Developing the Coupled CWRF‐FVCOM Modeling System to Understand and Predict Atmosphere‐Watershed Interactions Over the Great Lakes Region. (27th November 2020)

• Record Type: Journal Article
• Authors: Sun, Lei; Liang, Xin‐Zhong; Xia, Meng
• Is Part Of: Journal of advances in modeling earth systems. Volume 12:Number 12(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-27
• Subjects: Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2020MS002319
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: 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. Plain Language Summary: 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. We 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) and compared it with the baseline CWRF configured with 1‐D lake model to understand how 3‐D hydrodynamic processes affect the prediction of the lake and regional climate conditions. The coupled CWRF‐FVCOM system significantly improved the simulation of all the five lakes' conditions at seasonal to interannual scales and realistically reproduced the regional circulation patterns. Our analysis also explained the processes that are associated with such sensitivity. Furthermore, as a unique contribution to the literature, we constructed FVCOM to dynamically predict the water level fluctuations in direct response to the coupled CWRF NBS components and connecting channel flows based on a stage‐fall‐discharge formulation. This coupled CWRF‐FVCOM system represents a major advance in interacting regional climate and watershed processes to dynamically predict Great Lakes' water level seasonal‐interannual variations. Key Points: The coupled CWRF‐FVCOM modeling system was developed to understand and predict atmosphere‐watershed interactions over the Great Lakes Region The coupled system significantly improved the simulation of lakes conditions at seasonal to interannual scales at all five Lakes The coupled system dynamically predicted the water level fluctuations in direct response to the coupled CWRF NBS components