Coupling WRF Double-Moment 6-Class Microphysics Schemes to RRTMG Radiation Scheme in Weather Research Forecasting Model [PDF]
Advances in Meteorology, 2016 A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics
Soo Ya Bae +2 more
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Using surface remote sensors to derive radiative characteristics of Mixed-Phase Clouds: an example from M-PACE [PDF]
Atmospheric Chemistry and Physics, 2011 Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative ...
G. de Boer +3 more
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Geophysical Research Letters, 2021 To improve the numerical weather prediction model over Korea using a neural network (NN) radiation emulator, two types of compound parameterization (CP) were developed.
Hwan‐Jin Song +2 more
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Improved Weather Forecasting Using Neural Network Emulation for Radiation Parameterization
Journal of Advances in Modeling Earth Systems, 2021 In this study, a neural network (NN) emulator for radiation parameterization was developed to use in an operational weather forecasting model in the Korea Meteorological Administration. The development of the NN emulator was based on large‐scale training
Hwan‐Jin Song, Soonyoung Roh
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Applied Sciences, 2021 This study aims to improve the performance of the Weather Research and Forecasting (WRF) model in the sea breeze circulation using the micro-Genetic Algorithm (micro-GA).
Ji Won Yoon, Sujeong Lim, Seon Ki Park
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WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results [PDF]
Geoscientific Model Development, 2012 Air quality models such as the EPA Community Multiscale Air Quality (CMAQ) require meteorological data as part of the input to drive the chemistry and transport simulation.
D. C. Wong +9 more
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Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System: RRTMGP-NN 2.0 [PDF]
Geoscientific Model Development, 2023 Radiation schemes are physically important but computationally expensive components of weather and climate models. This has spurred efforts to replace them with a cheap emulator based on neural networks (NNs), obtaining large speed-ups, but at the ...
P. Ukkonen, R. J. Hogan, R. J. Hogan
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A Radiative Transfer Emulator Dataset for WRF RRTMG-K
, 2023 This dataset is used for training the NN models in paper "A Radiative Transfer Deep Learning Model Coupled into WRF with a Generic Fortran Torch Adaptor".
openaire +1 more source
Using a GPU to Accelerate a Longwave Radiative Transfer Model with Efficient CUDA-Based Methods
Applied Sciences, 2019 Climatic simulations rely heavily on high-performance computing. As one of the atmospheric radiative transfer models, the rapid radiative transfer model for general circulation models (RRTMG) is used to calculate the radiative transfer of electromagnetic
Yuzhu Wang +5 more
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Evaluating and improving the treatment of gases in radiation schemes: the Correlated K-Distribution Model Intercomparison Project (CKDMIP) [PDF]
Geoscientific Model Development, 2020 Most radiation schemes in weather and climate models use the “correlated k distribution” (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a
R. J. Hogan, M. Matricardi
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