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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 - PowerPoint PPT Presentation
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Dust storm forecasting at the UK Met OfficeMalcolm E. Brooks1*, Kerry Day1, Bruce Ingleby2, Yaswant Pradhan1, David Walters1,1 Met Office, Exeter, UK
2 ECMWF, Reading, UK
Castellanetta Marina, Italy, June 2014
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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!)
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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)
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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
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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.
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Downscaling the Global capability to high resolution
Consistent performance across global, SAM and 4km resolutions.
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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
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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.
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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.
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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.
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Upcoming developments - global resolution and dynamics
• 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
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• 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.
Current (GA3.1) model GA6.1 model
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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.
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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).
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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)
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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.
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Upcoming developments - Include MODIS obs. over 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
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• 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?
GA6.1 model + MODIS ocean
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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
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Upcoming developments - Dust included in global ensemble
• 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, main run T+120, main run
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T+0 T+120
• Individual N400 ensemble members, broadly comparable to the N768 main run.
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• 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.
• Ensemble mean also broadly comparable to N768 main run.
• Ensemble Std. Dev. is interesting.
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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.
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Questions?
• Dust AOD for 21Z, Thursday 6th June 2014, from 12Z Friday 30th May.
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Questions?
• Dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May (GA6.1, parallel suite)
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Questions?
• Ensemble mean dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May
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Questions and answers
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Dust Model Details
• NWP only: Verical flux partitioned to bins with prescribed emission size distribution
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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
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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.
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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.
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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!
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• Current combination of constraints and data do not give ‘optimal’ results…
• Need to look to other soil datasets
Dust emission control from soil properties
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Total Vertical flux: Gillette (1979)
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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.
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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.
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Dry river beds, lakebeds, Wadis
• Our emission scheme lacks alluvial sediement…
e.g. Sistan Basin – often dry