OMI measurements of volcanic ash. could we make it faster?

Transcription

1 OMI measurements of volcanic ash could we make it faster? Johanna Tamminen, Mikhail Sofiev, Janne Hakkarainen, Gerrit de Leeuw, Seppo Hassinen, Julius Vira, Osmo Aulamo, Nick Krotkov, Simon Carn and Pepijn Veefkind Aura Science Team meeting Boulder

2 Eyjafjallajökull eruption April/May 2010 The European air traffic was partly closed for almost one week starting on 15.4 Transport of the ash was forecasted using dispersion models. Decisions were made by flight authorities based on forecasts Measurements were also needed. Interest in satellite data increased Volcanic Ash Advisory Centre (London)

3 OMI: aerosols and SO2 OMI AAI OMI SO Images by Simon Carn, Michigan Techn. Univ

4 Satellite data to support dispersion forecasts SILAM dispersion model used at FMI Input needed: Source term Strength Plume height Temporal evolution Global data Operational data Satellite data used at FMI OMI SO2, AAI, MODIS AOD Initial verification of model forecasts Variability in source Contribute to source term calibration SILAM dispersion forecast

5 Comparing plumes: OMI SO 2 measurements and SILAM forecast OMI SO 2 SILAM forecast Movie by Janne Hakkarainen, FMI

6 SILAM source term calibration Source term largest uncertainty in modelling dispersion Manual tuning of source term based on OMI SO2 columns Episode was split into time intervals with roughly constant emission rates For each interval the emission rate was tuned to optimize the agreement with forecast and OMI SO Figure by J. Vira (FMI)

7 Comparing distributions Point-wise comparisons too sensitive to position and exact shape Distributions compared using quantiles Difficulties: OMI background level constant release rate in SILAM Cumulative distribution function Figures by J. Vira (FMI)

8 Comparing distributions Manually chosen sub-regions easier to compare Cumulative distribution function

9 Operative use need for fast availability of data OMI, GOME-2 and SCIAMACHY Near Real Time data (3h, AAI, SO2) available sacs.aeronomie.be/nrt GOME-2 morning orbit SCIAMACHY morning orbit OMI afternoon orbit

10 Sodankylä Direct Broadcast receiving system EOS-Terra: Modis Direct Broadcast data processed Up to 8-10 orbits / day EOS-Aura: Since 2005 OMI ozone and UV products have been processed and images distributed Typically 3-5 orbits / day Coverage: Northern Europe Larger antenna and upgrade of ground segment under construction in Sodankylä MODIS cloud top pressure Sodankylä Coverage of OMI VFD data

11 Sodankylä VFD extension Decision was made in April/May 2010 to expand Sodankylä processing system to process SO2 and aerosols Close collaboration with FMI, KNMI and NASA Aerosol algorithm by KNMI SO2 algorithm by NASA Implementation to Sodankylä by FMI and Space Systems Finland System running and first products processed August 2010 Processing time ~15 min. Direct Broadcast receiver Processing of the OMI data

12 First tests: comparison of aerosol index Off-line VFD Clear discrepancy VFD values generally higher

13 First tests: comparison of SO2 Off-line VFD Clear discrepancy in SO2 products Stripes more visible in VFD

14 First tests: comparison of cloud fraction Off-line VFD

15 First tests: comparison of cloud fraction Off-line VFD Clear discrepancy in cloud products at some places

16 Validation of VFD SO2 and AAI on-going First products processed Discrepancy btw off-line and VFD products found Work ongoing to understand and correct differences Algorithm versions Level 1b data Auxiliary data AAI difference (off-line VFD)

17 Conclusions The international co-operation in interpreting OMI SO2 and AAI was very helpful for FMI. The interest in satellite measurements of atmospheric chemistry and aerosols increased considerably at FMI during and after the volcanic eruption in Iceland OMI data was found to be useful for monitoring the plume distribution and calibrating the emission source of Eyjafjällajökull eruption Decision was made to extend VFD system to process also SO2 and aerosol products. Implementation done Processing time ~15 min Validation on-going

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