Real Time Modeling of Volcanic Clouds and Applications to Air Traffic Flow Algorithms

Forecasting the transport of volcanic ash clouds is vital in the predictions of regions that are potentially hazardous to aviation.  Constructing accurate forecasts of volcanic SO₂ and ash clouds is difficult as many parameters necessary to initialize model simulations are not well understood at the time of a volcanic eruption.  Analyses that combine observations and model simulations provide useful constraints on volcanic emission source terms and can progressively improve the modeled dispersion.  Recent developments in the NASA GOES-5 model allow for the dual simulation of volcanic ash and SO₂ clouds.  Column SO₂ and aerosol profile observations from the Ozone Monitoring and Profiler Suite (OMPS) Nadir Mapper and limb profiler instruments on board NOAA-NASA Suomi NPP satellite provide an initial estimate of the total SO₂ mass and altitude, and are used with backward transport analysis to make an initial volcanic emission height estimate.  Successive column SO₂ and aerosol measurements are utilized to “nudge” the modeled SO₂ into better agreement with observations, thus providing an overall improvement in forecast accuracy.

Producing real time volcanic cloud forecasts requires rapid inclusion of volcanic eruption events into the GEOS-5 Aerosol and SO₂ Forecasting System.  We propose implementing a parallel “dormant” model that is used to simulate the initial eruption off-line and update the operational model’s current state to include the current location of the volcanic emissions.  Air traffic flow algorithms can utilize real time quantitative forecasts of volcanic SO₂ and ash clouds to manage navigation around hazardous regions.  Metron Aviation has developed tools that use GEOS-5 volcanic simulations to estimate the impact to aviation of volcanic ash and/or SO₂ avoidance.  The details of the proposed system to process real time volcanic cloud forecasts is presented, and the application of GEOS-5 volcanic emissions forecasts within the Metron Aviation air traffic flow algorithms is demonstrated.