Modeling Volcanic Ash Transport and Dispersion: Expectations and Reality

Environment CanadaMeteorological Service of Canada

Environnement CanadaService météorologique du Canada

Modeling Volcanic Ash Transport and

Dispersion:Expectations and Reality

René Servranckx & Peter ChenMontréal Volcanic Ash Centre

Canadian Meteorological Centre



Presentation Topics: Ash Transport Models

Reality 20 years from now Expectations for Ash Transport Models (TM) Reality today / Limiting factors Areas for improvement



June 22, 2024



June 22, 2024



June 22, 2004!



• ACCURATE guidance on SPACE / TIME LOCATION / 3D STRUCTURE of airborne ash

• LITTLE (or no) UNCERTAINTY (ash / no ash)

• TIMELY delivery

Implications for TM?

What area aviation users TM expectations?



Components: Ash Modeling Problem

Accuracy and timeliness of TM guidance depends on:

• Volcanic Ash Source (‘’Source Term’’ / eruption parameters)

• Meteorology

• Transport and Dispersion (TM)



Despite uncertainties, TM:

• Are of great value!• Especially important for REAL-TIME, operational response • Sometimes, the ONLY guidance available • Must be used in conjunction with other tools (remote sensing, etc.)• Can not be used blindly!



Limiting Factors : VOLCANIC ASH SOURCE

• Eruption parameters largely unknown / poorly quantified• Detection of eruptions / airborne ash is problematic• Poor quantitative estimates of atmospheric ash loading / only 2D 3D is needed for TM• Threshold ash concentrations that pose threat to ‘’aviation’’ (?) May be very small (NASA DC-8 Hekla incident)• ‘’Visual Ash Cloud’’ criterion on TM guidance is subjective• DEFAULT SCENARIOS and LOW THRESHOLD values in TM guidance



Limiting Factors : METEOROLOGY

• HORIZONTAL and VERTICAL resolution of Numerical Weather Prediction (NWP) Models• Vertical coordinates are not Flight Levels ‘’standard atmosphere’’• Representation of earth’s surface (topography) in NWP models

• Mt Mckinley, AK 6194 m 2640 m

• Incomplete knowledge of initial conditions of the atmosphere• Predictability of atmosphere / Accuracy of NWP vary with flows / patterns



Limiting Factors : TRANSPORT / DISPERSION

• VOLCANIC ASH SOURCE component• METEOROLOGY component • Parameterization of dispersal, removal and deposition of ash• Real time assimilation of airborne ash is not done• Predictive ability varies with atmospheric conditions



Areas for improvement: VOLCANIC ASH SOURCE COMPONENT

• 1998 and 2003 WMO / ICAO volcanic ash meetings: ‘’Substantial improvements could be made in TM guidance if source term estimates were improved’’• ICAO (IAVW Ops Group) to IAVCEI: QUANTITATIVE estimates of eruption parameters for TM? • NASA DC-8 encounter with Hekla diffuse plume: damage from very small ash concentrations (?)



Areas for improvement: VOLCANIC ASH SOURCE COMPONENT

• If unconditional ash-avoidance is the rule, small concentrations must be accurately predicted Good estimate of Source term is important!• Remote sensing: Any technological advancement that might improve quantitative estimates of the 3D distribution of airborne ash • Assimilation of volcanic ash data in TM : Exploratory work has been done (Siebert et al. 2002; NOAA Air Resources Laboratory) • How much can we achieve? Highly dependent on remote sensing improvements (quantitative 3D distribution)



Areas for improvement: METEOROLOGY and DISPERSION / TRANSPORT Components

• Improvements to NWP Models are ongoing• Improvements to TM also ongoing• ENSEMBLE FORECASTING: Already done for NWP Models; applicable to TM • Many runs (single or multiple models) using slightly different initial conditions• BASIC IDEA: AVERAGE of many runs BETTER than single run• Spread among runs is gives an estimate of uncertainty



Example: ‘’Visual ash clouds’’ from 4 TM runs valid at same time



Finagle’s Laws of Information

• The information you have is not what you want

• The information you want is not what you need

• The information you need is not what you can obtain

• The information you can obtain costs more that you want to pay



Corollaries

• What you ‘’see’’ / interpretation depend on :

• Tools / Technology

• How information is presented

• How one looks at information

• What you ‘’see’’ may not be what you get !









Impact of changing ‘’visual ash cloud’’ value

•ALL IMAGES TO FOLLOW ARE FROM SAME TRANSPORT MODEL RUN WITH SAME SOURCE TERM CONDITIONS • 1 hour eruption of Cleveland starting 15 UTC 19 Feb 2001• Images valid 45 hours after start of eruption• CANERM (TM) diagnostic average ash concentration in FL200 - FL350 (micrograms per cubic meter) • perception of where ash is or is not present!



200 100 80

50 10 1



Summary Transport Models:

Expectations are high Despite uncertainties, VALUABLE! Must be used with other sources of information Can not be used blindly /require careful interpretation

/ knowledge of uncertainties New ways of looking at information and estimating

uncertainties (Ensemble forecasts) Accuracy can be increased by reducing uncertainties

What can we do to bridge the gaps?

Documents

Modeling Volcanic Ash Transport and Dispersion: Expectations and Reality