Cited by 816Meteorological Phenomena and SimulationsClimate variability and modelsForecasting Techniques and Applications

Improved Weather and Seasonal Climate Forecasts from Multimodel Superensemble

Krishnamurti, T. N., Kishtawal, C. M., LaRow, Timothy E., Bachiochi, David R., Zhang, Zhan, Williford, C. Eric, Gadgil, Sulochana, Surendran, Sajani·1999·Science

Abstract

A method for improving weather and climate forecast skill has been developed. It is called a superensemble, and it arose from a study of the statistical properties of a low-order spectral model. Multiple regression was used to determine coefficients from multimodel forecasts and observations. The coefficients were then used in the superensemble technique. The superensemble was shown to outperform all model forecasts for multiseasonal, medium-range weather and hurricane forecasts. In addition, the superensemble was shown to have higher skill than forecasts based solely on ensemble averaging.

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Crossref · 10.1126/science.285.5433.1548

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Authors
Krishnamurti, T. N., Kishtawal, C. M., LaRow, T. E., Bachiochi, D. R., Zhang, Z., Williford, C. E., Gadgil, S., & Surendran, S.
Affiliations
  • Florida State University (US)
  • Indian Institute of Science Bangalore (IN)
Venue
Science
Published
1999-09-03
Volume
285
Issue
5433
Pages
1548-1550
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2021510303
Cited by
816
References
0
Citations by year
2026: 18 · 2025: 15 · 2024: 26 · 2023: 28 · 2022: 34 · 2021: 36 · 2020: 43 · 2019: 36 · 2018: 43 · 2017: 26 · 2016: 51 · 2015: 38 · 2014: 43 · 2013: 40 · 2012: 37
FWCI
9.31
Type
journal article
Language
en
Open access
closed
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
  • NOT FOUND REPOSITORY (Indian Institute of Science Bangalore) (acceptedVersion)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
Keywords
weather forecasting, seasonal climate forecasting, multiple linear regression, ensemble averaging, hurricane forecasting, medium-range forecasting, forecast skill

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