Articles | Volume 15, issue 22
https://doi.org/10.5194/gmd-15-8541-2022
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, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park

Related authors

Optimized Stochastic Representation of Soil States Model Uncertainty of WRF (v4.2) in the Ensemble Data Assimilation System
Sujeong Lim, Seon Ki Park, and Claudio Cassardo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-28,https://doi.org/10.5194/gmd-2023-28, 2023
Revised manuscript not accepted
Short summary
Ensemble data assimilation of total column ozone using a coupled meteorology–chemistry model and its impact on the structure of Typhoon Nabi (2005)
S. Lim, S. K. Park, and M. Zupanski
Atmos. Chem. Phys., 15, 10019–10031, https://doi.org/10.5194/acp-15-10019-2015,https://doi.org/10.5194/acp-15-10019-2015, 2015
Short summary
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation
S. K. Park, S. Lim, and M. Zupanski
Geosci. Model Dev., 8, 1315–1320, https://doi.org/10.5194/gmd-8-1315-2015,https://doi.org/10.5194/gmd-8-1315-2015, 2015
Short summary

Related subject area

Atmospheric sciences
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024,https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024,https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024,https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024,https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024,https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary

Cited articles

Anderson, E. A.: National Weather Service River Forecast System: Snow Accumulation and Ablation Model, Tech. Mem., US Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, vol. 17, https://repository.library.noaa.gov/view/noaa/13507 (last access: 24 October 2022), 1973. a, b
Annan, J. D. and Hargreaves, J. C.: Efficient parameter estimation for a highly chaotic system, Tellus A, 56, 520–526, 2004. a
Bonekamp, P. N. J., Collier, E., and Immerzeel, W. W.: The impact of spatial resolution, land use, and spinup time on resolving spatial precipitation patterns in the Himalayas, J. Hydrometeorol., 19, 1565–1581, 2018. a
Carroll, D. L.: Genetic algorithms and optimizing chemical oxygen-iodine lasers, Devel. Theor., 18, 411–424, 1996. a, b
Carroll, D. L.: Fortran Genetic Algorithm Front-End Driver Code, CU Aerospace [code], https://cuaerospace.com/products-services/genetic-algorithm/ga-drive-free-download, last access: 24 October 2022. a
Download
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.