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
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024,https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Assessment of object-based indices to identify convective organization
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024,https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
The Global Forest Fire Emissions Prediction System version 1.0
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024,https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024,https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
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

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.