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Start of funding 01.01.2015

Implementation of a new gridding technique for an improved NASA OMI NO2 data product

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Recently, many efforts have been made to improve satellite measurement data sets of air pollutants for applications on a regional scale. The collaborative research of the Meteorological Institute of the Ludwig-Maximilians-Universität (LMU) and the Atmospheric Science Center at University of California (UC) Berkeley focuses on improving the satellite NO₂ data product of the Ozone Monitoring Instrument (OMI) on board of NASA’s Aura satellite. The global data product has a maximum spatial resolution of 13km by 24km and is typically sampled on a 0.25° x 0.25° grid. However, in order to be able to study processes and events on a regional scale, data sets with a higher spatial resolution are needed. The proposed efforts to achieve this goal include using updated ancillary parameters needed for the retrieval algorithm, like NO₂ profile shapes, surface albedo, terrain pressure, and aerosol profiles coming from simulations using a regional chemical transport model or satellite data sets with a higher spatial resolution. Another area of improvements will be the gridding process using histopolation methods that produce more detailed and realistic visualization of NO₂ distributions, so that e.g. cities and industrial areas can be better analyzed.

Final report:
The goal of this project was to combine the Berkeley High-Resolution (BEHR) NO2 retrieval data product from Prof. Cohen’s group with the newly developed gridding technique developed in Prof. Wenig’s group. The BEHR algorithm utilizes terrain and profile inputs for the retrieval of NO2 vertical column density from OMI with a higher resolution compared to the operational retrievals in order to account for the spatial and seasonal variation of these parameters that have been shown to significantly affect the retrieved NO2 column densities. This produces a NO2 data product with a spatial resolution higher than the OMI ground pixel size would allow. In order to combine the OMI data with higher resolved auxiliary data a new gridding technique has been used that interpolates the OMI data to a higher resolved grid while still reproducing the correct measurement values when integrating over the OMI pixel area. This process is called histopolation and allowed us to produce a data set which can show more spatial structures and details in the NO2 concentration maps.