On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting

Figa, Julia; Stoffelen, Ad

doi:10.1109/36.851772

Cited by 37 publications

(26 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To avoid the bias inherent to such binning process when calculations are performed versus one wind reference (Freilich, 1997), the difference between QuikSCAT and ASCAT winds (in this order) is estimated according to QuikSCAT and ASCAT wind speed 1 m/s bins. Therefore, the difference is significant if the two calculations provide similar trends.…”

Section: Data Coherencymentioning

confidence: 99%

See 1 more Smart Citation

Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

2008

View full text Add to dashboard Cite

Abstract.The new scatterometer Advanced SCATterometer (ASCAT) onboard MetOp-A satellite provides surface wind speed and direction over global ocean with a spatial resolution of 25 km square over two swaths of 550 km widths. The accuracy of ASCAT wind retrievals is determined through various comparisons with moored buoys. The comparisons indicate that the remotely sensed wind speeds and directions agree well with buoy data. The root-mean-squared differences of the wind speed and direction are less than 1.72 m/s and 18 • , respectively. At global scale, ASCAT winds are compared with surface winds derived from QuikSCAT scatterometer. The results confirm the buoy analyses, especially for wind speed ranging between 3 m/s and 20 m/s. For higher wind conditions, ASCAT is biased low. The ASCAT underestimation with respect to QuikSCAT winds is wind speed dependent. The comparisons based on the collocated scatterometer data collected after 17 of October 2007 indicate that there are significant improvements compared to previous periods.

show abstract

Section: Data Coherencymentioning

confidence: 99%

“…They were successfully used within assimilation process in numerical weather prediction models (e.g. Figa et al, 2000). Numerous studies demonstrated the positive impact of scatterometer wind retrievals in predicting and describing tropical cyclones (e.g.…”

Section: Introductionmentioning

confidence: 99%

Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

2008

View full text Add to dashboard Cite

show abstract

“…Considering that conventional wind-only retrieval does not explicitly account for the sensitivity of backscatter measurements to rain, rain contamination introduces errors to retrieved wind velocities, particularly at high incidence angles. In order to prevent adverse rain impact on retrieved winds, quality control (QC) methods [4]- [6] are used to discard raincontaminated measurements-a process that causes the loss of Manuscript coverage. Considering that the successor of ESCAT, which is the advanced scatterometer instrument (ASCAT) on the MetOp-A satellite, has a higher incidence angle coverage than ESCAT, wind retrieval from ASCAT measurements is expected to be more sensitive to rain.…”

Section: Introductionmentioning

confidence: 99%

A C-Band Scatterometer Simultaneous Wind/Rain Retrieval Method

Nie

Long

2008

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Using collocated ERS scatterometer (ESCAT), Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), and European Centre for Medium-Range Weather Forecasts (ECMWF) data, the effects of rain on ESCAT wind-only retrieval are evaluated. Additional scattering from rain causes estimated wind speeds to appear higher than expected. Selected directions of the rain-corrupted wind vectors are biased toward along-track directions under conditions of heavy rain, which is regardless of the true wind direction. Rain becomes more significant for data acquired at a high incidence angle. To compensate for rain-induced backscatter, a simultaneous wind/rain retrieval (SWRR) method, which simultaneously retrieves wind velocity and surface rain rate from ESCAT measurements with an incidence angle > 40 • , is developed by using a C-band wind/rain backscatter model. The performance of SWRR under typical wind/rain conditions is evaluated through simulation and validation with collocated TRMM PR and ECMWF data sets. SWRR is shown to significantly improve wind velocity estimates, and the SWRR estimated surface rain rate has relatively high accuracy in moderate to heavy rain cases. Although SWRR-retrieved rain is somewhat biased, it can be corrected. We note that for ESCAT, about 1.5% of all the collocated measurements are affected by significant rain.

show abstract

“…The use of satellite-derived high-spatial-resolution SSW for validation and assimilation in atmospheric circulation models is another important challenge. The current literature includes several examples of scatterometer-derived SSW assimilation in numerical weather prediction (NWP) models (Figa and Stoffelen 2000;Singh, Kumar, and Pal 2012) but, to our knowledge, the assimilation of synthetic aperture radar (SAR)-derived SSW in NWP models and the validation of NWP models by means of sensitivity studies are described in Section 3 and the conclusions are given in the final section (Section 6). For the sake of simplicity and clarity we will refer to the XMOD2 GMF developed by Li and Lehner (2014) as XMOD2-DLR, while XMOD2-ASI denotes the GMF developed by Nirchio and Venafra (2013).…”

Section: Introductionmentioning

confidence: 99%

Application of state-of-the-art SAR X-band geophysical model functions (GMFs) for sea surface wind (SSW) speed retrieval to a data set of the Italian satellite mission COSMO-SkyMed

Grieco

Nirchio

Migliaccio

2015

International Journal of Remote Sensing

View full text Add to dashboard Cite

The concurrent presence of three satellite X-band SAR systems makes it interesting to test the interoperability of retrieval approaches meant for one system on the others. To approach this problem a description of the state of the art of the SAR X-band geophysical model functions (GMFs) for sea surface wind (SSW) speed retrieval is carried out. A sensitivity study of wind speed retrieval with respect to the wind direction when using the XMOD2 GMFs developed at the German Aerospace Center (DLR) and the Italian Space Agency (ASI) is presented. An application of these two GMFs to a series of data sets of stripmap images with vertical polarization VV acquired by the Italian satellite mission COSMO-SkyMed (CSK) is discussed, and the results of the SSW speed retrieval are compared to both the National Centers for Environmental Prediction (NCEP) blended sea winds and in situ buoy data from the National Data Buoy Center (NDBC). The retrieval exercises show that the two GMFs have similar performance. The sensitivity study shows that an error of ±10°may introduce an error greater that 10% in the retrieval of SSW speed.

show abstract

On the assimilation of Ku-band scatterometer winds for weather analysis and forecasting

Cited by 37 publications

References 11 publications

Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

A C-Band Scatterometer Simultaneous Wind/Rain Retrieval Method

Application of state-of-the-art SAR X-band geophysical model functions (GMFs) for sea surface wind (SSW) speed retrieval to a data set of the Italian satellite mission COSMO-SkyMed

Contact Info

Product

Resources

About