SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil

Abstract

Amazon rainforest controls, to some extent, the global hydrological cycle. The objectives of the present work were (i) to investigate hydrologicalpatterns in a larger regionof the Brazilian rainforestthrough 9-month SPEI series and (ii) to search for long or short-term correlation within the number of days with precipitation by monthand accumulated monthly rainfall. Data sets were collected from 15 meteorological stations spanning a large area of the Amazonian rainforest in Brazil. We computed SPEI values from monthly precipitation and monthly meantemperature time series and determined Hurst exponents from detrendedtime series of days with precipitationand accumulated monthly rainfall. In the first case SPEI was determined on a 9-month timescale while Hurst exponents were calculated from rescaled range analysis. Percentage of SPEI values in the near normal class (-1 ≤SPEI ≤ 1) ranged from 59.8% (Peixe, TO) to 69.7% (Tarauaca, AC). The Hurst exponent varied from 0.382 (Diamantino, MT) to 0.636 (Tefé, AM) and correlated positively with the monthly meanrainfall. This indicates a persistenttrend of wet patterns in the futurein some areas. Hurst analysis of days with precipitation and monthly rainfallcould be an additional tool for interpreting rainfall data.

Effect of Various Types of ENSO Events on Moisture Conditions in the Humid and Subhumid Tropics

“…Prior studies investigating the effects of El Niño and La Niña on the surface moisture conditions of terrestrial ecosystems mainly explored the relationships between the ENSO indices and precipitation variability [37,[41][42][43][44][45][46], as well as how these atmospheric phenomena affect forest fires [39,44,47]. Several studies also evaluated surface moisture conditions using dryness or moisture indices [48][49][50][51][52]. Dryness or moisture indices can be a more effective tool to assess the possible effects of ENSO anomalies on terrestrial ecosystems since they account for multiple factors that affect land surface energy and water budgets (e.g., surface temperature, potential and actual evapotranspiration, runoff) [49,53].…”

“…Several studies also evaluated surface moisture conditions using dryness or moisture indices [48][49][50][51][52]. Dryness or moisture indices can be a more effective tool to assess the possible effects of ENSO anomalies on terrestrial ecosystems since they account for multiple factors that affect land surface energy and water budgets (e.g., surface temperature, potential and actual evapotranspiration, runoff) [49,53].…”