Upload
others
View
2
Download
0
Embed Size (px)
Citation preview
Modeling and forecasting the distribution of volcanic ash from the Eyjafjallajökull
eruption
A. Stohl, N. I. Kristiansen, S. Eckhardt, P. Seibert, F. Prata, J. F. Burkhart, K. Tørseth
Picture courtesy: Magnús Tumi Guðmundsson
This
study is partly supported
by ESA within
the Support to Aviation
for Volcanic Ash Avoidance
(SAVAA) project
15 April 0 UTC 16 April 0 UTC
17 April 0 UTC 18 April 0 UTC
The synoptic situation: Geopotential
@ 500 hPa
The FLEXPART modelLagrangian
particle
dispersion
model, similar
to the one
used
at the London VAAC
Meteorological
input data:Forecasts
use
NCEP GFS data, Analyses ECMWF data
Simulation
of volcanic
ash
in 31 size
bins-
gravitational
settling
-
dry deposition-
wet
deposition
Transport of 15 million ash
particles
by mean
winds, turbulence, convection, sedimentation
FLEXPART simulations of the eruptionSecond forecast ready: 15 April 16:00 UTC
http://transport.nilu.no/products/eyjafjallajokull
Forecasting System
Interactive
Tool
The source term – the first great unknown• Total ash
emission highly
uncertain-
Assume
10% of reported
tephra
production
in modeled
size
range (0.5-290 μm)
• Time variation
of emission rate not well
known-
Take what’s
available, anecdotal
evidence
• Eruption
column
height
is variable-
Reports, satellite
data (max. height
11 km)
• Height
emission profile
unknown- 4-layer C-shape
• Ash
size
distribution
at point
of emission not well
known-
Taken
from ground
samples around
Eyjafjallajökull
but
they
are biased
towards
larger
sizes
All these
uncertainties
will
affect
the final model
result!
Ash plume transport to Europe
Comparison with SEVIRI ash retrievals
15 April, 10 UTC
FLEXPART total ash15 April, 9-12 UTC
Comparison with SEVIRI ash retrievals (credit: Mike Pavolonis)
17 April, 20 UTC
FLEXPART total ash17 April, 18-21 UTC
Comparison with SEVIRI ash retrievals (credit: Mike Pavolonis)
18 April, 4:20 UTC
FLEXPART total ash18 April, 3-6 UTC
CloudsClouds
Comparison with AURA/OMI aerosol index (credit: AURA/OMI team)
FLEXPART total ash15 April 9-12
AURA/OMI aerosol index15 April 12 UTC
?
Increased
emission rate too
late?
Comparison with SEVIRI ash retrievals
16 April, 6 UTC
FLEXPART total ash16 April, 3-6 UTC
Comparison with SEVIRI ash retrievals
16 April, 18:30 UTC
FLEXPART total ash16 April, 18-21 UTC
Good agreement with London VAAC: 16 April 00:00
Notice: qualitative
comparison;isolines
not strictly
comparable
16 April 18:00
17 April 12:00
Howto
improve
the source termUse
observation
at the eruption
Site
(a priori) andUse
inverse modelling
approach
Effect
of wind
shear4-Nov-2002 eruption of Reventador, Ecuadorare
SO2
and Ash
Eruption
Sources x
(1..n) xa
a priory profile
Satellite observation y0
(1..m)
M
Emission sensitivity Matrix (m
n), as obtained from FLEXPART
σ
standard error of observation
Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode, P. Seibert and A. Frank, ACP, 4, 51-63, 2004.
Inversion
Method
Emission Profile
(Jebel, 2007)
Challenges
of the EYJA* eruptionSource TermEruption
takes place
over a long
time periode, emissions
are constantly
added
up (started
runs every
3 hours
over 2 weeks, satellite
images available
every
15 mins -
SEVIRI)3 unknown
variables: timing, emission profile, size
distribution
TransportMainly
Ash
is emitted
–
shows many small‐scale features:
‐
ground‐bases lidar
of limited representativity, aircraft in‐situ data may
also be difficult to interpret
‐
satellite data probably best data source
‐
observations alone far from delivering information need by air traffic
authorities
Why
is EYJA* difficult
to model
Different grainsize
–
settling
–
different transport direction
Conclusions•
Comparison with
measurement
data encouraging, FLEXPART and operational
VAAC model
(NAME) in good qualitative agreement
•
Quantitative dispersion simulations require quantitative source term (function of height, time, particle size range) -
SO2
source terms for explosive
eruptions can be derived well with our inversion method ‐
ash
source term for
continuous eruption much more complicated, research and development needed ‐
important role for inverse modelling
of satellite data is likely, but kind and way of
usage of additional (in‐situ, ground‐based and airborne) measurements needs to
be worked out
•
Long‐lasting eruption of medium strength, emitting into the middle and upper
troposphere, have the strong impacts on air traffic as large regions are
contaminated (due to synoptic variability) and starting/landing
inhibited (due to
low elevation of ash) ‐
the cloud shape tends to be quite complicated after some
days of transport
Thank
you
for your
attention, ESA for funding.