Abstract This work aims to assess a diagnostic approach which links evapotranspiration (ET) to land surface temperature (LST) measured by thermal remote sensing in the Alps. We estimated gridded ET, from field (30 m) to regional (1 km) scales, and we performed a specific study on grassland ecosystems in the Alps in South Tyrol (Italy), to evaluate the model sensitivity to different types of land management. The energy balance model TSEB ALEXI (Two Source Energy Balance Atmosphere Land EXchange Inverse) was first applied to Meteosat satellite data. Then ET was estimated by the flux disaggregation procedure DisALEXI, driven by MODIS and Landsat LST retrievals, which has never been applied before in a mountain region. We evaluated the model against eddy-covariance (EC) measurements from established stations in the Alps, and analyzed the main limitations which affect the model performance in mountainous regions. The TSEB model, applied in plot-scale mode using tower-based meteorological and LST input data, performed well with errors in daytime (6–18 UTC+1) latent heat flux around 30–60 W m−2 in comparison with flux measurements corrected for the lack of closure in the energy balance. For landscape ET retrievals, while Landsat resolution (30 m) is preferable for capturing small-scale heterogeneity in landscape moisture conditions, and for direct comparison with tower fluxes, persistent cloud cover resulted in no clear Landsat scenes during the study period. MODIS-based retrievals at 1 km resolution are too coarse to resolve the flux tower footprint in this complex landscape, yielding discrepancies of 100 W m−2 in model-measurement comparisons. Still, MODIS DisALEXI partitioning of the energy budget was reasonable and enabled to detect evaporative stress at regional scale expressed as the ratio between actual and potential ET, fPET. We evaluated fPET in comparison with a crop stress index based on cumulative air temperature and precipitation at different stations in the study area, and investigated ability to capture differential responses between managed and unmanaged grasslands. Results show that in the Alps i) moderate resolution thermal data can be used to monitor evaporative stress at the regional scale; ii) the spatial-temporal evolution of ET can be characterized from MODIS and Landsat thermal data with limitations which are due to the low availability of clear-sky scenes and to the small-scale (∼10 m) changes in soil moisture, topography and canopy density, which control ET patterns in mountainous regions; iii) solar radiation and leaf area index are critical variables which strongly affect the accuracy of the modeled energy fluxes.

中文翻译：

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高寒草地蒸散的双源能量平衡模型

摘要 这项工作旨在评估一种诊断方法，该方法将蒸散量 (ET) 与阿尔卑斯山热遥感测量的地表温度 (LST) 联系起来。我们估计了从田地 (30 m) 到区域 (1 km) 尺度的网格 ET，我们对南蒂罗尔（意大利）阿尔卑斯山的草地生态系统进行了一项具体研究，以评估模型对不同土地管理类型的敏感性。能量平衡模型TSEB ALEXI（双源能量平衡大气土地交换逆）首先应用于Meteosat卫星数据。然后通过通量分解程序 DisALEXI 估计 ET，该程序由 MODIS 和 Landsat LST 反演驱动，以前从未在山区应用过。我们根据来自阿尔卑斯山已建站的涡流协方差 (EC) 测量值评估了模型，并分析了影响山区模型性能的主要局限性。TSEB 模型使用基于塔的气象和 LST 输入数据以地块尺度模式应用，与通量测量相比，白天 (6-18 UTC+1) 潜热通量约 30-60 W m-2 的误差表现良好纠正了能量平衡缺乏闭合。对于景观 ET 反演，虽然 Landsat 分辨率 (30 m) 更适合捕获景观水分条件下的小尺度异质性，并且为了与塔通量直接比较，持续的云层覆盖导致研究期间没有清晰的 Landsat 场景。在 1 公里分辨率下基于 MODIS 的反演太粗糙，无法解决这个复杂景观中的通量塔足迹，在模型测量比较中产生 100 W m-2 的差异。仍然，MODIS DisALEXI 对能量预算的划分是合理的，并且能够检测区域尺度的蒸发应力，表示为实际和潜在 ET、fPET 之间的比率。我们根据研究区域不同站点的累积气温和降水，将 fPET 与作物胁迫指数进行比较，并研究了捕捉管理和未管理草地之间差异响应的能力。结果表明，在阿尔卑斯山 i) 中等分辨率的热数据可用于监测区域尺度的蒸发应力；ii) ET 的时空演化可以从 MODIS 和 Landsat 热数据中表征，其局限性是由于晴空场景的可用性低以及土壤水分、地形和冠层密度，控制山区的ET模式；iii) 太阳辐射和叶面积指数是严重影响模拟能量通量准确性的关键变量。