Development and validation of ARMS-gb v2.0: extending fast radiative transfer modeling capability to all-sky conditions for ground-based microwave radiometer retrievals

Ground-based microwave radiometers provide continuous, all-weather observations of boundary-layer temperature and humidity, closing a critical near-surface observation gap. The Advanced Radiative Transfer Modeling System – ground-based (ARMS-gb) is a fast radiative transfer model specifically designed to simulate the brightness temperatures observed by these instruments. This paper presents ARMS-gb v2.0, which introduces a hydrometeor absorption and scattering module and an accelerated discrete ordinate method (ADOM) solver for multiple scattering. The model now simulates cloud water, rain, ice, snow, and graupel using optical-property look-up tables computed with Mie theory and the discrete dipole approximation (DDA). The existing tangent-linear and adjoint (TL/AD) modules are also extended to include hydrometeor processes, supporting all-sky retrieval and variational data assimilation. Validation against field measurements from 14- and 22-channel ground-based microwave radiometers indicates that ARMS-gb v2.0 effectively simulates brightness temperatures under cloudy non-precipitating conditions, with the mean observed minus simulated brightness temperature generally within 1 K of the corresponding clear-sky baseline. Compared with ARMS-gb v1.0, which neglects cloud effects, the root mean square error (RMSE) under cloudy conditions decreases by 1–2 K in the water-vapor band, most notably at 30 GHz, where the coefficient of determination ( R ² ) increases from 0.55 to 0.77. In the weak oxygen band, where frozen hydrometeors have stronger scattering effects, the observation-minus-background (O–B) decreases by 3–4 K. At 51 GHz, the RMSE decreases from 5.23 to 3.22 K, and R ² increases from 0.52 to 0.81. Moreover, the results indicate that the DDA model slightly outperforms the Mie model in characterizing frozen hydrometeors at these channels. However, large O–B departures remain during precipitation events, with RMSE values in the water-vapor absorption band reaching 30–40 K, reflecting rain-contaminated measurement effects and atmospheric hydrometeor uncertainties that require dedicated quality control and observation-error modeling before assimilation or retrieval applications.