scholarly journals Ocean Wind Fields from Satellite Active Microwave Sensors

10.5772/9111 ◽  
2010 ◽  
Author(s):  
S. Zecchetto
Keyword(s):  
Wind Fields ◽  
Ocean Wind ◽  
Microwave Sensors

scholarly journals Improved ocean wind forcing products

2020 ◽  
Author(s):  
Rianne Giesen ◽  
Ana Trindade ◽  
Marcos Portabella ◽  
Ad Stoffelen
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Surface Wind ◽  
Ocean Surface ◽  
Ocean Model ◽  
Wind Forcing ◽  
Small Scale ◽  
Wind Fields ◽  
Ocean Surface Wind ◽  
Ocean Wind

<p>The ocean surface wind plays an essential role in the exchange of heat, gases and momentum at the atmosphere-ocean interface. It is therefore crucial to accurately represent this wind forcing in physical ocean model simulations. Scatterometers provide high-resolution ocean surface wind observations, but have limited spatial and temporal coverage. On the other hand, numerical weather prediction (NWP) model wind fields have better coverage in time and space, but do not resolve the small-scale variability in the air-sea fluxes. In addition, Belmonte Rivas and Stoffelen (2019) documented substantial systematic error in global NWP fields on both small and large scales, using scatterometer observations as a reference.</p><p>Trindade et al. (2019) combined the strong points of scatterometer observations and atmospheric model wind fields into ERA*, a new ocean wind forcing product. ERA* uses temporally-averaged differences between geolocated scatterometer wind data and European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis fields to correct for persistent local NWP wind vector biases. Verified against independent observations, ERA* reduced the variance of differences by 20% with respect to the uncorrected NWP fields. As ERA* has a high potential for improving ocean model forcing in the CMEMS Model Forecasting Centre (MFC) products, it is a candidate for a future CMEMS Level 4 (L4) wind product. We present the ongoing work to further improve the ERA* product and invite potential users to discuss their L4 product requirements.</p><p>References:</p><p>Belmonte Rivas, M. and A. Stoffelen (2019): <em>Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT</em>, Ocean Sci., 15, 831–852, doi: 10.5194/os-15-831-2019.</p><p>Trindade, A., M. Portabella, A. Stoffelen, W. Lin and A. Verhoef (2019), <em>ERAstar: A High-Resolution Ocean Forcing Product</em>, IEEE Trans. Geosci. Remote Sens., 1-11, doi: 10.1109/TGRS.2019.2946019.</p>

scholarly journals Validation of Backscatter Measurements from the Advanced Scatterometer on MetOp-A

2011 ◽  
Vol 29 (1) ◽  
pp. 77-88 ◽  
Author(s):  
C. Anderson ◽  
J. Figa ◽  
H. Bonekamp ◽  
J. J. W. Wilson ◽  
J. Verspeek ◽  
...  
Keyword(s):  
Incidence Angle ◽  
Absolute Calibration ◽  
Calibration Error ◽  
Wind Fields ◽  
Worst Case ◽  
Antarctic Sea Ice ◽  
Geophysical Model ◽  
Geophysical Model Function ◽  
Calibration Accuracy ◽  
Ocean Wind

Abstract The Advanced Scatterometer (ASCAT) on the Meteorological Operational (MetOp) series of satellites is designed to provide data for the retrieval of ocean wind fields. Three transponders were used to give an absolute calibration and the worst-case calibration error is estimated to be 0.15–0.25 dB. In this paper the calibrated data are validated by comparing the backscatter from a range of naturally distributed targets against models developed from European Remote Sensing Satellite (ERS) scatterometer data. For the Amazon rainforest it is found that the isotropic backscatter decreases from −6.2 to −6.8 dB over the incidence angle range. The ERS value is around −6.5 dB. All ASCAT beams are within 0.1 dB of each other. Rainforest backscatter over a 3-yr period is found to be very stable with annual changes of approximately 0.02 dB. ASCAT ocean backscatter is compared against values from the C-band geophysical model function (CMOD-5) using ECMWF wind fields. A difference of approximately 0.2 dB below 55° incidence is found. Differences of over 1 dB above 55° are likely due to inaccuracies in CMOD-5, which has not been fully validated at large incidence angles. All beams are within 0.1 dB of each other. Backscatter from regions of stable Antarctic sea ice is found to be consistent with model backscatter except at large incidence angles where the model has not been validated. The noise in the ice backscatter indicates that the normalized standard deviation of the backscatter values Kp is around 4.5%, which is consistent with the expected value. These results agree well with the expected calibration accuracy and give confidence that the calibration has been successful and that ASCAT products are of high quality.

A real-time assimilation algorithm applied to near-surface ocean wind fields

2008 ◽  
Vol 19 (3) ◽  
pp. 319-330 ◽  
Author(s):  
Anders Malmberg ◽  
Jan Holst ◽  
Ulla Holst
Keyword(s):  
Real Time ◽  
Wind Fields ◽  
Near Surface ◽  
Surface Ocean ◽  
Ocean Wind
Sign in / Sign up

Export Citation Format

Share Document