Coverage, spatial and temporal resolution
Period and temporal resolution:
- 2003-02-05 to 2019-09-15
- Daily (2 times, ascending & descending overpasses)
Missing days: Aug. 9-11 2017, Jan. 10-13 2019
Coverage and spatial resolution:
- Global, over open water
- Spatial resolution: 0.25° x 0.25°, cartesian grid
- Geographic longitude: 0°E to 360°E
- Geographic latitude: -90°N to 90°N
- Dimension: 1440 columns x 720 rows
- Altitude: 0.0 m
The data set offered here does not include any explicit uncertainty estimations.
The antenna temperatures measured by the sensor from the fore and aft looking directions are processed into top-of-the-atmosphere brightness temperatures (TBs) and inter-calibrated with other satellite passive microwave instruments (see GMI_ATBD).
The product comes at 0.25° grid resolution. However, the effective resolution of the product depends on the footprint size of the sensors' channels used. All products which are using TBs from the 6.8 GHz channels with the coarsest spatial resolution have the corresponding effective spatial resolution which is given in a separate column in the table under parameters.
The advantage of a multi-frequency, multi-polarization instrument like WindSat is that contributions from atmospheric parameters such as water vapor, cloud liquid water and rain can be directly estimated from the same set of TBs (similar to what is done from SSM/I data for the HOAPS data set) which helps to optimize the wind speed and also wind direction retrieval. High values in any of these three parameters might still deteriorate the wind vector retrieval. In particular the wind direction retrieval using WindSat is hampered by rain rates above 15 mm/hour. Note further that wind direction cannot be retrieved under wind speeds below 3 m/s.
The capability of WindSat to measure TBs at 6.8 GHz and 10.7 GHz also allows to retrieve the SST which also helps to optimize the wind vector retrieval. At the same time, however, RFI and sun glint effect the TBs at these low-frequency channels and the SST retrieval and therefore also the wind vector retrieval; affected grid cells are flagged accordingly.
All above-mentioned parameters retrieved from WindSat data are included in the data set.
We refer to the section references for further information.
Remote Sensing Systems
Santa Rosa, CA, U.S.A.
email: support (at) remss.com
ICDC / CEN / University of Hamburg
email: stefan.kern (at) uni-hamburg.de
When using the data please cite as follows:
Wentz, F. J., L. Ricciardulli, C. Gentemann, T. Meissner, K. A. Hilburn, and J. Scott, 2013: Remote Sensing Systems Coriolis WindSat Daily Environmental Suite on 0.25 deg grid, Version 7.0.1. Remote Sensing Systems, Santa Rosa, CA. Available online at www.remss.com/missions/windsat. [Accessed from www.remss.com, last access date: Oct 15 2019]. Downloaded in netCDF file format from the Integrated Climate Data Center (ICDC, icdc.cen.uni-hamburg.de) University of Hamburg, Hamburg, Germany.
In addition please add to the acknowledgements:
WindSat data are produced by Remote Sensing Systems and sponsored by the NASA Earth Science MEaSUREs DISCOVER Project and the NASA Earth Science Physical Oceanography Program. RSS WindSat data are available at www.remss.com.