© 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 Outline of Presentation Where Are We Now? What’s New: Observation Sensitivities. Resolution/climatological covariance upgrade (Nov 2010). Hybrid 4D-Var, moist control Variable (July 2011). What’s next?

© Crown copyright Met Office Where Are We Now?

© Crown copyright Met Office Operational NWP Models: Jun 2011 Global  25km 70L  4DVAR – 60km  60h forecast twice/day  144h forecast twice/day  +24member EPS at 60km 2x/day NAE  12km 70L  4DVAR – 24km  60h forecast  4 times per day  +24member EPS at 18km 2x/day UK-V (& UK-4)  1.5km 70L  3DVAR (3 hourly)  36h forecast  4 times per day

© Crown copyright Met Office What’s new?

Observation impacts: Model Comparison Richard Marriott

© Crown copyright Met Office Parallel Suite 25 : Nov 2010 Global Data Assimilation - 4DVAR to 60km; CovStats from EC Ensemble Seasonal Forecast Model to L85 (from L38) Parallel Suite 26 : Mar 2011 Global Model – GA3.1 – Removal of Spurious Light Problem (since PS24) UK models - Improvements to Drizzle/Fog in (DrFog) + JULES Seasonal Forecast System - more members for 30day forecast Post-processing - Best Data via Blending/Lagging sites UK4 run as Global Model Downscaler Parallel Suite 27 : Jul 2011 Global DA– Hybrid Data Assimilation, Moisture Control Variable, New Obs Global Model – Non-interactive Prognostic Dust UK DA – Doppler Radar Winds UK Model – More complete DrFog package Recent Operational Upgrades

© Crown copyright Met Office Climatological Covariances Training dataOld (NMC method)New (ECStats) UM forecast differences T+30 – T+6 laggedUM T+6 ensemble(10) from EC analysis perturbations ResolutionN216L70N320L70 PeriodJan Oct 2006 Cov modelcurrentunchanged

© Crown copyright Met Office Impact Of N216 4D-Var + ECStats Verif Vs Obs (Above), Vs Anal(below) Res impact Vs Obs = Res impact Vs Anal = ECStats impact Vs Anal = ECStats impact Vs Obs = -0.02Joint impact Vs Obs = Joint impact Vs Obs = +5.52

Towards ‘Quasi-Continuous’ 4D-Var UM (QU06) model background OPS (QG12) VAR N108 analysis increment UM (QG12) VAR N216 Hessian eigenvectors vguess GMT Preconditioning N108 4D-Var reduces final N216 4D-Var cost from 21mins to 13mins Rick Rawlins

© Crown copyright Met Office SSMIS UAS + GPSRO to 60 km : November 2009 Solid: Control Dashed: GPSRO+SSMIS DA covariances introduces slow temperature drift near model model. Solutions: Analysis increment ramping (reduce increments near top). Additional data: GPS RO + SSMIS (Channels 21 and 22).

© Crown copyright Met Office PS27: Global Data Assimilation Upgrade (July 2011) Assimilation method Hybrid 4D-Var algorithm: Coupling DA and MOGREPS. Moisture control variable: Replacing RH with scaled humidity variable Observation changes Introduce METARS GOES/Msat-7 clear-sky radiances, extra IASI (land) Revisions to MSG clear-sky processing and GPSRO Reduced spatial thinning (ATOVS/SSMIS/IASI/AIRS/aircraft)

© Crown copyright Met Office PS27 Hybrid data-assimilation Basic idea: Use data from MOGREPS-G to improve the representation of background error covariances in global 4D-Var: MOGREPS COV MOGREPS is sensitive to the position of the front, and gives covariances that stretch the increment along the temperature contours. Ensemble currently too small to provide the full covariance, so we blend the MOGREPS covariances with the current climatological covariances; i.e., we use a hybrid system: Climatological COV u response to single u observation: Hybrid COV

© Crown copyright Met Office Dec uncoupled: +1.2 Pre-operational hybrid trials Verification vs. obs Better/neutral/worse NHTRSH Dec uncoupled (29 days)29/94/06/117/012/109/2 Jun coupled (28 days)34/89/09/114/046/74/3 Jun coupled: +1.6 Skill: RMSE:

© Crown copyright Met Office Dec uncoupled: -4.0 Pre-operational hybrid trials Verification vs. own analyses Better/neutral/worse NHTRSH Dec uncoupled (29 days)16/91/167/69/473/106/14 Jun coupled (28 days)49/63/119/86/2818/82/23 Jun coupled: -0.2 Skill: RMSE:

© Crown copyright Met Office Dec uncoupled: (1.338%) Pre-operational hybrid trials Verification vs. ECMWF analyses Better/neutral/worse NHTRSH Dec uncoupled (29 days)35/79/039/75/014/100/0 Jun coupled (23/28 days)51/63/027/87/046/66/2 Jun coupled: (1.298%) Skill: RMSE:

© Crown copyright Met Office PS27 Moisture control variable Limits on q/RH skew distribution Plot shows O vs B B vs A similar Near 0% or 100% RH, (A-B) is very skewed Transform to a function of (A+B)/2 (Holm) – distribution is much more symmetric This makes the analysis nonlinear Much better fit of humidity- sensitive satellite obs to background Reduced spin-down of precipitation

© Crown copyright Met Office Moisture control variable - improved fit of observations to background forecast

© Crown copyright Met Office PS27: Impact of Package Components Combined Winter/Summer Results Hybrid 4D-Var Moisture control variable, replacing RH with scaled humidity variable Introduce METARS GOES/Msat-7 clear-sky radiances, extra IASI (land) Revisions to MSG clear-sky processing and GPSRO Reduced spatial thinning (ATOVS/SSMIS/IASI/AIRS/aircraft) NWP index vs obs NWP index vs anl

© Crown copyright Met Office Global Modelling Centre Comparison Northern Hem. NWP Index (v. Anl) basket % diff relative to Met Office Met Office KMACAWC R NCMRWF

© Crown copyright Met Office What’s next?

Global  16-20km 85L (85km top)  Hybrid 4DVAR (50km inner-loop)  60 hour forecast twice/day  144 hour forecast twice/day  48/12member 40km MOGREPS-G 4*/day MOGREPS-EU  Common NWP/reanalysis domain.  12Km 70L (40km top)  3D-Var (or NoDA)  48 hour forecast  12 members ; 4 times per day UKV  1.5km 70L (40km top)  3DVAR (hourly)  36 hour forecast  4 times per day  12 member 2.2km MOGREPS-UK Operational NWP Configs: Spring 2013 (Tentative)

Nowcasting Demonstration Project 1.5 km NWP-based nowcasting system Southern UK only Hourly cycling, ~12 hour forecasts To be run in experimental mode during London’s summer Olympics in /4DVAR with Doppler winds/reflectivities. Result below fro 4 cases/10-20cycles per case: David Simonin

Continue to optimize 4D-Var: SE + algorithmic changes. Continue to develop hybrid for short/medium-term ( ): Increase ensemble size, more sophisticated localization, etc. Consider replacing ETKF as ensemble perturbation generator. Develop UKV DA hybrid 3/4D-Var ( ). Develop 4D-Ensemble-Var: Code and test within current VAR framework ( ). Extend to an ‘Ensemble of 4D-Ensemble-Vars’ ( ). Retire PF model if/when 4D-Ensemble-Var beats 4D-PF-Var. Coupled DA: Monitor DA developments in ESM components and increase modularity/sharing of algorithms where appropriate: ‘seamless DA’. DAE Techniques: Strategy Going Forward

© Crown copyright Met Office Thank You Questions?

© Crown copyright Met Office PS28 (late 2011): Prepare for 6 hour EPS Production Cycle Still MOGREPS-R domain at PS28 Not until PS30 24 members 12 hourly 12 members 6 hourly

Conclusion: On average, 51-52% of observations are beneficial! Fraction Of Beneficial Observations Richard Marriott