---
OA_type: closed access
_id: '22475'
abstract:
- lang: eng
  text: This study extends a stochastic downscaling methodology to generation of an
    ensemble of hourly time series of meteorological variables that express possible
    future climate conditions at a point-scale. The stochastic downscaling uses general
    circulation model (GCM) realizations and an hourly weather generator, the Advanced
    WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed
    for several climate statistics using a Bayesian methodology that can weight GCM
    realizations based on the model relative performance with respect to a historical
    climate and a degree of disagreement in projecting future conditions. A Monte
    Carlo technique is used to sample the factors of change from their respective
    marginal distributions. As a comparison with traditional approaches, factors of
    change are also estimated by averaging GCM realizations. With either approach,
    the derived factors of change are applied to the climate statistics inferred from
    historical observations to re-evaluate parameters of the weather generator. The
    re-parameterized generator yields hourly time series of meteorological variables
    that can be considered to be representative of future climate conditions. In this
    study, the time series are generated in an ensemble mode to fully reflect the
    uncertainty of GCM projections, climate stochasticity, as well as uncertainties
    of the downscaling procedure. Applications of the methodology in reproducing future
    climate conditions for the periods of 2000–2009, 2046–2065 and 2081–2100, using
    the period of 1962–1992 as the historical baseline are discussed for the location
    of Firenze (Italy). The inferences of the methodology for the period of 2000–2009
    are tested against observations to assess reliability of the stochastic downscaling
    procedure in reproducing statistics of meteorological variables at different time
    scales.
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: V. Y.
  full_name: Ivanov, V. Y.
  last_name: Ivanov
- first_name: E.
  full_name: Caporali, E.
  last_name: Caporali
citation:
  ama: Fatichi S, Ivanov VY, Caporali E. Assessment of a stochastic downscaling methodology
    in generating an ensemble of hourly future climate time series. <i>Climate Dynamics</i>.
    2013;40:1841-1861. doi:<a href="https://doi.org/10.1007/s00382-012-1627-2">10.1007/s00382-012-1627-2</a>
  apa: Fatichi, S., Ivanov, V. Y., &#38; Caporali, E. (2013). Assessment of a stochastic
    downscaling methodology in generating an ensemble of hourly future climate time
    series. <i>Climate Dynamics</i>. Springer Nature. <a href="https://doi.org/10.1007/s00382-012-1627-2">https://doi.org/10.1007/s00382-012-1627-2</a>
  chicago: Fatichi, Simone, V. Y. Ivanov, and E. Caporali. “Assessment of a Stochastic
    Downscaling Methodology in Generating an Ensemble of Hourly Future Climate Time
    Series.” <i>Climate Dynamics</i>. Springer Nature, 2013. <a href="https://doi.org/10.1007/s00382-012-1627-2">https://doi.org/10.1007/s00382-012-1627-2</a>.
  ieee: S. Fatichi, V. Y. Ivanov, and E. Caporali, “Assessment of a stochastic downscaling
    methodology in generating an ensemble of hourly future climate time series,” <i>Climate
    Dynamics</i>, vol. 40. Springer Nature, pp. 1841–1861, 2013.
  ista: Fatichi S, Ivanov VY, Caporali E. 2013. Assessment of a stochastic downscaling
    methodology in generating an ensemble of hourly future climate time series. Climate
    Dynamics. 40, 1841–1861.
  mla: Fatichi, Simone, et al. “Assessment of a Stochastic Downscaling Methodology
    in Generating an Ensemble of Hourly Future Climate Time Series.” <i>Climate Dynamics</i>,
    vol. 40, Springer Nature, 2013, pp. 1841–61, doi:<a href="https://doi.org/10.1007/s00382-012-1627-2">10.1007/s00382-012-1627-2</a>.
  short: S. Fatichi, V.Y. Ivanov, E. Caporali, Climate Dynamics 40 (2013) 1841–1861.
das_tickbox: '1'
date_created: 2026-07-27T12:30:23Z
date_published: 2013-04-01T00:00:00Z
date_updated: 2026-08-12T14:05:37Z
day: '01'
doi: 10.1007/s00382-012-1627-2
extern: '1'
fulldoi: https://doi.org/10.1007/s00382-012-1627-2
intvolume: '        40'
keyword:
- Stochastic downscaling
- Weather generator
- Uncertainty assessment
- Firenze
- Italy
language:
- iso: eng
month: '04'
oa_version: None
page: 1841-1861
publication: Climate Dynamics
publication_identifier:
  eissn:
  - 1432-0894
  issn:
  - 0930-7575
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Assessment of a stochastic downscaling methodology in generating an ensemble
  of hourly future climate time series
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 40
year: '2013'
...