Real-Time Estimation of Volcanic Ash/SO2 Cloud Height from Combined UV/IR Satellite Observations and Numerical Modeling Gilberto A. Vicente NOAA National Environmental Satellite, Data, and Information Service (NESDIS) Office of Satellite Data Processing and Distribution (OSDPD) CICS Science Team Meeting September 8 th 2010 College Park, MD Eric Hughes University of Maryland - College Park Cooperative Institute for Climate and Satellites (CICS) Wilfrid Schroeder University of Maryland - College Park Cooperative Institute for Climate and Satellites (CICS)

Source 1 : How volcano chaos unfolded: in graphics, BBC News ( Volcanic emissions damage aircraft British Airways Flight 9 - (1982) Experienced full engine failure mid-flight (flame-out of all four engines) Ash Ash melts and forms glassy coating Clogs Jets fuel and cooling systems Source 1 The effects on volcanic ash on airplanes: Several reports of Airplane-Ash interactions occurred in the 1980’s and early 1990’s. The results of such interactions were: severe damage to airplanes and often mid- flight engine failure. Volcanic Eruptions Hazards to Aviation “Ladies and gentlemen, this is your captain speaking. We have a small problem. All four engines have stopped. We are doing our damnedest to get them under control. I trust you are not in too much distress.” - Cpt. Eric Moody

In the 1990’s, a global network of 9 Volcanic Ash Advisory Centers (VAACs) were established. The Role of the VAACs  Monitoring and tracking volcanic ash in their areas of attention.  Coordinate the Meteorological Watch Offices (MWO’s), Volcano Observatories, and Area Control Centers/Flight Information Centers (ACC/FIC) for the prompt notification and distribution of volcanic ash information and warnings. Still high demand for more accurate monitoring/forecasting techniques. Uncertainties in monitoring/forecasting lead to the closure of large air spaces.  $1.7 Billion: Estimated airspace closure cost from Iceland's Eyjafjallajokull volcanic eruption 2 Source 2 : IATA Map of global VAAC coverage Monitoring/forecasting improvements have lead to few hazardous Airplane/Ash interactions since the early 1990’s.

Ash forecasts from the London VAAC The ash height was understood to be between 2km – 11km [ April 15 th 06:00 UTC ] Satellite Observations Dispersion Models Reports: IR: AIRS, AVHRR UV: OMI, GOME-2 Vis: GOES, MODIS (multi) Vis/IR: MSG(SEVERI) PUFF HySPLIT NAMES Flex-Part SIGMETs Airlines News Volcanologists (Observatories, USGS, Smithsonian) Volcano Cameras etc … VAAC Resources Producing Ash Forecasts

UV Sensors - Polar OMI SO 2 IR – Polar/Geo April 15 th 13:30 UTC Measurement Technique  nm difference from Rayleigh spectrum Advantages  Effective over land or sea  No water cloud interference Disadvantages  Day time only  Smoke and dust have same signature  Longer latency time Advantages  Day and Night Times  Operational Satellites  Geo: High spatial/temporal res. Disadvantages  Misses detections due to water vapor interference and cold clouds – false alarms  Geo: Poor observations at high latitudes 10 – 12  m BTD - Split Window April 15 th 12:00 UTC MODIS (Terra) April 15 th 11:35 UTC AIRS AI (Ash)Ash Acknowledgments to Arlin Krueger April 16 th 16:00 UTC MSG RGB VIS/IR – Polar/Geo VAAC Resources Satellite Observations

Ash Forecasts (Washington VAAC) Hybrid Single Particle Lagrangian Integrated Trajectory Model (HySPLIT) Simulations for 4 altitude regions and 6 and 12 hour forecast  PUFF (Alaska - VAAC)  NAMES (London - VAAC)  FLEX-PART (NILU)  HySPLIT (Washington, DC - VAAC) Simulate the dispersion and transport of volcanic ash into the atmosphere using meteorological forecast data Approaches: Lagrangian, Eulerian or both VAAC Resources Dispersion Models

Using Models and Satellite Observations to Forecast Ash Transport Even with current capabilities, there are several unknown “variables” in ash forecasting: Ash density (size distribution) Ash height Start and stop eruption times An understanding of the ash height and concentration are the most important variables needed in airline rerouting. These VAAC resources are typically used as follows: Reports: Find information about eruptions time/duration and injection altitude (when available) Satellites: Locate and track ash plumes Models: Forecast ash transport

Volcano Monitoring Create a platform that allows users to view near real-time volcanic data products. Volcanic Cloud Height Estimation Construct a system which compares near real-time data with model simulation data. Project Overview Our Approach Run various dispersion model simulations and see which initial height conditions reconstruct satellite observations.

Volcano Monitoring Volcanic Cloud Height Estimation Retrieve satellite data* SO2/AI Retrieval* Place SO2/AI maps and data files on our web server These project parts were developed independently, but work together as a set of tools for users. Model Initialization Run model simulations Post-Processing Compare to satellite observations Users * Processed at NASA GSFC Project Overview

Volcano Monitoring The NOAA/NESDIS OMISO2 product delivery and visualization user interface Global composites Volcano sectors Satellite orbit Digital images

SO 2 Cloud (Reflectivity)AI Volcanic Sector Imagery Volcano Monitoring

Input data Gridded data Compare overlap AIRS (Ash) PUFF (2km Simulation) Overlapping region: Estimating Cloud Heights: Implementation  Compare the results from the various simulations to satellite observations.  Run the dispersion model (PUFF) using various initial height conditions Basic Concept Volcanic Cloud Height Estimation

Statistical comparison: A = Number of Coincident Satellite and Model points B = Number of Satellite points NOT coincident with model data C = Number of Model points NOT coincident with satellite data Compute two statistic variables:  Probability of Detection (PoD): PoD = A / (A+B)  False Alarm Rate (FAR): FAR = C / (A+C) Probability of Detection Simulation Height (km) Currently algorithm uses only PoD Model-Satellite Comparisons Volcanic Cloud Height Estimation

Volcanic Cloud Height Estimation: Online Model

OMI-AI April 15 th 12:00 UTC Input Data

PUFF Simulation OMI AI

All profiles show two distinct peaks in height: 8-10 km and 5-4 km. OMI – AI/SO 2 AIRS-Ash The Eyjafjallajokull eruption Analysis Summary Observations from April 15 th 2010

8 km 2 km OMI-AI Vertical profile Visual Analysis April 15 th 12:00 UTC  The statistical and visual analysis do not match exactly  The statistics predicts the 10km and 4km simulations heights  A visual analysis suggests the 8-7km and 2-3km heights  False Alarm Rate (FAR) analysis should improve the statistics The Eyjafjallajokull eruption Limitations

Description of an automated system to compare dispersion model outputs with Near-Real-Time (NRT) satellite observations of volcanic emission  Generate a series of maps overlaying various model simulations atop of satellite observations  Perform a statistical analysis on the simulation/satellite data to determine which simulation injection heights produce the best match to satellite observations  Perform these tasks quickly, requiring little input from the analyst Summary and Conclusions

 Compare the model simulations with volcanic ash products from other satellites/sensors: GOES, MSG (SEVERI) AVHRR, MetOp-A (IASI), MODIS, etc.  Generate automated volcanic ash height forecast based on the statistical analysis of the simulation/satellite data. Future plans

Arlin Krueger, Simon Carn, and Keith Evans: JCET/UMBC George Serafino: NOAA/NESDIS Nick Krotkov and Kai Yang; GEST/UMBC Jerry Guo: Perot Systems Government Services Pieternel Levelt: KNMI Acknowledgements

USER/WEB SERVERDATA SERVERMODEL SERVER Submit request (User) Check to see if a request has been submitted … Retrieve the request, then submit the request to PUFF Run the PUFF simulations and perform the height analysis. Generate output images w/ IDL Retrieve output images and data files. Submit them to the USER SERVER (web) Display the results Firewall … show the status of the analysis … Online model setup

MISR Team, JPL and GSFC Plume Heights MISR Stereo-Derived Ash Plume Heights April 14 th, 2010 MISR derived heights: The leading part of the ash cloud is around 7.3 km and the trailing part around 2.3 km Visual analysis: Closely agrees with the MISR derived heights Statistical analysis: Higher than the MISR derived heights, but agrees the VAAC reports (cited the max height ~11km) Comparison with other height measurements The Eyjafjallajokull eruption