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

Acknowledgements for providing critical resources and 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

Objective: 1.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 2.Learn what level of rain spatial resolution is sufficient to obtain satisfactory corrections 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.

Approach: Physically based electromagnetic model to correct each SIGMA0 measurement for the effects of rain volume backscatter and 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 K u -band reflectivity and attenuation (2-km horizontal resolution)

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

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

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

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

Electromagnetic Model of the NRCS (σ ax ) Measured by SeaWinds Scatterometer Use of “x” subscript below will represent either “h” or “v” polarization σ ax =Total measured NRCS at Receiver;Contributions from Surface and Rain Volume σ wdx = sea surface NRCS due to wind driven roughness alone (wind-NRCS) σ rnx = sea surface NRCS due to rain impact roughness alone (rain-NRCS) α x (r)= attenuation, in nepers/m for each polarization, function of local volume rainrate or precipitation water content σ ox (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=46 o & θv=54 o )

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

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

Attenuation formula from TRMM Project, (Courtesy of R. Meneghini) α = 4x10 -4 * Z 0.72 dB/km (Z is Ku-band Reflectivity, in Linear Units)

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

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

PODAAC L2B Product Wind Magnitude across area observed by NEXRAD

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

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

SUMMARY 1.The high resolution (~1 km) S-band reflectivity is used to model the volume reflectivity and attenuation for each L2A SCAT cell. Corrections are made to attempt to remove all effects of rain. 2.The Wind Retrieval algorithm recalculates the wind magnitudes at the same locations as the L2B winds The corrections are appreciable, and produce improved wind estimates. These are supported by an in-situ buoy observation. 3.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.