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© Crown copyright Met Office Recent & planned developments to the Met Office Global and Regional Ensemble Prediction System (MOGREPS) Richard Swinbank, Warren Tennant, Sarah Beare, Christine Johnson, Neill Bowler, Ken Mylne, Nigel Roberts and Adam Clayton GIFS-TIGGE Working Group meeting #9, Sept 2011
© Crown copyright Met Office 24-member ensemble designed for short-range forecasting Regional ensemble over Atlantic and Europe (NAE) to T+54 at 06Z and 18Z (18km grid, 70 levels) Global ensemble to T+72 at 00Z and 12Z (~60 km grid, 70 levels) Medium-range version of MOGREPS-G: MOGREPS-15, used for TIGGE. ETKF for initial condition perturbations Stochastic physics Aim to assess uncertainty in short-range, eg.: Rapid cyclogenesis Local details (wind etc) Precipitation Fog and cloud MOGREPS – The Met Office ensemble MOGREPS has been running since August 2005, and was made Operational in September NAE
© Crown copyright Met Office Recent ( ) upgrades
© Crown copyright Met Office Increased MOGREPS resolution (2010) Global N144 (~90km) to N216 (~60km) Regional (NAE) 24km to 18km Both systems 38L to 70L:
© Crown copyright Met Office Summary of 2010 MOGREPS upgrades - not just resolution changes GlobalRegional PS23 (Spring) N144L38 to N216L70 L70 physics changes SKEB2 implementation ETKF vertical localisation MOGREPS-15 as Global NAE 24km L38 to 18km L38 minimal physics changes PS24 (Summer) IAU - Increments added at T+0 ETKF & OPS changes RP2 – additional BL parameters SKEB2 – add KE term NAE 18km L38 to 18km L70 Physics changes for L70
© Crown copyright Met Office IAU (Incremental Analysis Update) The IAU was originally developed to add unbalanced (3DVar) analysis increments to the background state. MOGREPS uses the technique to add initial perturbations. The increment is added in gradually over time to damp fast gravity waves.
© Crown copyright Met Office MOGREPS global ensemble MOGREPS-G uses the ETKF to generate perturbations. These are then added to the reconfigured global analysis to create the set of the ensemble members.
© Crown copyright Met Office Ranked Probability Score Precip T850 control No IAU Shifted IAU RPS is similar to mean- square-error but measuring probabilities over a range of thresholds. No IAU gives improvement for precip but degradation for T850.
© Crown copyright Met Office Met Office hybrid implementation (Adam Clayton, Dale Barker, Andrew Lorenc,...) Basic details: Alpha control variable hybrid, with localisation in control variable space (streamfunction, velocity potential, unbalanced pressure, humidity). 23 error modes from MOGREPS-G. Static localisation in horizontal and vertical. 80% climatological / 50% ensemble covariance. (Total variance inflated to maintain analysis fit to obs.) Performance: ~1% improvement against obs and ECMWF analyses. Operational implementation: July Dec uncoupled (29 days)Jun coupled (28 days) RMSE changes vs. obs :
© Crown copyright Met Office Future upgrades
© Crown copyright Met Office Plans for MOGREPS changes following HPC mid-life upgrade Allows further improvements in resolution of operational forecast models For MOGREPS we will use a two-step nesting strategy: Global ensemble MOGREPS-G grid ~40 km Regional ensemble MOGREPS-EU ~12 km UK convective-scale ensemble MOGREPS-UK 2.2 km The short-range ensemble forecasts will run four times a day, with 12 members (1 control + 11 perturbed) Products calculated from pairs of lagged forecasts The ETKF will use 22 (later, more) perturbed members with a 6-hour cycle MOGREPS-15 will continue to run twice a day
© Crown copyright Met Office Proposed (schematic) schedule Each configuration to run 3 hours after driving ensemble to obtain freshest boundary conditions.
© Crown copyright Met Office Proposed new MOGREPS-EU domain Adopt new set of 70 levels to improve resolution in lower troposphere Also used for EURO4M reanalysis project, covering EEA countries & Mediterranean. Covers Storm Surge and ocean Atlantic Margin model domains Will investigate sensitivity to western boundary. Aim to use 12km grid for MOGREPS-EU, so that MOGREPS- EU control run can directly replace 12km NAE – to be retired
© Crown copyright Met Office UKV Model Domain for MOGREPS-UK Variable resolution, 2.2km in inner domain Based on 1.5km UKV model used for convective-scale deterministic forecasting Same 70-level set as MOGREPS-EU
© Crown copyright Met Office Implementation schedule Originally planned as big bang implementation at PS29 (Spring 2012), but due to delay in IBM P7 delivery, implementation will be phased: PS28 (Autumn 2011) 4 cycles per day with current models, but using new schedule. PS30 (late Spring 2012) Introduce MOGREPS-UK in time for Olympics PS31 (Autumn 2012) MOGREPS-EU Other resolution & physics changes at PS31 or PS32
© Crown copyright Met Office Medium-range and Seamless Forecasting Currently the medium-range ensemble, MOGREPS-15 is essentially the same as MOGREPS-G but run to 15 days using UK member-state computer time at ECMWF. Met Office strategy is to make forecasts consistent across different timescales, from short-range NWP to climate prediction. We are planning to bring together ensemble prediction systems on the medium-range and monthly to seasonal timescales, including. Initial condition perturbations from ETKF and, in longer term, Ensemble Data Assimilation System; Coupled model to better represent ocean-atmosphere interactions.
© Crown copyright Met Office Suite 1 20 members 15 days Suite 2 2 members 2 months Suite 3 2 members 7 months Suite 4 X members Hindcast Medium-range products Monthly products Seasonal products Schematic of possible coupled medium-range/ monthly/ seasonal EPS
© Crown copyright Met Office Any Questions?
Page 1 © Crown copyright 2005 ECMWF User Meeting, June 2006 Developments in the Use of Short and Medium-Range Ensembles at the Met Office Ken Mylne.
Page 1© Crown copyright Sarah Beare (nee John) Neill Bowler, Marie Dando, Anette Van der Wal, Rob Darvell Performance of the MOGREPS Regional Ensemble.
Ensemble Forecasting of High-Impact Weather Richard Swinbank with thanks to various, mainly Met Office, colleagues High-Impact Weather THORPEX follow-on.
© Crown copyright Met Office Recent [Global DA] Developments at the Met Office Dale Barker, Weather Science, Met Office THORPEX/DAOS Meeting, 28 June 2011.
Page 1 NAE 4DVAR Oct 2006 © Crown copyright 2006 Mark Naylor Data Assimilation, NWP NAE 4D-Var – Testing and Issues EWGLAM/SRNWP meeting Zurich 9 th -12.
© Crown copyright Met Office Met Office progress report Andy Brown WGNE, Tokyo, October 2010.
Current Status and Plans of Ensemble Prediction System at KMA Seung-Woo Lee Numerical Model Development Division Korea Meteorological Administration GIFS-TIGGE.
Page 1 Developments in regional DA Oct 2007 © Crown copyright 2007 Mark Naylor, Bruce Macpherson, Richard Renshaw, Gareth Dow Data Assimilation and Ensembles,
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
© Crown copyright Met Office Stochastic Physics developments for the Met Office ensemble prediction system Richard Swinbank, Warren Tennant, Anne McCabe.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
© British Crown copyright 2014 Met Office A comparison between the Met Office ETKF (MOGREPS) and an ensemble of 4DEnVars Marek Wlasak, Stephen Pring, Mohamed.
Sub-seasonal to seasonal prediction David Anderson.
Numerical Weather Prediction Models Prepared by C. Tubbs, P. Davies, Met Office UK Revised, delivered by P. Chen, WMO Secretariat SWFDP-Eastern Africa.
© Crown copyright Met Office Investigating a perturbed physics scheme in a wave ensemble system Ray Bell (Line manager: Francois-Bocquet) Ocean Iced Tea.
© Crown copyright Met Office Data Assimilation Developments at the Met Office Recent operational changes, and plans Andrew Lorenc, DAOS, Montreal, August.
ESA DA Projects Progress Meeting 2University of Reading Advanced Data Assimilation Methods WP2.1 Perform (ensemble) experiments to quantify model errors.
© Crown copyright Met Office Predictability and systematic error growth in Met Office MJO predictions Ann Shelly, Nick Savage & Sean Milton, UK Met Office.
30 th September 2010 Bannister & Migliorini Slide 1 of 9 High-resolution assimilation and weather forecasting Ross Bannister and Stefano Migliorini (NCEO,
Page 1© Crown copyright 2004 Seasonal forecasting activities at the Met Office Long-range Forecasting Group, Hadley Centre Presenter: Richard Graham ECMWF.
Meteorological Training Course, 20 March /25 Using Combined Prediction Systems (CPS) for wind energy applications European Centre for Medium-Range.
© Crown copyright Met Office UM 4D-Var Regional Reanalysis Progress Richard Renshaw, Stephen Oxley, Adam Maycock, Peter Jermey, Dale Barker, DingMin Li.
© European Centre for Medium-Range Weather Forecasts Operational and research activities at ECMWF now and in the future Sarah Keeley Education Officer.
© Crown copyright Met Office Implementation of a new dynamical core in the Met Office Unified Model Andy Brown, Director of Science.
© Crown copyright 2007 A fully resolved stratosphere: Impact on seasonal forecasting Alberto Arribas Monthly-to-Decadal area, Met Office Hadley Centre.
Norwegian Meteorological Institute met.no TEPS/LAMEPS at met.no Marit Helene Jensen, Inger-Lise Frogner, Hilde Haakenstad and Ole Vignes.
Page 1 Andrew Lorenc WOAP 2006 © Crown copyright 2006 Andrew Lorenc Head of Data Assimilation & Ensembles Numerical Weather Prediction Met Office, UK Data.
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology Nowcasting and Short Range NWP at the.
Trials of a 1km Version of the Unified Model for Short Range Forecasting of Convective Events Humphrey Lean, Susan Ballard, Peter Clark, Mark Dixon, Zhihong.
ECMWF Training course 26/4/2006 DRD meeting, 2 July 2004 Frederic Vitart 1 Predictability on the Monthly Timescale Frederic Vitart ECMWF, Reading, UK.
© Crown copyright Met Office Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting Jean-François Caron … or why limited-area.
Development of Data Assimilation Systems for Short-Term Numerical Weather Prediction at JMA Tadashi Fujita (NPD JMA) Y. Honda, Y. Ikuta, J. Fukuda, Y.
The Australian Community Climate Earth-System Simulator The Australian Community Climate and Earth System Simulator Kamal Puri (ACCESS Group Leader)
© Crown copyright Met Office The Met Office high resolution seasonal prediction system Anca Brookshaw – Monthly to Decadal Variability and Prediction,
© Crown copyright Met Office NEMOVAR status and plans Matt Martin, Dan Lea, Jennie Waters, James While, Isabelle Mirouze NEMOVAR SG, ECMWF, Jan 2012.
User Meeting 15 June 2005 Monthly Forecasting Frederic Vitart ECMWF, Reading, UK.
© Crown Copyright Source: Met Office Dale Barker, Tomas Landelius, Eric Bazile, Christoph Frei, Phil Jones 2 April 2012 EURO4M – WP2: Regional Reanalysis.
© Crown copyright Met Office Adaptive mesh method in the Met Office variational data assimilation system Chiara Piccolo and Mike Cullen Adaptive Multiscale.
Ensemble-variational sea ice data assimilation Anna Shlyaeva, Mark Buehner, Alain Caya, Data Assimilation and Satellite Meteorology Research Jean-Francois.
© Crown copyright Met Office Strategic Intervention A novel use of Ensembles in Forecast Guidance Ken Mylne (Ensemble Forecasting Applications Manager)
Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.
Norwegian Meteorological Institute met.no LAMEPS – Limited area ensemble forecasting in Norway, using targeted EPS Marit Helene Jensen, Inger-Lise Frogner,
© Crown copyright Met Office GloSea4: the new Met Office Seasonal Forecasting System A. Arribas, M. Glover, D. Peterson, A. Maidens, M. Gordon, C. MacLachlan,
Comparison of Different Approaches NCAR Earth System Laboratory National Center for Atmospheric Research NCAR is Sponsored by NSF and this work is partially.
An Overview of the UK Met Office Weymouth Bay wind model for the 2012 Summer Olympics Mark Weeks 1. INTRODUCTION In the summer of 2012 a very high resolution.
The NCEP operational Climate Forecast System : configuration, products, and plan for the future Hua-Lu Pan Environmental Modeling Center NCEP.
© Crown copyright Met Office UK report for GOVST Matt Martin GOVST-V, Beijing, October 2014.
NWP Activities at INM Bartolomé Orfila Estrada Area de Modelización - INM 28th EWGLAM & 13th SRNWP Meetings Zürich, October 2005.
© Crown copyright Met Office An Introduction to PRECIS PRECIS Workshop, University of Reading, 13 th -17 th May, 2013.
Overview of KMA s Operational LRF Services Korea Meteorological Administration.
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