The wealth of data recorded by meteorological networks provides a great opportunity for analyzing and discovering knowledge. However, efficient data storage and its effective handling are prerequisites for meteorological and hydro-climatological research and require strategies for capturing, delivering, storing and processing that guarantee quality and consistency of the data. The purpose of this work is to develop a conceptual model for a data warehouse in a star schema that allows the structured storage and multidimensional analysis of historical hydro-climatological data. Information registered by two telemetered networks of hydro-meteorological stations has been collected in the city of Manizales, Colombia. From the designed data warehouse schema, the data warehouse exploits the data (in some cases extending back more than 50 years) in order to apply online analytical processing (OLAP) techniques and discovery potential high-value hidden relationships, in a region particularly affected by climate change and climate variability phenomena. The core contribution of this paper encompasses the exploration of alternatives to the traditional storage and analysis methods and the presentation of a number of cases, showing the effectiveness of the proposed model in the evaluation of the data quality and the visualization of relationships among diverse variables in different scales and for specific cases.