Articles | Volume 7, issue 5
https://doi.org/10.5194/gmd-7-2517-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-2517-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
29 Oct 2014
Development and technical paper |
| 29 Oct 2014
Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm
S. Hong
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Korea
now at: Department of Climate & Ecology, National Institute of Ecology, Seocheon, Korea
X. Yu
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Korea
now at: Tropical Marine Science Institute, National University of Singapore, Singapore
S. K. Park
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Korea
Severe Storm Research Center, Ewha Womans University, Seoul, Korea
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Korea
Department of Atmospheric Science and Engineering, Ewha Womans University, Seoul, Korea
Y.-S. Choi
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Korea
Severe Storm Research Center, Ewha Womans University, Seoul, Korea
Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Korea
Department of Atmospheric Science and Engineering, Ewha Womans University, Seoul, Korea
B. Myoung
Center for Climate/Environment Change Prediction Research, Ewha Womans University, Seoul, Korea
now at: Center for Excellence in Earth Systems Modeling & Observations, Chapman University, California, USA
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25 citations as recorded by crossref.
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- Assessing snow simulation performance of typical combination schemes within Noah-MP in northern Xinjiang, China Y. You et al. 10.1016/j.jhydrol.2019.124380
- Scheme-Based Optimization of Land Surface Model Using a Micro-Genetic Algorithm: Assessment of Its Performance and Usability for Regional Applications S. Hong et al. 10.2151/sola.2015-030
- Assessing the simulated soil hydrothermal regime of the active layer from the Noah-MP land surface model (v1.1) in the permafrost regions of the Qinghai–Tibet Plateau X. Li et al. 10.5194/gmd-14-1753-2021
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- Evaluation of Noah-MP Land-Model Uncertainties over Sparsely Vegetated Sites on the Tibet Plateau G. Zhang et al. 10.3390/atmos11050458
- An optimal ensemble of the Noah-MP land surface model for simulating surface heat fluxes over a typical subtropical forest in South China M. Chang et al. 10.1016/j.agrformet.2019.107815
- Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes J. Li et al. 10.1029/2021JD035753
- Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a) S. Lim et al. 10.5194/gmd-15-8541-2022
- Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy C. Cassardo et al. 10.3390/w10070954
- Improving the Asian dust storm prediction using WRF-Chem through combinational optimization of physical parameterization schemes J. Yoon et al. 10.1016/j.atmosenv.2024.120461
- Comparative analysis of the meteorological elements simulated by different land surface process schemes in the WRF model in the Yellow River source region Y. Zhang et al. 10.1007/s00704-019-02955-0
- Comparison of the Forecast Performance of WRF Using Noah and Noah-MP Land Surface Schemes in Central Asia Arid Region C. Ju et al. 10.3390/atmos13060927
- Sensitivity Analysis of the Noah‐MP Land Surface Model for Soil Hydrothermal Simulations Over the Tibetan Plateau W. Hu et al. 10.1029/2022MS003136
- Assessment and Reduction of the Physical Parameterization Uncertainty for Noah‐MP Land Surface Model Y. Gan et al. 10.1029/2019WR024814
- Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy C. Cassardo et al. 10.5194/hess-22-3331-2018
- A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea S. Park & S. Park 10.5194/gmd-14-6241-2021
- Implementation and Evaluation of a Unified Turbulence Parameterization Throughout the Canopy and Roughness Sublayer in Noah‐MP Snow Simulations R. Abolafia‐Rosenzweig et al. 10.1029/2021MS002665
- Quantifying Contributions of Uncertainties in Physical Parameterization Schemes and Model Parameters to Overall Errors in Noah‐MP Dynamic Vegetation Modeling J. Li et al. 10.1029/2019MS001914
- Soil temperature response in Korea to a changing climate using a land surface model S. Park et al. 10.1007/s13143-017-0048-x
- Assessing uncertainties in the Noah‐MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign G. Zhang et al. 10.1002/2016JD024928
- Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm J. Yoon et al. 10.3390/app112311221
- Assessment and improvement of Noah-MP for simulating water and heat exchange over alpine grassland in growing season S. Sun et al. 10.1007/s11430-021-9852-2
- An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah‐MP H. Gim et al. 10.1002/2016MS000890
- Evaluation of Land Surface Subprocesses and Their Impacts on Model Performance With Global Flux Data J. Li et al. 10.1029/2018MS001606
24 citations as recorded by crossref.
- Estimation of water balance components by Noah-MP land surface model for the Neyshaboor watershed, Khorasan Razavi, Iran S. Mirshafee et al. 10.1007/s13201-023-02076-0
- Assessing snow simulation performance of typical combination schemes within Noah-MP in northern Xinjiang, China Y. You et al. 10.1016/j.jhydrol.2019.124380
- Scheme-Based Optimization of Land Surface Model Using a Micro-Genetic Algorithm: Assessment of Its Performance and Usability for Regional Applications S. Hong et al. 10.2151/sola.2015-030
- Assessing the simulated soil hydrothermal regime of the active layer from the Noah-MP land surface model (v1.1) in the permafrost regions of the Qinghai–Tibet Plateau X. Li et al. 10.5194/gmd-14-1753-2021
- SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model G. Grelle et al. 10.5194/gmd-9-1567-2016
- Evaluation of Noah-MP Land-Model Uncertainties over Sparsely Vegetated Sites on the Tibet Plateau G. Zhang et al. 10.3390/atmos11050458
- An optimal ensemble of the Noah-MP land surface model for simulating surface heat fluxes over a typical subtropical forest in South China M. Chang et al. 10.1016/j.agrformet.2019.107815
- Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes J. Li et al. 10.1029/2021JD035753
- Optimization of snow-related parameters in the Noah land surface model (v3.4.1) using a micro-genetic algorithm (v1.7a) S. Lim et al. 10.5194/gmd-15-8541-2022
- Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy C. Cassardo et al. 10.3390/w10070954
- Improving the Asian dust storm prediction using WRF-Chem through combinational optimization of physical parameterization schemes J. Yoon et al. 10.1016/j.atmosenv.2024.120461
- Comparative analysis of the meteorological elements simulated by different land surface process schemes in the WRF model in the Yellow River source region Y. Zhang et al. 10.1007/s00704-019-02955-0
- Comparison of the Forecast Performance of WRF Using Noah and Noah-MP Land Surface Schemes in Central Asia Arid Region C. Ju et al. 10.3390/atmos13060927
- Sensitivity Analysis of the Noah‐MP Land Surface Model for Soil Hydrothermal Simulations Over the Tibetan Plateau W. Hu et al. 10.1029/2022MS003136
- Assessment and Reduction of the Physical Parameterization Uncertainty for Noah‐MP Land Surface Model Y. Gan et al. 10.1029/2019WR024814
- Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy C. Cassardo et al. 10.5194/hess-22-3331-2018
- A micro-genetic algorithm (GA v1.7.1a) for combinatorial optimization of physics parameterizations in the Weather Research and Forecasting model (v4.0.3) for quantitative precipitation forecast in Korea S. Park & S. Park 10.5194/gmd-14-6241-2021
- Implementation and Evaluation of a Unified Turbulence Parameterization Throughout the Canopy and Roughness Sublayer in Noah‐MP Snow Simulations R. Abolafia‐Rosenzweig et al. 10.1029/2021MS002665
- Quantifying Contributions of Uncertainties in Physical Parameterization Schemes and Model Parameters to Overall Errors in Noah‐MP Dynamic Vegetation Modeling J. Li et al. 10.1029/2019MS001914
- Soil temperature response in Korea to a changing climate using a land surface model S. Park et al. 10.1007/s13143-017-0048-x
- Assessing uncertainties in the Noah‐MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign G. Zhang et al. 10.1002/2016JD024928
- Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm J. Yoon et al. 10.3390/app112311221
- Assessment and improvement of Noah-MP for simulating water and heat exchange over alpine grassland in growing season S. Sun et al. 10.1007/s11430-021-9852-2
- An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah‐MP H. Gim et al. 10.1002/2016MS000890
1 citations as recorded by crossref.
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