Effective use of general circulation model outputs for forecasting monthly rainfalls to long lead times. Issue 9 (5th September 2013)
- Record Type:
- Journal Article
- Title:
- Effective use of general circulation model outputs for forecasting monthly rainfalls to long lead times. Issue 9 (5th September 2013)
- Main Title:
- Effective use of general circulation model outputs for forecasting monthly rainfalls to long lead times
- Authors:
- Hawthorne, Sandra
Wang, Q. J.
Schepen, Andrew
Robertson, David - Abstract:
- <abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>[1] Long lead rainfall forecasts are highly valuable for planning and management of water resources and agriculture. In this study, we establish multiple statistical calibration and bridging models that use general circulation model (GCM) outputs as predictors to produce monthly rainfall forecasts for Australia with lead times up to 8 months. The statistical calibration models make use of raw forecasts of rainfall from a coupled GCM, and the statistical bridging models make use of sea surface temperature (SST) forecasts of the GCM. The forecasts from the multiple models are merged through Bayesian model averaging to take advantage of the strengths of individual models. The skill of monthly rainfall forecasts is generally low. Compared to forecasting seasonal rainfall totals, it is more challenging to forecast monthly rainfall. However, there are regions and months for which forecasts are skillful. In particular, there are months of the year for which forecasts can be skillfully made at long lead times. This is most evident for the period of November and December. Using GCM forecasts of SST through bridging clearly improves monthly rainfall forecasts. For lead time 0, the improvement is particularly evident for February to March, July and October to December. For longer lead times, the benefit of bridging is more apparent. As lead time increases, bridging is able to maintain forecast<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>[1] Long lead rainfall forecasts are highly valuable for planning and management of water resources and agriculture. In this study, we establish multiple statistical calibration and bridging models that use general circulation model (GCM) outputs as predictors to produce monthly rainfall forecasts for Australia with lead times up to 8 months. The statistical calibration models make use of raw forecasts of rainfall from a coupled GCM, and the statistical bridging models make use of sea surface temperature (SST) forecasts of the GCM. The forecasts from the multiple models are merged through Bayesian model averaging to take advantage of the strengths of individual models. The skill of monthly rainfall forecasts is generally low. Compared to forecasting seasonal rainfall totals, it is more challenging to forecast monthly rainfall. However, there are regions and months for which forecasts are skillful. In particular, there are months of the year for which forecasts can be skillfully made at long lead times. This is most evident for the period of November and December. Using GCM forecasts of SST through bridging clearly improves monthly rainfall forecasts. For lead time 0, the improvement is particularly evident for February to March, July and October to December. For longer lead times, the benefit of bridging is more apparent. As lead time increases, bridging is able to maintain forecast skill much better than when only calibration is applied.</p> </abstract> … (more)
- Is Part Of:
- Water resources research. Volume 49:Issue 9(2013:Sep.)
- Journal:
- Water resources research
- Issue:
- Volume 49:Issue 9(2013:Sep.)
- Issue Display:
- Volume 49, Issue 9 (2013)
- Year:
- 2013
- Volume:
- 49
- Issue:
- 9
- Issue Sort Value:
- 2013-0049-0009-0000
- Page Start:
- 5427
- Page End:
- 5436
- Publication Date:
- 2013-09-05
- Subjects:
- Hydrology -- Periodicals
333.91 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973 ↗
http://www.agu.org/pubs/current/wr/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/wrcr.20453 ↗
- Languages:
- English
- ISSNs:
- 0043-1397
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9275.150000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3387.xml