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Page 1© Crown copyright 2004 Unified Model Developments 2004 Mike Bush NWP Met Office
Page 2© Crown copyright 2004 Outline Operational Unified Model (UM) configurations Recent Global Model changes and future plans Recent Limited Area Model changes and future plans Problems over Greenland and the Alps UM forecasts over the U.S.A., Spain… Future supercomputer plans Summary
Page 3© Crown copyright 2004 New Headquarters & Operations Centre
Page 4© Crown copyright 2004 Operational UM configurations Global 38 levels, N216= 432x325 (~60km) North Atlantic European (NAE) 38 levels, 0.18 deg (20km) UK Mesoscale 38 levels, 0.11 deg (12km) Stratospheric 50 levels 100-1hpa), N48=96x73 (~300km) Crisis models (CAMMS) Middle East, SW Asia
Page 5© Crown copyright 2004 External Users CGAM, U.K ICM Warsaw (University), Poland NIWA, New Zealand met.no, Norway INM, Spain
Page 6© Crown copyright 2004 Recent changes to the Global model G32 27 th April 2004 – Upgrade to UM6.0 G33 26 th May 2004 – Additional/better use of satellite data High spectral resolution IR sounder data (AIRS) on Aqua 30 minute locally received ATOVS data (EARS) ATOVS over land where elevation > 1000m AMSU-A from Aqua (redundancy with NOAA-16) Improved RTM (RTTOV-7) in 3D-VAR Improved bias correction (model predictor) G34 5 th October 2004 – Introduction of 4D-VAR
Page 7© Crown copyright 2004 Southern Hemisphere – 500 hPa Height Stephen English > 5% better Operations 3/44 Experiment 24/44
Page 8© Crown copyright 2004 Forecast tracksof Super Typhoon Nida Julian Heming
Page 9© Crown copyright D-VAR Has been in the pipeline for the last 10 years Successor to 3D-VAR Requires 3-5 times the computing resources of 3D-VAR Single outer loop Effective resolution is N108 (half model resolution) Further scope for improvement via the use of more data (less temporal thinning) in 2005
Page 10© Crown copyright D-VAR vs 3D-VAR: % Reduction in RMSE Rick Rawlins Positive impact in NH, SH and Tropics Strongest signal in SH Satellites are the main data source in the SH Satellite data is asynoptic and so particularly suited to 4D-VAR
Page 11© Crown copyright D-VAR Parallel Trial and Danielle Julian Heming T+144 PMSL VT: 00Z 23/08/2004 Blue= Trial Black= Op
Page 12© Crown copyright D-VAR Parallel Trial Julian Heming PMSL Analysis VT: 12Z 23/08/2004
Page 13© Crown copyright 2004 Global future plans 2004 – 2005 Sean Milton Saharan Albedo - November 2004 Improved Microphysics - November 2004 Boundary Layer - revised diagnosis of K profile depths - Spring 2005? 70 levels - Summer 2005 (retirement of the Stratospheric model) Prognostic Cloud and condensate - Summer 2005 40km horizontal resolution - Summer 2005 Soil level increments from screen level data
Page 14© Crown copyright 2004 Global future plans 2005 – 2006 Sean Milton Ensembles - Summer 2005 Improvements to existing convection scheme? - Autumn 2005 Entrainment (tuning) Smooth detrainment Mid level convection Downdraughts New turbulence based convection – 2006 New spectral files for radiation Reduced thinning of satellite data
Page 15© Crown copyright 2004 Saharan albedo: New soil ancillary - Control Malcolm Brooks Increase in surface albedo Decrease in Max Tstar Comparisons of clear- sky albedo and OLR (GERB observations) with UM simulations reveal discrepancies over the Saharan and Saudi deserts. Clear-sky albedo was underestimated by approximately 0.05 in July 2003, causing an overestimate of the OLR by Wm2 => overestimated surface temperatures Geostationary Earth Radiation Budget
Page 16© Crown copyright 2004 Improved microphysics – 1.5m Temperature Malcolm Brooks Blue = Trial Red = Control RMSE Northern Hemisphere Mean of 5 cases 12Z 20/06/ Z 06/09/2004 Bias Error against Forecast range
Page 17© Crown copyright 2004 Recent changes to Limited area models U.K Mesoscale M27 17 th February Upgrade to UM5.5 Revised convection scheme 2 Targeted moisture diffusion w>1.0 ms -1 Bug fix to PMSL diagnostic M28 27 th April 2004 – Upgrade to UM6.0 North Atlantic European (NAE) E3 3 rd December Upgrade to UM5.5 Revised convection scheme 2 Targeted moisture diffusion w>1.0 ms -1 E4 27 th April Upgrade to UM6.0 E5 22 nd September DA/UM upgrade
Page 18© Crown copyright 2004 Changes to Limited area models Balkans model 23 rd March Withdrawn (replaced by NAE) Middle East model 27 th April Upgrade to UM6.0 South West Asia model 27 th April Upgrade to UM6.0 Falklands model (new) 5 th October Introduction
Page 19© Crown copyright 2004 U.K Mesoscale UM5.5 upgrade: PMSL differences Jorge Bornemann UM5.5 UM5.3 12Z on 22/02/2003 (T+36)
Page 20© Crown copyright 2004 Targeted moisture diffusion Model failures due to grid point storms can cause Operational products to be delayed Standard procedure is to re-run the forecast using a shorter timestep (e.g. 6 mins instead of 7.5 mins for the NAE) We could use a shorter timestep all the time but it is more costly in terms of computer resources/run time Targeted diffusion has helped reduce grid point storm failures by 65% (comparing 2003 with 2004).
Page 21© Crown copyright 2004 North Atlantic-European Model (NAE)
Page 22© Crown copyright 2004 Greenland – Valley cooling problem Low values of theta caused model to crash (<100K !) Cold spots confined to certain locations (valleys) in Greenland and Northern Canada Forced to reconfigure from Global 6 times last Winter…
Page 23© Crown copyright 2004 Greenland – Cross section across valleys Chris Smith, Nigel Wood Investigations revealed that the problem was present in no physics runs Implication: a numerical instability in the dynamics Runaway cooling occurs when the Courant number falls below a critical threshold: C < C_crit (N, Δh) Δh is valley depth
Page 24© Crown copyright 2004 Alps – Cold spot in Valle D’Aosta Sam Smith, Andy Malcolm Similar problems were encountered in 2km resolution modelling of MAP case studies Theta advection uses non-interpolating Semi Lagrangian in the vertical Mod to use full 3D SL theta advection with strict monotonicity cures the problem Overall model stability still remains an issue
Page 25© Crown copyright 2004 NAE upgrade 22/09/04 A clear improvement to the NAE performance as a result of a package of changes to the UM and the data assimilation system Introduction of additional observations (MOPS, local ATOVS and Meteosat rapid scan winds). 3-hourly assimilation cycle (previously 6-hourly) Retune of the forecast error statistics Revised orography ancillary file Increased Gravity Wave Drag at the surface Operational status from 22/09/04
Page 26© Crown copyright 2004 ATOVS data coverage Brett Candy QY06 01/10/04 RTTOV-5 + ATOVSG RTTOV-7 + ATOVSL Blue = NOAA16 Red = NOAA15
Page 27© Crown copyright 2004 NAE performance relative to Global & UK Mes Wind Cloud RMSE against Lead Time 18/08/2004 – 17/09/2004 Red = NAE Green = Global Blue = UK Mes
Page 28© Crown copyright 2004 NAE performance relative to Global & UK Mes Jorge Bornemann
Page 29© Crown copyright 2004 NAE future plans Reduced domain - Winter 2004 38 levels ozone - Winter 2004 Physics changes (Microphysics, Boundary Layer, Prognostic cloud + condensate, Convection…) as per Global - Spring 2005 Saharan Albedo - Spring 2005 Use of 9 surface tiles (currently 1) - Spring 2005 12km horizontal resolution - Spring 2005 Replace U.K Mesoscale model
Page 30© Crown copyright 2004 NAE future plans Nimrod soil state model for the U.K radar area (currently reset to climatology once a week) - Spring 2005 Full resolution AMSU-B - Summer 2005 Ensembles - Summer 2005 70 levels - Summer 2005 Use of soil level increments from screen level data outside the U.K radar area - Winter 2005/2006 4DVAR (currently 3D-VAR) - Winter 2005/2006
Page 31© Crown copyright 2004 NAE – reduced domain from Winter 2004
Page 32© Crown copyright 2004 NAE LAMEPS Alberto Arribas and Neill Bowler Global Run to T+72 N144 (~ 90 km) NAE LAMEPS Run to T+36 20 km Limited Area Model Ensemble Prediction System Focus on short-range (up to 3-days) Model run daily using the 06Z and 18Z analysis 18 members (each one paired with a Global member) Initial Condition perturbations: ETKF (u,v,q,T,P – all levels) Lateral Boundary Conditions from the Global Stochastic physics
Page 33© Crown copyright 2004 Falklands CAMM configuration Glenn Greed Falklands: 172x130 grid points (~12km) and 38 levels. Assimilation of observations, INCLUDING station temperature and RH. 18z forecast run to T+48.
Page 34© Crown copyright 2004 U.S.A test CAMM (17km) – Hurricane Ivan Glenn Greed
Page 35© Crown copyright 2004 TRMM Rain 09Z, GOES-12 IR 0745Z Glenn Greed
Page 36© Crown copyright 2004 Hurricane Ivan – Global forecast Glenn Greed
Page 37© Crown copyright 2004 INM collaboration - 5 Km UM over Spain Jorge Bornemann Resolution 0.05 degrees (~5 Km) 606x430 grid boxes 38 levels Rotated grid
Page 38© Crown copyright 2004 Spain 5Km model. 10m Winds Jorge Bornemann Mistral and Levante sensibly captured 18Z 05/01/2004 (T+18)
Page 39© Crown copyright 2004 Supercomputing plans Paul Selwood Currently have two sets of 15 SX6 nodes split over two computer halls These will be combined to form a 30 node sx6 15 new SX6X nodes (a.k.a SX8) - Summer 2005 Each SX8 node is twice as powerful as a SX6 node Double the computing power will enable the planned increases in resolution and NAE 4D-VAR to go ahead
Page 40© Crown copyright 2004 Summary 2004 Balkans model withdrawn All operational models ported to the SX6 and upgraded to UM6.0 (April) Satellite upgrade to the Global model (May) NAE upgrade (September) 4D-VAR in Global (October) Falklands model (October) Reduced NAE domain (November)
Page 41© Crown copyright 2004 Summary of plans 2005 70 levels in all models Withdraw Stratospheric model 40km Global model Physics changes in all models Introduce Global and Limited Area Ensembles 12km NAE model Withdraw U.K Mesoscale model Introduce 4km UK model
Page 42© Crown copyright 2004 Questions & Answers
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
Page 1© Crown copyright 2006 Modelled & Observed Atmospheric Radiation Balance during the West African Dry Season. Sean Milton, Glenn Greed, Malcolm Brooks,
Page 1© Crown copyright 2004 Unified Model Developments 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia Mike Bush NWP.
1 10/2003 © Crown copyright Unified Model Developments 2003 Clive Wilson NWP Met Office.
Page 1 Developments in regional DA Oct 2007 © Crown copyright 2007 Mark Naylor, Bruce Macpherson, Richard Renshaw, Gareth Dow Data Assimilation and Ensembles,
EUMETSAT04 04/2004 © Crown copyright Use of EARS in Global and Regional NWP Models at the Met Office Brett Candy, Steve English, Roger Saunders and Amy.
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 Implementation of a new dynamical core in the Met Office Unified Model Andy Brown, Director of Science.
© Crown copyright Met Office Data Assimilation Developments at the Met Office Recent operational changes, and plans Andrew Lorenc, DAOS, Montreal, August.
GERB/CERES Meeting 2006 Exeter Evaluation of clouds and radiation in the Met Office global forecast model using GERB/SEVIRI data Richard Allan, Tony Slingo.
© Crown copyright Met Office Impact experiments using the Met Office global and regional model Presented by Richard Dumelow to the WMO workshop, Geneva,
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.
Page 1© Crown copyright Modelling the stable boundary layer and the role of land surface heterogeneity Anne McCabe, Bob Beare, Andy Brown EMS 2005.
© Crown copyright Met Office Impact of aerosols on South Asian Monsoon on short and medium-range timescales Jane Mulcahy Met Office, Exeter, UK.
Evaluating the Met Office global forecast model using GERB data Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading.
1 ATOVS and SSM/I assimilation at the Met Office Stephen English, Dave Jones, Andrew Smith, Fiona Hilton and Keith Whyte.
SYSTEMATIC BIASES 3-hourly comparisons of top of atmosphere radiation from GERB and the Met Office global forecast model Systematic biases in model fluxes.
Evaluating the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data Richard Allan, Tony Slingo Environmental Systems.
GERB science meeting, Oct 2006 The bias in OLR over west Africa in the Met Office Unified Model: detection, attribution, and future plans Jonathan Taylor.
© Crown copyright Met Office UK report for GOVST Matt Martin GOVST-V, Beijing, October 2014.
Global vs mesoscale ATOVS assimilation at the Met Office Global Large obs error (4 K) NESDIS 1B radiances NOAA-15 & 16 HIRS and AMSU thinned to 154 km.
1 3D-Var assimilation of CHAMP measurements at the Met Office Sean Healy, Adrian Jupp and Christian Marquardt.
© Crown copyright Met Office Assimilating infra-red sounder data over land John Eyre for Ed Pavelin Met Office, UK Acknowledgements: Brett Candy DAOS-WG,
25 th EWGLAM/10 th SRNWP Lisbon, Portugal 6-9 October 2003 Use of satellite data at Météo-France Élisabeth Gérard Météo-France/CNRM/GMAP/OBS, Toulouse,
Page 1 NAE 4DVAR Mar 2006 © Crown copyright 2006 Bruce Macpherson, Marek Wlasak, Mark Naylor, Richard Renshaw Data Assimilation, NWP Assimilation developments.
Operational assimilation of dust optical depth Bruce Ingleby, Yaswant Pradhan and Malcolm Brooks © Crown copyright 08/2013 Met Office and the Met Office.
© Crown copyright Met Office Recent [Global DA] Developments at the Met Office Dale Barker, Weather Science, Met Office THORPEX/DAOS Meeting, 28 June 2011.
© Crown copyright Met Office Met Office dust forecasting Using the Met Office Unified Model™ David Walters: Manager Global Atmospheric Model Development,
1 Met Office, UK 2 Japan Meteorological Agency 3 Bureau of Meteorology, Australia Assimilation of data from AIRS for improved numerical weather prediction.
Using GERB and CERES data to evaluate NWP and Climate models over the Africa/Atlantic region Richard Allan, Tony Slingo, Ali Bharmal Environmental Systems.
Page 1© Crown copyright 2005 Met Office Verification -status Clive Wilson, Presented by Mike Bush at EWGLAM Meeting October 8- 11, 2007.
Urban Modelling 1 03/2003 © Crown copyright Urban Scale NWP with the Met Office's Unified Model Peter Clark Mesoscale Modelling Group Met Office Joint.
CAUSES (Clouds Above the United States and Errors at the Surface) "A new project with an observationally-based focus, which evaluates the role of clouds,
MODIS Polar Winds in ECMWF’s Data Assimilation System: Long-term Performance and Recent Case Studies Lueder von Bremen, Niels Bormann and Jean-Noël Thépaut.
- Current status of COMS AMV in KMA/NMSC E.J. CHA, H.K. JEONG, E.H. SOHN, S.J. RYU Satellite Analysis Division National Meteorological Satellite Center.
Page 1© Crown copyright 2005 DEVELOPMENT OF 1- 4KM RESOLUTION DATA ASSIMILATION FOR NOWCASTING AT THE MET OFFICE Sue Ballard, September 2005 Z. Li, M.
Page 1© Crown copyright 2006 Boundary layer mechanisms in extra-tropical cyclones Bob Beare.
1 MODIS winds assimilation experiments and impact studies to date at the Met Office Howard Berger, Mary Forsythe, Met Office, Bracknell/Exeter, UK UW-CIMSS.
1 Satellite Winds Superobbing Howard Berger Mary Forsythe John Eyre Sean Healy Image Courtesy of UW - CIMSS Hurricane Opal October 1995.
6 th SMOS Workshop, Lyngby, DK Using TMI derived soil moisture to initialize numerical weather prediction models: Impact studies with ECMWF’s.
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.
Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental Satellite (GOES)-R platform. The sensor.
1 Systematic and Random Errors in Operational Forecasts by the UK Met Office Global Model Tim Hewson Met Office Exeter, England Currently at SUNY, Albany.
EUMETSAT 2006 Helsinki Exploitation of GERB/SEVIRI data for evaluation of the Met Office global forecast model Richard Allan, Tony Slingo Environmental.
Initial Results from the Diurnal Land/Atmosphere Coupling Experiment (DICE) Weizhong Zheng, Michael Ek, Ruiyu Sun, Jongil Han, Jiarui Dong and Helin Wei.
© Crown copyright Met Office Radiation developments Latest work on the radiation code in the Unified Model James Manners, Reading collaboration meeting.
© Crown copyright Met Office Plans for Met Office contribution to SMOS+STORM Evolution James Cotton & Pete Francis, Satellite Applications, Met Office,
Page 1 Met Office © Crown copyright 2007 CAMM model performance assessed during DODO2 Steph Woodward – climate model dust scheme Glenn Greed – implementation.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
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