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© Crown copyright Met Office Improving seasonal forecasting: role of teleconnections Madrid. Febrero Alberto Arribas
© Crown copyright Met Office The new Met Office Seasonal Forecasting System: GloSea4 Huge team effort! Expected to become operational in April 2009 Main drivers: Adaptation to climate change: Seasonal-to-Decadal system Bridge NWP-CR: Facilitate model development …. And improved seasonal forecasts!
© Crown copyright Met Office The new Met Office Seasonal Forecasting System: GloSea4 GloSea4 is not a model GloSea4 is an ensemble prediction system (build around our latest model: HadGEM3) Initialization (+ uncertainties) Model Model uncertainties Post-processing (eg. Calibration) Probabilistic Forecast
© Crown copyright Met Office Outline … or, why are we changing? GloSea4: the new Ensemble Prediction System HadGEM3: the new model (improving teleconnections)
© Crown copyright Met Office Skill of seasonal forecasts
© Crown copyright Met Office Scope for improvement Perfect model skill – ECMWF model Potential skill – Atlantic SST, climate Change, El Nino and volcanoes Greenhouse gases are missing (Doblas et al. 2006) Atlantic SST response is weak (Rodwell et al. 2004) El Nino teleconnection is missing (Toniazzo and Scaife 2006) Volcanic influence is weak (Stenchikov et al. 2006)
© Crown copyright Met Office Why do we need to change the system to improve the model?
© Crown copyright Met Office What are we changing? GloSea3GloSea4 Model HadCM3 (N48L19 – 1/3L40) HadGEM3 (N96L38-ORCA1L42) Initialization Atmos/soil: reconf. of ECMWF 4D-Var Ocean: UM-ocean 3D-OI Atmos/soil/sea-ice: reconf. of Met Office 4D-Var Ocean: NEMO 3D-OI IC uncertainties Wind stress and SST perturbations added to a central analysis Weekly lagged approach Model uncertainties NoneRP + SKEB2 Forecast ensemble 41-members (monthly bursts from 1 st ) ~ 30 members (weekly bursts) Hindcast ensemble Run a priori off-line 15-members / 15-years ( ) ERA-40 Run on real-time with forecast ~10-members / ~15-years ( ) ERA-interim
© Crown copyright Met Office Why are we changing the ensemble? Current system (GloSea3). Forecast: 1 st Jan st Feb 2009 Once a month Perturbations to initial conditions added to a central analysis No model uncertainties 40 ensemble members 6-month forecasts
© Crown copyright Met Office Forecast biases How to separate the signal from the bias? Obs. clim. fcst Temperature probability
© Crown copyright Met Office Dealing with model biases:
© Crown copyright Met Office Why are we changing the hindcast? Current system (GloSea3). Hindcast: 1 st Jan 1987, 1988, 1989 … st Feb 1987, 1988, 1989 … 2001 Run apriori 15 years; 15 members 6-month forecasts Estimate mean errors to calibrate forecast
© Crown copyright Met Office How to remove model biases How to separate the signal from the bias? Obs. clim. fcst Temperature probability fcst clim (estimated from hindcast!)
© Crown copyright Met Office Why are we changing the ensemble? New system (GloSea4). Forecast: Once a week No perturbations to ICs. Lagged approach Includes model uncertainties 29 th Jan th Jan th Jan th Jan st Jan ensemble members 6-month forecasts 10 ensemble members 6-month forecasts
© Crown copyright Met Office Why are we changing the hindcast? New hindcast (GloSea4). Fcst & Hcst: Run on real-time 15 years; 10 members 15 th Jan th Jan th Jan st Jan th Jan 22 th Jan 8 th Jan 1 st Jan Calibration on the fly!! Forecast Hindcast
© Crown copyright Met Office The new system gives us: Flexibility to introduce model changes Stand-alone hindcast suite for model improvement
© Crown copyright Met Office The new model: HadGEM3 Improved physics, dynamics. Increased resolution Further development until end 2010 linked to: Improvement of skill for seasonal-to-decadal Improvement of skill for regional prediction
© Crown copyright Met Office Improved teleconnections: ENSO-Europe and the role of the stratosphere (Adam Scaife, Sarah Ineson, Jeff Knight, Andrew Marshall)
© Crown copyright Met Office ObservationsL38 Model Observations show low pressure Not well captured by model Response to El Nino Observations Ineson and Scaife, Nature Geoscience, (2009)
© Crown copyright Met Office Weak El Nino Strong El Nino Response to El Nino Observations Toniazzo and Scaife, GRL, (2006)
© Crown copyright Met Office Hypothesis: Models capture ENSO-Europe trop. teleconnection but fail to reproduce strat. teleconnection
© Crown copyright Met Office Arctic polar vortex: Most intense during winter; steepest temperature gradient; sudden stratospheric warmings Planetary (Rossby) waves typically propagate upward and equatorward, contributing to vortex breakdown European response to El Niño in late winter and connection to Sudden Stratospheric Warmings Winter 05/06 (08/09 similar) Baldwin and Dunkerton 2001; Kodera et al 1990, Boville 1984
© Crown copyright Met Office Standard and Extended model Standard (L38)Extended (L60) 39.3km 84.1km Stratosphere (midlatitude mean profile)
© Crown copyright Met Office Role of stratosphere Zonal WindTemperature Role of stratosphere Ineson and Scaife, Nature Geoscience, (2009)
© Crown copyright Met Office Response to El Nino Observations L60 Model Response to El Nino Ineson and Scaife, Nature Geoscience, (2009)
© Crown copyright Met Office No active Active stratosphere Response to El Nino Ineson and Scaife, Nature Geoscience, (2009)
© Crown copyright Met Office Active strat. No active Strong Nino Trop. only
© Crown copyright Met Office Winter 2005/6 Adam Scaife No Strat. Stratosphere Observed Scaife and Knight, QJRMS, 2008
© Crown copyright Met Office Concluding … New Seasonal Forecasting System: – Improved initialization, representation of uncertainties and calibration – Flexible and focused on improving latest model: e.g. ENSO-Europe teleconnection only properly represented when stratosphere is included
© Crown copyright Met Office Perdon por el ingles, Muchas gracias … Alguna pregunta?
© Crown copyright Met Office GloSea4: the new Met Office Seasonal Forecasting System A. Arribas, M. Glover, D. Peterson, A. Maidens, M. Gordon, C. MacLachlan,
© Crown copyright 2007 Forecasting weeks to months ahead Dr. Alberto Arribas Monthly-to-Decadal area, Met Office Hadley Centre Exeter, April 2014.
© Crown copyright Met Office The stratosphere and Seasonal to Decadal Prediction Adam Scaife, Sarah Ineson, Jeff Knight and Andrew Marshall January 2009.
Influence of the stratosphere on surface winter climate Adam Scaife, Jeff Knight, Anders Moberg, Lisa Alexander, Chris Folland and Sarah Ineson. CLIVAR.
© Crown copyright Met Office Seasonal Forecasting EUROBRISA. Paraty, March 2007 Alberto Arribas.
© Crown copyright Met Office The Met Office high resolution seasonal prediction system Anca Brookshaw – Monthly to Decadal Variability and Prediction,
© Crown copyright /0653 Met Office and the Met Office logo are registered trademarks Met Office Hadley Centre, FitzRoy Road, Exeter, Devon, EX1.
© Crown copyright Met Office Strategy for Seasonal Prediction Development: UKMO and WGSIP activities Adam Scaife Head Monthly to Decadal Prediction Met.
Seasonal to decadal prediction of the Arctic Oscillation D. Smith, A. Scaife, A. Arribas, E. Blockley, A. Brookshaw, R.T. Clark, N. Dunstone, R. Eade,
Page 1© Crown copyright 2007 Influence of ENSO on European Climate via the Stratosphere Sarah Ineson and Adam Scaife 2007.
© Crown copyright Met Office Predictability of the Stratosphere and Associated Teleconnections Adam Scaife (Head Monthly to Decadal Prediction, UKMO)
The influence of the stratosphere on tropospheric circulation and implications for forecasting Nili Harnik Department of Geophysics and Planetary Sciences,
© Crown copyright Met Office Met Office seasonal forecasting for winter Jeff Knight (with thanks to many colleagues)
Beyond CMIP5 Decadal Predictions and the role of aerosols in the warming slowdown Doug Smith, Martin Andrews, Ben Booth, Nick Dunstone, Rosie Eade, Leon.
Integrating Climate Science into Adaptation Actions Alberto Arribas Kuala Lumpur, November.
© Crown copyright Met Office Stratospheric Extension to the CHFP “S-CHFP” and links to WCRP-SPARC Adam Scaife WGSIP July 2010.
Page 1© Crown copyright 2004 A Review of UK Met Office Seasonal forecasts for Europe (1-8 months ahead) Andrew Colman, Richard Graham Met Office Hadley.
© Crown copyright Met Office Andrew Colman presentation to EuroBrisa Workshop July Met Office combined statistical and dynamical forecasts for.
© Crown copyright Met Office Decadal predictions of the Atlantic ocean and hurricane numbers Doug Smith, Nick Dunstone, Rosie Eade, David Fereday, James.
© Crown copyright Met Office Long Range Forecasting and the Stratosphere a SPARC-WGSIP joint project? Adam Scaife October 2009.
© Crown copyright Met Office Decadal Climate Prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife.
Exeter 1-3 December 2010 Monthly Forecasting with Ensembles Frédéric Vitart European Centre for Medium-Range Weather Forecasts.
© Crown copyright 2007 A fully resolved stratosphere: Impact on seasonal forecasting Alberto Arribas Monthly-to-Decadal area, Met Office Hadley Centre.
The ENSO Signal in Stratospheric Temperatures from Radiosonde Observations Melissa Free NOAA Air Resources Lab Silver Spring 1.
© Crown copyright 2007 Monthly-Seasonal forecasting Alberto Arribas Monthly to Decadal group, Met Office Hadley Centre Geneva, December 2011.
© Crown copyright Met Office Stratospheric Influences on the Troposphere Adam Scaife December 2010.
1 Assessment of the CFSv2 real-time seasonal forecasts for Wanqiu Wang, Mingyue Chen, and Arun Kumar CPC/NCEP/NOAA.
The role of the stratosphere in extended- range forecasting Thomas Jung Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Germany.
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Subseasonal prediction.
LRF Training, Belgrade 13 th - 16 th November 2013 © ECMWF Sources of predictability and error in ECMWF long range forecasts Tim Stockdale European Centre.
© Crown copyright Met Office Predictability and systematic error growth in Met Office MJO predictions Ann Shelly, Nick Savage & Sean Milton, UK Met Office.
Enhanced seasonal forecast skill following SSWs DynVar/SNAP Workshop, Reading, UK, April 2013 Michael Sigmond (CCCma) John Scinocca, Slava Kharin.
Equatorial Atlantic Variability: Dynamics, ENSO Impact, and Implications for Model Development M. Latif 1, N. S. Keenlyside 2, and H. Ding 1 1 Leibniz.
ENSEMBLES RT4/RT5 Joint Meeting Paris, February 2005 Overview of Seasonal-to-Decadal (s2d) Activities during the Initial 18 Months Francisco J. Doblas.
Only 1 major sudden stratospheric warming (SSW) observed in SH (2002) but minor warmings occurred in 2009 and 2012 NH events occur in 3 out of every 5.
© Crown copyright Met Office The impact of initial conditions on decadal climate predictions Doug Smith, Nick Dunstone, Rosie Eade, James Murphy, Holger.
Page 1© Crown copyright 2004 WP5.3 Assessment of Forecast Quality ENSEMBLES RT4/RT5 Kick Off Meeting, Paris, Feb 2005 Richard Graham.
Verification of NCEP SFM seasonal climate prediction during Jae-Kyung E. Schemm Climate Prediction Center NCEP/NWS/NOAA.
© Crown copyright Met Office Forecasting the onset of the African rainy seasons Michael Vellinga, Alberto Arribas and Richard Graham S2S Conference, Washington,
El Niño Forecasting Stephen E. Zebiak International Research Institute for climate prediction The basis for predictability Early predictions New questions.
ECMWF Training course 26/4/2006 DRD meeting, 2 July 2004 Frederic Vitart 1 Predictability on the Monthly Timescale Frederic Vitart ECMWF, Reading, UK.
Decadal Climate Prediction Project (DCPP) © Crown copyright 09/2015 | Met Office and the Met Office logo are registered trademarks Met Office FitzRoy Road,
Climate Forecasting Unit Prediction of climate extreme events at seasonal and decadal time scale Aida Pintó Biescas.
Page 1© Crown copyright 2006 Matt Huddleston With thanks to: Frederic Vitart (ECMWF), Ruth McDonald & Met Office Seasonal forecasting team 14 th March.
RT5, WP5.2 : Evaluation of processes and phenomena Objectives : Analyse the capability of the models to reproduce and predict the major modes of variations.
NMME Tech Meeting 8 April 2011 NCEP, Room 209. Design of NMME for FY12+ Composition of each prediction system in the NMME? – CFSv2: 8468 (9-mon)
Course Evaluation https://uw.iasystem.org/survey/ Closes June 8th.
India summer monsoon rainfall in ECMWF Sys3 – ICTP, August Indian summer monsoon rainfall in the ECMWF seasonal fc. System-3: predictability and.
Review of Northern Winter 2010/11 Mike Blackburn National Centre for Atmospheric Science, University of Reading Seasonal Climate Discussion 15 April 2011.
Page 1© Crown copyright Sarah Beare (nee John) Neill Bowler, Marie Dando, Anette Van der Wal, Rob Darvell Performance of the MOGREPS Regional Ensemble.
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