---
OA_type: closed access
_id: '22556'
abstract:
- lang: eng
  text: Numerous studies across multiple disciplines search for insights on the effects
    of climate change at local spatial scales and at fine time resolutions. This study
    presents an overall methodology of using a weather generator for downscaling an
    ensemble of climate model outputs. The downscaled predictions can explicitly include
    climate model uncertainty, which offers valuable information for making probabilistic
    inferences about climate impacts. The hourly weather generator that serves as
    the downscaling tool is briefly presented. The generator is designed to reproduce
    a set of meteorological variables that can serve as input to hydrological, ecological,
    geomorphological, and agricultural models. The generator is capable of reproducing
    a wide set of climate statistics over a range of temporal scales, from extremes,
    to low-frequency interannual variability; its performance for many climate variables
    and their statistics over different aggregation periods is highly satisfactory.
    The use of the weather generator in simulations of future climate scenarios, as
    inferred from climate models, is described in detail. Using a previously developed
    methodology based on a Bayesian approach, the stochastic downscaling procedure
    derives the frequency distribution functions of factors of change for several
    climate statistics from a multi-model ensemble of outputs of General Circulation
    Models. The factors of change are subsequently applied to the statistics derived
    from observations to re-evaluate the parameters of the weather generator. Using
    embedded causal and statistical relationships, the generator simulates future
    realizations of climate for a specific point location at the hourly scale. Uncertainties
    present in the climate model realizations and the multi-model ensemble predictions
    are discussed. An application of the weather generator in reproducing present
    (1961–2000) and forecasting future (2081–2100) climate conditions is illustrated
    for the location of Tucson (AZ). The stochastic downscaling is carried out using
    simulations of eight General Circulation Models adopted in the IPCC 4AR, A1B emission
    scenario.
article_processing_charge: No
article_type: original
author:
- first_name: Simone
  full_name: Fatichi, Simone
  id: cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
  last_name: Fatichi
- first_name: Valeriy Y.
  full_name: Ivanov, Valeriy Y.
  last_name: Ivanov
- first_name: Enrica
  full_name: Caporali, Enrica
  last_name: Caporali
citation:
  ama: Fatichi S, Ivanov VY, Caporali E. Simulation of future climate scenarios with
    a weather generator. <i>Advances in Water Resources</i>. 2011;34(4):448-467. doi:<a
    href="https://doi.org/10.1016/j.advwatres.2010.12.013">10.1016/j.advwatres.2010.12.013</a>
  apa: Fatichi, S., Ivanov, V. Y., &#38; Caporali, E. (2011). Simulation of future
    climate scenarios with a weather generator. <i>Advances in Water Resources</i>.
    Elsevier. <a href="https://doi.org/10.1016/j.advwatres.2010.12.013">https://doi.org/10.1016/j.advwatres.2010.12.013</a>
  chicago: Fatichi, Simone, Valeriy Y. Ivanov, and Enrica Caporali. “Simulation of
    Future Climate Scenarios with a Weather Generator.” <i>Advances in Water Resources</i>.
    Elsevier, 2011. <a href="https://doi.org/10.1016/j.advwatres.2010.12.013">https://doi.org/10.1016/j.advwatres.2010.12.013</a>.
  ieee: S. Fatichi, V. Y. Ivanov, and E. Caporali, “Simulation of future climate scenarios
    with a weather generator,” <i>Advances in Water Resources</i>, vol. 34, no. 4.
    Elsevier, pp. 448–467, 2011.
  ista: Fatichi S, Ivanov VY, Caporali E. 2011. Simulation of future climate scenarios
    with a weather generator. Advances in Water Resources. 34(4), 448–467.
  mla: Fatichi, Simone, et al. “Simulation of Future Climate Scenarios with a Weather
    Generator.” <i>Advances in Water Resources</i>, vol. 34, no. 4, Elsevier, 2011,
    pp. 448–67, doi:<a href="https://doi.org/10.1016/j.advwatres.2010.12.013">10.1016/j.advwatres.2010.12.013</a>.
  short: S. Fatichi, V.Y. Ivanov, E. Caporali, Advances in Water Resources 34 (2011)
    448–467.
das_tickbox: '1'
date_created: 2026-07-27T12:30:24Z
date_published: 2011-04-01T00:00:00Z
date_updated: 2026-08-06T10:13:12Z
day: '01'
doi: 10.1016/j.advwatres.2010.12.013
extern: '1'
intvolume: '        34'
issue: '4'
keyword:
- Weather generator
- Stochastic downscaling
- Climate change
- Hydro-meteorology
- Rainfall model
language:
- iso: eng
month: '04'
oa_version: None
page: 448-467
publication: Advances in Water Resources
publication_identifier:
  issn:
  - 0309-1708
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simulation of future climate scenarios with a weather generator
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 34
year: '2011'
...