USP Electronic Research Repository

Non - homogeneous hidden Markov model for downscaling of short rains occurrence in Kenya

Nyongesa, Aston and Zeng, Gang and Ongoma, Victor (2020) Non - homogeneous hidden Markov model for downscaling of short rains occurrence in Kenya. Theoretical and Applied Climatology, 139 . pp. 1333-1347. ISSN 0177-798X

[img]
Preview
Image (JPEG) (Non-homogeneous hidden Markov model for downscaling of short rains occurrence in Kenya) - Cover Image
Download (138Kb) | Preview

    Abstract

    Non-homogeneous hidden Markov model (NHMM) is applied in modeling of daily rainfall occurrences across 16 synoptic stations in Kenya. The time series of the data sets was during the October–December (OND “short rains”) season from 1979 to 2005. The tool assumes that the diurnal rainfall events at a network of observing stations are influenced by unobserved states, that is, “weather states.” These states’ evolution is modeled based on a first-order Markov criterion with state-to-state transition probabilities conditioned on some atmospheric variable indices. The five states are selected using the Bayes information criterion (BIC). To downscale daily rainfall occurrences across 16 stations, a NHMM employed global circulation model (GCM) projection outputs for daily precipitation and sea surface temperatures during the study period. The interannual variability of the mean GCM simulated precipitation and mean historical stations rainfall depicts a weak correlation though significant at 90% confidence level. Thus, it implies that GCM-NHMM simulations do not simulate the rainfall occurrences well. The consecutive wet spell length between the historical rainfall datasets and GCM-NHMM simulated precipitation for 90-day frequencies shows a strong positive correlation significant at 95% confidence level. The findings from this study reveal that the modeling tool is suitable for statistical downscaling of daily rainfall occurrences at multisite stations network. The statistical inference from the model is applicable for drought/flood preparedness, water resource management, and inputs into crop models.

    Item Type: Journal Article
    Subjects: G Geography. Anthropology. Recreation > G Geography (General)
    G Geography. Anthropology. Recreation > GB Physical geography
    G Geography. Anthropology. Recreation > GE Environmental Sciences
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Geography, Earth Science and Environment
    Depositing User: Victor Ongoma
    Date Deposited: 01 May 2020 11:56
    Last Modified: 01 May 2020 11:56
    URI: http://repository.usp.ac.fj/id/eprint/11939
    UNSPECIFIED

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...