Abstract's details
Updated wind speed and sea state bias models for Ka-band altimetry
CoAuthors
Event: 2014 SARAL/AltiKa workshop
Session: Instrument processing
Presentation type: Type Poster
Contribution: PDF file
Abstract:
Recent wind speed models computed for Altika altimeter [Lillibridge et al, 2014; Abdalla, 2014] were developed by relating Altika data, backscatter solely or the pair (backscatter, SWH) to ECMWF model wind. Within the PEACHI project, a 2D wind speed model as a function of backscatter and SWH is also developed. Our approach is similar to the one adopted earlier for the TOPEX and Jason missions [Gourrion et al, 2002; Collard, 2005] and based on collocations between altimeter data and scatterometer winds. These latter are from the ASCAT sensor on METOP-A satellite over a year-period. Additionally, updated radiometer derived atmospheric attenuation correction is used to correct the Ka-band backscatter for its high sensitivity to the atmospheric liquid water and water vapor.
We expect further improvement in the wind speed estimations from the updated corrected backscatter, the use of scatterometer winds, the 2D model and the year-period dataset when one compares with existing estimates.
Concerning the SSB correction, a preliminary assessment based on the first four cycles of data has been performed by computing a 2D SSB solution, defined in the (SWH, wind speed) space and that used ECMWF model for both the wind and the wet tropospheric correction. These results were presented at the last OSTST 2013 meeting and at the 2014 SARAL International Science and Applications Meeting [Poisson et al, 2013; 2014]. Model estimations were used since the tunings of the wind speed and the radiometer based wet tropospheric correction were not yet optimums. The comparison of this preliminary solution with Jason-2 Ku-band solution (developed under the same conditions) shows that the SSB models display similar features for wind speed lower than 7 m/s. At higher wind, the Ka-band SSB estimates are lower than the Ku ones, in agreement with previous analyses.
Since, an updated 2D solution has been computed based on a year-period of AltiKa measurements with a fine-tuned altimeter wind speed and a refined radiometer wet troposphere correction. An alternative 3D solution will also be developed since measurable improvement could be gained with models that include mean wave period estimate from a global wave model (Wavewatch III) in addition to the traditional 2D input variables [Tran et al, 2010].
We expect further improvement in the wind speed estimations from the updated corrected backscatter, the use of scatterometer winds, the 2D model and the year-period dataset when one compares with existing estimates.
Concerning the SSB correction, a preliminary assessment based on the first four cycles of data has been performed by computing a 2D SSB solution, defined in the (SWH, wind speed) space and that used ECMWF model for both the wind and the wet tropospheric correction. These results were presented at the last OSTST 2013 meeting and at the 2014 SARAL International Science and Applications Meeting [Poisson et al, 2013; 2014]. Model estimations were used since the tunings of the wind speed and the radiometer based wet tropospheric correction were not yet optimums. The comparison of this preliminary solution with Jason-2 Ku-band solution (developed under the same conditions) shows that the SSB models display similar features for wind speed lower than 7 m/s. At higher wind, the Ka-band SSB estimates are lower than the Ku ones, in agreement with previous analyses.
Since, an updated 2D solution has been computed based on a year-period of AltiKa measurements with a fine-tuned altimeter wind speed and a refined radiometer wet troposphere correction. An alternative 3D solution will also be developed since measurable improvement could be gained with models that include mean wave period estimate from a global wave model (Wavewatch III) in addition to the traditional 2D input variables [Tran et al, 2010].