Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model, link to supplementary data

A global constant value of the extinction coefficient (Kd) is usually specified in lake models to parameterize water clarity. This study aimed to improve the performance of the 1-D freshwater lake (FLake) model using satellite-derived Kd for Lake Erie. The CoastColour algorithm was applied to MERIS satellite imagery to estimate Kd. The constant (0.2/m) and satellite-derived Kd values as well as radiation fluxes and meteorological station observations were then used to run FLake for a meteorological station on Lake Erie. Results improved compared to using the constant Kd value (0.2/m). No significant improvement was found in FLake-simulated lake surface water temperature (LSWT) when Kd variations in time were considered using a monthly average. Therefore, results suggest that a time independent, lake-specific, and constant satellite-derived Kd value can reproduce LSWT with sufficient accuracy for the Lake Erie station.
A sensitivity analysis was also performed to assess the impact of various Kd values on the simulation outputs. Results show that FLake is sensitive to variations in Kd to estimate the thermal structure of Lake Erie. Dark waters result in warmer spring and colder fall temperatures compared to clear waters. Dark waters always produce colder mean water column temperature (MWCT) and lake bottom water temperature (LBWT), shallower mixed layer depth (MLD), longer ice cover duration, and thicker ice. The sensitivity of FLake to Kd variations was more pronounced in the simulation of MWCT, LBWT, and MLD. The model was particularly sensitive to Kd values below 0.5/m. This is the first study to assess the value of integrating Kd from the satellite-based CoastColour algorithm into the FLake model. Satellite-derived Kd is found to be a useful input parameter for simulations with FLake and possibly other lake models, and it has potential for applicability to other lakes where Kd is not commonly measured.

湖泊模型通常会设定一个全局通用的消光系数(Kd)常数，以参数化水体透明度。本研究旨在利用针对伊利湖(Lake Erie)的卫星反演Kd，提升一维淡水湖模型(FLake)的模拟性能。研究采用CoastColour算法处理中分辨率成像光谱仪(MERIS)卫星影像以估算Kd。随后，将0.2/m的常数Kd、卫星反演Kd值，连同辐射通量与气象站观测数据，一同驱动伊利湖(Lake Erie)某气象站点对应的FLake模拟。相较于使用0.2/m的常数Kd，模拟结果得到了显著改善。当采用月均Kd以考虑Kd的时间变化时，FLake模拟的湖表面水温(LSWT)并未出现明显提升。因此，研究结果表明，采用与时间无关、适配伊利湖(Lake Erie)的卫星反演常数Kd值，即可为该站点的LSWT模拟提供足够精确的结果。
本研究同时开展了敏感性分析，以评估不同Kd值对模拟输出的影响。结果显示，在估算伊利湖(Lake Erie)热结构时，FLake模型对Kd的变化较为敏感。相较于清澈水体，深色水体对应的春季水温更高、秋季水温更低。深色水体始终会产生更低的平均水柱水温(MWCT)与湖底水温(LBWT)、更浅的混合层深度(MLD)、更长的冰盖持续时间以及更厚的冰层。FLake对Kd变化的敏感性在MWCT、LBWT及MLD的模拟中更为显著，且当Kd值低于0.5/m时，模型敏感性尤为突出。本研究首次评估了将基于卫星的CoastColour算法反演得到的Kd集成至FLake模型的应用价值。研究发现，卫星反演Kd可作为FLake乃至其他湖模型的有效输入参数，且有望推广至Kd未被常规监测的其他湖泊。