<b>Homogenous regions and rainfall probability models considering El Niño and La Niña in the State of Pará in the Amazon

Abstract

The determination of homogeneous regions with precipitation and probability models when considering the El Niño- Southern Oscillation (ENSO) phenomenon is important for the planning of water resources and for the study of how climate change affects precipitation regimes. Thus, six homogeneous regions with annual mean precipitation were determined through a cluster analysis using Ward's agglomeration method and applied to a historical series of 31 years (1960-1990) at 413 satellite monitoring points in the state of Pará, where the selected years occurred during an El Niño or a La Niña event. When adjusting the probability models, the chi-square test was applied to 413 monitoring points spread over the six homogeneous regions during years with a La Niña or an El Niño, as well as the complete set of years. The normal model (i.e., the normal function) had the best fit, with chi-square values below 3.84 (tabulated chi-square values). The model was validated using 12 rainfall stations of the National Water Agency (ANA), which were distributed across the six homogeneous regions. In this case, the chi-square test for the 12 stations also had values lower than 3.84. A good fit between the observed and the regionalized data demonstrated the potential of the methodology developed and used for estimating annual average precipitation probabilities.

Keywords

• climate change
• cluster analysis
• average annual rainfall
• Amazon.