Dust storm forecasting at the uk met office
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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

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

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

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 resolution1

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 resolution2

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 resolution3

Downscaling the Global capability to high resolution

Consistent performance across global, SAM and 4km resolutions.


Using dust observations to initialise forecasts

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

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

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

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 dynamics1

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.


Dust storm forecasting at the uk met office

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 dynamics2

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

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

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 ocean1

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 ocean2

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.


Dust storm forecasting at the uk met office

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 ocean3

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

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.


Dust storm forecasting at the uk met office

T+0

T+120

Main run

  • Individual N400 ensemble members, broadly comparable to the N768 main run.

Ensemble


Dust storm forecasting at the uk met office

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

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

Questions?

  • Dust AOD for 21Z, Thursday 6th June 2014, from 12Z Friday 30th May.


Questions1

Questions?

  • Dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May (GA6.1, parallel suite)


Questions2

Questions?

  • Ensemble mean dust AOD for 12Z, Thursday 6th June 2014, from 12Z Friday 30th May


Questions and answers

Questions and answers


Dust model details

Dust Model Details

  • NWP only: Verical flux partitioned to bins with prescribed emission size distribution


Dust storm forecasting at the uk met office

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

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 radiation1

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

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!


Dust emission control from soil properties1

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 properties2

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 properties3

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

Dry river beds, lakebeds, Wadis

e.g. Sistan Basin – often dry

  • Our emission scheme lacks alluvial sediement…


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