ECMWF | Reading | 2-5 April 2019
Workshop description
TIGGE (The International Grand Global Ensemble) is a dataset, established by the World Weather Research Programme in 2006, comprised of operational global ensemble forecast data from ten weather forecasting centres. TIGGE is designed to span the medium-range (out to day 15), but a similar multi-model ensemble, the S2S dataset, a joint World Weather Research Programme (WWRP) and World Climate Research Programme (WCRP) effort, has been created with contributions from 11 centres to extend across the sub-seasonal to seasonal range (up to day 60).
Both TIGGE and S2S data are archived at ECMWF and CMA providing a unique resource for predictability and dynamical processes research. TIGGE has already proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. TIGGE has added to our understanding of the dynamics of tropical cyclones, extra-tropical cyclones and storm tracks. The S2S database extends the time horizon and also the processes that are important to prediction out to a season, opening new avenues of research.
This workshop provided an opportunity to review the main scientific advances in predictability, dynamical process studies and applications of ensemble forecasts across the medium and S2S forecast ranges. Examples of sectors rapidly developing in ensemble applications include energy, retail and agriculture, as well as disaster risk mitigation worldwide. The emphasis was on the utilisation of the TIGGE and S2S databases in research and contributions on seamless prediction, multi-model prediction and ensemble post-processing were particularly welcome. One session was dedicated to the technical development of ensembles, the TIGGE and S2S data bases and proposals for future development.
Workshop themes
1. Database technical Development
In this theme, we welcomed contributions on various technical aspects related to the TIGGE and S2S data handling. It is crucial for the future to ensure the sustainable long-term minimum effort data processing from initial data production to the final archiving. The contributions related to users' experience with available data interfaces to access the data were also welcome.
2. Predictability and Dynamics
In this theme, we welcomed contributions addressing the representation and understanding of dynamical processes and sources of predictability on medium-range and intra-seasonal time scale. We also welcomed contributions addressing the design of TIGGE and S2S forecasting systems. This includes the design of data assimilation systems and the forecasting system (initialization, ensemble generation, ensemble size, resolution, complexity of the earth system needed for TIGGE and S2S forecasts ...), as well as studies of systematic errors and process-based diagnostics and metrics.
3. Prediction and Verification
In this theme, we welcomed contributions addressing the development of methodologies for calibration, evaluation of the skill of TIGGE and S2S forecasting systems and development of probabilistic forecast products. Contributions on seamless prediction from the short/medium range to the sub-seasonal time scale, and verification re particularly welcome.
4. Multi-model approaches to prediction
In this theme, we welcome contributions addressing the development of methodologies for multi-model combination, and comparison of multi-model versus single-model forecasting systems.
5. Application studies
In this theme, we welcome contributions in the broad area of socio-economic applications of TIGGE and S2S forecasts to meet decision-making needs (e.g. early warning-early action, risk management), such as in agriculture and food security, water resource management, retail, public health, energy, and disaster risk reduction... Contributions related to the seamless use of information from short/medium range to extended range forecasts are particularly welcome.
TIGGE/S2S challenge
As part of the meeting, we aim to promote the development of 'user-oriented variables' as a means of improving communication between the Forecasting and User communities. We define user-oriented variables as derived variables of forecast output which represent the metrological aspects that a given user might be sensitive to. A simple example might be V^3 for wind power. A key question is "How reliable and skilful are the ensemble forecasts within the TIGGE/S2S databases when predicting user-oriented variables? "
S2S/TIGGE challenge
Working Group reports
WG1 |
User-oriented variables (UOVs) to facilitate communication and development |
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WG2 |
S2S and TIGGE databases: technical aspects |
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WG3 |
Processes and forecasts |
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WG4 |
Dynamical processes and ensemble diagnostics |
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WG5 |
Verification / Calibration |
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WG6 |
The potential value of multi-model ensembles |
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Workshop report |
Presentations
Tuesday, 2 April
Introduction and welcome Florian Pappenberger (ECMWF) |
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Flow-dependent predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts Mio Matsueda (Center for Computational Sciences, University of Tsukuba) |
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The role of stratosphere-troposphere coupling in sub-seasonal to seasonal prediction using the S2S database Andrew Charlton-Perez (University of Reading) |
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Stratospheric influences on subseasonal predictability of European energy-industry-relevant parameters Dominik Büeler (Karlsruhe Institute of Technology) |
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Understanding predictability of the MJO in S2S ensemble Shuyi Chen (University of Washington) |
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MJO Impact on Temperature Extremes over Australia during Austral Spring Harry Hendon (Bureau of Meteorology) |
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Extratropical predictability from the Quasi-Biennial Oscillation and the MJO in S2S models Chaim Garfinkel (Hebrew University) |
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Intra-seasonal and Seasonal Variability of the Northern Hemisphere Extra-tropics Cristiana Stan (GMU) |
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Subseasonal Forecast Skill over the Northern Polar Region in Three Operational S2S Systems Hai Lin (Environment and Climate Change Canada) |
Wednesday, 3 April
The technical development of the TIGGE and S2S databases Manuel Fuentes (ECMWF) |
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Progress on TIGGE Archive Center in CMA FeiFei Yang (China Meteorological Administration) The progress of CMA S2S data center Xing Hu (China Meteorological Administration) |
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The S2S Data Base in IRI Data Library: Maprooms and online analysis tools Andrew Robertson (International Research Institute for Climate and Society) |
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Ensemble forecasting at ECMWF Martin Leutbecher (ECMWF) |
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ICON-EPS: a contribution to TIGGE? Michael Denhard (Deutscher Wetterdienst) |
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An Assessment of Predictability and Prediction of NCEP GEFS for Subseasonal Forecast Yuejian Zhu (EMC/NCEP/NWS/NOAA) |
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Using the S2S Database to Evaluate the Performance of the Navy Earth System Prediction Capability (ESPC) Ensemble Matthew Janiga (Naval Research Laboratory) |
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Receiver Operating Characteristic (ROC) curves Tilmann Gneiting (Heidelberg Institute for Theoretical Studies) |
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A verification framework for South American sub-seasonal precipitation predictions Caio Coelho (CPTEC/INPE) |
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Spread of global 2-meter temperature analyses: disentangling forecast systematic errors from mis-estimation of ensemble spread Tom Hamill (NOAA ESRL PSD) |
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Use of TIGGE/Global Ensembles in Tropical Cyclone Research and Operational Forecasts Helen Titley (Met Office) |
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Achieving seamless verification across sub-seasonal time scales from weather to climate Paul Dirmeyer (George Mason University) |
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Uncertainties in Extended-Range Precipitation Forecasts: Model Biases or Predictability Limits Mingyue Chen (Climate Prediction Center/NCEP/NWS/NOAA) |
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Ensemble Prediction and Predictability of Extreme Weather via Circulation Regimes Kathleen Pegion (George Mason University) |
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Forecast products for predicting Atlantic-European weather regimes on subseasonal time scales Christian M. Grams (IMK-TRO, Karlsruhe Institute of Technology (KIT)) |
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Prospects for subseasonal sea ice prediction at both poles Lorenzo Zampieri (Alfred Wegener Institute) |
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Assessment of conditional forecast skill for Brazilian precipitation Amulya Chevuturi (NCAS) |
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Predicting Sudden Stratospheric Warming 2018 and its Climate Impacts with S2S models Alexey Karpechko (Finnish Meteorological Institute) |
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A relationship between zonal migration of monsoon moisture flux convergence and variability in the strength of Madden-Julian Oscillation events Samson Hagos (Pacific Northwest National Laboratory) |
Thursday, 4 April
Ensemble Tropical Cyclone Forecast Performance and Prediction of Ensemble Forecast Error James Goerss (SAIC, NRL Monterey) |
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Multi-model Prediction on Subseasonal Timescales at the US NOAA Climate Prediction Center: Approaches to Calibration and the Identification of Forecasts of Opportunity Daniel Collins (NOAA Climate Prediction Center) |
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Isotonic Distributional Regression (IDR): A powerful nonparametric calibration technique Johanna Ziegel (University of Bern) |
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A Bayesian framework for postprocessing multi-ensemble weather forecasts Clair Barnes (Department of Statistical Science, University College London) |
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Benefits of a multimodel approach for forecasting precipitation over New Caledonia (SW Pacific) at S2S timescales Damien Specq (Météo-France) |
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Subseasonal Prediction of European Extreme Temperature Events in S2S hindcasts Ole Wulff (ETH Zurich) |
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Experimental S2S Forecasting of Atmospheric Rivers Over the Western United States Michael DeFlorio (Center for Western Weather and Water Extremes) |
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Digiscape: A one-platform solution for seasonal climate integration into Agriculture Jaclyn Brown (CSIRO Agriculture and Food) |
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A flood alert system for Switzerland based on integrated water vapor fluxes Jonas Bhend (MeteoSwiss) |
Friday, 5 April
Transmuting S2S forecasts into applications Ángel G. Muñoz (IRI - Columbia University) |
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The S2S4E project, sub-seasonal to seasonal climate predictions for energy Andrea Manrique-Suñén (Barcelona Supercomputing Center) |
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Drought Monitoring and Prediction Using Sub-Seasonal Predictions Yuhei Takaya (MRI/JMA) |
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Developing capacity of Southeast Asian countries to apply subseasonal-to-seasonal forecasts in impact forecasting tools Thea Turkington (Meteorological Service Singapore) |
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Subseasonal forecasting: Managing telecommunications fault risk David Brayshaw (University of Reading) |
Posters
Organising committee
Craig Bishop (craig.bishop@nrlmry.navy.mil)
Manuel Fuentes (manuel.fuentes@ecmwf.int)
John Methven (j.methven@reading.ac.uk)
David Richardson (david.richardson@ecmwf.int)
Andrew Robertson (awr@iri.columbia.edu)
Mark Rodwell (mark.rodwell@ecmwf.int)
Frederic Vitart (frederic.vitart@ecmwf.int)