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ENSEMBLES Progress and Plans Prepared by Chris Hewitt, Project Director Project Office can be contacted on ensemblesfp6@metoffice.gov.uk Web site is http://www.ensembles-eu.org. Motivation.
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ENSEMBLES Progress and Plans Prepared by Chris Hewitt, Project Director Project Office can be contacted on ensemblesfp6@metoffice.gov.uk Web site is http://www.ensembles-eu.org
Motivation Predictions of natural climate variability on seasonal to centennial timescales, and the human impact on climate are inherently probabilistic due to uncertainties in: • initial conditions • representation of key processes within models • climatic forcing factors Reliable forecasts and estimates of climatic risk can only be made through ensemble integrations of Earth-System Models in which these uncertainties are explicitly incorporated. The ENSEMBLES project will provide these probabilistic estimates.
ENSO predictions in seasonal forecasting Multi-model seasonal (MAM) predictions for Niño3.4 SSTs Slide courtesy of Francisco Doblas-Reyes
Current Status of Climate Change Prediction We can produce a small number of different predictions with little idea of how reliable they might be.
Probabilisticapproach From Murphy et al, Nature 2004
non-linear transformation 0 0 PDF of meteorological variables End-user PDF (eg crop yield) End-to-end methodology Slide courtesy of Francisco Doblas-Reyes
The ENSEMBLES Project • 5-year Integrated Project supported by EC FP6 funding 1 September 2004 – 31 August 2009 • 67 partners from across EU, Switzerland, Australia, US we welcome requests from new groups to participate on an unfunded basis – currently 11 such groups worldwide affiliated to the project • Builds upon FP5 projects e.g. DEMETER, MICE, PRUDENCE, STARDEX, PRISM, ATEAM • Work carried out in 10 Research Themes (RTs)
ENSEMBLES Strategic Objectives • Develop an ensemble prediction system based on global and regional Earth System models, validated against quality controlled, high resolution gridded datasets for Europe, to produce for the first time, an objective probabalistic estimate of uncertainty in future climate at the seasonal, decadal and longer timescales • Quantify and reduce uncertainty in the representation of physical, chemical, biological and human-related feedbacks in the Earth System • Exploit the results by linking the outputs to a range of applications, including agriculture, health, food security, energy, water resources
ENSEMBLES Research Themes RT1 Co-leaders: James Murphy, Tim Palmer • To build and test an ensemble prediction system based on global Earth System Models. RT2A Jean-Francois Royer, Erich Roeckner • To produce sets of multi-model climate simulations. RT3 Jens Christensen, Markku Rummukainen • To provide improved regional models. RT2B Clare Goodess, Daniela Jacob • To provide ensemble based regional climate scenarios and seasonal to decadal hindcasts. RT4 Julia Slingo, Jean-Louis Dufresne • To advance the understanding of the basic science.
ENSEMBLES Research Themes (continued) RT5 Antonio Navarra, Albert Klein Tank • To perform a comprehensive and independent evaluation . RT6 Andy Morse, Colin Prentice • To develop risk based estimates of impacts. RT7 Richard Tol, Roberto Roson • To provide scenarios of greenhouse gas emissions, land-use changes and adaptive capacity. RT8 Martin Beniston, Christos Giannakopolous • Represents the interface with a wider audience that includes scientists, stakeholders, policymakers and the general public.
Progress: seasonal to decadal Three different seasonal to decadal forecast systems to estimate model uncertainty: • Multi-model system for s2d forecasts installed at ECMWF built from EUROSIP operational activities and DEMETER experience • Perturbed parameter system, built from the decadal prediction system (DePreSys) at the Met Office • Stochastic physics system, from the CASBS system developed for medium-range forecasting at ECMWF Design of a set of common experiments to determine the benefits of each approach
Progress: anthropogenic climate change • New set of GCM ACC simulations (for IPCC 4AR) Conducted historical runs (1860-2000) and scenario runs (IPCC A1B, A2, B1)
OLD (ECA daily dataset)NEW 0.22º (25km) grid mesh (courtesy of Burkhardt Rockel) Progress (continued) • Defined RCM domain, ERA40 (1961-2000) runs underway • Scientific analyses (e.g. cloud feedbacks, carbon, sea-ice, …) • Linking impact models to probabilistic scenarios • Publicly available Climate Explorer http://climexp.knmi.nl/ further developed as integrated diagnostic tool • Producing daily high-resolution gridded datasets for evaluation
Progress (continued) • Scientific papers published or in prep. • Published overview articles, newsletters, brochures
Plans for 2006-2007 • Finish “Stream 1” simulations using existing models: • s2d hindcasts 1991-2001 • 1860-2000 historical simulations • 21st Century scenarios (A1B, A2, B1) • RCM ERA40@50km 1961-2000 (first multi-model RCM system) • Start “Stream 2” simulations: • s2d hindcasts 1960 onwards • 1860-2000 simulations using updated models • 21st Century scenarios (A1B, A2, B1, ENS1) using updated models • RCM ERA40@25km 1961-2000
Plans for 2006-2007 (continued) • Develop databases • S2d @ ECMWF building on DEMETER database • RCM @ DMI building on PRUDENCE database • GCM @ MPIMET building on IPCC WCDC activities • Develop impacts models (e.g. crops, water resources, energy) • Testing the sensitivity of emissions scenarios to climate change • Develop new emissions scenario (ENS1) for Stream 2 simulations • Develop statistical downscaling tools • Improved estimates for changes in extreme events • Workshops (Climatic change and impacts in Eastern Europe, Romania 13-15 Sep; Adaptation to the impacts of climate change in the European Alps, Switzerland 4-6 Oct; Extreme climatic events and Impacts, Switzerland 2007; 5th Study Conference on BALTEX, Estonia 2007)
Concluding remark ENSEMBLES brings together largely separate communities and integrates world-leading European research on the Earth system: s2d,anthropogenic climate change, global modellers, regional modellers (dynamical and statistical downscaling), climate and chemistry, scientific understanding,evaluation with observations,application modellers to deliver climate impacts, emission scenario developers, training programmes