A new method, Multisensor Retrieval of Atmospheric Properties (MRAP), is presented for deriving vertical profiles of atmospheric parameters throughout the troposphere. MRAP integrates measurements from multiple, diverse, remote sensing, and in situ instruments, the combination of which provides better capabilities than any instrument alone. Since remote sensors can deliver measurements automatically and continuously with high time resolution, MRAP provides better coverage than traditional rawinsondes. MRAP's design is flexible, being capable of incorporating measurements from different instruments in order to take advantage of new or developing advanced sensor technology. Furthermore, new or alternative atmospheric parameters for a variety of applications may be easily added as products of MRAP.
A combination of passive radiometric, active radar, and in situ observations provide the best temperature and humidity profile measurements. Therefore, MRAP starts with a traditional, radiometer-based, physical retrieval algorithm provided by the International TOVS (TIROS-N Operational Vertical Sounder) Processing Package (ITPP) that constrains the retrieved profiles to agree with brightness temperature measurements. The first-guess profiles required by the ITPP's iterative retrieval algorithm are obtained by using a statistical inversion technique and ground-based remote sensing measurements. Because the individual ground-based remote sensing measurements are usually of sufficiently high quality, the first-guess profiles by themselves provide a satisfactory solution to establish the atmospheric water vapor and temperature state, and the TOVS data are included to provide profiles with better accuracy at higher levels, MRAP provides a physically consistent mechanism for combining the ground- and space-based humidity and temperature profiles.
Data that have been used successfully to retrieve humidity and temperature profiles with MRAP are the following: temperature profiles in the lower troposphere from the ground-based Radio Acoustic Sounding System (RASS); total water vapor measurements from the Global Positioning System; specific humidity gradient profiles from the wind-profiling radar/RASS system; surface meteorological observations from standard instruments; cloud-base heights from a lidar ceilometer; temperature from the Aeronautical Radio, Incorporated Communication, Addressing and Reporting System aboard commercial airlines; and brightness temperature observations from TOVS.
Data from the experiment conducted in the late summer of 1995 at Point Loma, California, were used for comparisons of MRAP results and 20 nearby rawinsonde releases to assess the statistical error estimates of MRAP. The temperature profiles had a bias of −0.27°C and a standard deviation of 1.56°C for the entire troposphere. Dewpoint profile retrievals did not have an overall accuracy as high as that of the temperature profiles but they exhibited a markedly improved standard deviation and bias in the lower atmosphere when the wind profiler/RASS specific humidity gradient information was available as a further constraint on the process. The European Centre for Medium-Range Weather Forecasts (ECMWF) model profiles of humidity and temperature for the grid point nearest to the Point Loma site were also used for comparison with the rawinsonde soundings to establish the usefulness of MRAP profiles to the weather forecasting community. The comparison showed that the vertical resolution of the ECMWF model profiles within the planetary boundary layer is not capable of detecting sharp gradients.