Preprints
https://doi.org/10.5194/amt-2021-86
https://doi.org/10.5194/amt-2021-86

  23 Mar 2021

23 Mar 2021

Review status: this preprint is currently under review for the journal AMT.

Observing system simulation experiments double scientific return of surface-atmosphere synthesis

Stefan Metzger1,2, David Durden1, Sreenath Paleri2, Matthias Sühring3, Brian Butterworth2, Christopher Florian1, Matthias Mauder4, David M. Plummer5, Luise Wanner4, Ke Xu6, and Ankur R. Desai2 Stefan Metzger et al.
  • 1Battelle, National Ecological Observatory Network, 1685 38th Street, Boulder, CO 80301, USA
  • 2Dept. of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, 1225 West Dayton Street, Madison, WI 53706, USA
  • 3Institute of Meteorology and Climatology, Leibniz University Hannover, Herrenhäuser Straße 2, 30419 Hannover, Germany
  • 4Institute of Meteorology and Climate Research - Atmospheric Environmental Research, Karlsruhe Institute of Technology, Kreuzeckbahnstraße 19, 82467 Garmisch-Partenkirchen, Germany
  • 5Dept. of Atmospheric Science, University of Wyoming-Laramie, 1000 E. University Ave., Laramie, WY 82071, USA
  • 6Dept. of Climate and Space Sciences and Engineering, University of Michigan-Ann Arbor, 2455 Hayward St, Ann Arbor, MI 48109, USA

Abstract. The observing system design of multi-disciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increase in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel approach to observing system simulation experiments that aids surface-atmosphere synthesis at the interface of meso- and microscale meteorology. We used this approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19).

During pre-field simulation experiments, we considered the placement of 20 eddy-covariance flux towers, operations for 72 hours of low-altitude flux aircraft measurements, and integration of various remote sensing data products. High-resolution Large Eddy Simulations generated a super-sample of virtual ground, airborne, and satellite observations to explore two specific design hypotheses. We then analyzed these virtual observations through Environmental Response Functions to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals.

We demonstrate how this novel approach doubled CHEESEHEAD19’s ability to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its extensibility, the approach lends itself to optimize observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection and multi-species applications, among other use cases.

Stefan Metzger et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-86', Anonymous Referee #1, 06 May 2021
    • AC1: 'Reply on RC1', Stefan Metzger, 16 Jun 2021
  • RC2: 'Comment on amt-2021-86', Anonymous Referee #2, 10 May 2021
    • AC2: 'Reply on RC2', Stefan Metzger, 16 Jun 2021

Stefan Metzger et al.

Stefan Metzger et al.

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Short summary
Key Points: (i) Integrative observing system design can multiply the scientific return of surface-atmosphere field measurements. (ii) Catalyzing numerical simulations and first-principles machine learning open up observing system simulation experiments to novel applications. (iii) Use cases include natural climate solutions, emission inventory validation, urban air quality, and industry leak detection.