Community Radiative Transfer Model for Inter-Satellites Calibration and Verification

Quanhua Liu, University of Maryland College Park, College Park, United States, Nicholas R Nalli, IMSG, Inc., at National Oceanic and Atmospheric Administration (NOAA), College Park MD, United States, Alexander Ignatov, NOAA/NESDIS, STAR, College Park, MD, United States, Kevin Garrett, NOAA/NWS/OMD, College Park, United States, Yong Chen, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, Fuzhong Weng, NOAA, Boulder, CO, United States, Sid Ahmed Boukabara, NOAA NESDIS, Camp Springs, MD, United States, Paul F van Delst, IMSG, Inc., Alexandria, VA, United States, David Neil Groff, IMSG, College Park, MD, United States, Andrew Collard, NOAA/NWS/NCEP/EMC, College Park, United States, Everette Joseph, Howard University, Washington, DC, United States, Vernon R Morris, Arizona State University, Associate Dean, New College ASU West, Tempe, AZ, United States and Peter J Minnett, University of Miami, Rosenstiel School of Marine, Atmospheric, and Earth Science, Department of Ocean Sciences, Miami, United States
Abstract:
Developed at the Joint Center for Satellite Data Assimilation, the Community Radiative Transfer Model (CRTM) [1], operationally supports satellite radiance assimilation for weather forecasting. The CRTM also supports JPSS/NPP and GOES-R missions [2] for instrument calibration, validation, monitoring long-term trending, and satellite retrieved products [3].

The CRTM is used daily at the NOAA NCEP to quantify the biases and standard deviations between radiance simulations and satellite radiance measurements in a time series and angular dependency. The purposes of monitoring the data assimilation system are to ensure the proper performance of the assimilation system and to diagnose problems with the system for future improvements. The CRTM is a very useful tool for cross-sensor verifications. Using the double difference method, it can remove the biases caused by slight differences in spectral response and geometric angles between measurements of the two instruments. The CRTM is particularly useful to reduce the difference between instruments for climate studies [4].

In this study, we will carry out the assessment of the Suomi National Polar-orbiting Partnership (SNPP) [5] Cross-track Infrared Sounder (CrIS) data [6], Advanced Technology Microwave Sounder (ATMS) data, and data for Visible Infrared Imaging Radiometer Suite (VIIRS) [7][8] thermal emissive bands. We use dedicated radiosondes and surface data acquired from NOAA Aerosols and Ocean Science Expeditions (AEROSE) [9]. The high quality radiosondes were launched when Suomi NPP flew over NOAA Ship Ronald H. Brown situated in the tropical Atlantic Ocean. The atmospheric data include profiles of temperature, water vapor, and ozone, as well as total aerosol optical depths. The surface data includes air temperature and humidity at 2 meters, skin temperature (Marine Atmospheric Emitted Radiance Interferometer, M-AERI [10]), surface temperature, and surface wind vector.

[1] Liu, Q., and F. Weng, 2006: JAS

[2] Liu, Q., and S. Boukabara, 2013: RSE

[3] Boukabara et al., 2011: TGARS

[4] Wang, LK, Zou C-Z. 2013: JGR

[5] Weng et al, 2012: JGR

[6] Han, Y., et al., 2013: JGR

[7] Caoet al, 2013: GR

[8] Liang, X, A. Ignatov, 2013: JGR

[9] Nalliet al 2011: BAMS

[10] Minnett et al, 2001: JAOT

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