Assessing Drought Vulnerability in the Brazilian Atlantic Forest Using High Frequency Data DOI Open Access
Mahelvson Bazilio Chaves, Fábio Farias Pereira,

Claudia Marina Rivera

и другие.

Опубликована: Янв. 11, 2024

This research investigates the exposure of plant species to extreme drought events in Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across region. Meteorological indicators derived hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized quantify past, current, future conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window exhibits modest percentage missing data. Missing excluded analysis, aligning with decision refrain imputation methods due potential bias. Drought quantification involved computation Aridity Index, analysis consecutive hours without classification wet dry days per month. Mann-Kendall trend was applied assess trends evapotranspiration considering their significance. hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated ranking meteorological identify regions most exposed events. results revealed consistent occurrences rainfall events, indicated by positive outliers monthly precipitation values. However, significant observed, including increase daily temperature coupled decrease Forest. No correlation between vulnerability ranks station latitudes elevation found, suggesting geographical location does not strongly influence observed dryness trends.

Язык: Английский

Assessing Drought Vulnerability in the Brazilian Atlantic Forest Using High Frequency Data DOI Open Access
Mahelvson Bazilio Chaves, Fábio Farias Pereira,

Claudia Marina Rivera

и другие.

Опубликована: Янв. 11, 2024

This research investigates the exposure of plant species to extreme drought events in Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across region. Meteorological indicators derived hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized quantify past, current, future conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window exhibits modest percentage missing data. Missing excluded analysis, aligning with decision refrain imputation methods due potential bias. Drought quantification involved computation Aridity Index, analysis consecutive hours without classification wet dry days per month. Mann-Kendall trend was applied assess trends evapotranspiration considering their significance. hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated ranking meteorological identify regions most exposed events. results revealed consistent occurrences rainfall events, indicated by positive outliers monthly precipitation values. However, significant observed, including increase daily temperature coupled decrease Forest. No correlation between vulnerability ranks station latitudes elevation found, suggesting geographical location does not strongly influence observed dryness trends.

Язык: Английский

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