Projectes de transferència

Recent developments on the Ku-band scatterometer wind geophysical model function (GMF) include a sea surface temperature (SST) dependent term. It has been found that the SST effects on the radar backscatter are wind speed dependent and more pronounced in vertical polarization (VV) than in horizontal poolarisation (HH) and at higher incidence angles, and are only relevant at radar wavelenghts smaller tan C-band. The new Ku-band GMF, NSCAT-5, is based on a physical model and Rapidscat radar backscatter measurements, which are only available at two incidence angles, i.e., 49⁰ and 56⁰, for HH and VV beams, respectively. The aim of this study is to verify the NSCAT-5 GMF at other incidence angles, using data from the recently-launched Indian SCATSat-1, which operates at 42.6⁰ (HH) and 49.3⁰ (VV) incidence angle.

 Scatterometer-derived sea-surface vector winds, such as those from the Advanced Scatterometers (ASCAT-A & B) onboard Metop-A & B, and atmospheric motion vectors (AMVs) derived from geostationary satellite images, such as those provided with MSG satellite series by NWC/GEO-HRW algorithm, are routinely assimilated into numerical weather prediction (NWP) models, such as the European Centre for Medium-Range Weather Forecasts (ECMWF). Two particular relevant problems in the Atmospheric Motion Vectors are: - The height assignment process, in which sometimes it is difficult to find an optimum pressure level for the derived AMVs, due to the vertical extension of the cloud and moisture tracers which are tracked by the AMV algorithm. This way, the “height assignment process” keeps on being the main source of errors related to the calculated AMVs. - The general scarcity, and the larger errors, of AMV data at the lowest atmospheric levels (near the ground). This is caused by the fact that with the current implementations, AMVs cannot be calculated below a layer of opaque clouds, so limiting the capabilities of the algorithm to extract winds near the surface. On the other side, validation statistics of low level AMVs (between 700 and 1000 hPa) have always shown to be the worst, in part due to the larger difficulties to differentiate and track clouds near the ground, which in infrared channels do not differentiate too much from the surrounding ground, and in part also due to the difficulties to relate the AMVs (mean winds related to the displacement of a tracer during several minutes) with the winds near the ground (which change in shorter temporal and spatial frames). The goal of this study is to perform a preliminary characterization of the differences between ASCAT winds and AMVs near the surface, as a function of the AMV height and wind variability conditions at the surface. This study also aims at assessing the potential of using scatterometer winds to characterize possible systematic errors in the AMVs and their estimated heights.