Implementation of a Discrete Dipole Approximation Scattering Database Into Community Radiative Transfer Model

Abstract

Assimilation of all-sky satellite microwave (MW) observations into Numerical Weather Prediction (NWP) models plays an important role in improving routine weather forecasts as well as prediction of extreme weather events such as tropical cyclones (Duncan et al., 2022). Unlike infrared observations which are normally saturated in the presence of optically thick clouds, MW instruments continue to provide useful information even in the presence of deep convective clouds. Data assimilation systems generally use a fast radiative transfer (RT) model as the forward operator to assimilate satellite observations into the first guess provided by the NWP models (Baordo &

Impact of Microphysics Parameterization Schemes on the Assimilation of GOES‐16 ABI All‐Sky Infrared Radiances for a Bow Echo Analysis and Prediction

“…Journal of Geophysical Research: Atmospheres 10.1029/2023JD040046 necessary for enhancing the consistency between microphysics schemes and the radiative transfer model in future studies. Such consistency can be achieved by developing new look-up tables, similar to previous studies that focused on microwave channels (Moradi et al, 2022;Ren et al, 2023;Sieron et al, 2017Sieron et al, , 2018. To efficiently update various scales, it is recommended to consider the utilization of the multiscale data assimilation (MDA) method, as suggested in previous studies (X.…”

“…r e ). It is noted that this approach, using the default CRTM look‐up table, is still limited compared to previous studies, which improved the consistency for microwave channels by constructing new tables based on identical particle size distributions (Sieron et al., 2017), mass‐size relationships (Ren et al., 2023), and particle shapes (Moradi et al., 2022; Sieron et al., 2018).…”

Toward the Next Generation of Microwave Sounders: Benefits of a Low-Earth Orbit Hyperspectral Microwave Instrument in All-Weather Conditions Using AI

“…As argued in [3], it may be possible to infer cloud and hydrometeor particle effective radii from HyMS spectra, however, in this study we prescribed particle effective radii as in the microwave integrated retrieval system MiRS [9]. We also note that the parameterizations of cloud and particle scattering, which are based on Mie-Lorenz theory in the version of the CRTM used in this study, are known to limit the accuracy of CRTM all-sky calculations [10,11]. In the future, we plan on utilizing updated parameters and parameterizations as described in [10] and assess the ability of hyperspectral microwave sounders to retrieve cloud microphysical properties such as effective radius and/or particle habit.…”

Direct assimilation of AVHRR satellite radiance measurements in a reanalysis system

“…The process of assimilation of AVHRR radiance in a reanalysis system is described briefly in the next section. Tang et al, 2017;Stegmann et al, 2018;Stegmann et al, 2022;Lu et al, 2022;Nalli et al, 2022;Moradi et al, 2022;Karpowicz et al, 2022). The CRTM takes skin SST as an input, as well as the atmospheric profile and aerosol properties of the column.…”

“…All satellite observations are directly assimilated by Gridpoint Statistical Interpolation software (GSI; Kleist et al ., 2009) using Community Radiative Transfer Model (CRTM; Tang et al ., 2017; Stegmann et al ., 2018; Stegmann et al ., 2022; Lu et al ., 2022; Nalli et al ., 2022; Moradi et al ., 2022; Karpowicz et al ., 2022). The CRTM takes skin SST as an input, as well as the atmospheric profile and aerosol properties of the column.…”