In situ validation of ash cloud model

Transcripción

Jet Propulsion Laboratory
California Institute of Technology
David Pieri
Jet Propulsion Laboratory/NASA
Pasadena, California, USA
Gary Hufford
NOAA National Weather Service
Anchorage, Alaska, USA
Geoff Bland
NASA Goddard Space Flight Center
Wallops Island, Virginia, USA
Ali Abtahi
Aerospace Missions Corporation
El Paso, Texas, USA
In situ validation of ash-cloud
models—
R&D
a) Powerful rapidly dispersing ash clouds present a
dynamic aviation threat that widens minute by minute
during and after an eruption.
b) Starts at local scale but rapidly becomes regional and
large eruptions can become continental to global in
effect.
c) Physical characteristics of the eruption clouds are
inferred from remote sensing data with few validation
measurements.
d) Ash concentration, trajectory, altitude, and lateral
extent estimates are highly dependent on
• Dispersion models
• Radiative transfer models
• Remote sensing data reduction models
Ash & SO2 transport
(courtesy of D. Schneider)
SO2 Detection and Tracking—Orbital Detection
of Tropospheric SO2 ASTER over Hawaii
(Courtesy of V. Realmuto)
Courtesy Vince Realmuto, JPL
SO2 Detection and Tracking—Orbital Detection
of Tropospheric SO2 ASTER over Etna, 2000
Eruption
models—
R&D
a) Observations are necessarily often over
remote areas, far from operational
infrastructure.
b) Ash clouds from explosive eruptions exist
at high altitudes (~10KmASL+).
c) Accuracy and precision of orbital remote
sensing measurements are largely
educated guesses.
d) To date there has been little to no in situ
models—
R&D
“…there are no standard data products specifically designed for
volcanic ash and volcanic gases…” (Prata et al., IEEE, 2009)
“…There are also no internationally agreed satellite-based
volcanic product standards and no protocols or procedures in
place to permit specification of safe limits for aviation
encountering airborne volcanic substances. Part of this problem
lies with the lack of sufficient information regarding what
constitutes safe operating limits when flying near to volcanic
clouds. Part of the solution lies in being able to provide
quantitative satellite information and some means for validation.”
(Prata et al., IEEE, 2009)
“…Currently, there is no objective means for determining the
injection height of a volcanic eruption, and usually multiple
dispersion simulations must be run and matched “by eye” to
current or prior satellite imagery.” (Prata et al., IEEE, 2009)
models—
R&D
“…Sensitivity analyses by Wen and Rose [1994] suggest mass
loading errors of 40–50%.” (Prata and Kerkmann, GRL, 2007)
“…We emphasize here that neither of these SEVIRI retrieval
schemes have been properly validated against independent
measurements. Based on an error budget for the TOVS/HIRS SO2
retrieval scheme [Prata et al., 2003], a conservative error for
SEVIRI is ±10 D.U. on a single pixel basis. This gives a mass
loading retrieval error of approximately ±0.01 Tg(S), for the SO2
clouds discussed here. (Prata and Kerkmann, GRL, 2007)
“…there is experimental evidence that lapilli can be suspended in
air for some hours after the explosion. A sorting of ash particles
is also typical during the evolution of the erupted volcanic cloud.
Unfortunately, we do not have any chance to verify these results
within the ash plume…The lack of in situ ground data
unfortunately prevents the validation of these radar-retrieved
f h
t ” (M
t l IEEE 2006)
models—
R&D
• Cheap-ish (individual investigators)
– Small UAVs, tethered balloons, low altitude, limited
range
– Radiosonde-class balloons, free-flying with small
payloads: 20-30Kft, 30mi range
– Larger hobby class rockets, 30-40Kft, limited lateral
range
• Expensive-ish (national assets)
– Professional sounding rockets: 100Kft, 100+mi range
– Manned aircraft with dropsondes: <65Kft, 4-5000mi
range
– UAVs with dropsondes: <65Kft, 11,000mi range
– Fly NASA DC-8 through a Hekla Volcano plume
(US$3.5M)
NASA Volcanic Ash Collection Platform
NASA DC-8 Research Aircraft Landing
at Kiruna, Sweden, 2002, as part of
the international SOLVE experiment
Ground track of NASA DC-8 volcanic ash encounter, flight 123, Feb 27-28, 2000, Edwards, USA to
Kiruna, Sweden
Forecast mostnortherly extent
of ash
Hekla
Volcan
o
NOAA AVHRR Image
Hekla Ash Cloud
North of Iceland with DC8 flight track
Little to no split-window detection—ice coated particles
NASA DC-8 Research Aircraft Engine
Parts after disassembly upon return
from the SOLVE experiment
(Courtesy NASA Dryden FRC)
Plugged Cooling Holes
Blistered thermal coating
Erosion of Leading Edge
Build-up of Ash
Inside Passages
Onboard solid aerosol collection data
from the NASA DC-8 Research
Aircraft engaged in the Kiruna SOLVE
experiment
(Courtesy NASA Langley RC)
Caltech Scanning Electron Microscope backscatter
chemistry results from analyses of Keddegg Air
Conditioning Filters from NASA DC-8 Research
Aircraft
(from Pieri et al., 2002)
Unused
Normal use
Caltech Scanning Electron
Microscope imaging of the Keddeg
Air Conditioning Filters from NASA
DC-8 Research Aircraft
(from Pieri et al., 2002)
After ash
encounter
Unmanned NASA Global Hawk, Dryden Facil
(Serious!) National Asset
60,000ft
11,000mi
>30hrs
“Deliberate”
Response
(1-2wks?)
Payloads:
Imaging,
Dropsondes,
In situ
sampling
Unmanned NASA Ikhana, Dryden Facility
40,000+ft
2500+mi
~30hrs
Moderate
Response
(<1wk?)
Payloads:
Imaging,
Dropsondes,
In situ
sampling
Other NASA Research Aircraft
National Assets
NASA
Gulfstream III
45,000ft
3,400mi
6hrs
Quick response
(<3hrs)
NASA ER-2
70,000ft+
>4,000mi
10hrs
Payloads:
Moderate Response
Imaging,
(24hrs)
Dropsondes,
(In situ sampling)
Payloads:
Imaging,
Dropsondes,
(In situ sampling)
JPL Micro-UAV for ASTER SO2
National Asset (Not! ☺)
cal/val
XPi/SO2-1 “Profiler”
3rd
generation
SO2
sensorSO2-C
µUAV developed in partnership between
Geoff Bland and Ted Miles at NASA Wallops
Island Flight Test Facility, VA
and
Dave Pieri and Ali Abtahi at JPL
(SO2, %H2O, T, P, GPS, ; 1ppb sensitivity ]
• ~500ft AGL
• 1km radius
• ~30min flight duration
• radio controlled
• instrument test bed
Dave Pieri, JPL
JPL Micro-UAV for ASTER SO2
cal/val
T (K ), A lt(ft), [S O 2 ]p p b * 1 0 , H 2 O %
(p e r le g e n d )
SO2 Profiler Data Flt#1--19Jun06
500
450
400
350
300
250
200
150
100
50
0
T [K]
Altitude [ft AGL]
SO2 [ppb]*10
H2O [%]
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70
Elapsed time (min)
University of Bologna Prototype UAV
Courtesy of Drs. Saggiani and Buongiorno
22
SIERRA UAV, NASA Ames
23
SO2 /Ash Retrieval
Geoff Bland, NASA Wallops µUAVs
Sensors With Wings: Recent Projects
Aeros 205: Visible and
Thermal Infrared Video
Downlink, GPS, T/RH/P
Follow-on to ImageAire
series, Aeros 100 & 200
(Coronado, et al.)
Sulfur Dioxide Sensor
for Volcano Plume
Research (Pieri, et al.)
G. Bland - March 22, 2006
“Critter Chaser” for
Animal Tracking
(Wilkelski, et al.)
National Assets
models—
R&D
NASA
Wallops
Flight
Facility,
Wallops
Island,
VA, USA
models—
R&D
International Assets
For NASA Wallops Flight
Facility
National Asset
models—
R&D
Poker Flat Research Range
University of Alaska,
Under contract to
NASA Wallops
2001 eruption of Mt. Cleveland, Alaska—
threat to aviation
On-the-cheap
Micro Sensor Package In flight on tethered balloon
Sand Canyon, Santa Clarita, CA; March 2009
On-the-cheap
Micro Sensor Package: SO2, P, T, %H2O, Data Logg
Balloon, Kite, and/or Free-Flying UAV
models—
R&D
On-the-cheap
Sand Canyon Tethered Balloon Package Flight Test Data, March 2009
Derived Pressure Altitude (ftAGL)
0
Instrument “Time”→
27min
models—
R&D
• The validation of the accuracy of aerosol and gas
retrieval algorithms for the characterization of high
altitude (~10kmASL) drifting ash clouds from explosive
eruptions remains a difficult challenge.
• Of special concern with respect to aircraft operations are
the validity of estimates of the lateral and vertical extent
and concentrations of drifting volcanic ash clouds
provided by aerosol transport models and remote sensing
techniques.
• Actual in situ sampling of the spatial distribution and
concentration of airborne volcanic ash and sulfur dioxide
has been rare and serendipitous.
models—
R&D
• The current paucity of in situ data is dictated by the
obvious extreme difficulty of deploying and recovering
samples and physical/chemical data over remote regions
and high altitudes where such clouds occur, especially
given the demonstrated danger to manned aircraft that
such ash concentrations generally present.
• Nevertheless, there exist a variety of technological
approaches for conducting such in situ validation
experiments, including the deployment of dropsondes, the
use of unmanned aircraft to fly through ash clouds, and the
deployment of instrumented balloons and sounding
rockets through such clouds, in coordination with
multispectral satellite, airborne, and ground-based
models—
R&D
a) Most important: how crucial are the
validations of models and data reduction
techniques? Is just knowing the ash is there
“enough” to manage safety concerns? Sine
qua non.
b) What are the consequences of establishing
better confidence on knowledge of ash
concentrations? Will this propagate to smaller
safety margins as air carriers make more finely
tuned risk-benefit analyses? “Don’t ask, don’t
tell?”
c) How strongly are we willing to advocate for
models—
R&D
a) In situ observations by Individual
Investigators:
• Low cost options for low altitudes (<5Kft?):
balloons, kites, small UAVs?
• Low cost options for higher altitudes (530Kft?): small sounding rockets, balloons?
• Sponsored by individual research grants
b) In situ observations by Organized Consortia:
• More expensive options (0-65Kft)
• National assets: manned aircraft,
unmanned aircraft, Skyhook balloons,
larger sounding rockets.
c) Coordination:
• Informal working groups?
• Organized international workshops?

In situ validation of ash cloud model

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