The Berkeley High Resolution Tropospheric NO_2 product

Creators: Laughner, Joshua L.; Zhu, Qindan; Cohen, Ronald C.

Abstract

We describe upgrades to the Berkeley High Resolution (BEHR) NO2 satellite retrieval product. BEHR v3.0B builds on the NASA version 3 standard Ozone Monitoring Instrument (OMI) tropospheric NO_2 product to provide a high spatial resolution product for a domain covering the continental United States and lower Canada that is consistent with daily variations in the 12km a priori NO_2 profiles. Other improvements to the BEHR v3.0 product include surface reflectance and elevation, and factors affecting the NO_2 a priori profiles such as lightning and anthropogenic emissions.- We describe the retrieval algorithm in detail and evaluate the impact of changes to the algorithm between v2.1C and v3.0B on the retrieved NO_2 vertical column densities (VCDs). Not surprisingly, we find that, on average, the changes to the a priori NO_2 profiles and the update to the new NASA slant column densities have the greatest impact on the retrieved VCDs. More significantly, we find that using daily a priori profiles results in greater average VCDs than using monthly profiles in regions and times with significant lightning activity. The BEHR product is available as four subproducts on the University of California DASH repository, using monthly a priori profiles at native OMI pixel resolution (https://doi.org/10.6078/D1N086) and regridded to 0.05° × 0.05° (https://doi.org/10.6078/D1RQ3G) and using daily a priori profiles at native OMI (https://doi.org/10.6078/D1WH41) and regridded (https://doi.org/10.6078/D12D5X) resolutions. The subproducts using monthly profiles are currently available from January 2005 to July 2017, and will be expanded to more recent years. The subproducts using daily profiles are currently available for years 2005–2010 and 2012–2014; 2011 and 2015 on will be added as the necessary input data are simulated for those years.

Additional Information

© Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 16 May 2018 – Discussion started: 25 Jun 2018 – Revised: 09 Oct 2018 – Accepted: 30 Oct 2018 – Published: 27 Nov 2018. The authors gratefully acknowledge support from NASA ESS Fellowship NNX14AK89H, NASA grant NNX15AE37G, and TEMPO project grant SV3-83019. We would like to acknowledge high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. This research also used the Savio computational cluster resource provided by the Berkeley Research Computing program at the University of California, Berkeley (supported by the UC Berkeley Chancellor, Vice Chancellor for Research, and Chief Information Officer). We acknowledge use of WRF-Chem preprocessor tools MOZBC, fire_emiss, etc., provided by the Atmospheric Chemistry Observations and Modeling (ACOM) laboratory of NCAR. We also thank Eric Bucsela and Jim Gleason for very helpful discussions about the new formulation of the visible-only AMF. Author contributions. JLL, QZ and RCC articulated a vision for a new BEHR algorithm. JLL and QZ converted those ideas to the code of the BEHR algorithm; JLL led the writing of the manuscript with input from QZ and RCC. RCC provided guidance and mentoring throughout the project and secured funding. All the authors reviewed the manuscript. Supplement. The supplement related to this article is available online at: https://doi.org/10.5194/essd-10-2069-2018-supplement. The authors declare that they have no conflict of interest. Edited by: David Carlson. Reviewed by: two anonymous referees.

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