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David E. Weissman Hofstra University Hempstead, New York

Corrections to Scatterometer Wind Vectors from the Effects of Rain, Using High Resolution NEXRAD Radar Collocations. David E. Weissman Hofstra University Hempstead, New York

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David E. Weissman Hofstra University Hempstead, New York

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  1. Corrections to Scatterometer Wind Vectors from the Effects of Rain, Using High Resolution NEXRAD Radar Collocations David E. Weissman Hofstra University Hempstead, New York Mark A. Bourassa Center for Ocean Atmosphere Prediction Studies/FSU Tallahassee, Florida

  2. Acknowledgements for providing critical resourcesand consultation: Jeffrey Tongue, National Weather Service, New York Office Michael Istok, NOAA/NWS Office of Science and Technology Greg Apgar, Dept. of Engineering, Hofstra University Steven Durden, Jet Propulsion Laboratory

  3. Motivating Problem: Rain in the atmosphere and impacts on the sea surface produce erroneously high NRCS and wind estimates.Methods of correcting the satellite SIGMA0 are being developed and tested. • Objective: • Create corrected SIGMA0’s over the rain affected area;then use this modified L2A data set to produce corrected wind vectors in the L2B data product • Learn what level of rain spatial resolution is sufficient to obtainsatisfactory corrections

  4. Approach: Physically based electromagnetic model to correct eachSIGMA0 measurement for the effects of rain volume backscatterand two-way attenuation Technique: Use coincident and collocated 3-D rain measurements that provide volumetric S-Band radar reflectivity, “Z”, (NEXRAD) to permit estimation of the Ku-band reflectivity and attenuation (2-km horizontal resolution)

  5. S-Band Reflectivity at Elevation of 500-m, Circles at 50 km Spacing

  6. Locations of the SeaWinds L2A SIGMA0 Cells – “O” = V-pol, “+” = H-pol B B

  7. Subdivision of SCAT Elliptical Footprint into 5 km Square, 2 km High Cells (0-to-8km)NEXRAD Reflectivity is determined in each cell – Correction to SIGMA0 in each cell

  8. Relative Positions of Reflectivity Cells Along Incident Beam, V-pol Case

  9. Electromagnetic Model of the NRCS (σax) Measured by SeaWinds Scatterometer Use of “x” subscript below will represent either “h” or “v” polarization σax =Total measured NRCS at Receiver;Contributions from Surface and Rain Volume σwdx= sea surface NRCS due to wind driven roughness alone (wind-NRCS) σrnx = sea surface NRCS due to rain impact roughness alone (rain-NRCS) αx(r)= attenuation, in nepers/m for each polarization, function of local volume rainrate or precipitation water content σox (r)= surface equivalent of volumetric rain RCS, = constant * Zx (the radar reflectivity factor for Ku-band, Zx, varies with position, “r”) lenx=path length of radar beam for each polarization = len/Cos(θx) (rain column height, over scatterometer footprint = len, θh=46o & θv=54o)

  10. Horizontal slices of the NEXRAD Reflectivity of a H-pol Cell (Lat=29o, Long=281o)

  11. Calculations of Ku band reflectivity in term of the S-band NEXRAD reflectivity,based on Haddad, et al, drop size distribution, and Durdenraindrop RCS Solid Line – Stratiform Dash Line - Convective

  12. Attenuation formula from TRMM Project, (Courtesy of R. Meneghini) α = 4x10-4 * Z0.72 dB/km (Z is Ku-band Reflectivity, in Linear Units)

  13. HISTOGRAMS – Showing the populations of the L2A data (dB) indifferent levels “before” (top) and“after” (below) full correction

  14. 24-July-03 Wind Magnitudes Estimated by NCEP / Model Winds providedby the L2B data product Buoy Wind =5.3 m/s Buoy Wind=0.4 m/s

  15. PODAAC L2B Product Wind Magnitude across area observed by NEXRAD

  16. Corrected Wind Magnitudes Using the Modified L2A SIGMA0 Values – Using volume backscatter, attenuation and “surface splash” effects

  17. Differences in Wind Magnitudes Between the L2B data product and the Correctedwinds from the previous slide. Reductions up to 6 m/s are made from erroneous winds

  18. SUMMARY • The high resolution (~1 km) S-band reflectivity is used to model the volume reflectivity and attenuation foreach L2A SCAT cell. Corrections are made to attemptto remove all effects of rain. • The Wind Retrieval algorithm recalculates the wind magnitudes at the same locations as the L2B windsThe corrections are appreciable, and produce improved wind estimates. These are supported by an in-situ buoy observation. • If this technique can produce satisfactory results, it can be generalized to determine what is the required rain resolution over the ocean to support future Scatterometer wind measurements in rain.

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