Zonal Statistics of Climate Indicators from ERA5-Land for Brazilian Municipalities, 2024

Climate indicators are used in several statistical models for many research areas and are especially important for modelling Climate Sensitive Diseases (CSD) incidence. Those models usually adopt a lattice structure, where their data is aggregated at administrative boundaries (e.g, disease incidence), but climate indicators are usually presented in a continuous, regular grid format. To make climate indicators compatible with lattice structures, zonal statistics may be adopted. Zonal statistics are descriptive statistics calculated using a set of cells that spatially intersect a given spatial boundary. For each boundary in a map, statistics like average, maximum value, minimum value, standard deviation, and sum are obtained to represent the cell's values that intersect the boundary. This dataset presents zonal statistics of climate indicators computed from Copernicus ERA5-Land daily aggregates for the Brazilian municipalities, for the year 2024.气候指标（climate indicators）被广泛应用于多个研究领域的各类统计模型中，尤其在气候敏感性疾病（Climate Sensitive Diseases, CSD）发病率的建模工作中至关重要。此类模型通常采用格网结构，其数据会按行政边界进行聚合（例如疾病发病率数据），但气候指标通常以连续的规则格网格式呈现。 为使气候指标与格网结构兼容，可采用区域统计（zonal statistics）。区域统计是指利用与给定空间边界在空间上相交的一组格网单元计算得到的描述性统计量。针对地图中的每个边界，可计算得到平均值、最大值、最小值、标准差与总和等统计量，用以表征与该边界相交的格网单元的数值。 本数据集提供了基于哥白尼（Copernicus）ERA5-Land逐日聚合数据所计算得到的气候指标区域统计量，覆盖2024年巴西所有市镇。