Spatial and seasonal dynamics of rainfall in subtropical Brazil

Abstract: The mapping of rainfall is fundamental in the hydrological modeling process. In this sense, the importance of knowing the geographic and seasonal dynamics of average estimates of rainfall and associated uncertainties is evident. Thus, the present study aimed to predict the spatial and seasonal distribution of rainfall, with the estimation of related uncertainties, in the state of Rio Grande do Sul (RS). Average rainfall varies over the months of the year. In January, February, June, July, August, and September it rains more north and northeast. In March, April, May, October, November, and December it rains more northwest and north. In general, it rains a lot in October and little rain in August. From a geographical point of view, it is possible to highlight that greater volumes of rain occur in the northern part of the state of RS. The uncertainties associated with rainfall estimates show divergent temporal dynamics, with the greatest uncertainties tending to occur in January, February, September, and October and that the smallest uncertainties are observed in June, July, and August.摘要：降雨空间分布制图是水文建模流程中的基础性工作。就此而言，掌握降雨平均估算值及其相关不确定性的地理与季节动态特征，其重要性不言而喻。因此，本研究旨在对南里奥格兰德州（Rio Grande do Sul，简称RS）的降雨时空分布进行预测，并估算相关不确定性。年内各月的平均降雨量存在显著差异：1月、2月、6月、7月、8月及9月，该州北部与东北部地区降雨量偏多；3月、4月、5月、10月、11月及12月，西北部与北部地区降雨量偏多。总体而言，10月降雨量充沛，8月则降水稀少。从地理维度来看，南里奥格兰德州北部地区降雨量整体更高。降雨估算相关的不确定性呈现出差异化的时间动态特征：不确定性峰值多出现于1月、2月、9月及10月，而6月、7月与8月的不确定性水平最低。