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The influence of atmospheric wave dynamics on interannual variation in the surface temperature of lakes in the English Lake District

机译:大气波动力学对英国湖区湖泊地表温度年际变化的影响

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Surface water temperatures in four lakes of the English Lake District (T-L) are shown to be sensitive to climate change and a large-scale atmospheric phenomenon known as tropospheric Rossby wave breaking (RWB). RWB occurs frequently near the English Lake District, bringing warm and moist air, or cool and dry air, from distant sources. RWB case examples and composites are used to show three dimensional circulations and anomalies of near-surface temperature and humidity associated with the two types of RWB (anticyclonic and cyclonic). Statistical models of lake surface temperature are developed for each season using objectively identified variability patterns of anticyclonic and cyclonic RWB, along with an index of Northern Hemisphere annual mean surface temperature (T-NH) to account for climate change. The statistical models, depending on season, account for 54-69% of T-L variance. RWB alone contributes significantly during each season, accounting for 37-52% of T-L variance after the effect of T-NH is removed. RWB is a key physical mechanism underlying the North Atlantic Oscillation (NAO), a regional-scale weather-pattern that is frequently related to coherent lake properties. RWB may therefore be a more fundamental driver than the NAO in controlling interannual variation in the properties of lakes such as ice duration, metabolic rates, phenology, species composition and, via effects on stratification, underwater light-climate, nutrient-cycling and oxygen-depletion. Variation in other meteorological features that are linked to RWB, such as precipitation, may have additional effects. RWB is also likely to influence terrestrial and marine environments.
机译:英格兰湖区(T-L)的四个湖泊的地表水温度显示出对气候变化和被称为对流层Rossby波浪破碎(RWB)的大规模大气现象敏感。 RWB经常发生在英吉利湖区附近,从远处吸入温暖潮湿的空气,或凉爽干燥的空气。 RWB案例和复合材料用于显示三维循环以及与两种类型的RWB(反气旋和气旋)相关的近地表温度和湿度异常。利用客观确定的反气旋和旋风RWB的变化模式,以及北半球年度平均地表温度(T-NH)指数来解释气候变化,从而为每个季节开发湖面温度的统计模型。统计模型取决于季节,占T-L方差的54-69%。在每个季节,仅RWB的贡献就很大,占去除T-NH效应后T-L变化的37-52%。 RWB是北大西洋涛动(NAO)背后的关键物理机制,NAO是一种区域尺度的天气模式,经常与连贯的湖泊特性有关。因此,与NAO相比,RWB在控制湖泊特性的年际变化(例如冰期,新陈代谢率,物候,物种组成以及通过对分层,水下光气候,养分循环和氧气的影响)方面可能是更基本的驱动力。消耗。与RWB相关的其他气象特征的变化(例如降水)可能会产生其他影响。 RWB也可能会影响陆地和海洋环境。

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