Assessing Drought Vulnerability in the Brazilian Atlantic Forest Using High-Frequency Data

Mahelvson Bazilio Chaves, Fábio Farias Pereira, Claudia Rivera Escorcia, Nathacha Cavalcante
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Abstract

This research investigates the exposure of plant species to extreme drought events in the Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across the region. Meteorological indicators derived from hourly data, encompassing precipitation and maximum and minimum air temperature, were utilized to quantify past, current, and future drought conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window and exhibits a modest percentage of missing data. Missing data were excluded from analysis, aligning with the decision to refrain from using imputation methods due to potential bias. Drought quantification involved the computation of the aridity index, the analysis of consecutive hours without precipitation, and the classification of wet and dry days per month. Mann–Kendall trend analysis was applied to assess trends in evapotranspiration and maximum air temperature, considering their significance. The hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated the ranking of meteorological indicators to identify regions most exposed to drought events. The results revealed consistent occurrences of extreme rainfall events, indicated by positive outliers in monthly precipitation values. However, significant trends were observed, including an increase in daily maximum temperature and consecutive hours without precipitation, coupled with a decrease in daily precipitation across the Brazilian Atlantic Forest. No significant correlation between vulnerability ranks and weather station latitudes and elevation were found, suggesting that geographical location and elevation do not strongly influence observed dryness trends.
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利用高频数据评估巴西大西洋森林的干旱脆弱性
这项研究利用从巴西大西洋森林地区 205 个自动气象站收集的大量数据集,调查了该地区植物物种受极端干旱事件影响的情况。从每小时数据(包括降水量、最高和最低气温)中得出的气象指标被用来量化过去、现在和未来的干旱状况。数据集包括 10,299,236 个数据点,时间跨度较大,缺失数据比例不大。分析中排除了缺失数据,这与因潜在偏差而避免使用估算方法的决定一致。干旱量化包括干旱指数的计算、连续无降水小时数的分析以及每月干湿天数的分类。曼-肯德尔趋势分析用于评估蒸散量和最高气温的趋势,并考虑其重要性。危害评估结合了影响树木生长动态的环境因素,有助于对气象指标进行排序,以确定最易受干旱事件影响的地区。结果显示,极端降雨事件持续发生,月降水量值的正离群值表明了这一点。不过,也观察到了一些重要趋势,包括日最高气温和连续无降水小时数的增加,以及整个巴西大西洋森林日降水量的减少。在脆弱性等级与气象站纬度和海拔之间没有发现明显的相关性,这表明地理位置和海拔对观测到的干旱趋势没有很大影响。
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