Discrete Ordinate Adding Method (DOAM), a new solver for Advanced Radiative transfer Modeling System (ARMS).

Area of Science:

• Atmospheric Physics and Remote Sensing
• Computational Science and Numerical Modeling

Background:

• Satellite data assimilation in Numerical Weather Prediction (NWP) relies on fast and accurate radiative transfer models.
• Existing models like RTTOV, CRTM, and ARMS are widely used, with ARMS incorporating solvers from CRTM.

Purpose of the Study:

• To introduce and evaluate a novel Discrete Ordinate Adding Method (DOAM) for solving radiative transfer equations.
• To assess DOAM's accuracy and computational efficiency for satellite data assimilation and remote sensing.

Main Methods:

• Developed DOAM to solve radiative transfer equations, incorporating solar and thermal sources.
• Employed single scattering approximation for computational acceleration in specific layers.
• Utilized principles of invariance to link radiances between layers and validated against DISORT and Doubling Adding method.

Main Results:

• DOAM demonstrated high accuracy, with biases decreasing as stream numbers increased, showing minimal bias (around 1%) with 8 streams in visible cases.
• Single scattering correction significantly reduced biases, especially in thermal cases where 4-stream DOAM showed maximum bias of -1.69%.
• DOAM exhibited superior computational efficiency compared to DISORT, with 2-stream DOAM calculating radiances in seconds versus DISORT's minutes.

Conclusions:

• DOAM is a computationally efficient and accurate radiative transfer solver suitable for NWP data assimilation.
• Its integration into ARMS enables reliable simulations for instruments like MWHS and MWRI.
• DOAM represents a valuable advancement for satellite remote sensing and weather prediction.