ROSES Proposals
PolArimetric RetrievAls of Biomass-burning aerosols Over LAnd (PARABOLA)
PI: Jacek Chowdhary - Columbia UniversityCo-Is: Snorre Stamnes (NASA Langley Research Center); Hans Moosmüller (Desert Research Institute); Matteo Ottaviani (Terra Research, Inc); Keren Mezuman (Columbia University)
PACE data will offer unprecedented opportunities for new aerosol products from inversions of space-borne observations. Of particular interest will be the synergistic exploitation of UV-VIS multi-angle polarimetry from the SPEXone and HARP2, which has already been proven to increase the accuracy of aerosol retrievals over oceans. PACE polarimetry offers also unique yet unexplored opportunities to retrieve aerosols retrievals over land because land polarization is dominated by the variance of slope distribution and the refractive index of the reflecting surface facets – both of which can be considered spectrally invariant in the UV-VIS as opposed to land surface albedo.
PARABOLA will use PACE polarimetry data to retrieve a complete suite of ambient aerosol properties over land with a focus on smoke plumes over the Western US from SPEXone and HARP2 data. The retrieval results will be compared with those from coincident AERONET and PACE-PAX observations. Furthermore, PARABOLA will use these retrievals to infer PM2.5 data that will be shared with our collaborators and stakeholders in the air quality and climate modeling communities to (1) improve air quality forecasts by the NOAA National Weather Station (NWS) that inform vulnerable populations of poor air quality and possible mitigative action; (2) improve predictive smoke emission and transport models that aid suppression efforts for wildfires and planning efforts for prescribed burns toward minimizing human exposure, especially for vulnerable populations.
PARABOLA will use PACE polarimetry data to retrieve a complete suite of ambient aerosol properties over land with a focus on smoke plumes over the Western US from SPEXone and HARP2 data. The retrieval results will be compared with those from coincident AERONET and PACE-PAX observations. Furthermore, PARABOLA will use these retrievals to infer PM2.5 data that will be shared with our collaborators and stakeholders in the air quality and climate modeling communities to (1) improve air quality forecasts by the NOAA National Weather Station (NWS) that inform vulnerable populations of poor air quality and possible mitigative action; (2) improve predictive smoke emission and transport models that aid suppression efforts for wildfires and planning efforts for prescribed burns toward minimizing human exposure, especially for vulnerable populations.
Collaborators:
Susanne Bauer,
Maegan DeLessio,
Kostas Tsigaridis,
and Kenneth Sinclair (Columbia University, NASA GISS);
Alexei Lyapustin (NASA GSFC);
Vanderlei Martins and
Lorraine Remer (UMBC);
Johnathan Hair and
Gregory Schuster (NASA Langley Research Center);
Fred Harris (EPSCoR/IDEA Foundation);
Bret Schichtel (Cooperative Institute for Research in the Atmosphere);
Matthew Strickland (University of Nevada, Reno);
Adam Watts (US Forest Service);
Otto Hasekamp and
Bastiaan van Diedenhoven (SRON)