Articles | Volume 9, issue 3
https://doi.org/10.5194/gmd-9-1073-2016
© Author(s) 2016. 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-9-1073-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
17 Mar 2016
Development and technical paper |
| 17 Mar 2016
Parameterization of the snow-covered surface albedo in the Noah-MP Version 1.0 by implementing vegetation effects
Sojung Park
Department of Atmospheric Science and Engineering,
Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction
Research, Ewha Womans University, Seoul, Republic of Korea
Severe Storm Research Center, Ewha Womans
University, Seoul, Republic of Korea
Department of Atmospheric Science and Engineering,
Ewha Womans University, Seoul, Republic of Korea
Department of Environmental Science and Engineering,
Ewha Womans University, Seoul, Republic of Korea
Center for Climate/Environment Change Prediction
Research, Ewha Womans University, Seoul, Republic of Korea
Severe Storm Research Center, Ewha Womans
University, Seoul, Republic of Korea
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Cited
25 citations as recorded by crossref.
- Improving snow albedo parameterization scheme based on remote sensing data H. Li et al. 10.1016/j.atmosres.2022.106602
- Surface albedo and reflectance: Review of definitions, angular and spectral effects, and intercomparison of major data sources in support of advanced solar irradiance modeling over the Americas C. Gueymard et al. 10.1016/j.solener.2019.02.040
- A review of machine learning models and influential factors for estimating evapotranspiration using remote sensing and ground-based data S. Amani & H. Shafizadeh-Moghadam 10.1016/j.agwat.2023.108324
- Sensitivity analysis of snow depth and surface air temperature to various WRF/Noah-MP model configurations in Central Europe Á. Varga & H. Breuer 10.1016/j.atmosres.2024.107659
- Optimization of snow-related processes in Noah-MP land surface model over the mid-latitudes of Asian region X. Cao et al. 10.1016/j.atmosres.2024.107711
- Assessing Noah‐MP Parameterization Sensitivity and Uncertainty Interval Across Snow Climates Y. You et al. 10.1029/2019JD030417
- 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
- Improved Parameterization of Snow Albedo in WRF + Noah: Methodology Based on a Severe Snow Event on the Tibetan Plateau L. Liu et al. 10.1007/s00376-022-1232-1
- Quantitative assessment of the parameterization sensitivity of the WRF/Noah-MP model of snow dynamics in the Tianshan Mountains, Central Asia Q. Li et al. 10.1016/j.atmosres.2022.106310
- Toward Optimization of Key Parameters in Noah-MP Surface Albedo Using Satellite Remote Sensing Products J. CHEN et al. 10.11728/cjss2023.06.2023-0086
- Soil temperature response in Korea to a changing climate using a land surface model S. Park et al. 10.1007/s13143-017-0048-x
- On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy C. Cassardo & V. Andreoli 10.3390/app9183880
- Evaluation of snow depth and snow cover represented by multiple datasets over the Tianshan Mountains: Remote sensing, reanalysis, and simulation Q. Li et al. 10.1002/joc.7459
- 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
- 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
- Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing I. Vorobevskii et al. 10.5194/hess-26-3177-2022
- Assessment of Soil Moisture‐Temperature Feedbacks With the CCSM‐WRF Model System Over East Asia K. Li et al. 10.1029/2017JD028202
- Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEPCFSv2 S. Saha et al. 10.1002/2016MS000845
- Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy C. Cassardo et al. 10.3390/w10070954
- Implementation of snow albedo schemes of varying complexity and their performances in offline Noah and Noah coupled with NCEP CFSv2 A. Rai et al. 10.1007/s00382-019-04632-4
- Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau L. Liu et al. 10.5194/hess-25-4967-2021
- Impact of forcing data and land surface properties on snow simulation in a regional climate model: a case study over the Tianshan Mountains, Central Asia Q. Li et al. 10.1007/s11629-020-6621-2
- 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
- Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review W. Lee et al. 10.1007/s13143-023-00344-2
25 citations as recorded by crossref.
- Improving snow albedo parameterization scheme based on remote sensing data H. Li et al. 10.1016/j.atmosres.2022.106602
- Surface albedo and reflectance: Review of definitions, angular and spectral effects, and intercomparison of major data sources in support of advanced solar irradiance modeling over the Americas C. Gueymard et al. 10.1016/j.solener.2019.02.040
- A review of machine learning models and influential factors for estimating evapotranspiration using remote sensing and ground-based data S. Amani & H. Shafizadeh-Moghadam 10.1016/j.agwat.2023.108324
- Sensitivity analysis of snow depth and surface air temperature to various WRF/Noah-MP model configurations in Central Europe Á. Varga & H. Breuer 10.1016/j.atmosres.2024.107659
- Optimization of snow-related processes in Noah-MP land surface model over the mid-latitudes of Asian region X. Cao et al. 10.1016/j.atmosres.2024.107711
- Assessing Noah‐MP Parameterization Sensitivity and Uncertainty Interval Across Snow Climates Y. You et al. 10.1029/2019JD030417
- 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
- Improved Parameterization of Snow Albedo in WRF + Noah: Methodology Based on a Severe Snow Event on the Tibetan Plateau L. Liu et al. 10.1007/s00376-022-1232-1
- Quantitative assessment of the parameterization sensitivity of the WRF/Noah-MP model of snow dynamics in the Tianshan Mountains, Central Asia Q. Li et al. 10.1016/j.atmosres.2022.106310
- Toward Optimization of Key Parameters in Noah-MP Surface Albedo Using Satellite Remote Sensing Products J. CHEN et al. 10.11728/cjss2023.06.2023-0086
- Soil temperature response in Korea to a changing climate using a land surface model S. Park et al. 10.1007/s13143-017-0048-x
- On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy C. Cassardo & V. Andreoli 10.3390/app9183880
- Evaluation of snow depth and snow cover represented by multiple datasets over the Tianshan Mountains: Remote sensing, reanalysis, and simulation Q. Li et al. 10.1002/joc.7459
- 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
- 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
- Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing I. Vorobevskii et al. 10.5194/hess-26-3177-2022
- Assessment of Soil Moisture‐Temperature Feedbacks With the CCSM‐WRF Model System Over East Asia K. Li et al. 10.1029/2017JD028202
- Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEPCFSv2 S. Saha et al. 10.1002/2016MS000845
- Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy C. Cassardo et al. 10.3390/w10070954
- Implementation of snow albedo schemes of varying complexity and their performances in offline Noah and Noah coupled with NCEP CFSv2 A. Rai et al. 10.1007/s00382-019-04632-4
- Improved parameterization of snow albedo in Noah coupled with Weather Research and Forecasting: applicability to snow estimates for the Tibetan Plateau L. Liu et al. 10.5194/hess-25-4967-2021
- Impact of forcing data and land surface properties on snow simulation in a regional climate model: a case study over the Tianshan Mountains, Central Asia Q. Li et al. 10.1007/s11629-020-6621-2
- 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
- Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review W. Lee et al. 10.1007/s13143-023-00344-2
Saved (final revised paper)
Latest update: 23 Nov 2024
Short summary
Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the spatial characteristics of land cover and on the canopy density and structure. The Noah-MP model shows a bias error of albedo in winter due to no proper reflection of the vegetation effect. We developed new parameters, called leaf index and stem index, which reflect the vegetation effect on winter albedo. The Noah-MP's performance in albedo has prominently improved with about 69 % decrease in the RMSE.
Snow albedo varies with snow grain size, snow cover thickness, etc. It also depends on the...
