Singer, Michael ORCID: https://orcid.org/0000-0002-6899-2224, Michaelides, Katerina and Hobley, Daniel ORCID: https://orcid.org/0000-0003-2371-0534 2018. STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change. Geoscientific Model Development 11 , pp. 3713-3726. 10.5194/gmd-11-3713-2018 |
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Abstract
Assessments of water balance changes, watershed response, and landscape evolution to climate change require representation of spatially and temporally varying rainfall fields over a drainage basin, as well as the flexibility to simply modify key driving climate variables (evaporative demand, overall wetness, storminess). An empirical–stochastic approach to the problem of rainstorm simulation enables statistical realism and the creation of multiple ensembles that allow for statistical characterization and/or time series of the driving rainfall over a fine grid for any climate scenario. Here, we provide details on the STOchastic Rainfall Model (STORM), which uses this approach to simulate drainage basin rainfall. STORM simulates individual storms based on Monte Carlo selection from probability density functions (PDFs) of storm area, storm duration, storm intensity at the core, and storm center location. The model accounts for seasonality, orography, and the probability of storm intensity for a given storm duration. STORM also generates time series of potential evapotranspiration (PET), which are required for most physically based applications. We explain how the model works and demonstrate its ability to simulate observed historical rainfall characteristics for a small watershed in southeast Arizona. We explain the data requirements for STORM and its flexibility for simulating rainfall for various classes of climate change. Finally, we discuss several potential applications of STORM.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Earth and Environmental Sciences Water Research Institute (WATER) |
Publisher: | European Geosciences Union (EGU) / Copernicus Publications |
ISSN: | 1991-959X |
Date of First Compliant Deposit: | 11 September 2018 |
Date of Acceptance: | 23 August 2018 |
Last Modified: | 05 May 2023 01:39 |
URI: | https://orca.cardiff.ac.uk/id/eprint/114808 |
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