Two new datasets provide Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) footprint data products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014.
Meteorological fields from version 3.6.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio (ppm) per surface flux (umol m-2 s-1), quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. Footprints are provided for the two receptors at two temporal and spatial scales: three days of surface influence over the whole North American coverage area at 1-degree resolution and 24 hours of surface influence within a smaller region close to the measurement locations ('near field') at 0.1-degree resolution.
Note that the "particle" dataset contains both the particle trajectories and the gridded footprint data. The "footprint" data are also provided as a stand-alone dataset, for ease of use.
Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Particle Trajectories for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1596
Nehrkorn, T., M. Sargent, S.C. Wofsy, and M. Mountain. 2018. WRF-STILT Gridded Footprints for Boston, MA, USA, 2013-2014. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1572
Data center: ORNL DAAC
Sponsor: NASA EOSDIS