EGU23-16639
https://doi.org/10.5194/egusphere-egu23-16639
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Veljko Petković1, Patrick Stegmann2, Huan Meng3, Ralph Ferraro1, and John Xun Yang1
Veljko Petković et al.
  • 1University of Maryland, ESSIC, College Park, MD, United States of America (veljko.petkovic@umd.edu)
  • 2Joint Center for Satellite Data Assimilation, UCAR, USA
  • 3NOAA/NESDIS/STAR, College Park, MD, USA

Following the success of MetOp, EUMETSAT Polar System Second Generation (EPS-SG) will provide satellite observations from polar orbit to support Numerical Weather Prediction and climate monitoring in the 2024 to mid-2040's timeframe. Designed to fly on board the EPS-SG satellite-B series and cover 19-183 GHz frequency range, Microwave Imager (MWI) is expected to deliver high-quality measurements of radiometric properties relevant to precipitation, clouds, near-surface ocean winds and snow/ice cover. With goal to build an enterprise MWI retrieval in support to NOAA operational Environmental Data Records (EDRs) productiondevelopment of new and adaptation of the existing microwave imager algorithm procedures are underway at University of MarylandAs part of this effort and to ensure timely delivery of day-1 retrievals, we simulate MWI level-1 data over prolonged periods of time (up to 12 months) using radiative transfer techniques. Two datasets will be presented. The first, oriented towards precipitation retrieval development, relies on Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) observations to construct a state vector in radiative transfer calculations. The second dataset relies exclusively on ERA5 parameters. Two radiative transfer models have been considered in the production of simulated MWI brightness temperatures: a) Community Radiative Transfer Model (CRTM) and b) Edington model. Each model uses MWI observation geometry, following DPR and GCOM-W1 AMSR2 sampling, respectively. 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 sensorthe simulations reflect exceptionally high accuracy. In addition to the methodology and proxy data sets, preliminary results for MWI precipitation EDR retrieval will be presented.

How to cite: Petković, V., Stegmann, P., Meng, H., Ferraro, R., and Yang, J. X.: Building an EPS-SG Microwave Imager Retrieval Suite: Level-1 Proxy Data Record, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16639, https://doi.org/10.5194/egusphere-egu23-16639, 2023.