---
res:
  bibo_abstract:
  - 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.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Simone
      foaf_name: Fatichi, Simone
      foaf_surname: Fatichi
      foaf_workInfoHomepage: http://www.librecat.org/personId=cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6
  - foaf_Person:
      foaf_givenName: Valeriy Y.
      foaf_name: Ivanov, Valeriy Y.
      foaf_surname: Ivanov
  - foaf_Person:
      foaf_givenName: Enrica
      foaf_name: Caporali, Enrica
      foaf_surname: Caporali
  bibo_doi: 10.1016/j.advwatres.2010.12.013
  bibo_issue: '4'
  bibo_volume: 34
  dct_date: 2011^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/0309-1708
  dct_language: eng
  dct_publisher: Elsevier@
  dct_subject:
  - Weather generator
  - Stochastic downscaling
  - Climate change
  - Hydro-meteorology
  - Rainfall model
  dct_title: Simulation of future climate scenarios with a weather generator@
...