropical clouds contained more small drops and fewer large drops than predicted by the Marshall–Palmer drop size distribution. Last, the angular distribution of reflected radiation from ocean surface appears to be specular.
The HCM is compared to the Wilheit et al. model (WILM). The HCM differs from the WILM at low rain rates by as much as 10 K. At high rain rates, the HCM and the WILM produce similar brightness temperatures. However, this result is fortuitous because both models have substantially different thermodynamics and microphysics incorporated into them. Next, the brightness temperatures generated by the HCM are compared to observations from TOGA COARE. It is found that the brightness temperatures produced by the HCM closely agree with the observations. This study shows that a plane-parallel microwave radiative transfer algorithm coupled with a cloud model based on microphysical observations can accurately simulate rainfall observed in the Tropics.
Abstract
In preparation for the launch of TRMM, new algorithms must be created that take advantage of the combined data from radar and microwave radiometers that will be on board the satellite. A microwave radiative transfer algorithm with a one-dimensional cloud model is created that incorporates data from radar and radiometers using data obtained from TCM-90 and TOGA COARE flown over the western Pacific in 1990 and 1993, respectively.
A hybrid cloud model (HCM) was developed using observations from TOGA COARE, TCM-90, and other field projects. The HCM is a physically based model that is not “tuned” by limited “ground truth.” Therefore, the HCM incorporated new microphysical data based on observations of clouds. Cloud observations changed the HCM in four ways. First, stratiform clouds with low rain rates were shown to have a low cloud liquid water content (<0.1 g m−3). Second, radar data showed a linear decrease in the logarithm of the backscatter of ice particles above the freezing level. Third, tropical clouds contained more small drops and fewer large drops than predicted by the Marshall–Palmer drop size distribution. Last, the angular distribution of reflected radiation from ocean surface appears to be specular.
The HCM is compared to the Wilheit et al. model (WILM). The HCM differs from the WILM at low rain rates by as much as 10 K. At high rain rates, the HCM and the WILM produce similar brightness temperatures. However, this result is fortuitous because both models have substantially different thermodynamics and microphysics incorporated into them. Next, the brightness temperatures generated by the HCM are compared to observations from TOGA COARE. It is found that the brightness temperatures produced by the HCM closely agree with the observations. This study shows that a plane-parallel microwave radiative transfer algorithm coupled with a cloud model based on microphysical observations can accurately simulate rainfall observed in the Tropics.
Abstract
A physically based retrieval algorithm is presented that retrieves water vapor profiles from Special Sensor Microwave/Temperature-2 (SSM/T-2) passive microwave brightness temperature measurements. This method can use SSM/T-2 data alone or in conjunction with data from the Special Sensor Microwave/Imager (SSM/I). Several SSM/I channels, as well as total integrated water vapor (TIWV) retrieved from SSM/I, are tested to see if they add value to the retrieval. In the retrieval process, TIWV is formally treated as a separate channel. It is found that using the SSM/I TIWV increases the yield of the retrieval (the percentage of retrieved profiles whose brightness temperatures agree with the observations, on average, to within the noise level of the instrument), as well as reduces the average normalized brightness temperature error. Also, use of the TIWV allows the omission of the SSM/T-2 150-GHz channel data without a significant impact on results. It is shown that by using the SSM/I TIWV, retrievals can be made further into areas of precipitation and heavy clouds than when using data from only the SSM/T-2. Examples of retrieved profiles are shown to agree with the general features of profiles from radiosondes and the European Centre for Medium-Range Weather Forecasts analyses.
Abstract
A physically based retrieval algorithm is presented that retrieves water vapor profiles from Special Sensor Microwave/Temperature-2 (SSM/T-2) passive microwave brightness temperature measurements. This method can use SSM/T-2 data alone or in conjunction with data from the Special Sensor Microwave/Imager (SSM/I). Several SSM/I channels, as well as total integrated water vapor (TIWV) retrieved from SSM/I, are tested to see if they add value to the retrieval. In the retrieval process, TIWV is formally treated as a separate channel. It is found that using the SSM/I TIWV increases the yield of the retrieval (the percentage of retrieved profiles whose brightness temperatures agree with the observations, on average, to within the noise level of the instrument), as well as reduces the average normalized brightness temperature error. Also, use of the TIWV allows the omission of the SSM/T-2 150-GHz channel data without a significant impact on results. It is shown that by using the SSM/I TIWV, retrievals can be made further into areas of precipitation and heavy clouds than when using data from only the SSM/T-2. Examples of retrieved profiles are shown to agree with the general features of profiles from radiosondes and the European Centre for Medium-Range Weather Forecasts analyses.
