Presentation is loading. Please wait.

Presentation is loading. Please wait.

Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting 2005 3-5 October 2005, Ljubljana, Slovenia.

Published byAriel Dawson Modified over 9 years ago

Similar presentations

Presentation on theme: "Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting 2005 3-5 October 2005, Ljubljana, Slovenia."— Presentation transcript:

1 Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting 2005 3-5 October 2005, Ljubljana, Slovenia Mike Bush NWP

2 Page 2© Crown copyright 2004 1.SRNWP/Met Office/HIRLAM workshop in Exeter 2.Global model 4D-VAR 3.NAE model 4D-VAR 4.U.K 4km model 3D-VAR

3 Page 3© Crown copyright 2004 SRNWP/Met Office/HIRLAM Workshop  Joint SRNWP/Met Office/HIRLAM Workshop on High resolution data assimilation: towards 1-4km resolution  Held at the Met Office, Exeter 15 -17 November 2004  What is different for the convective scale?  High resolution observations – their assimilation & utility  Assimilating cloud and precipitation observations  Analysis techniques, 3D-Var and error covariances  4D-Var issues

4 Page 4© Crown copyright 2004 1.SRNWP/Met Office/HIRLAM workshop in Exeter 2.Global model 4D-VAR 3.NAE model 4D-VAR 4.U.K 4km model 3D-VAR

5 Page 5© Crown copyright 2004 4D-VAR: The Perturbation Forecast (PF) model  PF model is an approximation to the tangent linear model  Dynamical core:  Start from continuous equations  ECMWF start from the discrete equations for the dynamical core  scale analysis  Choose appropriate terms at an asymptotic limit  then discretize  Physics:  Simplified physics

6 Page 6© Crown copyright 2004 4D-VAR : PF model physics  Simplified physics:  Boundary layer: friction and vertical diffusion of heat and momentum (following Buizza).  Latent heating scheme (simplified microphysics).  No convection.  No radiation.  No gravity wave drag

7 Page 7© Crown copyright 2004 Global 4D-VAR  G33 5 th October 2004  Introduction of 4D-VAR.  Single outer loop  Half model resolution (N108)  Positive benefit – greatest impact in the SH  Satellite data is asynoptic and so particularly suited to 4D-VAR

8 Page 8© Crown copyright 2004 PMSL NH T+24 RMS Error against analysis 8 4DVAR

9 Page 9© Crown copyright 2004 500hPa Height SH T+24 RMS Error against analysis 9 4DVAR

10 Page 10© Crown copyright 2004 250hPa Wind SH T+72 RMS Vector Error vs analysis 10 4DVAR

11 Page 11© Crown copyright 2004 1.SRNWP/Met Office/HIRLAM workshop in Exeter 2.Global model 4D-VAR 3.NAE model 4D-VAR 4.U.K 4km model 3D-VAR

12 Page 12© Crown copyright 2004 NAE 4D-VAR: how to treat the boundaries  Increments zero at the lateral boundaries  Weights of 0, 0, 0, 0, 0, 0.25, 0.5, 0.75 applied going away from the rim  Simple but cheap way of treating the boundaries  HIRLAM have a more sophisticated system using periodic boundaries  Only obs within ½ gridlength of the boundary are excluded

13 Page 13© Crown copyright 2004 NAE 4D-VAR testing  2-week run at half-resolution was completed  Encouraging benefit to PMSL verification.  Other fields are more neutral/slight detriments.  Global 4DVAR does not assimilate screen level data, nor does it assimilate hourly sequences of the surface obs that it does use.  These new aspects of regional 4DVAR might need further tuning.  No problems with using persistence as the PF forecast for aerosol in the 2-week run  This means that experiments with visibility assimilation can go ahead

14 Page 14© Crown copyright 2004 NAE 3D-VAR vs 4D-VAR PMSL Bias and RMSE 14

15 Page 15© Crown copyright 2004 3D-VAR vs 4D-VAR Temperature Bias and RMSE 15

16 Page 16© Crown copyright 2004 1.SRNWP/Met Office/HIRLAM workshop in Exeter 2.Global model 4D-VAR 3.NAE model 4D-VAR 4.U.K 4km model 3D-VAR

17 Page 17© Crown copyright 2004 U.K 4km model: 3D-VAR  Initial solution is to introduce 3D-VAR assimilation system (plus Analysis Correction scheme for cloud and precipitation)  So far 12 case studies run from June – September 2005  Parallel Suite running scheduled for October 2005  Implementation scheduled for November 2005  Later upgrade will address consistency with larger scale increments from the driving model

18 Page 18© Crown copyright 2004 U.K 4km model 3D-VAR impact: PMSL

19 Page 19© Crown copyright 2004 U.K 4km model 3D-VAR impact: 1.5m Temperature

20 Page 20© Crown copyright 2004 U.K 4km model 3D-VAR impact: 10m wind

21 Page 21© Crown copyright 2004 U.K 4km model 3D-VAR impact: cloud

22 Page 22© Crown copyright 2004 Questions?

Download ppt "Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting 2005 3-5 October 2005, Ljubljana, Slovenia."

Similar presentations

© Crown copyright Met Office EURO4M Work Package 2 (chiefly WP2.1) Richard Renshaw EURO4M GA1, De Bilt, April 14 th 2010.

© Crown copyright Met Office EURO4M Work Package 2 (chiefly WP2.1) Richard Renshaw EURO4M GA1, De Bilt, April 14 th 2010.
© Crown copyright Met Office Implementing a diurnal model at the Met Office James While, Matthew Martin.

© Crown copyright Met Office Implementing a diurnal model at the Met Office James While, Matthew Martin.
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.

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.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, 15-18 september 2008.

Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
Status and performance of HIRLAM 4D-Var Nils Gustafsson.

Status and performance of HIRLAM 4D-Var Nils Gustafsson.
Page 1© Crown copyright 2004 Unified Model Developments 2004 Mike Bush NWP Met Office.

Page 1© Crown copyright 2004 Unified Model Developments 2004 Mike Bush NWP Met Office.
1 Met Office, UK 2 Japan Meteorological Agency 3 Bureau of Meteorology, Australia Assimilation of data from AIRS for improved numerical weather prediction.

1 Met Office, UK 2 Japan Meteorological Agency 3 Bureau of Meteorology, Australia Assimilation of data from AIRS for improved numerical weather prediction.
Page 1 NAE 4DVAR Mar 2006 © Crown copyright 2006 Bruce Macpherson, Marek Wlasak, Mark Naylor, Richard Renshaw Data Assimilation, NWP Assimilation developments.

Page 1 NAE 4DVAR Mar 2006 © Crown copyright 2006 Bruce Macpherson, Marek Wlasak, Mark Naylor, Richard Renshaw Data Assimilation, NWP Assimilation developments.
Introduction to parametrization Introduction to Parametrization of Sub-grid Processes Anton Beljaars room 114) What is parametrization?

Introduction to parametrization Introduction to Parametrization of Sub-grid Processes Anton Beljaars room 114) What is parametrization?
1 00/XXXX © Crown copyright Use of radar data in modelling at the Met Office (UK) Bruce Macpherson Mesoscale Assimilation, NWP Met Office EWGLAM / COST-717.

1 00/XXXX © Crown copyright Use of radar data in modelling at the Met Office (UK) Bruce Macpherson Mesoscale Assimilation, NWP Met Office EWGLAM / COST-717.
© Crown copyright Met Office Impact experiments using the Met Office global and regional model Presented by Richard Dumelow to the WMO workshop, Geneva,

© Crown copyright Met Office Impact experiments using the Met Office global and regional model Presented by Richard Dumelow to the WMO workshop, Geneva,
C ontacts: Marit Helene Jensen, Norwegian Meteorological Institute, P.O.Box 43 Blindern, N-0313 OSLO, NORWAY. HIRLAM at met.no.

C ontacts: Marit Helene Jensen, Norwegian Meteorological Institute, P.O.Box 43 Blindern, N-0313 OSLO, NORWAY. HIRLAM at met.no.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss The Latent Heat Nudging Scheme of COSMO EWGLAM/SRNWP Meeting,

Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss The Latent Heat Nudging Scheme of COSMO EWGLAM/SRNWP Meeting,
The 2014 Warn-on-Forecast and High-Impact Weather Workshop

The 2014 Warn-on-Forecast and High-Impact Weather Workshop
1 ATOVS and SSM/I assimilation at the Met Office Stephen English, Dave Jones, Andrew Smith, Fiona Hilton and Keith Whyte.

1 ATOVS and SSM/I assimilation at the Met Office Stephen English, Dave Jones, Andrew Smith, Fiona Hilton and Keith Whyte.
Introduction to Numerical Weather Prediction and Ensemble Weather Forecasting Tom Hamill NOAA-CIRES Climate Diagnostics Center Boulder, Colorado USA.

Introduction to Numerical Weather Prediction and Ensemble Weather Forecasting Tom Hamill NOAA-CIRES Climate Diagnostics Center Boulder, Colorado USA.
Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model Polly Smith, Alison Fowler & Amos Lawless School of.

Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model Polly Smith, Alison Fowler & Amos Lawless School of.
Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.

Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.
© Crown copyright Met Office UK report for GOVST Matt Martin GOVST-V, Beijing, October 2014.

© Crown copyright Met Office UK report for GOVST Matt Martin GOVST-V, Beijing, October 2014.
Numerical Weather Prediction Division The usage of the ATOVS data in the Korea Meteorological Administration (KMA) Sang-Won Joo Korea Meteorological Administration.

Numerical Weather Prediction Division The usage of the ATOVS data in the Korea Meteorological Administration (KMA) Sang-Won Joo Korea Meteorological Administration.

Similar presentations

Ads by Google