IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p11284-d1198036.html
   My bibliography  Save this article

The Evaluation of Snow Depth Simulated by Different Land Surface Models in China Based on Station Observations

Author

Listed:
  • Shuai Sun

    (Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
    National Meteorological Information Center, Beijing 100081, China)

  • Chunxiang Shi

    (National Meteorological Information Center, Beijing 100081, China)

  • Xiao Liang

    (National Meteorological Information Center, Beijing 100081, China)

  • Shuai Zhang

    (Institute of Urban Meteorology of Beijing, Beijing 100089, China)

  • Junxia Gu

    (National Meteorological Information Center, Beijing 100081, China)

  • Shuai Han

    (National Meteorological Information Center, Beijing 100081, China)

  • Hui Jiang

    (National Meteorological Information Center, Beijing 100081, China)

  • Bin Xu

    (National Meteorological Information Center, Beijing 100081, China)

  • Qingbo Yu

    (Meteorological Information and Network Center of Jilin Province, Changchun 130062, China)

  • Yujing Liang

    (National Meteorological Information Center, Beijing 100081, China)

  • Shuai Deng

    (National Meteorological Information Center, Beijing 100081, China)

Abstract

Snow plays an important role in catastrophic weather, climate change, and water recycling. In order to analyze the ability of different land surface models to simulate snow depth in China, we used atmospheric forcing data from the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) to drive the CLM3.5 (the Community Land Model version 3.5), Noah (NCEP, OSU, Air Force and Office of Hydrology Land Surface Model), and Noah-MP (the community Noah land surface model with multi-parameterization options) land surface models. We also used 2380 daily snow-depth site observations of CMA to analyze the simulation effects of different models on the snow depth in China and different regions during the periods of snow accumulation and snowmelt from 2015 to 2019. The results show that CLM3.5, Noah, and Noah-MP can simulate the spatial distribution of the snow depth in China, but there are some differences between the models. In particular, the snow depth and snow cover simulated by CLM3.5 are lower than those simulated by Noah and Noah-MP in Northwest China and the Tibetan Plateau. From the overall quantitative assessment results for China, the snow depth simulated by CLM3.5 is underestimated, while that simulated by Noah is overestimated. Noah-MP has the best overall performance; for example, the biases of the three models during the snow-accumulation periods are −0.22 cm, 0.27 cm, and 0.15 cm, respectively. Furthermore, the three models perform differently in the three snowpack regions of Northeast China, Northwest China, and the Tibetan Plateau; Noah-MP has the best snow-depth performance in Northeast China, while CLM3.5 has the best snow-depth performance in the Tibetan Plateau region. Noah-MP performs best in the snow-accumulation period, and Noah performs best in the snowmelt period for Northwest China. In conclusion, no single model can perform optimally for snow simulations in different regions of China and at different times of the year, and the multi-model integration of snow may be an effective way to obtain high-quality snow simulation results. So this study provides some scientific references for the spatiotemporal evolution of snow in the context of climate change, monitoring and analysis of snow, the study of land surface models for snow, and the sustainable development and utilization of snow resources in China and other regions.

Suggested Citation

  • Shuai Sun & Chunxiang Shi & Xiao Liang & Shuai Zhang & Junxia Gu & Shuai Han & Hui Jiang & Bin Xu & Qingbo Yu & Yujing Liang & Shuai Deng, 2023. "The Evaluation of Snow Depth Simulated by Different Land Surface Models in China Based on Station Observations," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11284-:d:1198036
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/11284/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/11284/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gina R. Henderson & Yannick Peings & Jason C. Furtado & Paul J. Kushner, 2018. "Snow–atmosphere coupling in the Northern Hemisphere," Nature Climate Change, Nature, vol. 8(11), pages 954-963, November.
    2. Kurt Christian Kersebaum, 2022. "Frost risk by dwindling snow cover," Nature Climate Change, Nature, vol. 12(5), pages 421-423, May.
    3. T. P. Barnett & J. C. Adam & D. P. Lettenmaier, 2005. "Potential impacts of a warming climate on water availability in snow-dominated regions," Nature, Nature, vol. 438(7066), pages 303-309, November.
    4. Gang Deng & Zhiguang Tang & Guojie Hu & Jingwen Wang & Guoqing Sang & Jia Li, 2021. "Spatiotemporal Dynamics of Snowline Altitude and Their Responses to Climate Change in the Tienshan Mountains, Central Asia, during 2001–2019," Sustainability, MDPI, vol. 13(7), pages 1-21, April.
    5. Keith N. Musselman & Nans Addor & Julie A. Vano & Noah P. Molotch, 2021. "Winter melt trends portend widespread declines in snow water resources," Nature Climate Change, Nature, vol. 11(5), pages 418-424, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dalei Hao & Gautam Bisht & Hailong Wang & Donghui Xu & Huilin Huang & Yun Qian & L. Ruby Leung, 2023. "A cleaner snow future mitigates Northern Hemisphere snowpack loss from warming," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Urszula Somorowska, 2023. "Warming Air Temperature Impacts Snowfall Patterns and Increases Cold-Season Baseflow in the Liwiec River Basin (Poland) of the Central European Lowland," Resources, MDPI, vol. 12(2), pages 1-18, January.
    3. Molini, A. & Talkner, P. & Katul, G.G. & Porporato, A., 2011. "First passage time statistics of Brownian motion with purely time dependent drift and diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 1841-1852.
    4. Xiuchen Wu & Hongyan Liu & Dali Guo & Oleg A Anenkhonov & Natalya K Badmaeva & Denis V Sandanov, 2012. "Growth Decline Linked to Warming-Induced Water Limitation in Hemi-Boreal Forests," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-12, August.
    5. Hengzhou Xu & Chuanrong Zhang & Weidong Li & Wenjing Zhang & Hongchun Yin, 2018. "Economic growth and carbon emission in China:a spatial econometric Kuznets curve?," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(1), pages 11-28.
    6. S . K. Oni & F. Mieres & M. N. Futter & H. Laudon, 2017. "Soil temperature responses to climate change along a gradient of upland–riparian transect in boreal forest," Climatic Change, Springer, vol. 143(1), pages 27-41, July.
    7. Diana R. Gergel & Bart Nijssen & John T. Abatzoglou & Dennis P. Lettenmaier & Matt R. Stumbaugh, 2017. "Effects of climate change on snowpack and fire potential in the western USA," Climatic Change, Springer, vol. 141(2), pages 287-299, March.
    8. Alvaro Calzadilla & Katrin Rehdanz & Richard Betts & Pete Falloon & Andy Wiltshire & Richard Tol, 2013. "Climate change impacts on global agriculture," Climatic Change, Springer, vol. 120(1), pages 357-374, September.
    9. Potter, Nicholas A. & Hrozencik, R. Aaron & Wallander, Steven, 2023. "Irrigation Organizations: Water Inflows and Outflows," Economic Brief 338976, United States Department of Agriculture, Economic Research Service.
    10. Leiwen Jiang & Karen Hardee, 2011. "How do Recent Population Trends Matter to Climate Change?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(2), pages 287-312, April.
    11. Schaefli, Bettina & Manso, Pedro & Fischer, Mauro & Huss, Matthias & Farinotti, Daniel, 2017. "The role of glacier retreat for Swiss hydropower production," Earth Arxiv 7z96d, Center for Open Science.
    12. Haiyan Fang & Zemeng Fan, 2021. "Impacts of climate and land use changes on water and sediment yields for the black soil region, northeastern China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 6259-6278, April.
    13. Hanjra, Munir A. & Qureshi, M. Ejaz, 2010. "Global water crisis and future food security in an era of climate change," Food Policy, Elsevier, vol. 35(5), pages 365-377, October.
    14. Chen, Zi-yue & Huang, Zhen-hai & Nie, Pu-yan, 2018. "Industrial characteristics and consumption efficiency from a nexus perspective – Based on Anhui’s Empirical Statistics," Energy Policy, Elsevier, vol. 115(C), pages 281-290.
    15. R. R. McCrary & L. O. Mearns & M. R. Abel & S. Biner & M. S. Bukovsky, 2022. "Projections of North American snow from NA-CORDEX and their uncertainties, with a focus on model resolution," Climatic Change, Springer, vol. 170(3), pages 1-25, February.
    16. Donna, Javier & Espin-Sanchez, Jose, 2014. "The Illiquidity of Water Markets," MPRA Paper 55078, University Library of Munich, Germany.
    17. Xiaofeng Ren & Erwen Xu & C. Ken Smith & Michael Vrahnakis & Wenmao Jing & Weijun Zhao & Rongxin Wang & Xin Jia & Chunming Yan & Ruiming Liu, 2024. "Changes in Surface Runoff and Temporal Dispersion in a Restored Montane Watershed on the Qinghai–Tibetan Plateau," Land, MDPI, vol. 13(5), pages 1-22, April.
    18. Donna, Javier D. & Espin-Sanchez, Jose, 2018. "Are Water Markets Liquid? Evidence from Southeastern Spain," MPRA Paper 117032, University Library of Munich, Germany.
    19. Wu, Hao & Xu, Min & Peng, Zhuoyue & Chen, Xiaoping, 2022. "Quantifying the potential impacts of meltwater on cotton yields in the Tarim River Basin, Central Asia," Agricultural Water Management, Elsevier, vol. 269(C).
    20. Shakil Ahmad Romshoo & Jasia Bashir & Irfan Rashid, 2020. "Twenty-first century-end climate scenario of Jammu and Kashmir Himalaya, India, using ensemble climate models," Climatic Change, Springer, vol. 162(3), pages 1473-1491, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11284-:d:1198036. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.