Publication | Open Access
The THORPEX Interactive Grand Global Ensemble
469
Citations
7
References
2010
Year
Artificial IntelligenceHydrological PredictionEngineeringMachine LearningWeather ForecastingClimate ModelingIntelligent SystemsEarth ScienceClimate PhysicsProbabilistic ForecastingInteractive Machine LearningNumerical Weather PredictionData ScienceAtmospheric ScienceEnsemble ForecastingApplied MeteorologyRobot LearningAtmospheric ModelingClimate ForecastingHydrometeorologyMeteorologyClimate SciencesTigge DataGeographyForecastingClimate DynamicsRobot CompetitionTigge Data PolicyEnsemble Algorithm
Ensemble forecasting is increasingly accepted as a powerful tool to improve early warnings for high‑impact weather, and ensembles that combine forecasts from different systems have recently attracted considerable interest. TIGGE was initiated to enable advanced research and demonstration of the multimodel ensemble concept and to pave the way toward operational implementation at the international level, with objectives to foster cooperation between academia and operations and to explore the benefits of multimodel probabilistic forecasts for high‑impact weather prediction. Ten operational centers provide near‑real‑time daily global ensemble forecasts to.
Ensemble forecasting is increasingly accepted as a powerful tool to improve early warnings for high-impact weather. Recently, ensembles combining forecasts from different systems have attracted a considerable level of interest. The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Globa l Ensemble (TIGGE) project, a prominent contribution to THORPEX, has been initiated to enable advanced research and demonstration of the multimodel ensemble concept and to pave the way toward operational implementation of such a system at the international level. The objectives of TIGGE are 1) to facilitate closer cooperation between the academic and operational meteorological communities by expanding the availability of operational products for research, and 2) to facilitate exploring the concept and benefits of multimodel probabilistic weather forecasts, with a particular focus on high-impact weather prediction. Ten operational weather forecasting centers producing daily global ensemble forecasts to 1–2 weeks ahead have agreed to deliver in near–real time a selection of forecast data to the TIGGE data archives at the China Meteorological Agency, the European Centre for Medium-Range Weather Forecasts, and the National Center for Atmospheric Research. The volume of data accumulated daily is 245 GB (1.6 million global fields). This is offered to the scientific community as a new resource for research and education. The TIGGE data policy is to make each forecast accessible via the Internet 48 h after it was initially issued by each originating center. Quicker access can also be granted for field experiments or projects of particular interest to the World Weather Research Programme and THORPEX. A few examples of initial results based on TIGGE data are discussed in this paper, and the case is made for additional research in several directions.
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