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Dust storm forecasting at the UK Met Office. Castellanetta Marina, Italy, June 2014. Malcolm E. Brooks 1 *, Kerry Day 1 , Bruce Ingleby 2 , Yaswant Pradhan 1 , David Walters 1 , 1 Met Office, Exeter, UK 2 ECMWF, Reading, UK. Global Model Forecasts. N512 (~25km) resolution, 70 levels
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Dust storm forecasting at the UK Met Office Castellanetta Marina, Italy, June 2014 Malcolm E. Brooks1*, Kerry Day1, Bruce Ingleby2, Yaswant Pradhan1, David Walters1, 1 Met Office, Exeter, UK 2 ECMWF, Reading, UK
Global Model Forecasts • N512 (~25km) resolution, 70 levels • 4D VAR ensemble-hybrid data assimilation of wind, temperature, humidity etc. • 4D Var assimilation of MODIS dust obs. over Land • Soil Moisture assimilation uses ASCAT/Synop obs • Dust advected with 2 bins • Forecasts daily at 00Z and 12Z, runs for 144 hours • N768 (~17km) resolution upgrade due July 2014 • N1024 (~10km) due in 2016(ish!)
Downscaling the Global capability to high resolution • Global resolution converging on SAM • Implies SAM retirement • Does a higher resolution model work for dust? Global (25km) SAM (12km) Afghan (4km)
Downscaling the Global capability to high resolution • Global model drives an Afghan 4km ‘dynamical downscaler’ • Initialised from global, for every forecast, with global data at boundaries • No independent assimilation of obs
Downscaling the Global capability to high resolution • Meant to ‘add detail’ to global forecasts. Does it? • It appears to do that – needs more detailed verification.
Downscaling the Global capability to high resolution Consistent performance across global, SAM and 4km resolutions.
Using dust observations to initialise forecasts • 12km LAMs will be retired in late 2014. • Focus on improving the global model, • either in the forecast model or assimilation of dust observations
Assimilation of Dust Observations Merged MODIS “DEEP BLUE” and standard AOD product: • Near global coverage over a day (before filtering). • Uses obs only over land. • Standard MODIS filtered by type. • All DEEPBLUE obs included. • Results from ocean assimilation to come later.
Assimilation of Dust Observations:mean behaviour • Test results of re-running global forecasting system for December 2011, into January 2012. • Assimilating MODIS obs mostly adds dust • Esp. over Asia • Dust redistributed in Sahara • Improves skill vs AERONET. • Went operational in April 2013.
Upcoming developments - global resolution and dynamics • Global model upgrade due in July 2014 includes: • New dynamical core: • Improved solver, slight change of grid. • Less diffusive, more energetic, as forecast evolves. • More expensive, but more scalable on many cores. • Resolution upgrade from N512 (~25km) to N768 (~17km). • Physics upgrades to improve ‘weather’: surface T, cloud etc. • The most significant NWP upgrade at the Met Office in at least a decade. • No direct impact on dust forecast, • but does the dust forecast maintain skill? • Part of the ‘Global Atmosphere’ (GA) model development process. • Current model is GA3.1, upgrading to GA6.1.
Upcoming developments - global resolution and dynamics GA6.1 model Current (GA3.1) model • Comparison of dust AOD from current operational and resolution/dynamics/physics upgrade (untuned). • No major differences stand out. • Time mean AODs also similar.
Current (GA3.1) model GA6.1 model • Long range forecast drift away from the DA analysis (forecast bias): • Slightly reduced in the GA6.1 model. • Forecast model is slightly more consistent with the DA, and hence obs.
Upcoming developments - global resolution and dynamics Skill scores vs AERONET: • Equitable Threat Score • 0 – no skill • 1 – perfect model. • L1.5 data, 1hr window • Forecast shows skill, and GA6.1 neutral to slightly positive. • Poor skill at low AOD events – non dust aerosol? • Moderate dust events improved in GA6.1 • ETS always poor for rare events.
Upcoming developments - Dust interacting with radiation • Proposed model upgrade for late 2014 • Interactive dust used in radiation (instead of climatology). • No change at analysis time. • Bias at T+120 broadly similar, with a dipole pattern over N. Africa. • With a slight reduction in biases over N. Africa bias pattern. • Small (positive) impact on dust and general forecast evolution. • A reasonable dust climatology does most of the work. • Our dust has reflective optical properties (SSA = ~0.95 to ~0.97).
Upcoming developments - Include MODIS obs. over ocean • Proposed model upgrade for late 2014 • Bellouin, N., Boucher, O., Haywood, J., and Reddy, M. S. (2005) Global estimate of aerosol direct radiative forcing from satellite measurements Nature, 2005, 438, 1138-1141. • Jones, T. A., and Christopher, S. A. (2011) A reanalysis of MODIS fine mode fraction over ocean using OMI and daily GOCART simulations, Atmos. Chem. Phys., 11, 5805-5817, doi:10.5194/acp-11-5805-2011 • Includes MODIS observations over ocean, in specified regions: • Non dust aerosol filtered using additional MODIS retrievals, using criteria: • Fine Mode Fraction ≤ 0.4 • Angstrom Exponent ≤ 0.5 • Effective Radius > 1.0 μm • Mass Concentration ≥ 1.2×10−4 kg m-2 • AOD > 0.1 (still under review)
Upcoming developments - Include MODIS obs. over ocean • Proposed model upgrade for late 2014 • An example set of MODIS obs, after filtering, for a typical DA cycle.
Upcoming developments - Include MODIS obs. over ocean GA6.1 model + MODIS ocean • Comparison of dust AOD the upcoming GA6.1 model, and including MODIS over ocean (plus interactive dust). • Dust is being added in Saharan/other outflow.
GA6.1 model + MODIS ocean • By improving the analysis, the forecast drift from analysis changes: • Highlights future model developments to improve (long range transport): • Change fallspeeds? size distribution? Retune emissions? Soil properties in W. Africa?
Upcoming developments - Include MODIS obs. over ocean MODIS Ocean ETS: • Improves all AODs at T+0 • Skill score increase persists to T+24 • and to T+120, • throughout the forecast
Upcoming developments - Dust included in global ensemble T+0, main run T+120, main run • The GA6.1 operational suite is now running, in parallel, for final testing of performance, timeliness and robustness. • Dust included in the global ensemble when this parallel suite was set up. • Global 12 member ensemble, twice daily. • N400 (~30km) resolution, forecasts to T+144.
T+0 T+120 Main run • Individual N400 ensemble members, broadly comparable to the N768 main run. Ensemble
Main run • Ensemble mean also broadly comparable to N768 main run. • Ensemble Std. Dev. is interesting. • This is very much initial work – where do we go from here? • N400 dust configuration may need tuning. • Ensemble DA now an option for dust. Ens. mean
Summary: • Dust forecasting at the Met Office started with Local Area Models for defence applications. • We have since moved to a global model, • which successfully drives dust in high resolution dynamical downscalers. • Global Model forecasts benefit from MODIS dust observations over land (merging standard and DEEPBLUE). • Met Office to upgrade global resolution, dynamical core and model physics. Dust forecast performance is neutral to slightly improved. • Using forecast dust interactively in model radiation gives a very small benefit (relative to a dust climatology). • Assimilating filtered MODIS AOD over ocean gives a larger improvement in dust forecast skill. • Dust now included in our Global Ensemble forecasts, but we are not sure what to do with it yet.
Questions? • Dust AOD for 21Z, Thursday 6th June 2014, from 12Z Friday 30th May.
Questions? • Dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May (GA6.1, parallel suite)
Questions? • Ensemble mean dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May
Dust Model Details • NWP only: Verical flux partitioned to bins with prescribed emission size distribution
Assimilation of Dust Observations Met Office/Imperial College London AOD retrieval using SEVIRI (MSG): • Uses differences in IR channels • and a radiative transfer model, with 16 days of NWP model data to find a dust-free comparison. • Produces hourly observations.
Assimilation of Dust Observations: Assessment • Comparing against AERONET observations. • An ETS of 1 is a perfect forecast • 0 has no skill – this is a hard score as the obs a daylight only, so have a shorter time window than precip verification. • Dust assimilation gives a large increase in skill • Including SEVIRI is not quite right yet.
Upcoming developments - Dust interacting with radiation • Proposed model upgrade for late 2014 • Interactive dust used in radiation (instead of climatology). • NWP index: an internal metric of large scale global forecast performance • Interactive dust has a small positive impact.
Dust emission control from soil properties • Libyan coast dust: regular occurrence in the model, during the 2011 Air campaign • Intense scrutiny of forecasts and SEVIRI pink imagery during this period. • Benghazi was a source, but the coastal dust did not happen!
Total Vertical flux: Gillette (1979) Dust emission control from soil properties • Current combination of constraints and data do not give ‘optimal’ results… • Need to look to other soil datasets
Dust emission control from soil properties Reprocess current HWSD data? Even old datasets like Zobler 1degree look useful… Recent datasets like GMINER30 have a lot more detail. Are they useful? Geomorphology from Digital Elevation Models.
Dust emission control from soil properties • A preferential source map: • Ginoux (widely used) • Marticorena ’97: • or Bullard ’11: • Both global coverage and high resolution is required.
Dry river beds, lakebeds, Wadis e.g. Sistan Basin – often dry • Our emission scheme lacks alluvial sediement…