Improved sub-seasonal meteorological forecast skill using weighted multi-model ensemble simulations

Details

• Journal Title:
  Environmental Research Letters
• Personal Author:
  Wanders, Niko ; Wood, Eric F
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office)
• Description:
  Sub-seasonal to seasonal weather and hydrological forecasts have the potential to provide vital information for a variety of water-related decision makers. Here, we investigate the skill of four sub-seasonal forecast models from phase-2 of the North American Multi-Model Ensemble using reforecasts for the period 1982-2012. Two weighted multi-model ensemble means from the models have been developed for predictions of both sub-seasonal precipitation and temperature. By combining models through optimal weights, the multi-model forecast skill is significantly improved compared to a 'standard' equally weighted multi-model forecast mean. We show that optimal model weights are robust and the forecast skill is maintained for increased length of time and regions with a low initial forecast skill show significant skill after optimal weighting of the individual model forecast. The sub-seasonal model forecasts models show high skill over the tropics, approximating their skill at monthly resolution. Using the weighted approach, a significant increase is found in the forecast skill for dry, wet, cold and warm extreme events. The weighted mean approach brings significant advances to sub-seasonal forecasting due to its reduced uncertainty in the forecasts with a gain in forecast skill. This significantly improves their value for end-user applications and our ability to use them to prepare for upcoming extreme conditions, like floods and droughts.
• Source:
  Environ. Res. Lett. 11 094007
• DOI:
  https://doi.org/10.1088/1748-9326/11/9/094007
• Document Type:
  Journal Article
• Funding:
  Grant no. NA15OAR4310075
• Rights Information:
  CC BY
• Compliance:
  PMC
• Download URL:
  https://repository.library.noaa.gov/view/noaa/26076/noaa_26076_DS1.pdf
• File Type:
  [PDF - 1.81 MB]
• Collection(s):
  Office of Oceanic and Atmospheric Research (OAR)
• Main Document Checksum:
  urn:sha-512:5b9bb7b6b4fc1357b812aedbddc7f1a25ca8f05ac7558796f4cfc717e35c9d9b02840ca2e7d7979188a16aca33aad5d03729230e2eb19274938af4eb65afdb7c