Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model
As one of the most sensitive natural elements in response to climate change， snow cover has a significant effect on the Earth's surface radiation balance and water cycle.The global snow cover area is approximately 46×106 km2 and 98% of the snow cover distributed in the Northern Hemisphere.Due t...
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Science Press, PR China
2024-12-01
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| author | Xulei WANG Hui SUN Hui GUO Chula SA Fanhao MENG Min LUO |
| author_facet | Xulei WANG Hui SUN Hui GUO Chula SA Fanhao MENG Min LUO |
| author_sort | Xulei WANG |
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| description | As one of the most sensitive natural elements in response to climate change， snow cover has a significant effect on the Earth's surface radiation balance and water cycle.The global snow cover area is approximately 46×106 km2 and 98% of the snow cover distributed in the Northern Hemisphere.Due to its distinctive radiative properties （high surface albedo） and thermal characteristics （low thermal conductivity）， changes in snow cover play a crucial role in the energy balance and water cycle between land and the atmosphere.In the context of global warming， the snow cover in the Northern Hemisphere has been decreasing in recent decades， especially in the spring.Therefore， the capabilities of CMIP6 （Coupled Model Intercomparison Project Phase 6） data to simulate the snow cover area were evaluated based on observational data and the future changes in snow cover were also assessed using a multi-model average in this study.By using the snow cover products from the National Oceanic and Atmospheric Administration/National Climatic Data Center （NOAA/NCDC） as reference data， the Taylor skill scoring， relative deviation， and other methods were applied to evaluate the spring snow cover （SCF） data in the Northern Hemisphere from the International Coupled Model Comparison Project Phase 6 （CMIP6） during 1982 -2014.The ensemble average of the top three models was further selected to predict the spatiotemporal variation characteristics of SCF under different emission scenarios from 2015 to 2099， providing insights into the modeling capabilities of CMIP6 and future changes in SCF.During the historical period （1982 -2014）， SCF was characterized by high coverage at high latitudes and low coverage at low latitudes， with high-altitude regions such as Tibetan Plateau and eastern Asia having higher snow coverage than those at the same latitudes.Overall， 68.37% of the regions in the Northern Hemisphere showed a decreasing trend in SCF， while 31.63% of the regions showed an increasing trend in SCF.Most CMIP6 models overestimated SCF in the Tibetan Plateau region compared to the reference data.In addition， most models simulated larger areas with a decreasing trend in SCF than those evaluated by the reference data and underestimated SCF in March， April， and May.Various models exhibited differing abilities to simulate SCF， with NorESM2-MM， CESM2， BBC-CSM2-MR， NorESM2-LM， and CESM2-WACCM demonstrating superior capabilities.The Multi-Model Ensemble Mean （MME） consistently outperformed individual models， closely aligning with observational data.There were significant differences in the ability of the CMIP6 models to simulate the spatial distribution， inter-annual variation trends， and intra-annual variations of SCF in the Northern Hemisphere.At the end of the 21st-century （2067 -2099）， SCF in the Northern Hemisphere exhibited a decreasing trend in most areas， which intensifies with increasing emission intensity.The changes in SCF were relatively consistent under different emission scenarios before 2040.SCF maintains a steady state under the SSP1-2.6 scenario， showed a slight decreasing trend under the SSP2-4.5 scenario， and showed a significant decreasing trend under the SSP5-8.5 scenario after 2040. |
| format | Article |
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| spelling | doaj-art-fd70ef398f7a4481b9e90e2e17c011512025-08-20T02:00:13ZzhoScience Press, PR ChinaGaoyuan qixiang1000-05342024-12-014361397141510.7522/j.issn.1000-0534.2024.000291000-0534（2024）06-1397-19Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 ModelXulei WANG0Hui SUN1Hui GUO2Chula SA3Fanhao MENG4Min LUO5College of Geographical Science， Inner Mongolia Normal University， Hohhot 010022， Inner Mongolia， ChinaCollege of Geographical Science， Inner Mongolia Normal University， Hohhot 010022， Inner Mongolia， ChinaState Key Laboratory of Hydroscience and Engineering， Department of Hydraulic Engineering， Tsinghua University， Beijing 100084， ChinaCollege of Geographical Science， Inner Mongolia Normal University， Hohhot 010022， Inner Mongolia， ChinaCollege of Geographical Science， Inner Mongolia Normal University， Hohhot 010022， Inner Mongolia， ChinaCollege of Geographical Science， Inner Mongolia Normal University， Hohhot 010022， Inner Mongolia， ChinaAs one of the most sensitive natural elements in response to climate change， snow cover has a significant effect on the Earth's surface radiation balance and water cycle.The global snow cover area is approximately 46×106 km2 and 98% of the snow cover distributed in the Northern Hemisphere.Due to its distinctive radiative properties （high surface albedo） and thermal characteristics （low thermal conductivity）， changes in snow cover play a crucial role in the energy balance and water cycle between land and the atmosphere.In the context of global warming， the snow cover in the Northern Hemisphere has been decreasing in recent decades， especially in the spring.Therefore， the capabilities of CMIP6 （Coupled Model Intercomparison Project Phase 6） data to simulate the snow cover area were evaluated based on observational data and the future changes in snow cover were also assessed using a multi-model average in this study.By using the snow cover products from the National Oceanic and Atmospheric Administration/National Climatic Data Center （NOAA/NCDC） as reference data， the Taylor skill scoring， relative deviation， and other methods were applied to evaluate the spring snow cover （SCF） data in the Northern Hemisphere from the International Coupled Model Comparison Project Phase 6 （CMIP6） during 1982 -2014.The ensemble average of the top three models was further selected to predict the spatiotemporal variation characteristics of SCF under different emission scenarios from 2015 to 2099， providing insights into the modeling capabilities of CMIP6 and future changes in SCF.During the historical period （1982 -2014）， SCF was characterized by high coverage at high latitudes and low coverage at low latitudes， with high-altitude regions such as Tibetan Plateau and eastern Asia having higher snow coverage than those at the same latitudes.Overall， 68.37% of the regions in the Northern Hemisphere showed a decreasing trend in SCF， while 31.63% of the regions showed an increasing trend in SCF.Most CMIP6 models overestimated SCF in the Tibetan Plateau region compared to the reference data.In addition， most models simulated larger areas with a decreasing trend in SCF than those evaluated by the reference data and underestimated SCF in March， April， and May.Various models exhibited differing abilities to simulate SCF， with NorESM2-MM， CESM2， BBC-CSM2-MR， NorESM2-LM， and CESM2-WACCM demonstrating superior capabilities.The Multi-Model Ensemble Mean （MME） consistently outperformed individual models， closely aligning with observational data.There were significant differences in the ability of the CMIP6 models to simulate the spatial distribution， inter-annual variation trends， and intra-annual variations of SCF in the Northern Hemisphere.At the end of the 21st-century （2067 -2099）， SCF in the Northern Hemisphere exhibited a decreasing trend in most areas， which intensifies with increasing emission intensity.The changes in SCF were relatively consistent under different emission scenarios before 2040.SCF maintains a steady state under the SSP1-2.6 scenario， showed a slight decreasing trend under the SSP2-4.5 scenario， and showed a significant decreasing trend under the SSP5-8.5 scenario after 2040.http://www.gyqx.ac.cn/EN/10.7522/j.issn.1000-0534.2024.00029snow cover fractionnorthern hemispherecmip6assessmentprediction |
| spellingShingle | Xulei WANG Hui SUN Hui GUO Chula SA Fanhao MENG Min LUO Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model Gaoyuan qixiang snow cover fraction northern hemisphere cmip6 assessment prediction |
| title | Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model |
| title_full | Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model |
| title_fullStr | Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model |
| title_full_unstemmed | Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model |
| title_short | Simulation and Prediction of Spring Snow Cover in Northern Hemisphere by CMIP6 Model |
| title_sort | simulation and prediction of spring snow cover in northern hemisphere by cmip6 model |
| topic | snow cover fraction northern hemisphere cmip6 assessment prediction |
| url | http://www.gyqx.ac.cn/EN/10.7522/j.issn.1000-0534.2024.00029 |
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