Sensor-based clear and cloud radiance calculations in the community radiative transfer model

Area of Science:

• Atmospheric Science and Meteorology
• Radiative Transfer Modeling
• Satellite Data Assimilation

Background:

• The Community Radiative Transfer Model (CRTM) is crucial for satellite radiance simulations in NOAA's data assimilation systems.
• Assimilation of clear-sky radiances is successful, but cloudy radiances are computationally expensive, hindering severe weather forecasting improvements.
• Current cloud radiance calculations in CRTM are too slow for operational weather forecasting needs.

Purpose of the Study:

• To investigate the accuracy of the Optical Transmittance (OPTRAN) approximation within CRTM for cloudy satellite radiance simulations.
• To assess the feasibility of using OPTRAN-CRTM for affordable assimilation of cloudy radiances in numerical weather prediction.
• To understand the error sources associated with the OPTRAN approximation compared to line-by-line radiative transfer models.

Main Methods:

• Implemented the Optical Transmittance (OPTRAN) band model within CRTM, using cloud optical parameters at band central wavelengths.
• Compared OPTRAN-CRTM cloud radiance calculations against detailed Line-By-Line Radiative Transfer Model (LBLRTM) simulations.
• Evaluated accuracy using data from NOAA's High Resolution Infrared Radiation Sounder/3 (HIRS/3) and Advanced Microwave Sounding Unit (AMSU) sensors.

Main Results:

• OPTRAN-CRTM achieved accuracy better than 0.4 K for infrared (HIRS/3) and 0.1 K for microwave (AMSU) sensors.
• The OPTRAN approximation significantly improves computational efficiency by requiring only one radiative transfer solution per channel.
• The scaling method (SCALING-CRTM) showed larger errors, up to 7 K for HIRS/3 clear-sky and 3.5 K for cloudy conditions.

Conclusions:

• The OPTRAN-CRTM approximation provides adequate accuracy for operational satellite radiance assimilation in numerical forecast models.
• This computationally efficient method makes the assimilation of cloudy radiances affordable, paving the way for improved forecasting.
• OPTRAN-CRTM demonstrates superior performance over the SCALING-CRTM method, particularly under cloudy conditions.