Building an EPS-SG Microwave Imager Retrieval Suite: Level-1 Proxy Data Record

<p><span>F</span><span>ollowing&#160;</span><span>the</span><span>&#160;success of&#160;</span><span>MetOp</span><span>, EUMETSAT Polar System Second Generation (EPS-SG)</span><span>&#160;</span><span>will</span><span>&#160;</span><span>provide&#160;</span><span>satellite&#160;</span><span>observations from polar orbit</span><span>&#160;to support&#160;</span><span>N</span><span>umerical&#160;</span><span>W</span><span>eather&#160;</span><span>P</span><span>rediction</span><span>&#160;and climate monitoring in the 202</span><span>4</span><span>&#160;to mid-2040's timeframe.&#160;</span><span>Designed to fly&#160;</span><span>on board the EPS-SG satellite-B series and cove</span><span>r</span><span>&#160;1</span><span>9</span><span>-183 GHz frequency range, </span><span>Microwave Imager (MWI)&#160;</span><span>is&#160;</span><span>expected&#160;</span><span>to deliver high-quality measurements of radiometric properties relevant to precipitation, clouds, near-surface ocean winds and snow/ice cover.&#160;</span><span>With&#160;</span><span>a&#160;</span><span>goal to&#160;</span><span>build an enterprise MWI retrieval in support to NOAA operational Environmental Data Records (EDRs) production</span><span>,&#160;</span><span>a&#160;</span><span>development of new and ad</span><span>a</span><span>ptation of&#160;</span><span>the&#160;</span><span>existing microwave imager algorithm procedures</span><span> are underway</span><span>&#160;at University of Maryland</span><span>.&#160;</span><span>As part of&#160;</span><span>this effort and&#160;</span><span>to&#160;</span><span>ensure timely delivery of day-1 retrievals, we simulate MWI level-1 data&#160;</span><span>over</span><span>&#160;prolonged periods of time (up to 12 months) using radiative transfer</span><span>&#160;techniques</span><span>. Two datasets will be presented. The first, oriented towards precipitation retrieval&#160;</span><span>development</span><span>, relies on Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) observations </span><span>to </span><span>construct</span><span> a state vector&#160;</span><span>in&#160;</span><span>radiative transfer calculations</span><span>. T</span><span>he second dataset relies exclusively on ERA5 parameters. Two radiative transfer models have been&#160;</span><span>considered</span><span>&#160;in&#160;</span><span>the&#160;</span><span>production of simulated MWI brightness temperatures</span><span>:</span><span> a) Community Radiative Transfer Model (CRTM) and b) Edington model</span><span>. E</span><span>ach</span><span>&#160;model</span><span>&#160;us</span><span>es&#160;</span><span>MWI observation geometry, following DPR and&#160;</span><span>GCOM-W1 </span><span>AMSR2 sampling</span><span>, respectively</span><span>. To deliver the product, CRTM has been updated by, for this purpose derived, MWI coefficients using an idealized Spectral Response Function at each of the 26 channels. When compared to the common channels of AMSR2</span><span>&#160;sensor</span><span>,&#160;</span><span>the&#160;</span><span>simulations reflect exceptionally high accuracy. In addition to the methodology and proxy data sets, preliminary results for MWI precipitation&#160;</span><span>EDR</span><span>&#160;retrieval will be presented.</span></p>