HomePublications

Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation

Research output: Contribution to journalArticle

Open Access permissions

Open

Documents

  • accepted version, author's version

    Accepted author manuscript, 1 MB, PDF-document

    Embargo ends: 31/12/99

  • Pattern scaling using ClimGen

    Final published version, 2 MB, PDF-document

DOI

Authors

Organisational units

Abstract

Development, testing and example applications of the pattern-scaling approach for generating future climate change projections are reported here, with a focus on a particular software application called “ClimGen”. A number of innovations have been implemented, including using exponential and logistic functions of global-mean temperature to represent changes in local precipitation and cloud cover, and interpolation from climate model grids to a finer grid while taking into account land-sea contrasts in the climate change patterns. Of particular significance is a new approach for incorporating changes in the inter-annual variability of monthly precipitation simulated by climate models. This is achieved by diagnosing simulated changes in the shape of the gamma distribution of monthly precipitation totals, applying the pattern-scaling approach to estimate changes in the shape parameter under a future scenario, and then perturbing sequences of observed precipitation anomalies so that their distribution changes according to the projected change in the shape parameter. The approach cannot represent changes to the structure of climate timeseries (e.g. changed autocorrelation or teleconnection patterns) were they to occur, but is shown here to be more successful at representing changes in low precipitation extremes than previous pattern-scaling methods.

Details

Original languageEnglish
Pages (from-to)353-369
JournalClimatic Change
Volume134
Issue number3
Early online date7 Oct 2015
DOIs
StatePublished - Feb 2016
Peer-reviewedYes

Bibliographic note

Available under Open Access

View graph of relations

ID: 60710954