Articles | Volume 16, issue 5
https://doi.org/10.5194/essd-16-2525-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2525-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
30 May 2024
Data description paper |
| 30 May 2024
| 30 May 2024
Data collected using small uncrewed aircraft systems during the TRacking Aerosol Convection interactions ExpeRiment (TRACER)
Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Gijs de Boer
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA Physical Sciences Laboratory, Boulder, Colorado, USA
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Petra Klein
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Jonathan Hamilton
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA Physical Sciences Laboratory, Boulder, Colorado, USA
Michelle Spencer
Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
NOAA National Severe Storms Laboratory, Norman, Oklahoma, USA
Radiance Calmer
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Antonio R. Segales
Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
Michael Rhodes
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Tyler M. Bell
Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
Justin Buchli
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Kelsey Britt
Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
NOAA National Severe Storms Laboratory, Norman, Oklahoma, USA
Elizabeth Asher
NOAA Global Monitoring Laboratory, Boulder, Colorado, USA
Isaac Medina
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Brian Butterworth
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA Physical Sciences Laboratory, Boulder, Colorado, USA
Leia Otterstatter
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Madison Ritsch
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Bryony Puxley
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Angelina Miller
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Arianna Jordan
School of Meteorology, University of Oklahoma, Norman, Oklahoma, USA
Ceu Gomez-Faulk
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Elizabeth Smith
NOAA National Severe Storms Laboratory, Norman, Oklahoma, USA
Steven Borenstein
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, USA
NOAA Global Monitoring Laboratory, Boulder, Colorado, USA
Troy Thornberry
NOAA Chemical Sciences Laboratory, Boulder, Colorado, USA
Brian Argrow
Integrated Remote and In Situ Sensing, University of Colorado Boulder, Boulder, Colorado, USA
Elizabeth Pillar-Little
Science Department, Oklahoma State University Oklahoma City, Oklahoma City, Oklahoma, USA
formerly at: Cooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma, USA
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This paper describes data collected by uncrewed aircraft operated by the University of Colorado Boulder and Black Swift Technologies during the Lower Atmospheric Profiling Studies at Elevation – A Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. This effort was conducted in the San Luis Valley of Colorado in July 2018 and included intensive observing of the atmospheric boundary layer. This paper describes data collected by four aircraft operated by these entities.
Patricia K. Quinn, Elizabeth J. Thompson, Derek J. Coffman, Sunil Baidar, Ludovic Bariteau, Timothy S. Bates, Sebastien Bigorre, Alan Brewer, Gijs de Boer, Simon P. de Szoeke, Kyla Drushka, Gregory R. Foltz, Janet Intrieri, Suneil Iyer, Chris W. Fairall, Cassandra J. Gaston, Friedhelm Jansen, James E. Johnson, Ovid O. Krüger, Richard D. Marchbanks, Kenneth P. Moran, David Noone, Sergio Pezoa, Robert Pincus, Albert J. Plueddemann, Mira L. Pöhlker, Ulrich Pöschl, Estefania Quinones Melendez, Haley M. Royer, Malgorzata Szczodrak, Jim Thomson, Lucia M. Upchurch, Chidong Zhang, Dongxiao Zhang, and Paquita Zuidema
Earth Syst. Sci. Data, 13, 1759–1790, https://doi.org/10.5194/essd-13-1759-2021, https://doi.org/10.5194/essd-13-1759-2021, 2021
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ATOMIC took place in the northwestern tropical Atlantic during January and February of 2020 to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Measurements made from the NOAA RV Ronald H. Brown and assets it deployed (instrumented mooring and uncrewed seagoing vehicles) are described herein to advance widespread use of the data by the ATOMIC and broader research communities.
Tyler M. Bell, Petra M. Klein, Julie K. Lundquist, and Sean Waugh
Earth Syst. Sci. Data, 13, 1041–1051, https://doi.org/10.5194/essd-13-1041-2021, https://doi.org/10.5194/essd-13-1041-2021, 2021
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In July 2018, numerous weather sensing remotely piloted aircraft systems (RPASs) were flown in a flight week called Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). As part of LAPSE-RATE, ground-based remote and in situ systems were also deployed to supplement and enhance observations from the RPASs. These instruments include multiple Doppler lidars, thermodynamic profilers, and radiosondes. This paper describes data from these systems.
Elizabeth A. Pillar-Little, Brian R. Greene, Francesca M. Lappin, Tyler M. Bell, Antonio R. Segales, Gustavo Britto Hupsel de Azevedo, William Doyle, Sai Teja Kanneganti, Daniel D. Tripp, and Phillip B. Chilson
Earth Syst. Sci. Data, 13, 269–280, https://doi.org/10.5194/essd-13-269-2021, https://doi.org/10.5194/essd-13-269-2021, 2021
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During July 2018, researchers from OU participated in the LAPSE-RATE field campaign in San Luis Valley, Colorado. The OU team completed 180 flights using three RPASs over the course of 6 d of operation to collect vertical profiles of the thermodynamic and kinematic state of the ABL. This article describes sampling strategies, data collection, platform intercomparibility, data quality, and the dataset's possible applications to convective initiation, drainage flows, and ABL transitions.
Jessie M. Creamean, Gijs de Boer, Hagen Telg, Fan Mei, Darielle Dexheimer, Matthew D. Shupe, Amy Solomon, and Allison McComiskey
Atmos. Chem. Phys., 21, 1737–1757, https://doi.org/10.5194/acp-21-1737-2021, https://doi.org/10.5194/acp-21-1737-2021, 2021
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Arctic clouds play a role in modulating sea ice extent. Importantly, aerosols facilitate cloud formation, and thus it is crucial to understand the interactions between aerosols and clouds. Vertical measurements of aerosols and clouds are needed to tackle this issue. We present results from balloon-borne measurements of aerosols and clouds over the course of 2 years in northern Alaska. These data shed light onto the vertical distributions of aerosols relative to clouds spanning multiple seasons.
Gijs de Boer, Sean Waugh, Alexander Erwin, Steven Borenstein, Cory Dixon, Wafa'a Shanti, Adam Houston, and Brian Argrow
Earth Syst. Sci. Data, 13, 155–169, https://doi.org/10.5194/essd-13-155-2021, https://doi.org/10.5194/essd-13-155-2021, 2021
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This paper provides an overview of measurements collected in south-central Colorado (USA) during the 2018 LAPSE-RATE campaign. The measurements described in this article were collected by mobile surface vehicles, including cars, trucks, and vans, and include measurements of thermodynamic quantities (e.g., temperature, humidity, pressure) and winds. These measurements can be used to study the evolution of the atmospheric boundary layer at a high-elevation site under a variety of conditions.
David Brus, Jani Gustafsson, Ville Vakkari, Osku Kemppinen, Gijs de Boer, and Anne Hirsikko
Atmos. Chem. Phys., 21, 517–533, https://doi.org/10.5194/acp-21-517-2021, https://doi.org/10.5194/acp-21-517-2021, 2021
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This paper summarizes Finnish Meteorological Institute and Kansas State University unmanned aerial vehicle measurements during the summer 2018 Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) campaign in the San Luis Valley, providing an overview of the rotorcraft deployed, payloads, scientific goals and flight strategies and presenting observations of atmospheric thermodynamics and aerosol and gas parameters in the vertical column.
Gijs de Boer, Adam Houston, Jamey Jacob, Phillip B. Chilson, Suzanne W. Smith, Brian Argrow, Dale Lawrence, Jack Elston, David Brus, Osku Kemppinen, Petra Klein, Julie K. Lundquist, Sean Waugh, Sean C. C. Bailey, Amy Frazier, Michael P. Sama, Christopher Crick, David Schmale III, James Pinto, Elizabeth A. Pillar-Little, Victoria Natalie, and Anders Jensen
Earth Syst. Sci. Data, 12, 3357–3366, https://doi.org/10.5194/essd-12-3357-2020, https://doi.org/10.5194/essd-12-3357-2020, 2020
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This paper provides an overview of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign, held from 14 to 20 July 2018. This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. This overview paper provides insight into the campaign for a special issue focused on the datasets collected during LAPSE-RATE.
Martina Krämer, Christian Rolf, Nicole Spelten, Armin Afchine, David Fahey, Eric Jensen, Sergey Khaykin, Thomas Kuhn, Paul Lawson, Alexey Lykov, Laura L. Pan, Martin Riese, Andrew Rollins, Fred Stroh, Troy Thornberry, Veronika Wolf, Sarah Woods, Peter Spichtinger, Johannes Quaas, and Odran Sourdeval
Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, https://doi.org/10.5194/acp-20-12569-2020, 2020
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To improve the representations of cirrus clouds in climate predictions, extended knowledge of their properties and geographical distribution is required. This study presents extensive airborne in situ and satellite remote sensing climatologies of cirrus and humidity, which serve as a guide to cirrus clouds. Further, exemplary radiative characteristics of cirrus types and also in situ observations of tropical tropopause layer cirrus and humidity in the Asian monsoon anticyclone are shown.
Tyler M. Bell, Brian R. Greene, Petra M. Klein, Matthew Carney, and Phillip B. Chilson
Atmos. Meas. Tech., 13, 3855–3872, https://doi.org/10.5194/amt-13-3855-2020, https://doi.org/10.5194/amt-13-3855-2020, 2020
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It is well known that the atmospheric boundary layer is under-sampled in the vertical dimension. Recently, weather-sensing uncrewed aerial systems (WxUAS) have created new opportunities to sample this region of the atmosphere. This study compares a WxUAS developed at the University of Oklahoma to ground-based remote sensing and radiosondes. We find that overall the systems generally agreed well both thermodynamically and kinematically. However, there is still room to improve each system.
Antonio R. Segales, Brian R. Greene, Tyler M. Bell, William Doyle, Joshua J. Martin, Elizabeth A. Pillar-Little, and Phillip B. Chilson
Atmos. Meas. Tech., 13, 2833–2848, https://doi.org/10.5194/amt-13-2833-2020, https://doi.org/10.5194/amt-13-2833-2020, 2020
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The CopterSonde is an unmanned aircraft system designed with the purpose of sampling thermodynamic and kinematic parameters of the lower Earth's atmosphere, with a focus on vertical profiles in the planetary boundary layer. By incorporating adaptive sampling techniques and optimizing the sensor placement, our study shows that CopterSonde can provide similar information as a radiosonde, but with more control of its sampling location at much higher temporal and spatial resolution.
Tyler M. Bell, Petra Klein, Norman Wildmann, and Robert Menke
Atmos. Meas. Tech., 13, 1357–1371, https://doi.org/10.5194/amt-13-1357-2020, https://doi.org/10.5194/amt-13-1357-2020, 2020
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This study investigates the utility of using multi-Doppler retrievals during the Perdigão 2017 campaign. By combining scans from the multitude of Doppler lidars, it was possible to derive virtual towers that greatly extend the range of traditional in situ meteorological towers. Uncertainties from the measurements are analyzed and discussed. Despite multiple sources of error, it was found that the virtual towers are useful for analyzing the complex flows observed during the campaign.
Elizabeth Asher, Rebecca S. Hornbrook, Britton B. Stephens, Doug Kinnison, Eric J. Morgan, Ralph F. Keeling, Elliot L. Atlas, Sue M. Schauffler, Simone Tilmes, Eric A. Kort, Martin S. Hoecker-Martínez, Matt C. Long, Jean-François Lamarque, Alfonso Saiz-Lopez, Kathryn McKain, Colm Sweeney, Alan J. Hills, and Eric C. Apel
Atmos. Chem. Phys., 19, 14071–14090, https://doi.org/10.5194/acp-19-14071-2019, https://doi.org/10.5194/acp-19-14071-2019, 2019
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Halogenated organic trace gases, which are a source of reactive halogens to the atmosphere, exert a disproportionately large influence on atmospheric chemistry and climate. This paper reports novel aircraft observations of halogenated compounds over the Southern Ocean in summer and evaluates hypothesized regional sources and emissions of these trace gases through their relationships to additional aircraft observations.
Gijs de Boer, Darielle Dexheimer, Fan Mei, John Hubbe, Casey Longbottom, Peter J. Carroll, Monty Apple, Lexie Goldberger, David Oaks, Justin Lapierre, Michael Crume, Nathan Bernard, Matthew D. Shupe, Amy Solomon, Janet Intrieri, Dale Lawrence, Abhiram Doddi, Donna J. Holdridge, Michael Hubbell, Mark D. Ivey, and Beat Schmid
Earth Syst. Sci. Data, 11, 1349–1362, https://doi.org/10.5194/essd-11-1349-2019, https://doi.org/10.5194/essd-11-1349-2019, 2019
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This paper provides a summary of observations collected at Oliktok Point, Alaska, as part of the Profiling at Oliktok Point to Enhance YOPP Experiments (POPEYE) campaign. The Year of Polar Prediction (YOPP) is a multi-year concentrated effort to improve forecasting capabilities at high latitudes across a variety of timescales. POPEYE observations include atmospheric data collected using unmanned aircraft, tethered balloons, and radiosondes, made in parallel with routine measurements at the site.
Maximilian Maahn, Fabian Hoffmann, Matthew D. Shupe, Gijs de Boer, Sergey Y. Matrosov, and Edward P. Luke
Atmos. Meas. Tech., 12, 3151–3171, https://doi.org/10.5194/amt-12-3151-2019, https://doi.org/10.5194/amt-12-3151-2019, 2019
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Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Here, we present three novel methods for calibrating vertically pointing cloud radars. These calibration methods are based on microphysical processes of liquid clouds, such as the transition of cloud droplets to drizzle drops. We successfully apply the methods to cloud radar data from the North Slope of Alaska (NSA) and Oliktok Point (OLI) ARM sites.
Sabine Robrecht, Bärbel Vogel, Jens-Uwe Grooß, Karen Rosenlof, Troy Thornberry, Andrew Rollins, Martina Krämer, Lance Christensen, and Rolf Müller
Atmos. Chem. Phys., 19, 5805–5833, https://doi.org/10.5194/acp-19-5805-2019, https://doi.org/10.5194/acp-19-5805-2019, 2019
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The potential destruction of stratospheric ozone in the mid-latitudes has been discussed recently. We analysed this ozone loss mechanism and its sensitivities. In a certain temperature range, we found a threshold in water vapour, which has to be exceeded for ozone loss to occur. We show the dependence of this water vapour threshold on temperature, sulfate content and air composition. This study provides a basis to estimate the impact of potential sulphate geoengineering on stratospheric ozone.
Jessie M. Creamean, Rachel M. Kirpes, Kerri A. Pratt, Nicholas J. Spada, Maximilian Maahn, Gijs de Boer, Russell C. Schnell, and Swarup China
Atmos. Chem. Phys., 18, 18023–18042, https://doi.org/10.5194/acp-18-18023-2018, https://doi.org/10.5194/acp-18-18023-2018, 2018
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Warm-temperature ice nucleating particles (INPs) were observed during a springtime transition period of the melting of frozen surfaces in Northern Alaska. Such INPs were likely biological and from marine and terrestrial (tundra) sources. Influxes of these efficient INPs may have important implications for Arctic cloud ice formation and, consequently, the surface energy budget.
Amy Solomon, Gijs de Boer, Jessie M. Creamean, Allison McComiskey, Matthew D. Shupe, Maximilian Maahn, and Christopher Cox
Atmos. Chem. Phys., 18, 17047–17059, https://doi.org/10.5194/acp-18-17047-2018, https://doi.org/10.5194/acp-18-17047-2018, 2018
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The results of this study indicate that perturbations in ice nucleating particles (INPs) dominate over cloud condensation nuclei (CCN) perturbations in Arctic mixed-phase stratocumulus; i.e., an equivalent fractional decrease in CCN and INPs results in an increase in the cloud-top longwave cooling rate, even though the droplet effective radius increases and the cloud emissivity decreases. In addition, cloud-processing causes layering of aerosols with increased concentrations of CCN at cloud top.
Stefan Kaufmann, Christiane Voigt, Romy Heller, Tina Jurkat-Witschas, Martina Krämer, Christian Rolf, Martin Zöger, Andreas Giez, Bernhard Buchholz, Volker Ebert, Troy Thornberry, and Ulrich Schumann
Atmos. Chem. Phys., 18, 16729–16745, https://doi.org/10.5194/acp-18-16729-2018, https://doi.org/10.5194/acp-18-16729-2018, 2018
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We present an intercomparison of the airborne water vapor measurements during the ML-CIRRUS mission. Although the agreement of the hygrometers significantly improved compared to studies from recent decades, systematic differences remain under specific meteorological conditions. We compare the measurements to model data, where we observe a model wet bias in the lower stratosphere close to the tropopause, likely caused by a blurred humidity gradient in the model tropopause.
Brian R. Greene, Antonio R. Segales, Sean Waugh, Simon Duthoit, and Phillip B. Chilson
Atmos. Meas. Tech., 11, 5519–5530, https://doi.org/10.5194/amt-11-5519-2018, https://doi.org/10.5194/amt-11-5519-2018, 2018
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With the recent commercial availability of rotary-wing unmanned aircraft systems (rwUAS), their ability to collect observations in the lower atmosphere is quickly being realized. However, integrating sensors with an rwUAS can introduce errors if not sited properly. This study discusses an objective method of determining some of these error sources in temperature, including improper airflow and rotary motor heating. Errors can be mitigated by mounting thermistors under propellers near the tips.
Matthew S. Norgren, Gijs de Boer, and Matthew D. Shupe
Atmos. Chem. Phys., 18, 13345–13361, https://doi.org/10.5194/acp-18-13345-2018, https://doi.org/10.5194/acp-18-13345-2018, 2018
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Arctic mixed-phase clouds are a critical component of the Arctic climate system because of their ability to influence the surface radiation budget. The radiative impact of an individual cloud is closely linked to the ability of the cloud to convert liquid drops to ice. In this paper, we show through an observational record that clouds present in polluted atmospheric conditions have lower amounts of ice than similar clouds found in clean conditions.
Christopher R. Williams, Maximilian Maahn, Joseph C. Hardin, and Gijs de Boer
Atmos. Meas. Tech., 11, 4963–4980, https://doi.org/10.5194/amt-11-4963-2018, https://doi.org/10.5194/amt-11-4963-2018, 2018
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This study presents three signal-processing methods to improve estimates derived from a vertically pointing 35 GHz cloud radar deployed at Oliktok Point, Alaska. The first method removes ground clutter from the Doppler velocity spectra. The second method estimates multiple peaks and high-order moments from the improved spectra. The third method removes high-frequency variability in high-order moments by shifting original 2 s spectra to a common reference before averaging over a 15 s interval.
Jessie M. Creamean, Maximilian Maahn, Gijs de Boer, Allison McComiskey, Arthur J. Sedlacek, and Yan Feng
Atmos. Chem. Phys., 18, 555–570, https://doi.org/10.5194/acp-18-555-2018, https://doi.org/10.5194/acp-18-555-2018, 2018
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We report on airborne observations from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program's Fifth Airborne Carbon Measurements (ACME-V) campaign along the North Slope of Alaska during the summer of 2015. We show how local oil extraction activities, 2015's central Alaskan wildfires, and, to a lesser extent, long-range transport introduce aerosols and trace gases higher in concentration than previously reported in Arctic haze measurements to the North Slope.
Maximilian Maahn, Gijs de Boer, Jessie M. Creamean, Graham Feingold, Greg M. McFarquhar, Wei Wu, and Fan Mei
Atmos. Chem. Phys., 17, 14709–14726, https://doi.org/10.5194/acp-17-14709-2017, https://doi.org/10.5194/acp-17-14709-2017, 2017
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Liquid-containing clouds are a key component of the Arctic climate system and their radiative properties depend strongly on cloud drop sizes. Here, we investigate how cloud drop sizes are modified in the presence of local emissions from industrial facilities at the North Slope of Alaska using aircraft in situ observations. We show that near local anthropogenic sources, the concentrations of black carbon and condensation nuclei are enhanced and cloud drop sizes are reduced.
Maria A. Navarro, Alfonso Saiz-Lopez, Carlos A. Cuevas, Rafael P. Fernandez, Elliot Atlas, Xavier Rodriguez-Lloveras, Douglas Kinnison, Jean-Francois Lamarque, Simone Tilmes, Troy Thornberry, Andrew Rollins, James W. Elkins, Eric J. Hintsa, and Fred L. Moore
Atmos. Chem. Phys., 17, 9917–9930, https://doi.org/10.5194/acp-17-9917-2017, https://doi.org/10.5194/acp-17-9917-2017, 2017
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Inorganic bromine (Bry) plays an important role in ozone layer depletion. Based on aircraft observations of organic bromine species and chemistry simulations, we model the Bry abundances over the Pacific tropical tropopause. Our results show BrO and Br as the dominant species during daytime hours, and BrCl and BrONO2 as the nighttime dominant species over the western and eastern Pacific, respectively. The difference in the partitioning is due to changes in the abundance of O3, NO2, and Cly.
Bodo Werner, Jochen Stutz, Max Spolaor, Lisa Scalone, Rasmus Raecke, James Festa, Santo Fedele Colosimo, Ross Cheung, Catalina Tsai, Ryan Hossaini, Martyn P. Chipperfield, Giorgio S. Taverna, Wuhu Feng, James W. Elkins, David W. Fahey, Ru-Shan Gao, Erik J. Hintsa, Troy D. Thornberry, Free Lee Moore, Maria A. Navarro, Elliot Atlas, Bruce C. Daube, Jasna Pittman, Steve Wofsy, and Klaus Pfeilsticker
Atmos. Chem. Phys., 17, 1161–1186, https://doi.org/10.5194/acp-17-1161-2017, https://doi.org/10.5194/acp-17-1161-2017, 2017
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The paper reports on inorganic and organic bromine measured in the tropical tropopause layer (TTL) over the eastern Pacific in early 2013. Bryinorg is found to increase from a mean of 2.63 ± 1.04 ppt for θ in the range of 350–360 K to 5.11 ± 1.57 ppt for θ=390 ± 400 K, whereas in the subtropical lower stratosphere, it reaches 7.66 ± 2.95 ppt for θ in the range of 390–400 K. Within the TTL, total bromine is found to range from 20.3 ppt to 22.3 ppt.
Timothy A. Bonin, Jennifer F. Newman, Petra M. Klein, Phillip B. Chilson, and Sonia Wharton
Atmos. Meas. Tech., 9, 5833–5852, https://doi.org/10.5194/amt-9-5833-2016, https://doi.org/10.5194/amt-9-5833-2016, 2016
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Turbulence measurements are important to boundary layer meteorology and related fields. Doppler lidars are capable of providing continuous profiles of turbulence statistics. Herein, the most direct turbulence measurement, vertical velocity variance, is validated with those from sonic anemometers. Spectra are also compared. A method of calculating velocity variance using the autocovariance is shown to improve the accuracy of the measurement by mitigating effects of noise and averaging.
Andrew W. Rollins, Troy D. Thornberry, Steven J. Ciciora, Richard J. McLaughlin, Laurel A. Watts, Thomas F. Hanisco, Esther Baumann, Fabrizio R. Giorgetta, Thaopaul V. Bui, David W. Fahey, and Ru-Shan Gao
Atmos. Meas. Tech., 9, 4601–4613, https://doi.org/10.5194/amt-9-4601-2016, https://doi.org/10.5194/amt-9-4601-2016, 2016
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In situ measurements of SO2 in the tropical UT–LS have been scarce, in part due to limitations of existing instrumentation. Here we present a new laser-induced fluorescence instrument capable of measuring SO2 in the UT–LS region at single part-per-trillion (ppt) mixing ratios and demonstrate it on the NASA WB-57F aircraft up to 19.7 km altitude.
Jennifer F. Newman, Petra M. Klein, Sonia Wharton, Ameya Sathe, Timothy A. Bonin, Phillip B. Chilson, and Andreas Muschinski
Atmos. Meas. Tech., 9, 1993–2013, https://doi.org/10.5194/amt-9-1993-2016, https://doi.org/10.5194/amt-9-1993-2016, 2016
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Remote sensing devices known as lidars are often used to take measurements at potential wind farm sites. These instruments are however not optimized for measuring turbulence, small-scale changes in wind speed. In this manuscript, the impact of lidar configurations and atmospheric conditions on turbulence accuracy is explored. A new method was developed to correct lidar turbulence measurements and is described in detail such that other lidar users can apply it to their own instruments.
Gijs de Boer, Scott Palo, Brian Argrow, Gabriel LoDolce, James Mack, Ru-Shan Gao, Hagen Telg, Cameron Trussel, Joshua Fromm, Charles N. Long, Geoff Bland, James Maslanik, Beat Schmid, and Terry Hock
Atmos. Meas. Tech., 9, 1845–1857, https://doi.org/10.5194/amt-9-1845-2016, https://doi.org/10.5194/amt-9-1845-2016, 2016
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This paper provides an overview of a recently developed unmanned aerial system (UAS) for study of the lower atmosphere. This platform, the University of Colorado Pilatus UAS, is capable of providing measurements of atmospheric thermodynamics (temperature, pressure, humidity), atmospheric aerosol size distributions, and broadband radiation. These quantities are critical for understanding a variety of atmospheric processes relevant for characterization of the surface energy budget.
Stefan Kaufmann, Christiane Voigt, Tina Jurkat, Troy Thornberry, David W. Fahey, Ru-Shan Gao, Romy Schlage, Dominik Schäuble, and Martin Zöger
Atmos. Meas. Tech., 9, 939–953, https://doi.org/10.5194/amt-9-939-2016, https://doi.org/10.5194/amt-9-939-2016, 2016
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We present the development of a new airborne mass spectrometer AIMS-H2O for the fast and accurate measurement of water vapor in the upper troposphere and lower stratosphere. The high accuracy needed for e.g. quantification of atmospheric water vapor transport processes or cloud formation is achieved by an in-flight calibration of the instrument. AIMS-H2O is deployed on the DLR research aircraft HALO and Falcon where it covers a range of water vapor mixing ratios from 1 to 500 ppmv.
J. Meyer, C. Rolf, C. Schiller, S. Rohs, N. Spelten, A. Afchine, M. Zöger, N. Sitnikov, T. D. Thornberry, A. W. Rollins, Z. Bozóki, D. Tátrai, V. Ebert, B. Kühnreich, P. Mackrodt, O. Möhler, H. Saathoff, K. H. Rosenlof, and M. Krämer
Atmos. Chem. Phys., 15, 8521–8538, https://doi.org/10.5194/acp-15-8521-2015, https://doi.org/10.5194/acp-15-8521-2015, 2015
B. C. Kindel, P. Pilewskie, K. S. Schmidt, T. Thornberry, A. Rollins, and T. Bui
Atmos. Meas. Tech., 8, 1147–1156, https://doi.org/10.5194/amt-8-1147-2015, https://doi.org/10.5194/amt-8-1147-2015, 2015
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Measurements of upper tropospheric-lower stratospheric water vapor amounts in the tropics were made using the 1400 and 1900nm water vapor bands present in airborne solar spectral irradiance data. These were validated with radiative transfer modeling using in situ profiles of water vapor, temperature, and pressure. An approach to extending these types of measurements from aircraft altitudes to the top of the atmosphere to infer stratospheric water vapor amount is outlined.
T. D. Thornberry, A. W. Rollins, R. S. Gao, L. A. Watts, S. J. Ciciora, R. J. McLaughlin, and D. W. Fahey
Atmos. Meas. Tech., 8, 211–224, https://doi.org/10.5194/amt-8-211-2015, https://doi.org/10.5194/amt-8-211-2015, 2015
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The two-channel NOAA Water instrument was developed for in situ measurement of water vapor and cirrus cloud ice water content (IWC) in the upper troposphere and lower stratosphere. Tunable diode laser absorption is used to achieve accurate measurements at part per million H2O and low µg/m3 IWC. This paper reports the instrument’s design and performance achieved during its first aircraft deployment on the NASA Global Hawk during the 2013 ATTREX mission in the tropical tropopause layer.
J. M. Intrieri, G. de Boer, M. D. Shupe, J. R. Spackman, J. Wang, P. J. Neiman, G. A. Wick, T. F. Hock, and R. E. Hood
Atmos. Meas. Tech., 7, 3917–3926, https://doi.org/10.5194/amt-7-3917-2014, https://doi.org/10.5194/amt-7-3917-2014, 2014
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In winter 2011, the Global Hawk unmanned aircraft system (UAS) was deployed over the Arctic to evaluate a UAS dropsonde system at high latitudes. Dropsondes deployed from the Global Hawk successfully obtained high-resolution profiles of temperature, pressure, humidity, and wind speed and direction information between the stratosphere and surface. During the 25-hour polar flight, the Global Hawk released 35 sondes between the North Slope of Alaska and 85° N latitude.
C. Wesslén, M. Tjernström, D. H. Bromwich, G. de Boer, A. M. L. Ekman, L.-S. Bai, and S.-H. Wang
Atmos. Chem. Phys., 14, 2605–2624, https://doi.org/10.5194/acp-14-2605-2014, https://doi.org/10.5194/acp-14-2605-2014, 2014
G. de Boer, M. D. Shupe, P. M. Caldwell, S. E. Bauer, O. Persson, J. S. Boyle, M. Kelley, S. A. Klein, and M. Tjernström
Atmos. Chem. Phys., 14, 427–445, https://doi.org/10.5194/acp-14-427-2014, https://doi.org/10.5194/acp-14-427-2014, 2014
T. A. Bonin, P. B. Chilson, B. S. Zielke, P. M. Klein, and J. R. Leeman
Geosci. Instrum. Method. Data Syst., 2, 177–187, https://doi.org/10.5194/gi-2-177-2013, https://doi.org/10.5194/gi-2-177-2013, 2013
T. D. Thornberry, A. W. Rollins, R. S. Gao, L. A. Watts, S. J. Ciciora, R. J. McLaughlin, C. Voigt, B. Hall, and D. W. Fahey
Atmos. Meas. Tech., 6, 1461–1475, https://doi.org/10.5194/amt-6-1461-2013, https://doi.org/10.5194/amt-6-1461-2013, 2013
G. de Boer, T. Hashino, G. J. Tripoli, and E. W. Eloranta
Atmos. Chem. Phys., 13, 1733–1749, https://doi.org/10.5194/acp-13-1733-2013, https://doi.org/10.5194/acp-13-1733-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Meteorology
Multifrequency radar observations of marine clouds during the EPCAPE campaign
LGHAP v2: a global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big Earth data analytics
Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg
The 2023 National Offshore Wind data set (NOW-23)
Dataset of stable isotopes of precipitation in the Eurasian continent
A 7-year record of vertical profiles of radar measurements and precipitation estimates at Dumont d'Urville, Adélie Land, East Antarctica
Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
Spatially Extensive Long-term Quality-assured Land-atmosphere Interactions Dataset over the Tibetan Plateau
Special Observing Period (SOP) Data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)
Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)
Year-long buoy-based observations of the air–sea transition zone off the US west coast
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: a comprehensive long-term dataset of remote sensing observations
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output
Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Derivation and compilation of lower-atmospheric properties relating to temperature, wind, stability, moisture, and surface radiation budget over the central Arctic sea ice during MOSAiC
CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
An integrated and homogenized global surface solar radiation dataset and its reconstruction based on a convolutional neural network approach
IWIN: the Isfjorden Weather Information Network
A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations
A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range
The EUPPBench postprocessing benchmark dataset v1.0
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Database of the Italian disdrometer network
East Asia Reanalysis System (EARS)
Data rescue of historical wind observations in Sweden since the 1920s
LegacyClimate 1.0: a dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the last 30 kyr and beyond
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Combined wind lidar and cloud radar for high-resolution wind profiling
An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020
TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations
The AntAWS dataset: a compilation of Antarctic automatic weather station observations
HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020
A long-term 1 km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites
Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium
Combined high-resolution rainfall and wind data collected for 3 months on a wind farm 110 km southeast of Paris (France)
Sub-mesoscale observations of convective cold pools with a dense station network in Hamburg, Germany
Observational data from uncrewed systems over Southern Great Plains
A global dataset of spatiotemporally seamless daily mean land surface temperatures: generation, validation, and analysis
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
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A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
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Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
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This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
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We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
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This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
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Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
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Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaoming Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-9, https://doi.org/10.5194/essd-2024-9, 2024
Revised manuscript accepted for ESSD
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Current models and the satellites struggle to accurately represent the land-atmosphere (L-A) interactions over the Tibetan Plateau. We present the most extensive compilation of in-situ observations to date, comprising 17 years of data on L-A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region and it enables new investigations of fine-scale L-A processes and their mechanistic drivers
Zen Mariani, Sara Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie Hartten, Jareth Holt, Christopher Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-497, https://doi.org/10.5194/essd-2023-497, 2024
Revised manuscript accepted for ESSD
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During the Year of Polar Prediction (YOPP) we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of data sets that have been collected to facilitate user uptake and model-observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODF), including a description of the sites, data format, and instruments.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
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The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
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Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
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We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
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We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
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Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
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This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
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This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
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The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
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Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
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This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
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A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
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The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
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A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
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Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
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Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
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EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
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This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
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This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
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We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
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To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
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It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
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Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Eva Beele, Maarten Reyniers, Raf Aerts, and Ben Somers
Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, https://doi.org/10.5194/essd-14-4681-2022, 2022
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This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
Auguste Gires, Jerry Jose, Ioulia Tchiguirinskaia, and Daniel Schertzer
Earth Syst. Sci. Data, 14, 3807–3819, https://doi.org/10.5194/essd-14-3807-2022, https://doi.org/10.5194/essd-14-3807-2022, 2022
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The Hydrology Meteorology and Complexity laboratory of École des Ponts ParisTech (https://hmco.enpc.fr) has made a data set of high-resolution atmospheric measurements (rainfall, wind, temperature, pressure, and humidity) available. It comes from a campaign carried out on a meteorological mast located on a wind farm in the framework of the Rainfall Wind Turbine or Turbulence project (RW-Turb; supported by the French National Research Agency – ANR-19-CE05-0022).
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
Fan Mei, Mikhail S. Pekour, Darielle Dexheimer, Gijs de Boer, RaeAnn Cook, Jason Tomlinson, Beat Schmid, Lexie A. Goldberger, Rob Newsom, and Jerome D. Fast
Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
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This work focuses on an expanding number of data sets observed using ARM TBS (133 flights) and UAS (seven flights) platforms by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research, such as the aerosol–cloud interaction in the boundary layer.
Falu Hong, Wenfeng Zhan, Frank-M. Göttsche, Zihan Liu, Pan Dong, Huyan Fu, Fan Huang, and Xiaodong Zhang
Earth Syst. Sci. Data, 14, 3091–3113, https://doi.org/10.5194/essd-14-3091-2022, https://doi.org/10.5194/essd-14-3091-2022, 2022
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Daily mean land surface temperature (LST) acquired from satellite thermal sensors is crucial for various applications such as global and regional climate change analysis. This study proposed a framework to generate global spatiotemporally seamless daily mean LST products (2003–2019). Validations show that the products outperform the traditional method with satisfying accuracy. Our further analysis reveals that the LST-based global land surface warming rate is 0.029 K yr−1 from 2003 to 2019.
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Reineman, B. D., Lenain, L., and Melville, W. K.: The Use of Ship-Launched Fixed-Wing UAVs for Measuring the Marine Atmospheric Boundary Layer and Ocean Surface Processes, J. Atmos. Ocean. Tech., 33, 2029–2052, https://doi.org/10.1175/JTECH-D-15-0019.1, 2016. a
Segales, A. R., Greene, B. R., Bell, T. M., Doyle, W., Martin, J. J., Pillar-Little, E. A., and Chilson, P. B.: The CopterSonde: an insight into the development of a smart unmanned aircraft system for atmospheric boundary layer research, Atmos. Meas. Tech., 13, 2833–2848, https://doi.org/10.5194/amt-13-2833-2020, 2020. a
Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., Miskus, D., and Stephens, S.: The Drought Monitor, B. Am. Meteorol. Soc., 83, 1181–1190, https://doi.org/10.1175/1520-0477-83.8.1181, 2002. a
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Short summary
This article provides an overview of the lower-atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
This article provides an overview of the lower-atmospheric dataset collected by two uncrewed...
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