Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Technical Report · Sun Oct 01 00:00:00 EDT 2023

DOI:https://doi.org/10.2172/2202672· OSTI ID:2202672

Jensen, Michael P. ^[1]; Flynn, James H. ^[2]; Kollias, P. ^[3]; Kuang, C. ^[1]; McFarquhar, G. ^[4]; Powers, H. ^[5]; Brooks, S. ^[6]; Bruning, E. ^[7]; Collins, Don ^[8]; Collis, S. M. ^[9]; Fan, J. ^[9]; Fridlind, A. ^[10]; Giangrande, S. E. ^[1]; Griffin, R. ^[11]; Hu, J. ^[4]; Jackson, R. C. ^[9]; Kumjian, M. ^[12]; Logan, T. ^[6]; Matsui, T. ^[13]; Nowotarski, C. J. ^[6] ; Oue, M. ^[3]; Rapp, A. D. ^[6]; Rosenfeld, D. ^[14]; Ryzhkov, A. ^[15]; Sheesley, R. ^[16]; Snyder, J. ^[17]; Stier, P. ^[18]; Usenko, S. ^[16]; van den Heever, S. C. ^[19]; van Lier-Walqui, M. ^[20]; Varble, A. ^[21]; Wang, Y. ^[2]; Aiken, A. ^[5]; Deng, M. ^[1]; Dexheimer, Dari ^[22]; Dubey, M. ^[5]; Feng, Y. ^[9]; Ghate, V. P. ^[9]; Johnson, K. L. ^[1]; Lamer, K. ^[1]; Saleeby, S. M. ^[19]; Wang, D. ^[1]; Zawadowicz, M. A. ^[1]; Zhou, A. ^[1]

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1. Brookhaven National Laboratory (BNL), Upton, NY (United States)
2. Univ. of Houston, TX (United States)
3. Stony Brook Univ., NY (United States)
4. Univ. of Oklahoma, Norman, OK (United States)
5. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
6. Texas A & M Univ., College Station, TX (United States)
7. Texas Tech Univ., Lubbock, TX (United States)
8. Univ. of California, Riverside, CA (United States)
9. Argonne National Laboratory (ANL), Argonne, IL (United States)
10. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
11. Roger Williams Univ., Bristol, RI (United States)
12. Pennsylvania State Univ., University Park, PA (United States)
13. Univ. of Maryland, College Park, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
14. Hebrew Univ. of Jerusalem (Israel)
15. National Oceanic and Atmospheric Administration (NOAA), Norman, OK (United States). National Severe Storms Laboratory; Univ. of Oklahoma, Norman, OK (United States)
16. Baylor Univ., Waco, TX (United States)
17. National Oceanic and Atmospheric Administration (NOAA), Norman, OK (United States). National Severe Storms Laboratory
18. Univ. of Oxford (United Kingdom)
19. Colorado State Univ., Fort Collins, CO (United States)
20. Columbia Univ., New York, NY (United States)
21. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
22. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Contributing Organization: Pacific Northwest National Laboratory (PNNL); Brookhaven National Laboratory (BNL); Argonne National Laboratory (ANL); Oak Ridge National Laboratory (ORNL)
• DOE Contract Number: AC06-76RL01830
• OSTI ID: 2202672
• Report Number(s): DOE/SC-ARM-23-038
• Country of Publication: United States
• Language: English

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54 ENVIRONMENTAL SCIENCES