08 Sep 2021

08 Sep 2021

Review status: a revised version of this preprint is currently under review for the journal HESS.

Stochastic daily rainfall generation on tropical islands with complex topography

Lionel Benoit1,2, Lydie Sichoix2, Alison D. Nugent3, Matthew P. Lucas4, and Thomas W. Giambelluca1 Lionel Benoit et al.
  • 1Water Resources Research Center, University of Hawai‘i at Mānoa, 96822 Honolulu, Hawai‘i, USA
  • 2GePaSud Laboratory, University of French Polynesia, 98702 Tahiti, French Polynesia
  • 3Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, 96822 Honolulu, Hawai‘i, USA
  • 4Department of Geography, University of Hawai‘i at Mānoa, 96822 Honolulu, Hawai‘i, USA

Abstract. Stochastic rainfall generators are probabilistic models of rainfall space-time behavior. During parameterization and calibration, they allow the identification and quantification of the main modes of rainfall variability. Hence, stochastic rainfall models can be regarded as probabilistic conceptual models of rainfall dynamics.

As with most conceptual models in Earth Sciences, the performance of stochastic rainfall models strongly relies on their adequacy in representing the rain process at hand. On tropical islands with high elevation topography, orographic rain enhancement challenges most existing stochastic models because it creates localized rains with strong spatial gradients, which break down the stationarity of rain statistics. To allow for stochastic rainfall modeling on tropical islands, despite non-stationarity, we propose a new stochastic daily rainfall generator specifically for areas with significant orographic effects.

Our model relies on a preliminary classification of daily rain patterns into rain types based on rainfall space and intensity statistics, and sheds new light on rainfall variability at the island scale. Within each rain type, the spatial distribution of rainfall through the island is modeled following a meta-Gaussian approach combining empirical spatial copulas and a Gamma transform function, which allows us to generate realistic daily rain fields.

When applied to the stochastic simulation of rainfall on the islands of O‘ahu (Hawai‘i, United States of America) and Tahiti (French Polynesia) in the tropical Pacific, the proposed model demonstrates good skills in jointly simulating site specific and island scale rain statistics. Hence, it provides a new tool for stochastic impact studies in tropical islands, in particular for watershed water resources management and downscaling of future precipitation projections.

Lionel Benoit et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-453', Anonymous Referee #1, 06 Oct 2021
    • AC1: 'Response to the comments of Reviewer1', Lionel Benoit, 16 Nov 2021
  • RC2: 'Comment on hess-2021-453', Geoff Pegram, 07 Oct 2021
    • AC2: 'Response to the comments of Prof. Geoff Pegram (Reviewer2)', Lionel Benoit, 16 Nov 2021

Lionel Benoit et al.

Model code and software

StochasticRainfallGenerator_TropicalIslands Lionel Benoit

Lionel Benoit et al.


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Short summary
This study presents a probabilistic model able to reproduce the spatial patterns of rainfall on tropical islands with complex topography. It sheds new light on rainfall variability at the island scale, and explores the links between rainfall patterns and atmospheric circulation. The proposed model has been tested on two islands of the tropical Pacific, and demonstrates good skills in simulating both site specific and island scale rain behavior.