Fog plays a critical role in tropical montane and premontane forests, influencing tree traits, providing vital nutrients, and regulating carbon, water, and energy cycles, making understandings its dynamics essential. In this work, data were collected from two towers at the Texas A&M Soltis Center in Costa Rica, which were equipped with various sensors, providing comprehensive atmospheric and in-canopy micrometeorological data. To complement these sensor-based observations, a StarDot phenocamera was used. The camera captured images which were used to analyze fog intensity over a 40-month period from August 2018 to December 2021. The image classification algorithm showed an accuracy of 0.96 when compared to a human rater. Fog occurrence showed a distinct bimodal pattern with increased frequency during early morning and late afternoon hours and an increased seasonal frequency during the October-Februrary months. Foggy conditions limited net solar radiation to below 200 W/m2, attenuating about, 78–85 % of the incoming solar radiation. The proportion of PAR in the solar radiation was also affected, with an increased median ratio in foggy conditions which varied non-linearly with fog intensity (0.76 for light fog; 0.51–0.55 for medium/heavy fog) compared to clear skies (0.44). Fog events significantly increased leaf wetness compared to clear skies, with medium/heavy fog showing higher wetness than light fog. Notably, deeper into the canopy, medium/heavy fog wetness was almost equivalent to rain, emphasizing fog's crucial role in moisture delivery deep within the canopy, influencing plant efficiency and nutrient cycles. Our results indicate the importance of fog intensity and its timing on productivity of forest ecosystems since we find that fog occurrence not only alleviates water stress but also reduces light availability.

中文翻译：

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使用表照图像描述雾：来自哥斯达黎加热带雨林的分析


雾在热带山地和山地前森林中起着关键作用，影响树木特性，提供重要的营养物质，并调节碳、水和能量循环，因此了解其动力学至关重要。在这项工作中，从哥斯达黎加德克萨斯 A&M Soltis 中心的两座塔收集了数据，这些塔配备了各种传感器，提供了全面的大气和树冠内微气象数据。为了补充这些基于传感器的观察，使用了 StarDot 表型相机。该相机拍摄的图像用于分析 2018 年 8 月至 2021 年 12 月的 40 个月期间的雾强度。与人工评分者相比，图像分类算法的准确率为 0.96。雾的发生显示出明显的双峰模式，在清晨和傍晚的频率增加，而在 10 月至 2 月的月份则增加季节性频率。大雾条件将太阳净辐射限制在 200 W/m2 以下，衰减了大约 78-85% 的入射太阳辐射。PAR 在太阳辐射中的比例也受到影响，与晴朗的天空 （0.44） 相比，雾条件下的中位数比增加，雾的强度与雾强度非线性变化（轻雾为 0.76;中/重雾为 0.51-0.55）。与晴朗的天空相比，雾事件显着增加了树叶的湿度，中/重雾的湿度高于轻雾。值得注意的是，在树冠深处，中/重雾湿度几乎相当于雨水，强调了雾在树冠深处输送水分的关键作用，影响植物效率和养分循环。 我们的结果表明雾强度及其时间对森林生态系统生产力的重要性，因为我们发现雾的发生不仅缓解了水的压力，还降低了光的可用性。