Met Office update Malcolm Brooks, Yaswant Pradhan, Ben Johnson Fanny Peers (University of Exeter) ICAP, Greenbelt MD, USA – 12/07/2016

Contents Forecast availabilty: Standard ‘met’ fields Arrival times. Additional aerosol model Science configuration Arrival times, issues

Forecast support Standard ‘met’ fields A Post-processing system for operational and research models: Locates and polls for completion of forecast runs on HPC. (Max 5 minute latency). Extracts required fields and basic manipulation. Plotting and web page produced quickly. External transfer of sub-set of products.

Forecast support Standard ‘met’ fields Demo: Met Office internal: http:www-nwp/~dust/monitoring/Monitoring Fastest arrival time. Competitive to Ops. Centre. All available models, intercomparisons Internal Met Office ‘customers’ of this page, not just Obs campaigns. External pages, for a sub-set of products: http://www.metresearch.com/flyingforecasts http://gws-access.ceda.ac.uk/public/mo_forecasts/ Involve an extra transfer (time, reliability). Password protected pages.

Standard ‘met’ fields Arrival times Post-processing system for operational and research models: Operational global 00Z completes ~0330Z – 0400Z 06Z completes ~0930Z – 1000Z 12Z completes ~1530Z – 1600Z 18Z completes ~2130Z – 2200Z Research models align to this, but have to queue. Locates and polls for completion of forecast runs on HPC. Max 5 minute latency. Extracts required fields and basic manipulation. Runs on HPC. Optimisied, completes in ~5-10 minutes. Plotting and web page produced on queued linux servers. Highly parallelised. Internal imagery updated on webpage when ANY model/section completes. latest imagery arrives in stages and viewable before all completed. Rough priority order: Precip, winds, cloud, then the rest.... Internal arrival times logged: Global: 00Z from ~0415Z – 0600Z. 06Z from ~1000Z – 1115Z 12Z from ~1645Z – 1800Z 18Z from ~2200Z – 2300Z. External transfer of sub-set of products. Arrive approx 1 hour later. External transfers more variable.

Standard ‘met’ fields Arrival times Post-processing system for operational and research models: Operational global 00Z completes ~0330Z – 0400Z 06Z completes ~0930Z – 1000Z 12Z completes ~1530Z – 1600Z 18Z completes ~2130Z – 2200Z Research models align to this, but have to queue. Locates and polls for completion of forecast runs on HPC. Max 5 minute latency. Extracts required fields and basic manipulation. Runs on HPC. Optimisied, completes in ~5-10 minutes. Plotting and web page produced on queued linux servers. Highly parallelised. Internal imagery updated on webpage when ANY model/section completes. latest imagery arrives in stages and viewable before all completed. Rough priority order: Precip, winds, cloud, then the rest.... Internal arrival times logged: Global: 00Z from ~0415Z – 0600Z. (+ ~1 hrs transfer) 06Z from ~1000Z – 1115Z 12Z from ~1645Z – 1800Z 18Z from ~2200Z – 2300Z. External transfer of sub-set of products. Arrive approx 1 hour later. External transfers more variable.

Other aerosols (Ben Johnson) Carbonaceous aerosol, CLASSIC: fossil fuel bio-fuel biomass burning Anthropogenic emissions: 2014 monthly mean MACC/CityZen Biomass burning: 1 day lagged from GFAS Total carbon scaled x1.7 Once airborne, only dust assimilated in these runs!

Other aerosols Cost increase ~30% to ~40% Land DMS emss. Ocean DMS Antrhop. SO2 emiss. Sulphate aerosol forecasts with CLASSIC: Anthropogenic SO2 (MACC/CityZen) Volcanic SO2 Land based DMS Ocean DMS conc (fluxes wind based) Dust, carbonaceous, sulphate Just missing nitrate and sea salt? Cost increase ~30% to ~40%

Obs... DA Ensemble Other aerosols Extra aerosols in operational model? No. Cost. Running as operational? No. Cost, complexity. Run a single forecast instead.

Other aerosols Run a single forecast instead. Wait on operational forecast. Copy the start files Copy the aerosol from previous run Then run forecast. For this to work, Dust is from operational (with DA), other aerosols are passive tracers.

Other aerosols

Evaluation of reseach aerosol model (Fanny Peers, Exeter Uni.) vs AERONET

Case studies, comparing forecast vs MODIS

Case studies, comparing forecast vs MODIS Forecast performance: no systematic verification yet what has been done looks quite good.

Summary Met Office global NWP model developed in tandem with atmosphere climate model component. Resolution and major physics upgrade coming soon. No dust changes included. Dust changes for global NWP: land surface, bare soil z0, and convection interaction in development. Moving to MODIS Collection 6, monitoring PMAP. UK regional aerosol/chemistry model now mature Climate model migrated to GLOMAP MODE aerosol/chemistry Not ready for NWP use yet.

Summary In order to support flight campaigns, used old aerosol scheme (CLASSIC) to add ‘carbonaceous’ and sulphate aerosol to a research NWP run. Intended for Africa and India. Biomass burning aerosol used from GFAS fire emissions With a background biofuel+industrial emissions from climatology Cost is ~30 to 40% at 17km resolution. Limited verifcation so far, but looks good. Aircraft just completed first campaign in India. DACCIWA underway! Hopefully a demonstrated capability. Implementation pathway is not clear.

Questions and answers