Abstract ID: 605

Moisture index model for classification of Earth zones with arid, tropical and temperate climates based on temperature and rainfall information

Considering the lack of weather elements needed to characterize the climate of a particular region, the objective of the present study was to develop and implement a linear regression model to characterize the moisture index of Thornthwaite based on geographical database of average annual mean air temperature and annual rainfall. The regression model was developed using data of climatic elements of 39 INMET stations located at Minas Gerais state and neighborhood areas. The moisture index was generated based on water balance calculation, according to Thornthwaite methodology, adopting evapotranspiration data estimated by the FAO Peanman-Monteith method. The generated model was implemented for the classification of arid, tropical and temperate climate zones using 1 km2 resolution of interpolated temperature and rainfall Earth surfaces, from the current scenario of 1950-2000 and future data of CCCMA model, 3th assessment, referent to A2 and B2 scenarios, from the period of 2020, 2050 and 2080. The generated model enabled to explain 92% of the moisture index behavior when compared to observed data and could be applied for climate change studies of moisture index across Earth zones with arid, tropical and temperate climates.

Session:  Feedbacks to Climate - Land cover, surface hydrology, and atmospheric feedbacks.

Presentation Type:  Poster