1. WGNE activities and plans
Andy Brown and Christian Jakob
WGNE co-chairs
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2. Role of WGNE Working Group on Numerical Experimentation
Jointly established by the WCRP and the WMO Commission for Atmospheric Sciences (CAS)
Responsibility of fostering the development of atmospheric circulation models for use in weather prediction and climate studies on all time scales and diagnosing and resolving shortcomings.
A distillation of the Terms of Reference…..
Advice, liaison
Co-ordinated experiments
Workshops, publications, meetings
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3. Co-ordinated experiments and projects
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4. Transpose-AMIP GOOD PROGRESS SURFA SLOW PROGRESS Cloudy-radiance DONE
Grey-zone GOOD PROGRESS
Verification
NWP performance (eg TCs, precipitation) ONGOING
Polar (CBS-style; ConcordIASI intercomparsion) NEW
Climate metrics GOOD PROGRESS
Issues with verifcation against own analysis NEW
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5. Transpose-AMIP: testing climate models in NWP mode
Core experiment is to run 64 hindcasts, each 5 days long, initialised from ECMWF YOTC analysis.
Optional experiment to repeat the same set of hindcasts with NASA MERRA re-analysis or own analysis.
The hindcasts spread through the annual and diurnal cycles and chosen to tie in with YOTC and coincide with some of the IOPs in:
VOCALS (SE Pacific stratocumulus)
AMY (Asian monsoon)
T-PARC (mid-latitude Pacific)
9 centres committed to submit data
MIROC5, HADGEM2, CNRM-CM5 now available to download
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6. Expect at least some papers to make AR5 deadline
Data now being used!
Expect at least some papers to make AR5 deadline
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7. Grey zone Cold air outbreak case
WGNE and GASS supported project
Model intercomparison (9+ participating groups)
GCM
LAM
Idealized LAM / CRM.
How well do models represent convection and the evolution of the boundary layer in a cold air outbreak?
Use of high resolution ‘truth’ to investigate parametrization issues for coarser resolution models
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8. This may need updating?
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9. 31st January 2010
Aircraft obs
Radar obs
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10. CRM case based on ‘Lagrangian’ trajectory from 1.5km UM
Expt defines CRM forcing
The white trajectory is the one chosen for the CRM simulation – it ends where the aircraft and radar were sampling. Each + is ½ hour apart. The trajectory is 15 hours long.
UM 1.5km Control model was not moist enough. Made lots of changes to improve the UM simulation. The ‘expt’ curves are the final output from the UM 1.5km simulation – these are being used to set up the CRM case.
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11. Next steps Iterating setup for CRM case between Met Office and KNMI
Grey zone session at Pan-GASS meeting (Boulder Sept 2012). Show first results.
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12. Issues with verification against own analysis
green : wrt own analysis
pink : wrt ECMWF
Blue : wrt radiosondes
Red : wrt MO analysis
Purple : wrt ECMWF profiles at radiosonde locations
Being taken forward by
small group led by
Tom Hamill,
Laurie Wilson, and
Jean-Noel Thepaut
Best scores wrt own analysis
Similar results wrt ECMWF analysis globally or projected on radiosonde locations: discretisation by radiosonde network sufficient to capture main errors
Worse scores wrt radiosondes: difference in scales and quality of analysis
Convergence of scores after a few days, depending on the model

13. Workshops and meetings
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14. WGNE-THORPEX PDP
Joint expert meeting on “Diagnosis of Forecast Errors” held in Zurich, July 2010
WGNE/PDP/ECMWF Workshop on Representing Model Uncertainty and Error in Numerical Weather and Climate Prediction Models, ECMWF, June 2011
Brought together data assimilation, model physics and ensemble/stochastic physics communities
Stochastic parametrisation paradigm needs further development at the process level and to be incorporated as part of general parametrization development  WGNE/GASS efforts
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15. JPL workshop
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16. GOV/WGNE Ocean coupling workshop
Washington, USA. 19th-22nd March 2013
Follow on to ECMWF (2008) and Met Office (2009) workshops
Focus on coupled modelling for short and medium range
Use of short-range coupled to understand issues for longer range (e.g. subseasonal-seasonal)
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17. Time evolution of coupled model Sea surface temperature errors
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18. Tropical temperature verification
JJA 925hPa DJF 250hPa
-0.2
0.2
Bias
(K)
COUPLED
-1.0
-0.4
ATMOSPHERE
ONLY CONTROL
1.8
1.6
RMSE
(K)
Most of the focus in this section is on the tropics as this is where the main differences exist between the model configurations.
Following plots show bias (top) and rms error (bottom) for the coupled model (red) and the atmosphere control run (blue) averaged over 10 standard GA3.0 cases.
Results are pulled from both JJA and DJF.
Forecast length is on x–axis and is 15 days.
Temperature at 925hPa – so near surface. Coupled model is shown to have both lower biases and rms errors than the control run.
Temperature at 250hPa – coupled again is shown to have lower biases and rms errors from day 7.
At 100hPa, there is again benefit to be seen in the coupled model configuration.
Other variables where benefit is seen – relative humidity, geopotential height, wind speed
Mostly comparable in the extra-tropics but some areas where the coupled model does well eg wind speed biases are reduced in the southern hemisphere
0.6
0.4 12
Forecast range (days)
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19. 4th WGNE Workshop on Systematic Errors in Weather and Climate Models
Met Office, Exeter, UK. 15th- 19th April 2013
Weather and climate
Nature and causes of errors
Use of diagnostic techniques, observations, process models and simplified experiments to understand errors
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20. Systematic errors workshop scientific steering committee:
Keith Williams (chair and local organiser)
Christian Jakob and Andy Brown (WGNE co-chairs)
Sandrine Bony (representing WGCM)
Adam Scaife (representing WGSIP and SPARC)
Gokhan Danabasoglu (representing WGOMD)
Peter Gleckler (representing Climate Metrics Panel)
Beth Ebert (representing Joint Working Group on Verification)
Jon Petch (representing GEWEX)
Duane Waliser (representing the observational community and THORPEX/YOTC)
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21. Questions?
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22. Ctrl Mod BL Change to inhibit cumulus convection (in favour of
turbulent mixing) when
layer above LCL
sufficiently sheared
Obs
Mod BL
Ctrl
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23. Effect of mixing change on surface SW bias in climate model
NEW-OLD
OLD Error map
New Error map
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