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Community Radiative Transfer Model (CRTM) Support To Cloud Radiance Assimilation

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Wednesday, 7 January 2015
Quanhua Liu, NOAA/NESDIS, College Park, MD; and P. van Delst, D. Groff, H. Liu, E. H. Liu, M. Chen, A. Collard, S. A. Boukabara, F. Weng, and J. C. Derber

Developed at the Joint Center for Satellite Data Assimilation, the Community Radiative Transfer Model (CRTM) [1], operationally supports satellite radiance assimilation for weather forecasting [2]. The CRTM also supports JPSS/NPP [3] and GOES-R missions for the purposes instrument calibration [4], validation, monitoring long-term trending, and satellite retrieved products [5]. The CRTM development includes contributions from multiple U.S. government agencies, universities as well as private companies. This paper will present the updates associate with and beyond the CRTM version 2.1.3, which is applicable for passive microwave, infrared and visible sensors. It supports all NOAA satellite instruments, most visible, IR and microwave NASA instruments (including MODIS, AIRS, GMI, TMI, ), and many other meteorological satellites. This presentation will be concentrated on the CRTM developments for cloud radiance assimilation. We have added optional overcast radiance calculations that allow one to determine cloud height in the satellite radiance assimilation system. The CRTM is extended for a partial cloud radiance simulation and the sensitivity for an effective cloud fraction. The effective cloud fraction may be obtained from a cloud overlap scheme [6]. A faster radiative solver for two and four streams scattering is also developed and as the third solver in the CRTM. The solver may be adequate to the microwave and infrared radiance scatterings calculations under cloudy conditions. We will show preliminary results including studies about cloud-cleared radiance (CCR).

References [1] Liu, Q., and F. Weng, 2006: Advanced Doubling-Adding Method for Radiative Transfer in Planetary Atmosphere, J. Atmos. Sci., Vol. 63, No. 12, pages 34593465.

[2] Collard, A., F. Hilton, M. Forsythe, B. Candy, 2011: From Observations to Forecasts Part 8: The use of satellite observations in numerical weather prediction, Weather, 66, 3136.

[3] Weng, F., X. Zou, X. Wang, S. Yang, and M. D. Goldberg, 2012, Introduction to Suomi national polar-orbiting partnership advanced technology microwave sounder for numerical weather prediction and tropical cyclone applications, J. Geophys. Res.,117, D19112, doi:10.1029/2012JD018144.

[4] Liu, Q., and S. Boukabara, 2013: Community Radiation Transfer Model (CRTM) Applications in Supporting the Suomi National Polar-Orbiting Partnership (SNPP) Mission validation and Verification, Remote Sen. Environ., 140 (2014) 744754.

[5] Boukabara, S., Kevin Garrett, Wanchun Chen, Flavio Iturbide-Sanchez, Christopher Grassotti, Cezar Kongoli, Ruiyue Chen, Quanhua (Mark) Liu, Banghua Yan, Fuzhong Weng, Ralph Ferraro, Thomas J. Kleespies, Huan Meng, 2011: MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System. IEEE T. Geoscience and Remote Sensing 49(9): 3249-3272.

[6] Geer A. J., Bauer P. and ODell C.W., 2009. A revised cloud overlap scheme for fast microwave radiative transfer in rain and cloud. J. Applied Meteorology, 48, 22572270.