2024-03-29T10:17:42Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1413162022-01-19T10:14:31Zcom_10261_123com_10261_8col_10261_502
2016-12-12T12:30:16Z
urn:hdl:10261/141316
High Resolution Ocean Wind Forcing Product
Trindade, Ana
Stoffelen, Ad
Portabella, Marcos
de Kloe, Jos
2015 Institute of Electrical and Electronics Engineers (IEEE) Young Professional Conference on Remote Sensing, 3-4 December 2015, Barcelona, Spain.-- 1 page
Surface winds derived from earth Observation satellites are increasingly required for use in operational monitoring and forecasting of the ocean. A drawback of space borne wind observing systems, such as scatterometers, is that they provide time and space coverage unsuitable for, among others, high resolution ocean model forcing.
Recent attempts of combining scatterometer data and numerical weather prediction (NWP) outputs, blended ocean forcing products, allows for an increased temporal resolution (e.g., daily) but generally only resolves NWP spatial scales of ~200 km. Therefore, information on wind current interaction, on the diurnal wind cycle and on wind variability in moist convection areas is lost in such products. Moreover, known systematic NWP model (parameterization) errors are in fact propagated at times and locations where no scatterometer winds are available. The alternative, direct forcing from NWP results in even more extensive physical drawbacks. We propose to maintain the increased temporal coverage in a gridded wind and stress product, but also to maintain most beneficial physical qualities of the scatterometer winds, i.e., 25 km spatial resolution, wind current interaction, variability due to moist convection, etc., and, at the same time avoid the large scale NWP parameterization and dynamical errors. Additionally, we correct these winds for the effects of atmospheric stability and mass density, using stress equivalent 10 m winds, U10S.
In fact, collocations of scatterometer and global NWP winds show these physical differences, where the local mean and variability of these differences are rather constant in time and thus could be added to the ERA interim time record in order to better represent physical interaction processes and avoid NWP model errors. Correction of either the wind vector biases and wind vector variability is expected to affect ocean forcing. Information on the scatterometer wind sampling error is provided by these collocations
2016-12-12T12:30:16Z
2016-12-12T12:30:16Z
2015-12-03
2016-12-12T12:30:18Z
comunicación de congreso
2015 IEEE Young Professionals Conference on Remote Sensing: 19 (2015)
http://hdl.handle.net/10261/141316
eng
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Institute of Electrical and Electronics Engineers