Preprints
https://doi.org/10.5194/amt-2022-235
https://doi.org/10.5194/amt-2022-235
 
23 Sep 2022
23 Sep 2022
Status: this preprint is currently under review for the journal AMT.

Estimates of spatially complete, observational data-driven planetary boundary layer height over the contiguous United States

Zolal Ayazpour1, Shiqi Tao2,a, Dan Li2, Amy Jo Scarino3, Ralph E. Kuehn4, and Kang Sun1 Zolal Ayazpour et al.
  • 1Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
  • 2Department of Earth and Environmental Sciences, Boston University, Boston, MA, USA
  • 3NASA Langley Research Center, Hampton, VA, USA
  • 4Space Sciences Engineering Center, University of Wisconsin-Madison, Madison, WI, USA
  • anow at: Department of Geography, Clark University, Worcester, MA, USA

Abstract. This study aims to generate a spatially complete planetary boundary layer height (PBLH) product over the contiguous US (CONUS) with minimal biases from observational data sets. An eXtreme Gradient Boosting (XGB) regression model was developed using selected meteorological and geographical data fields as explanatory variables to fit the PBLH values that are derived from Aircraft Meteorological DAta Reporting (AMDAR) hourly profiles at 13:00–14:00 local solar time (LST) during 2005–2019. The PBLH prediction by this work as well as PBLHs from three reanalysis datasets (ERA5, MERRA-2, and NARR) were evaluated by independent PBLH observations from spaceborne lidar (CALIPSO), airborne lidar (High Spectral Resolution Lidar, HSRL), and in-situ aircraft profiles from the DISCOVER-AQ campaigns. Compared with PBLH products from reanalyses, the model prediction from this work shows in general closer agreement with the reference observations. The reanalysis datasets show significant high biases in the west CONUS relative to the reference observations. One direct application of this dataset is that it enables sampling PBLH at the sounding locations and times of sensors aboard satellites with overpass time in the early afternoon, e.g., the A-train, Suomi-NPP, JPSS, and Sentinel 5-Precursor satellite sensors. Since both AMDAR and ERA5 are continuous at hourly resolution, future work is expected to extend the observational data-driven PBLHs to other daytime hours for the TEMPO mission.

Zolal Ayazpour et al.

Status: open (until 28 Oct 2022)

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Zolal Ayazpour et al.

Zolal Ayazpour et al.

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Latest update: 23 Sep 2022
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Short summary
Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLH used in atmospheric models is often inaccurate. Using Aircraft Meteorological DAta Reporting (AMDAR) PBLH observation, we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US, which shows a better agreement with reference PBLH observations compared to commonly used PBLH products.