Research
The Observing System Research and Predictability Experiment (THORPEX) is a 10-year international research and development programme to accelerate improvements in the accuracy of one-day to two-week high impact weather forecasts for the benefit of society, the economy and the environment.
THORPEX establishes an organizational framework that addresses weather research and forecast problems whose solutions will be accelerated through international collaboration among academic institutions, operational forecast centres and users of forecast products.
TIGGE, the THORPEX Interactive Grand Global Ensemble, is a key component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts for the benefit of humanity. Centralized archives of ensemble model forecast data, from many international centers, are used to enable extensive data sharing and research. The designated TIGGE archive centers include the Chinese Meteorological Administration (CMA), The European Center for Medium-Range Weather Forecasts (ECMWF), and The National Center for Atmospheric Research (NCAR). Scientific data requirements and archive planning solidified in late 2005, and archive collection began in October 2006.
The Unidata LDM software package is used to transport the ensemble model data from the providers to the archive centers. Currently, the output from the ECMWF, UK Met Office (UKMO), CMA, Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP-USA), Meteorological Service of Canada (CMC), Bureau of Meteorology Australia (BOM), Centro de Previsao Tempo e Estudos Climaticos Brazil (CPTEC), Korea Meteorological Administration (KMA), and MeteoFrance (MF) global models, totaling 440 GB/day, is moved at up to 30 GB/hour to NCAR (Realtime Statistics). By requirement the parameter fields, atmospheric levels, and physical units are consistent across all data from the providers and encoded in WMO GRIB-2 format. In contrast, each provider may submit their model output in a resolution they choose.
TIGGE data are available to the public for non-commercial research, with a 48-hour delay after forecast initialization time. At NCAR, users can discover data through the TIGGE portal and select parameters, grid resolution, and spatial subsets for the most current two-week period. The most current two-week period of TIGGE data are also available for direct download in the form of forecast files through the RDA near realtime 3-month TIGGE archive. Long term TIGGE data archives are available through the RDA full TIGGE archive. Forecast files are organized by level type (single level, pressure level, potential vorticity level, and potential temperature level), and forecast time-step for a specified model. All ensemble members are included in each forecast file. At ECMWF, users can discover and download data through a web interface linked to the Meteorological Archival and Retrieval System (MARS). CMA offers an additional option for CMA TIGGE data access. Each center will offer fast access to terabytes of data kept online and delayed access to the long term archives preserved in their archive systems.
The key objectives of TIGGE
- An enhanced collaboration on development of ensemble prediction, internationally and between operational centres and universities,
- New methods of combining ensembles from different sources and of correcting for systematic errors (biases, spread over-/under-estimation),
- A deeper understanding of the contribution of observation, initial and model uncertainties to forecast error,
- A deeper understanding of the feasibility of interactive ensemble system responding dynamically to changing uncertainty (including use for adaptive observing, variable ensemble size, on-demand regional ensembles) and exploiting new technology for grid computing and high-speed data transfer,
- Test concepts of a TIGGE Prediction Centre to produce ensemble-based predictions of high-impact weather, wherever it occurs, on all predictable time ranges,
- The development of a prototype future Global Interactive Forecasting System.
Read more about this topic: Ensemble Forecasting
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