Chile is well known as a narrow and long country (over 4,000 km) that encompasses many climate zones and that presents significant west–east gradients as altitudes change from sea level to several thousand meters. Although Chile is recognized as one of the most affected countries by climate change, it is also one of the least covered by hydrometeorological measuring instruments. This data scarcity prevents thorough characterization of hydrological basins. To solve this problem, we constructed a decade-long (2000–2011) high-resolution (∼800 m) monthly gridded precipitation product for the central-southern zone (34∘S–41∘S) covering regions from O’Higgins to Los Ríos. These regions contain most of Chile’s agricultural land, livestock, forestry, and hydroelectric production. The study zone covers a variety of topographies and climates, including eight hydrological basins: Rapel, Mataquito, Maule, Itata, BioBío, Imperial, Toltén, and Valdivia. We develop a dynamic topo-climatic methodology that includes local and global data. We combined a dynamic downscaling and a spatial-temporal multivariate model over different geographical areas that considered high-resolution precipitation fields from model data, in situ stations, and different global precipitation datasets that also understand satellite observations. Results show that most of the precipitation spatial-temporal variability is well-captured by the model in the north and central regions, from O’Higgins to Biobío, with the goodness of fit (R2) fluctuating around 0.86 and 0.82, respectively. Toward the south, Araucanía and Los Ríos, the goodness of fit (R2) decreased to values around 0.74 and 0.72, respectively. Both the modified Willmott coefficient (d) and the nse indicated a good model skill, with values over 0.8 and 0.7, respectively. Meanwhile, the σe, nrmse, and pbias changed between 0.04–0.2, 0.35–0.52, and 12–22%, respectively. This database is freely available to different regional or national institutions and will help the development of a better understanding and management of local and regional hydrology.

智利是一个狭长的国家（超过4,000公里），它涵盖了许多气候区，并且随着海拔高度从海平面变化到几千米，呈现出明显的东西向梯度。尽管智利被公认是受气候变化影响最大的国家之一，但它也是水文气象测量仪器覆盖最少的国家之一。这种数据稀缺性阻碍了水文盆地的全面表征。为了解决这个问题，我们构建了长达十年（2000-2011年）的高分辨率（〜800 米） 中南部地区的每月网格降水产品 （34∘S–41∘小号）涵盖从奥希金斯到洛斯里奥斯的地区。这些地区包含智利大部分的农业用地，牲畜，林业和水力发电。该研究区涵盖了各种地形和气候，包括八个水文盆地：雷佩尔，马塔基托，毛勒，伊塔塔，比奥比奥，帝国，托尔滕和瓦尔迪维亚。我们开发了一种动态的地形气候方法，其中包括本地和全球数据。我们结合了不同地理区域的动态降尺度模型和时空多元模型，并考虑了模型数据中的高分辨率降水场，原位站，以及也了解卫星观测的不同全球降水数据集。结果表明，从O'Higgins到Biobío，在北部和中部地区，大多数降水时空变化都被该模型很好地捕获，并且具有拟合的优势。（[R2）分别在0.86和0.82附近波动。向南，阿劳卡尼亚（Araucanía）和洛斯里奥斯（LosRíos）（[R2）分别降至0.74和0.72左右。修正后的威尔莫特系数（d） 和 se表示模型技能很好，其值分别超过0.8和0.7。同时，σË， nrmse和 偏见 改变之间 0.04–0.2， 0.35–0.52和 12–22％， 分别。该数据库可免费提供给不同的地区或国家机构，并将有助于更好地理解和管理地方和地区水文学。