Beginning with the launch of the DMSP SSM/I F08 satellite, the remote sensing coverage of the global oceans in a 6-hour period increased from 20% in 1987 to nearly 70% in 2004. From 1987 to 2007, over thirteen satellites became operational including both passive microwave sensors and scatterometers. We previously described a variational analysis method (VAM) that was used to combine wind speeds derived from the DMSP SSM/I satellites into a consistent global analysis at 1x1 degree resolution (Atlas et al, 1996, BAMS, 77, 869-882). With NASA REASoN support, this work was significantly expanded. Cross-calibrated data sets of satellite surface wind data are obtained from Remote Sensing Systems (RSS) under the DISCOVER project (Distributed Information Services: Climate/Ocean Products and Visualizations for Earth Research). RSS now uses a highly accurate sea-surface emissivity model resulting in much better consistency between wind speed retrievals from microwave radiometers (SSM/I F08–F15, AMSRE, TRMM TMI) and those from scatterometers (SeaWinds and QuikSCAT). These observations and all conventional ship and buoy observations are referenced to a height of 10 meters assuming that the boundary layer over the ocean is neutrally stable. All observations were combined to create a consistent, long-term (1987 – 2007), global data set of ocean surface winds at high resolution (25 km). These data are currently available for interested investigators.
For this project, the VAM was enhanced for the assimilation of data from multiple platforms at high resolution. We now define a microwave ocean surface wind speed observation operator appropriate for SSM/I, TMI, AMSRE, and other similar instruments. To avoid overly smoothing small-scale features in the analysis where the time rates of change might be large we also now use the first guess at the appropriate time (FGAT) and a reformulated dynamical constraint. In areas of overlapping observations from multiple platforms, the linear approximations inherent in the FGAT procedure can lead to unrealistic analysis increments. Recognizing this, the FGAT procedure was enhanced to effectively de-weight the data as the difference between the observation time and the analysis time increases. Two background (first guess) analyses were used—10-meter winds from the ERA-40 Re-analysis for the period July 1987 to December 1998 and ECMWF operational analyses beginning in 1999.
The basic standard products are the 6-hourly 25-km gridded VAM analyses. These analyses are time averaged over 5-day and monthly periods, averaging over only those grid points with one or more quality controlled observations. Finally, directions from the VAM analyses are assigned to the wind speed observations for each passive microwave sensor to enhance the original RSS products.