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Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

  • Katia Lamer
  • , Zackary Mages
  • , Bernat Puigdomènech Treserras
  • , Paul Walter
  • , Zeen Zhu
  • , Anita D. Rapp
  • , Christopher J. Nowotarski
  • , Sarah D. Brooks
  • , James Flynn
  • , Milind Sharma
  • , Petra Klein
  • , Michelle Spencer
  • , Elizabeth Smith
  • , Joshua Gebauer
  • , Tyler Bell
  • , Lydia Bunting
  • , Travis Griggs
  • , Timothy J. Wagner
  • , Katherine McKeown
  • Brookhaven National Laboratory
  • Stony Brook University
  • McGill University
  • St. Edward's University
  • Texas A&M University
  • University of Houston
  • University of Oklahoma
  • National Oceanic and Atmospheric Administration
  • University of Wisconsin-Madison
  • Pennsylvania State University

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

Original languageEnglish
Article number661
JournalScientific data
Volume11
Issue number1
DOIs
StatePublished - Dec 2024
Externally publishedYes

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