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标题：Developing the Coupled CWRF‐FVCOM Modeling System to Understand and Predict Atmosphere‐Watershed Interactions Over the Great Lakes Region
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作者：Lei Sun ; Xin‐Zhong Liang ; Meng Xia 等
期刊名称：Journal of Advances in Modeling Earth Systems
电子版ISSN：1942-2466
出版年度：2020
卷号：12
期号：12
页码：307-323
DOI：10.1029/2020MS002319
出版社：John Wiley & Sons, Ltd.
摘要：Coupling 3‐D hydrodynamics with climate models is necessary but difficult for resolving multiscale interactions and has been rarely implemented in predicting Great Lakes' water level fluctuations because of issues in treating net basin supply (NBS) components and connecting channel flows. This study developed an interactive lake‐atmosphere‐hydrology modeling system by coupling the regional Climate‐Weather Research and Forecasting model (CWRF) with the 3‐D unstructured‐grid Finite Volume Coastal Ocean Model (FVCOM) in the Great Lakes region. The sensitivity of the coupled system, relative to the CWRF baseline using the 1‐D Lake, Ice, Snow and Sediment Simulator (LISSS), was evaluated in representing lake‐climate conditions during 1999–2015 against observations. As coupled with CWRF, FVCOM outperformed LISSS in simulating water surface temperature, ice cover, and vertical thermal structure at seasonal to interannual scales for all the five lakes and realistically reproduced the regional circulation patterns. In warm seasons, the improved lake conditions significantly corrected LISSS overestimates of surface air temperature together with larger‐scale circulation changes. Consequently, precipitation was generally reduced over each lake basin, mainly because of decreased surface moisture and heat fluxes along with enhanced atmospheric stability. Through the dynamic coupling, FVCOM predicts the water level fluctuations in direct response to the CWRF NBS components and connecting channel flows based on a stage‐fall‐discharge formulation. This coupled CWRF‐FVCOM reasonably captured the NBS variations and predicted the water level fluctuations for Lakes Superior and Michigan‐Huron. It represents a major advance in interacting regional climate and watershed processes to dynamically predict Great Lakes' water level seasonal‐interannual variations.