Downscaling of daily rainfall occurrence over Northeast Brazil using a hidden Markov model
A hidden Markov model (HMM) is used to describe daily rainfall occurrence at ten gauge stations in the state of Ceará in northeast Brazil during the February–April wet season 1975–2002. The model assumes that rainfall occurrence is governed by a few discrete states, with Markovian daily transitions...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.6761 http://iri.columbia.edu/~awr/papers/CearaHMM_FINAL.pdf |
| Summary: | A hidden Markov model (HMM) is used to describe daily rainfall occurrence at ten gauge stations in the state of Ceará in northeast Brazil during the February–April wet season 1975–2002. The model assumes that rainfall occurrence is governed by a few discrete states, with Markovian daily transitions between them. Four “hidden” rainfall states are identified. One pair of the states represents wet vs. dry conditions at all stations, while a second pair of states represents north-south gradients in rain-fall occurrence. The estimated daily state-sequence is characterized by a systematic seasonal evolution, together with considerable variability on intraseasonal, interannual and longer time scales. The first pair of states are shown to be associated with large-scale displacements of the tropical convergence zones, and with teleconnections typical of the El Niño-Southern Oscillation and the North Atlantic Oscillation. A trend toward greater rainfall occurrence in the north of Ceará compared to the south since the 1980s is identified with the second pair of states. A non-homogeneous HMM (NHMM) is then used to downscale daily precipitation |
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