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首页> 外文期刊>Journal of Climate >Improving climate sensitivity of deep lakes within a regional climate model and its impact on simulated climate.
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Improving climate sensitivity of deep lakes within a regional climate model and its impact on simulated climate.

机译:在区域气候模型内提高深湖的气候敏感性及其对模拟气候的影响。

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摘要

Regional climate models aim to improve local climate simulations by resolving topography, vegetation, and land use at a finer resolution than global climate models. Lakes, particularly large and deep lakes, are local features that significantly alter regional climate. The Hostetler lake model, a version of which is currently used in the Community Land Model, performs poorly in deep lakes when coupled to the regional climate of the International Centre for Theoretical Physics (ICTP) Regional Climate Model, version 4 (RegCM4). Within the default RegCM4 model, the lake fails to properly stratify, stifling the model's ability to capture interannual variability in lake temperature and ice cover. Here, the authors improve modeled lake stratification and eddy diffusivity while correcting errors in the ice model. The resulting simulated lake shows improved stratification and interannual variability in lake ice and temperature. The lack of circulation and explicit mixing continues to stifle the model's ability to simulate lake mixing events and variability in timing of stratification and destratification. The changes to modeled lake conditions alter seasonal means in sea level pressure, temperature, and low-level winds in the entire model domain, highlighting the importance of lake model selection and improvement for coupled simulations. Interestingly, changes to winter and spring snow cover and albedo impact spring warming. Unsurprisingly, regional climate variability is not significantly altered by an increase in lake temperature variability.
机译:区域气候模型旨在通过比全球气候模型更精细的分辨率解决地形,植被和土地利用,从而改善当地的气候模拟。湖泊,特别是大而深的湖泊,是局部特征,会大大改变区域气候。 Hostetler湖模型(目前在社区土地模型中使用)的一个版本在深湖中表现不佳,再加上国际理论物理中心(ICTP)第4版(RegCM4)的区域气候。在默认的RegCM4模型中,湖泊无法正确分层,从而扼杀了该模型捕获湖泊温度和冰盖的年际变化的能力。在这里,作者在纠正冰模型误差的同时,改善了建模的湖泊分层和涡流扩散率。生成的模拟湖泊在湖冰和温度方面显示出改善的分层和年际变化。缺乏环流和明确的混合继续扼杀了该模型模拟湖泊混合事件和分层和脱层时间变化的能力。建模的湖泊条件的变化改变了整个模型域中海平面压力,温度和低层风的季节性平均值,突出了湖泊模型选择和改进耦合模拟的重要性。有趣的是,冬季和春季积雪和反照率的变化会影响春季变暖。毫不奇怪,湖泊温度变异性不会明显改变区域气候变异性。

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