STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change
<p>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 de...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-09-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/11/3713/2018/gmd-11-3713-2018.pdf |
| _version_ | 1818273272593121280 |
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| author | M. B. Singer M. B. Singer K. Michaelides K. Michaelides D. E. J. Hobley |
| author_facet | M. B. Singer M. B. Singer K. Michaelides K. Michaelides D. E. J. Hobley |
| author_sort | M. B. Singer |
| collection | DOAJ |
| description | <p>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.</p> |
| first_indexed | 2024-12-12T21:55:20Z |
| format | Article |
| id | doaj.art-62b8ccc1dc4647469e9ded25b677e28d |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-12T21:55:20Z |
| publishDate | 2018-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-62b8ccc1dc4647469e9ded25b677e28d2022-12-22T00:10:40ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032018-09-01113713372610.5194/gmd-11-3713-2018STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate changeM. B. Singer0M. B. Singer1K. Michaelides2K. Michaelides3D. E. J. Hobley4School of Earth and Ocean Sciences, Cardiff University, Cardiff, UKEarth Research Institute, University of California Santa Barbara, Santa Barbara, CA, USASchool of Geographical Sciences, University of Bristol, Bristol, UKEarth Research Institute, University of California Santa Barbara, Santa Barbara, CA, USASchool of Earth and Ocean Sciences, Cardiff University, Cardiff, UK<p>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.</p>https://www.geosci-model-dev.net/11/3713/2018/gmd-11-3713-2018.pdf |
| spellingShingle | M. B. Singer M. B. Singer K. Michaelides K. Michaelides D. E. J. Hobley STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change Geoscientific Model Development |
| title | STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change |
| title_full | STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change |
| title_fullStr | STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change |
| title_full_unstemmed | STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change |
| title_short | STORM 1.0: a simple, flexible, and parsimonious stochastic rainfall generator for simulating climate and climate change |
| title_sort | storm 1 0 a simple flexible and parsimonious stochastic rainfall generator for simulating climate and climate change |
| url | https://www.geosci-model-dev.net/11/3713/2018/gmd-11-3713-2018.pdf |
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