Articles | Volume 15, issue 22
Geosci. Model Dev., 15, 8541–8559, 2022
https://doi.org/10.5194/gmd-15-8541-2022
Geosci. Model Dev., 15, 8541–8559, 2022
https://doi.org/10.5194/gmd-15-8541-2022
Development and technical paper
22 Nov 2022
Development and technical paper | 22 Nov 2022

Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a)

Sujeong Lim et al.

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Cited articles

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Short summary
The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.