Articles | Volume 8, issue 1
https://doi.org/10.5194/essd-8-199-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-8-199-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
12 May 2016
A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere
Christopher J. Cox
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental
Sciences, University of Colorado, Boulder, CO, USA
NOAA Earth System Research Laboratory, Physical Sciences
Division, Boulder, CO, USA
Penny M. Rowe
NorthWest Research Associates, Redmond, WA, USA
Department of Physics, Universidad de Santiago de
Chile, Santiago, Chile
Steven P. Neshyba
Department of Chemistry, University of Puget Sound,
Tacoma, WA, USA
Von P. Walden
Department of Civil and Environmental Engineering,
Washington State University, Pullman, WA, USA
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Carola Barrientos-Velasco, Christopher J. Cox, Hartwig Deneke, J. Brant Dodson, Anja Hünerbein, Matthew D. Shupe, Patrick C. Taylor, and Andreas Macke
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Understanding how clouds affect the climate, especially in the Arctic, is crucial. This study used data from the largest polar expedition in history, MOSAiC, and the CERES satellite to analyse the impact of clouds on radiation. Simulations showed accurate results, aligning with observations. Over the year, clouds caused the atmospheric-surface system to lose 5.2 W/m² of radiative energy to space, while the surface gained 25 W/m², and the atmosphere cooled by 30.2 W/m².
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. 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, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
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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 datasets 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 (MODFs), including a description of the sites, data format, and instruments.
Christopher J. Cox, Janet M. Intrieri, Brian Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-158, https://doi.org/10.5194/essd-2024-158, 2024
Preprint under review for ESSD
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Snow is an essential water resource in the intermountain western United States and predictions are made using models. We made observations to validate, constrain, and develop the models. The data is from the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in Colorado’s East River Valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 24, 1429–1450, https://doi.org/10.5194/acp-24-1429-2024, https://doi.org/10.5194/acp-24-1429-2024, 2024
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Observations collected during MOSAiC were used to identify the range in vertical structure and stability of the central Arctic lower atmosphere through a self-organizing map analysis. Characteristics of wind features (such as low-level jets) and atmospheric moisture features (such as clouds) were analyzed in the context of the varying vertical structure and stability. Thus, the results of this paper give an overview of the thermodynamic and kinematic features of the central Arctic atmosphere.
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.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 23, 13087–13106, https://doi.org/10.5194/acp-23-13087-2023, https://doi.org/10.5194/acp-23-13087-2023, 2023
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Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to determine the frequency of occurrence of various central Arctic lower atmospheric stability regimes and how the stability regimes transition between each other. Wind and radiation observations were analyzed in the context of stability regime and season to reveal the relationships between Arctic atmospheric stability and mechanically and radiatively driven turbulent forcings.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
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This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Christopher J. Cox, Sara M. Morris, Taneil Uttal, Ross Burgener, Emiel Hall, Mark Kutchenreiter, Allison McComiskey, Charles N. Long, Bryan D. Thomas, and James Wendell
Atmos. Meas. Tech., 14, 1205–1224, https://doi.org/10.5194/amt-14-1205-2021, https://doi.org/10.5194/amt-14-1205-2021, 2021
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Solar and infrared radiation are measured regularly for research, industry, and climate monitoring. In cold climates, icing of sensors is a poorly constrained source of uncertainty. D-ICE was carried out in Alaska to document the effectiveness of ice-mitigation technology and quantify errors associated with ice. Technology was more effective than anticipated, and while instantaneous errors were large, mean biases were small. Attributes of effective ice mitigation design were identified.
Penny M. Rowe, Christopher J. Cox, Steven Neshyba, and Von P. Walden
Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019, https://doi.org/10.5194/amt-12-5071-2019, 2019
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A better understanding of polar clouds is needed for predicting climate change, including cloud thickness and the sizes and amounts of liquid droplets and ice crystals. These properties can be estimated from an instrument (an infrared spectrometer) that sits on the surface and measures how much infrared radiation is emitted by the cloud. In this work we use model data to investigate how well such an instrument could retrieve cloud properties for different instrument and error characteristics.
Christopher J. Cox, David C. Noone, Max Berkelhammer, Matthew D. Shupe, William D. Neff, Nathaniel B. Miller, Von P. Walden, and Konrad Steffen
Atmos. Chem. Phys., 19, 7467–7485, https://doi.org/10.5194/acp-19-7467-2019, https://doi.org/10.5194/acp-19-7467-2019, 2019
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Fogs are frequently reported by observers on the Greenland Ice Sheet. Fogs play a role in the hydrological and energetic balances of the ice sheet surface, but as yet the properties of Greenland fogs are not well known. We observed fogs in all months from Summit Station for 2 years and report their properties. Annually, fogs impart a slight warming to the surface and a case study suggests that they are particularly influential by providing insulation during the coldest part of the day in summer.
Samantha Tremblay, Jean-Christophe Picard, Jill O. Bachelder, Erik Lutsch, Kimberly Strong, Pierre Fogal, W. Richard Leaitch, Sangeeta Sharma, Felicia Kolonjari, Christopher J. Cox, Rachel Y.-W. Chang, and Patrick L. Hayes
Atmos. Chem. Phys., 19, 5589–5604, https://doi.org/10.5194/acp-19-5589-2019, https://doi.org/10.5194/acp-19-5589-2019, 2019
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Atmospheric aerosols, tiny airborne particles, have an important impact on climate. However, a lack of understanding of the chemistry of aerosols is one of the largest contributors to uncertainty in predictions of climate change. Measurements of aerosols were carried out in the Arctic at Eureka Station, Canada, to better understand what role aerosols play in this fragile environment. It is found that organic aerosols, possibly originating from marine emissions, are ubiquitous during summertime.
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.
Amelie Driemel, John Augustine, Klaus Behrens, Sergio Colle, Christopher Cox, Emilio Cuevas-Agulló, Fred M. Denn, Thierry Duprat, Masato Fukuda, Hannes Grobe, Martial Haeffelin, Gary Hodges, Nicole Hyett, Osamu Ijima, Ain Kallis, Wouter Knap, Vasilii Kustov, Charles N. Long, David Longenecker, Angelo Lupi, Marion Maturilli, Mohamed Mimouni, Lucky Ntsangwane, Hiroyuki Ogihara, Xabier Olano, Marc Olefs, Masao Omori, Lance Passamani, Enio Bueno Pereira, Holger Schmithüsen, Stefanie Schumacher, Rainer Sieger, Jonathan Tamlyn, Roland Vogt, Laurent Vuilleumier, Xiangao Xia, Atsumu Ohmura, and Gert König-Langlo
Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, https://doi.org/10.5194/essd-10-1491-2018, 2018
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The Baseline Surface Radiation Network (BSRN) collects and centrally archives high-quality ground-based radiation measurements in 1 min resolution. More than 10 300 months, i.e., > 850 years, of high-radiation data in 1 min resolution from the years 1992 to 2017 are available. The network currently comprises 59 stations collectively representing all seven continents as well as island-based stations in the Pacific, Atlantic, Indian and Arctic oceans.
Emma L. Mungall, Jonathan P. D. Abbatt, Jeremy J. B. Wentzell, Gregory R. Wentworth, Jennifer G. Murphy, Daniel Kunkel, Ellen Gute, David W. Tarasick, Sangeeta Sharma, Christopher J. Cox, Taneil Uttal, and John Liggio
Atmos. Chem. Phys., 18, 10237–10254, https://doi.org/10.5194/acp-18-10237-2018, https://doi.org/10.5194/acp-18-10237-2018, 2018
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We measured gas-phase formic and acetic acid at Alert, Nunavut. These acids play an important role in cloud water acidity in remote environments, yet they are not well represented in chemical transport models, particularly in the Arctic. We observed high levels of formic and acetic acid under both cold, wet, and cloudy and warm, sunny, and dry conditions, suggesting that multiple sources significantly contribute to gas-phase concentrations of these species in the summer Arctic.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, and H. Alex McColl
Earth Syst. Sci. Data, 10, 1139–1164, https://doi.org/10.5194/essd-10-1139-2018, https://doi.org/10.5194/essd-10-1139-2018, 2018
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In early 2016 the NOAA's El Niño Rapid Response Field Campaign documented the ongoing strong event and its impacts. Observations from the warmed Pacific included 10 weeks of surface meteorology from Kiritimati Island and 4 weeks of surface meteorology and air–sea fluxes from NOAA Ship Ronald H. Brown. We have vetted the data, identifying issues and minimizing their impacts when possible. Measurements include a meter of rain at Kiritimati, and continuous ocean and air conditions from the ship.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, H. Alex McColl, Xiao-Wei Quan, and Matthew G. Winterkorn
Earth Syst. Sci. Data, 10, 1165–1183, https://doi.org/10.5194/essd-10-1165-2018, https://doi.org/10.5194/essd-10-1165-2018, 2018
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Radiosonde data collected during NOAA's El Niño Rapid Response Field Campaign in early 2016 have been reprocessed and lightly quality controlled. Temperature, humidity, and wind soundings from Kiritimati and NOAA Ship Ronald H. Brown capture the repeated advance and retreat of the ITCZ at Kiritimati, a variety of marine tropospheric environments encountered by the ship, and lower-stratospheric features of the 2015 2016 QBO (quasi-biennial oscillation).
Nathaniel B. Miller, Matthew D. Shupe, Christopher J. Cox, David Noone, P. Ola G. Persson, and Konrad Steffen
The Cryosphere, 11, 497–516, https://doi.org/10.5194/tc-11-497-2017, https://doi.org/10.5194/tc-11-497-2017, 2017
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A comprehensive observational dataset is assembled to investigate atmosphere–Greenland ice sheet interactions and characterize surface temperature variability. The amount the surface temperature warms, due to increases in cloud presence and/or elevated sun angle, varies throughout the annual cycle and is modulated by the responses of latent, sensible and ground heat fluxes. This observationally based study provides process-based relationships, which are useful for evaluation of climate models.
Penny M. Rowe, Christopher J. Cox, and Von P. Walden
Atmos. Meas. Tech., 9, 3641–3659, https://doi.org/10.5194/amt-9-3641-2016, https://doi.org/10.5194/amt-9-3641-2016, 2016
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Clouds play an important role in the rapid climate change occurring in polar regions, yet cloud measurements are challenging in such harsh, remote environments. Here we explore how well a proposed low-power infrared spectrometer, which would be highly portable, could be used to determine cloud height. Using simulated data, we estimate retrieval accuracy, finding that such an instrument would be able to constrain cloud height, particular for low, thick clouds, which are common in polar region.
Carola Barrientos-Velasco, Christopher J. Cox, Hartwig Deneke, J. Brant Dodson, Anja Hünerbein, Matthew D. Shupe, Patrick C. Taylor, and Andreas Macke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2193, https://doi.org/10.5194/egusphere-2024-2193, 2024
Short summary
Short summary
Understanding how clouds affect the climate, especially in the Arctic, is crucial. This study used data from the largest polar expedition in history, MOSAiC, and the CERES satellite to analyse the impact of clouds on radiation. Simulations showed accurate results, aligning with observations. Over the year, clouds caused the atmospheric-surface system to lose 5.2 W/m² of radiative energy to space, while the surface gained 25 W/m², and the atmosphere cooled by 30.2 W/m².
Ash Gilbert, Jennifer E. Kay, and Penny Rowe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2043, https://doi.org/10.5194/egusphere-2024-2043, 2024
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We developed a novel methodology for assessing whether a new physics parameterization should be added to a climate model based on its effect across a hierarchy of model complexities and time and spatial scales. Our study used this model hierarchy to evaluate the effect of a new cloud radiation parameterization on longwave radiation and determined that the parameterization should be added to climate radiation models, but its effect is not large enough to be a priority.
Zhongming Gao, Heping Liu, Dan Li, Bai Yang, Von Walden, Lei Li, and Ivan Bogoev
Atmos. Meas. Tech., 17, 4109–4120, https://doi.org/10.5194/amt-17-4109-2024, https://doi.org/10.5194/amt-17-4109-2024, 2024
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Using data collected from three levels of a 62 m tower, we found that both the temperature variances and sensible heat flux obtained from sonic anemometers are consistently lower, by a few percent, compared to those from fine-wire thermocouples.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. 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, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
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 datasets 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 (MODFs), including a description of the sites, data format, and instruments.
Christopher J. Cox, Janet M. Intrieri, Brian Butterworth, Gijs de Boer, Michael R. Gallagher, Jonathan Hamilton, Erik Hulm, Tilden Meyers, Sara M. Morris, Jackson Osborn, P. Ola G. Persson, Benjamin Schmatz, Matthew D. Shupe, and James M. Wilczak
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-158, https://doi.org/10.5194/essd-2024-158, 2024
Preprint under review for ESSD
Short summary
Short summary
Snow is an essential water resource in the intermountain western United States and predictions are made using models. We made observations to validate, constrain, and develop the models. The data is from the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in Colorado’s East River Valley, 2021–2023. The measurements include meteorology and variables that quantify energy transfer between the atmosphere and surface. The data are available publicly.
Zhenhai Zhang, F. Martin Ralph, Xun Zou, Brian Kawzenuk, Minghua Zheng, Irina V. Gorodetskaya, Penny M. Rowe, and David H. Bromwich
EGUsphere, https://doi.org/10.5194/egusphere-2024-254, https://doi.org/10.5194/egusphere-2024-254, 2024
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Atmospheric rivers are long and narrow corridors of strong water vapor transport in the atmosphere. ARs play an important role in extreme weather in polar regions, including heavy rain/snow, heat wave, and surface melt. The standard AR scale is developed based on the mid-latitude climate and is insufficient for polar regions. This paper introduces an extended version of the AR scale tuned to polar regions, aiming to quantify polar ARs objectively based on their strength and impact.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 24, 1429–1450, https://doi.org/10.5194/acp-24-1429-2024, https://doi.org/10.5194/acp-24-1429-2024, 2024
Short summary
Short summary
Observations collected during MOSAiC were used to identify the range in vertical structure and stability of the central Arctic lower atmosphere through a self-organizing map analysis. Characteristics of wind features (such as low-level jets) and atmospheric moisture features (such as clouds) were analyzed in the context of the varying vertical structure and stability. Thus, the results of this paper give an overview of the thermodynamic and kinematic features of the central Arctic atmosphere.
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
Short summary
Short summary
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.
Gina C. Jozef, John J. Cassano, Sandro Dahlke, Mckenzie Dice, Christopher J. Cox, and Gijs de Boer
Atmos. Chem. Phys., 23, 13087–13106, https://doi.org/10.5194/acp-23-13087-2023, https://doi.org/10.5194/acp-23-13087-2023, 2023
Short summary
Short summary
Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to determine the frequency of occurrence of various central Arctic lower atmospheric stability regimes and how the stability regimes transition between each other. Wind and radiation observations were analyzed in the context of stability regime and season to reveal the relationships between Arctic atmospheric stability and mechanically and radiatively driven turbulent forcings.
Heather Guy, David D. Turner, Von P. Walden, Ian M. Brooks, and Ryan R. Neely
Atmos. Meas. Tech., 15, 5095–5115, https://doi.org/10.5194/amt-15-5095-2022, https://doi.org/10.5194/amt-15-5095-2022, 2022
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Fog formation is highly sensitive to near-surface temperatures and humidity profiles. Passive remote sensing instruments can provide continuous measurements of the vertical temperature and humidity profiles and liquid water content, which can improve fog forecasts. Here we compare the performance of collocated infrared and microwave remote sensing instruments and demonstrate that the infrared instrument is especially sensitive to the onset of thin radiation fog.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
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We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Shima Bahramvash Shams, Von P. Walden, James W. Hannigan, William J. Randel, Irina V. Petropavlovskikh, Amy H. Butler, and Alvaro de la Cámara
Atmos. Chem. Phys., 22, 5435–5458, https://doi.org/10.5194/acp-22-5435-2022, https://doi.org/10.5194/acp-22-5435-2022, 2022
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Large-scale atmospheric circulation has a strong influence on ozone in the Arctic, and certain anomalous dynamical events, such as sudden stratospheric warmings, cause dramatic alterations of the large-scale circulation. A reanalysis model is evaluated and then used to investigate the impact of sudden stratospheric warmings on mid-atmospheric ozone. Results show that the position of the cold jet stream over the Arctic before these events influences the variability of ozone.
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data, 14, 19–31, https://doi.org/10.5194/essd-14-19-2022, https://doi.org/10.5194/essd-14-19-2022, 2022
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This article provides a summary of the collection of atmospheric data over the near-coastal zone upwind of Barbados during the ATOMIC and EUREC4A field campaigns. These data were collected to improve our understanding of the structure and dynamics of the lower atmosphere in the tropical trade-wind regime over the Atlantic Ocean and the influence of that portion of the atmosphere on the development and maintenance of clouds.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Christopher J. Cox, Sara M. Morris, Taneil Uttal, Ross Burgener, Emiel Hall, Mark Kutchenreiter, Allison McComiskey, Charles N. Long, Bryan D. Thomas, and James Wendell
Atmos. Meas. Tech., 14, 1205–1224, https://doi.org/10.5194/amt-14-1205-2021, https://doi.org/10.5194/amt-14-1205-2021, 2021
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Solar and infrared radiation are measured regularly for research, industry, and climate monitoring. In cold climates, icing of sensors is a poorly constrained source of uncertainty. D-ICE was carried out in Alaska to document the effectiveness of ice-mitigation technology and quantify errors associated with ice. Technology was more effective than anticipated, and while instantaneous errors were large, mean biases were small. Attributes of effective ice mitigation design were identified.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-266, https://doi.org/10.5194/amt-2020-266, 2020
Preprint withdrawn
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Optically thin clouds containing low amounts of water are difficult to observe, but due to their frequent presence they have a non-neglectible impact on Earth's radiative budget. Here we present a retrieval for mixed-phase clouds from thermal-infared spectra, measured using a FTIR spectrometer. Even in situations where the atmospheric windows in the far-infrared are not applicable, cloud optical depths, effective droplet radii and water paths of mixed-phase clouds can be retrieved.
Penny M. Rowe, Christopher J. Cox, Steven Neshyba, and Von P. Walden
Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019, https://doi.org/10.5194/amt-12-5071-2019, 2019
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A better understanding of polar clouds is needed for predicting climate change, including cloud thickness and the sizes and amounts of liquid droplets and ice crystals. These properties can be estimated from an instrument (an infrared spectrometer) that sits on the surface and measures how much infrared radiation is emitted by the cloud. In this work we use model data to investigate how well such an instrument could retrieve cloud properties for different instrument and error characteristics.
Shima Bahramvash Shams, Von P. Walden, Irina Petropavlovskikh, David Tarasick, Rigel Kivi, Samuel Oltmans, Bryan Johnson, Patrick Cullis, Chance W. Sterling, Laura Thölix, and Quentin Errera
Atmos. Chem. Phys., 19, 9733–9751, https://doi.org/10.5194/acp-19-9733-2019, https://doi.org/10.5194/acp-19-9733-2019, 2019
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The Arctic plays a very important role in the global ozone cycle. We use balloon-borne sampling and satellite data to create a high-quality dataset of the vertical profile of ozone from 2005 to 2017 to analyze ozone variations over four high-latitude Arctic locations. No significant annual trend is found at any of the studied locations. We develop a mathematical model to understand how deseasonalized ozone fluctuations can be influenced by various parameters.
Christopher J. Cox, David C. Noone, Max Berkelhammer, Matthew D. Shupe, William D. Neff, Nathaniel B. Miller, Von P. Walden, and Konrad Steffen
Atmos. Chem. Phys., 19, 7467–7485, https://doi.org/10.5194/acp-19-7467-2019, https://doi.org/10.5194/acp-19-7467-2019, 2019
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Fogs are frequently reported by observers on the Greenland Ice Sheet. Fogs play a role in the hydrological and energetic balances of the ice sheet surface, but as yet the properties of Greenland fogs are not well known. We observed fogs in all months from Summit Station for 2 years and report their properties. Annually, fogs impart a slight warming to the surface and a case study suggests that they are particularly influential by providing insulation during the coldest part of the day in summer.
Samantha Tremblay, Jean-Christophe Picard, Jill O. Bachelder, Erik Lutsch, Kimberly Strong, Pierre Fogal, W. Richard Leaitch, Sangeeta Sharma, Felicia Kolonjari, Christopher J. Cox, Rachel Y.-W. Chang, and Patrick L. Hayes
Atmos. Chem. Phys., 19, 5589–5604, https://doi.org/10.5194/acp-19-5589-2019, https://doi.org/10.5194/acp-19-5589-2019, 2019
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Atmospheric aerosols, tiny airborne particles, have an important impact on climate. However, a lack of understanding of the chemistry of aerosols is one of the largest contributors to uncertainty in predictions of climate change. Measurements of aerosols were carried out in the Arctic at Eureka Station, Canada, to better understand what role aerosols play in this fragile environment. It is found that organic aerosols, possibly originating from marine emissions, are ubiquitous during summertime.
Christopher Perro, Thomas J. Duck, Glen Lesins, Kimberly Strong, Penny M. Rowe, James R. Drummond, and Robert J. Sica
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-381, https://doi.org/10.5194/amt-2018-381, 2019
Publication in AMT not foreseen
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A satellite retrieval for water vapour column was adapted for use over different surfaces in the wintertime Arctic. The retrieval was validated at multiple locations where there was excellent agreement. Reanalyses were found to be 10–15 % drier compared to our water vapour retrieval. Reanalyses represent the present day understanding of the atmosphere so this discrepancy between reanalyses and our retrieval could have implications for the current understanding of the climate.
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.
Amelie Driemel, John Augustine, Klaus Behrens, Sergio Colle, Christopher Cox, Emilio Cuevas-Agulló, Fred M. Denn, Thierry Duprat, Masato Fukuda, Hannes Grobe, Martial Haeffelin, Gary Hodges, Nicole Hyett, Osamu Ijima, Ain Kallis, Wouter Knap, Vasilii Kustov, Charles N. Long, David Longenecker, Angelo Lupi, Marion Maturilli, Mohamed Mimouni, Lucky Ntsangwane, Hiroyuki Ogihara, Xabier Olano, Marc Olefs, Masao Omori, Lance Passamani, Enio Bueno Pereira, Holger Schmithüsen, Stefanie Schumacher, Rainer Sieger, Jonathan Tamlyn, Roland Vogt, Laurent Vuilleumier, Xiangao Xia, Atsumu Ohmura, and Gert König-Langlo
Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, https://doi.org/10.5194/essd-10-1491-2018, 2018
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The Baseline Surface Radiation Network (BSRN) collects and centrally archives high-quality ground-based radiation measurements in 1 min resolution. More than 10 300 months, i.e., > 850 years, of high-radiation data in 1 min resolution from the years 1992 to 2017 are available. The network currently comprises 59 stations collectively representing all seven continents as well as island-based stations in the Pacific, Atlantic, Indian and Arctic oceans.
Emma L. Mungall, Jonathan P. D. Abbatt, Jeremy J. B. Wentzell, Gregory R. Wentworth, Jennifer G. Murphy, Daniel Kunkel, Ellen Gute, David W. Tarasick, Sangeeta Sharma, Christopher J. Cox, Taneil Uttal, and John Liggio
Atmos. Chem. Phys., 18, 10237–10254, https://doi.org/10.5194/acp-18-10237-2018, https://doi.org/10.5194/acp-18-10237-2018, 2018
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We measured gas-phase formic and acetic acid at Alert, Nunavut. These acids play an important role in cloud water acidity in remote environments, yet they are not well represented in chemical transport models, particularly in the Arctic. We observed high levels of formic and acetic acid under both cold, wet, and cloudy and warm, sunny, and dry conditions, suggesting that multiple sources significantly contribute to gas-phase concentrations of these species in the summer Arctic.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, and H. Alex McColl
Earth Syst. Sci. Data, 10, 1139–1164, https://doi.org/10.5194/essd-10-1139-2018, https://doi.org/10.5194/essd-10-1139-2018, 2018
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In early 2016 the NOAA's El Niño Rapid Response Field Campaign documented the ongoing strong event and its impacts. Observations from the warmed Pacific included 10 weeks of surface meteorology from Kiritimati Island and 4 weeks of surface meteorology and air–sea fluxes from NOAA Ship Ronald H. Brown. We have vetted the data, identifying issues and minimizing their impacts when possible. Measurements include a meter of rain at Kiritimati, and continuous ocean and air conditions from the ship.
Leslie M. Hartten, Christopher J. Cox, Paul E. Johnston, Daniel E. Wolfe, Scott Abbott, H. Alex McColl, Xiao-Wei Quan, and Matthew G. Winterkorn
Earth Syst. Sci. Data, 10, 1165–1183, https://doi.org/10.5194/essd-10-1165-2018, https://doi.org/10.5194/essd-10-1165-2018, 2018
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Radiosonde data collected during NOAA's El Niño Rapid Response Field Campaign in early 2016 have been reprocessed and lightly quality controlled. Temperature, humidity, and wind soundings from Kiritimati and NOAA Ship Ronald H. Brown capture the repeated advance and retreat of the ITCZ at Kiritimati, a variety of marine tropospheric environments encountered by the ship, and lower-stratospheric features of the 2015 2016 QBO (quasi-biennial oscillation).
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
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A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Dan Weaver, Kimberly Strong, Matthias Schneider, Penny M. Rowe, Chris Sioris, Kaley A. Walker, Zen Mariani, Taneil Uttal, C. Thomas McElroy, Holger Vömel, Alessio Spassiani, and James R. Drummond
Atmos. Meas. Tech., 10, 2851–2880, https://doi.org/10.5194/amt-10-2851-2017, https://doi.org/10.5194/amt-10-2851-2017, 2017
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We have compared techniques used by several PEARL instruments to measure atmospheric water vapour. No single instrument can comprehensively map the atmosphere. We documented how well these techniques perform and quantified the agreement and biases between them. This work showed that new FTIR datasets at PEARL capture accurate measurements of High Arctic water vapour.
Nathaniel B. Miller, Matthew D. Shupe, Christopher J. Cox, David Noone, P. Ola G. Persson, and Konrad Steffen
The Cryosphere, 11, 497–516, https://doi.org/10.5194/tc-11-497-2017, https://doi.org/10.5194/tc-11-497-2017, 2017
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A comprehensive observational dataset is assembled to investigate atmosphere–Greenland ice sheet interactions and characterize surface temperature variability. The amount the surface temperature warms, due to increases in cloud presence and/or elevated sun angle, varies throughout the annual cycle and is modulated by the responses of latent, sensible and ground heat fluxes. This observationally based study provides process-based relationships, which are useful for evaluation of climate models.
Penny M. Rowe, Christopher J. Cox, and Von P. Walden
Atmos. Meas. Tech., 9, 3641–3659, https://doi.org/10.5194/amt-9-3641-2016, https://doi.org/10.5194/amt-9-3641-2016, 2016
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Clouds play an important role in the rapid climate change occurring in polar regions, yet cloud measurements are challenging in such harsh, remote environments. Here we explore how well a proposed low-power infrared spectrometer, which would be highly portable, could be used to determine cloud height. Using simulated data, we estimate retrieval accuracy, finding that such an instrument would be able to constrain cloud height, particular for low, thick clouds, which are common in polar region.
P. M. Rowe, S. Neshyba, and V. P. Walden
Atmos. Chem. Phys., 13, 11925–11933, https://doi.org/10.5194/acp-13-11925-2013, https://doi.org/10.5194/acp-13-11925-2013, 2013
Related subject area
Data, Algorithms, and Models
Improved maps of surface water bodies, large dams, reservoirs, and lakes in China
The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation
A high-resolution inland surface water body dataset for the tundra and boreal forests of North America
A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan
HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand
A dataset of microphysical cloud parameters, retrieved from Fourier-transform infrared (FTIR) emission spectra measured in Arctic summer 2017
A global long-term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network
First SMOS Sea Surface Salinity dedicated products over the Baltic Sea
HomogWS-se: a century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden
Mapping long-term and high-resolution global gridded photosynthetically active radiation using the ISCCP H-series cloud product and reanalysis data
Description of the China global Merged Surface Temperature version 2.0
TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning
Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations
Multi-site, multi-crop measurements in the soil–vegetation–atmosphere continuum: a comprehensive dataset from two climatically contrasting regions in southwestern Germany for the period 2009–2018
Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005–2017 based on a multi-variable random forest model
Median bed-material sediment particle size across rivers in the contiguous US
A flux tower dataset tailored for land model evaluation
A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018
A harmonized global land evaporation dataset from model-based products covering 1980–2017
Estimating population and urban areas at risk of coastal hazards, 1990–2015: how data choices matter
Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017
GRQA: Global River Water Quality Archive
A 1 km global cropland dataset from 10 000 BCE to 2100 CE
A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables
SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach
Nitrogen deposition in the UK at 1 km resolution from 1990 to 2017
ERA5-Land: a state-of-the-art global reanalysis dataset for land applications
An all-sky 1 km daily land surface air temperature product over mainland China for 2003–2019 from MODIS and ancillary data
100 years of lake evolution over the Qinghai–Tibet Plateau
The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019
Coastal complexity of the Antarctic continent
UAV-based very high resolution point cloud, digital surface model and orthomosaic of the Chã das Caldeiras lava fields (Fogo, Cabo Verde)
AQ-Bench: a benchmark dataset for machine learning on global air quality metrics
Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018
A new merged dataset for analyzing clouds, precipitation and atmospheric parameters based on ERA5 reanalysis data and the measurements of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner
A new satellite-derived dataset for marine aquaculture areas in China's coastal region
Database of petrophysical properties of the Mid-German Crystalline Rise
Landsat-derived bathymetry of lakes on the Arctic Coastal Plain of northern Alaska
Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China
Hyperspectral-reflectance dataset of dry, wet and submerged marine litter
A climate service for ecologists: sharing pre-processed EURO-CORDEX regional climate scenario data using the eLTER Information System
Crowdsourced air traffic data from the OpenSky Network 2019–2020
A restructured and updated global soil respiration database (SRDB-V5)
The Berkeley Earth Land/Ocean Temperature Record
Dielectric database of organic Arctic soils (DDOAS)
Global Carbon Budget 2020
A global long-term (1981–2000) land surface temperature product for NOAA AVHRR
A coastally improved global dataset of wet tropospheric corrections for satellite altimetry
Xinxin Wang, Xiangming Xiao, Yuanwei Qin, Jinwei Dong, Jihua Wu, and Bo Li
Earth Syst. Sci. Data, 14, 3757–3771, https://doi.org/10.5194/essd-14-3757-2022, https://doi.org/10.5194/essd-14-3757-2022, 2022
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We generated China’s surface water bodies, Large Dams, Reservoirs, and Lakes (China-LDRL) dataset by analyzing all available Landsat imagery in 2019 (19\,338 images) in Google Earth Engine. The dataset provides accurate information on the geographical locations and sizes of surface water bodies, large dams, reservoirs, and lakes in China. The China-LDRL dataset will contribute to the understanding of water security and water resources management in China.
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022, https://doi.org/10.5194/essd-14-3489-2022, 2022
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The potential degradation of mainstream global fire products leads to large uncertainty in the effective monitoring of wildfires and their influence. To fill this gap, we produced a Fengyun-3D (FY-3D) global active fire product with a similar spatial and temporal resolution to MODIS fire products, aiming to serve as continuity and a replacement for MODIS fire products. The FY-3D fire product is an ideal tool for global fire monitoring and can be preferably employed for fire monitoring in China.
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022, https://doi.org/10.5194/essd-14-3349-2022, 2022
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High-latitude water bodies differ greatly in their morphological and topological characteristics related to their formation, type, and vulnerability. In this paper, we present a water body dataset for the North American high latitudes (WBD-NAHL). Nearly 6.5 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2.
Amy McNally, Jossy Jacob, Kristi Arsenault, Kimberly Slinski, Daniel P. Sarmiento, Andrew Hoell, Shahriar Pervez, James Rowland, Mike Budde, Sujay Kumar, Christa Peters-Lidard, and James P. Verdin
Earth Syst. Sci. Data, 14, 3115–3135, https://doi.org/10.5194/essd-14-3115-2022, https://doi.org/10.5194/essd-14-3115-2022, 2022
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The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams described here generate routine estimates of snow, soil moisture, runoff, and other variables useful for tracking water availability. These data are hosted by NASA and USGS data portals for public use.
Thomas R. Etherington, George L. W. Perry, and Janet M. Wilmshurst
Earth Syst. Sci. Data, 14, 2817–2832, https://doi.org/10.5194/essd-14-2817-2022, https://doi.org/10.5194/essd-14-2817-2022, 2022
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Long time series of temperature and rainfall grids are fundamental to understanding how these variables affects environmental or ecological patterns and processes. We present a History of Open Temperature and Rainfall with Uncertainty in New Zealand (HOTRUNZ) that is an open-access dataset that provides monthly 1 km resolution grids of rainfall and mean, minimum, and maximum daily temperatures with associated uncertainties for New Zealand from 1910 to 2019.
Philipp Richter, Mathias Palm, Christine Weinzierl, Hannes Griesche, Penny M. Rowe, and Justus Notholt
Earth Syst. Sci. Data, 14, 2767–2784, https://doi.org/10.5194/essd-14-2767-2022, https://doi.org/10.5194/essd-14-2767-2022, 2022
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We present a dataset of cloud optical depths, effective radii and water paths from optically thin clouds observed in the Arctic around Svalbard. The data have been retrieved from infrared spectral radiance measured using a Fourier-transform infrared (FTIR) spectrometer. Besides a description of the measurements and retrieval technique, the data are put into context with results of corresponding measurements from microwave radiometer, lidar and cloud radar.
Jianglei Xu, Shunlin Liang, and Bo Jiang
Earth Syst. Sci. Data, 14, 2315–2341, https://doi.org/10.5194/essd-14-2315-2022, https://doi.org/10.5194/essd-14-2315-2022, 2022
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Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
Verónica González-Gambau, Estrella Olmedo, Antonio Turiel, Cristina González-Haro, Aina García-Espriu, Justino Martínez, Pekka Alenius, Laura Tuomi, Rafael Catany, Manuel Arias, Carolina Gabarró, Nina Hoareau, Marta Umbert, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 2343–2368, https://doi.org/10.5194/essd-14-2343-2022, https://doi.org/10.5194/essd-14-2343-2022, 2022
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We present the first Soil Moisture and Ocean Salinity Sea Surface Salinity (SSS) dedicated products over the Baltic Sea (ESA Baltic+ Salinity Dynamics). The Baltic+ L3 product covers 9 days in a 0.25° grid. The Baltic+ L4 is derived by merging L3 SSS with sea surface temperature information, giving a daily product in a 0.05° grid. The accuracy of L3 is 0.7–0.8 and 0.4 psu for the L4. Baltic+ products have shown to be useful, covering spatiotemporal data gaps and for validating numerical models.
Chunlüe Zhou, Cesar Azorin-Molina, Erik Engström, Lorenzo Minola, Lennart Wern, Sverker Hellström, Jessika Lönn, and Deliang Chen
Earth Syst. Sci. Data, 14, 2167–2177, https://doi.org/10.5194/essd-14-2167-2022, https://doi.org/10.5194/essd-14-2167-2022, 2022
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To fill the key gap of short availability and inhomogeneity of wind speed (WS) in Sweden, we rescued the early paper records of WS since 1925 and built the first 10-member centennial homogenized WS dataset (HomogWS-se) for community use. An initial WS stilling and recovery before the 1990s was observed, and a strong link with North Atlantic Oscillation was found. HomogWS-se improves our knowledge of uncertainty and causes of historical WS changes.
Wenjun Tang, Jun Qin, Kun Yang, Yaozhi Jiang, and Weihao Pan
Earth Syst. Sci. Data, 14, 2007–2019, https://doi.org/10.5194/essd-14-2007-2022, https://doi.org/10.5194/essd-14-2007-2022, 2022
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Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year high-resolution global gridded PAR dataset. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution.
Wenbin Sun, Yang Yang, Liya Chao, Wenjie Dong, Boyin Huang, Phil Jones, and Qingxiang Li
Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, https://doi.org/10.5194/essd-14-1677-2022, 2022
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The new China global Merged Surface Temperature CMST 2.0 is the updated version of CMST-Interim used in the IPCC's AR6. The updated dataset is described in this study, containing three versions: CMST2.0 – Nrec, CMST2.0 – Imax, and CMST2.0 – Imin. The reconstructed datasets significantly improve data coverage, especially in the high latitudes in the Northern Hemisphere, thus increasing the long-term trends at global, hemispheric, and regional scales since 1850.
Rohaifa Khaldi, Domingo Alcaraz-Segura, Emilio Guirado, Yassir Benhammou, Abdellatif El Afia, Francisco Herrera, and Siham Tabik
Earth Syst. Sci. Data, 14, 1377–1411, https://doi.org/10.5194/essd-14-1377-2022, https://doi.org/10.5194/essd-14-1377-2022, 2022
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This dataset with millions of 22-year time series for seven spectral bands was built by merging Terra and Aqua satellite data and annotated for 29 LULC classes by spatial–temporal agreement across 15 global LULC products. The mean F1 score was 96 % at the coarsest classification level and 87 % at the finest one. The dataset is born to develop and evaluate machine learning models to perform global LULC mapping given the disagreement between current global LULC products.
Chuanmin Hu
Earth Syst. Sci. Data, 14, 1183–1192, https://doi.org/10.5194/essd-14-1183-2022, https://doi.org/10.5194/essd-14-1183-2022, 2022
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Using data collected by the Hyperspectral Imager for the Coastal Ocean (HICO) between 2010–2014, hyperspectral reflectance of various floating matters in global oceans and lakes is derived for the spectral range of 400–800 nm. Such reflectance spectra are expected to provide spectral endmembers to differentiate and quantify the floating matters from existing multi-band satellite sensors and future hyperspectral satellite missions such as NASA’s PACE, SBG, and GLIMR missions.
Tobias K. D. Weber, Joachim Ingwersen, Petra Högy, Arne Poyda, Hans-Dieter Wizemann, Michael Scott Demyan, Kristina Bohm, Ravshan Eshonkulov, Sebastian Gayler, Pascal Kremer, Moritz Laub, Yvonne Funkiun Nkwain, Christian Troost, Irene Witte, Tim Reichenau, Thomas Berger, Georg Cadisch, Torsten Müller, Andreas Fangmeier, Volker Wulfmeyer, and Thilo Streck
Earth Syst. Sci. Data, 14, 1153–1181, https://doi.org/10.5194/essd-14-1153-2022, https://doi.org/10.5194/essd-14-1153-2022, 2022
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Presented are measurement results from six agricultural fields operated by local farmers in southwestern Germany over 9 years. Six eddy-covariance stations measuring water, energy, and carbon fluxes between the vegetated soil surface and the atmosphere provided the backbone of the measurement sites and were supplemented by extensive soil and vegetation state monitoring. The dataset is ideal for testing process models characterizing fluxes at the vegetated soil surface and in the atmosphere.
Runmei Ma, Jie Ban, Qing Wang, Yayi Zhang, Yang Yang, Shenshen Li, Wenjiao Shi, Zhen Zhou, Jiawei Zang, and Tiantian Li
Earth Syst. Sci. Data, 14, 943–954, https://doi.org/10.5194/essd-14-943-2022, https://doi.org/10.5194/essd-14-943-2022, 2022
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We constructed multi-variable random forest models based on 10-fold cross-validation and estimated daily PM2.5 and O3 concentration of China in 2005–2017 at a resolution of 1 km. The daily R2 values of PM2.5 and O3 were 0.85 and 0.77. The meteorological variables can significantly affect both PM2.5 and O3 modeling. During 2005–2017, PM2.5 exhibited an overall downward trend, while O3 experienced the opposite. The temporal trend of PM2.5 and O3 had spatial characteristics during the study period.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Anna M. Ukkola, Gab Abramowitz, and Martin G. De Kauwe
Earth Syst. Sci. Data, 14, 449–461, https://doi.org/10.5194/essd-14-449-2022, https://doi.org/10.5194/essd-14-449-2022, 2022
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Flux towers provide measurements of water, energy, and carbon fluxes. Flux tower data are invaluable in improving and evaluating land models but are not suited to modelling applications as published. Here we present flux tower data tailored for land modelling, encompassing 170 sites globally. Our dataset resolves several key limitations hindering the use of flux tower data in land modelling, including incomplete forcing variable, data format, and low data quality.
Hui Tao, Kaishan Song, Ge Liu, Qiang Wang, Zhidan Wen, Pierre-Andre Jacinthe, Xiaofeng Xu, Jia Du, Yingxin Shang, Sijia Li, Zongming Wang, Lili Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, and Hongtao Duan
Earth Syst. Sci. Data, 14, 79–94, https://doi.org/10.5194/essd-14-79-2022, https://doi.org/10.5194/essd-14-79-2022, 2022
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During 1984–2018, lakes in the Tibetan-Qinghai Plateau had the clearest water (mean 3.32 ± 0.38 m), while those in the northeastern region had the lowest Secchi disk depth (SDD) (mean 0.60 ± 0.09 m). Among the 10 814 lakes with > 10 years of SDD results, 55.4 % and 3.5 % experienced significantly increasing and decreasing trends of SDD, respectively. With the exception of Inner Mongolia–Xinjiang, more than half of lakes in all the other regions exhibited a significant trend of increasing SDD.
Jiao Lu, Guojie Wang, Tiexi Chen, Shijie Li, Daniel Fiifi Tawia Hagan, Giri Kattel, Jian Peng, Tong Jiang, and Buda Su
Earth Syst. Sci. Data, 13, 5879–5898, https://doi.org/10.5194/essd-13-5879-2021, https://doi.org/10.5194/essd-13-5879-2021, 2021
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This study has combined three existing land evaporation (ET) products to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25° to define the global proxy ET with lower uncertainties. The merged product is the best at capturing dynamics over different locations and times among all data sets. The merged product performed well over a range of vegetation cover scenarios and also captured the trend of land evaporation over different areas well.
Kytt MacManus, Deborah Balk, Hasim Engin, Gordon McGranahan, and Rya Inman
Earth Syst. Sci. Data, 13, 5747–5801, https://doi.org/10.5194/essd-13-5747-2021, https://doi.org/10.5194/essd-13-5747-2021, 2021
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New estimates of population and land area by settlement types within low-elevation coastal zones (LECZs) based on four sources of population data, four sources of settlement data and four sources of elevation data for the years 1990, 2000 and 2015. The paper describes the sensitivity of these estimates and discusses the fitness of use guiding user decisions. Data choices impact the number of people estimated within LECZs, but across all sources the LECZs are predominantly urban and growing.
Yanhua Xie, Holly K. Gibbs, and Tyler J. Lark
Earth Syst. Sci. Data, 13, 5689–5710, https://doi.org/10.5194/essd-13-5689-2021, https://doi.org/10.5194/essd-13-5689-2021, 2021
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We created 30 m resolution annual irrigation maps covering the conterminous US for the period of 1997–2017, together with derivative products and ground reference data. The products have several improvements over other data, including field-level details of change and frequency, an annual time step, a collection of ~ 10 000 ground reference locations for the eastern US, and improved mapping accuracy of over 90 %, especially in the east compared to others of 50 % to 80 %.
Holger Virro, Giuseppe Amatulli, Alexander Kmoch, Longzhu Shen, and Evelyn Uuemaa
Earth Syst. Sci. Data, 13, 5483–5507, https://doi.org/10.5194/essd-13-5483-2021, https://doi.org/10.5194/essd-13-5483-2021, 2021
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Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.
Bowen Cao, Le Yu, Xuecao Li, Min Chen, Xia Li, Pengyu Hao, and Peng Gong
Earth Syst. Sci. Data, 13, 5403–5421, https://doi.org/10.5194/essd-13-5403-2021, https://doi.org/10.5194/essd-13-5403-2021, 2021
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In the study, the first 1 km global cropland proportion dataset for 10 000 BCE–2100 CE was produced through the harmonization and downscaling framework. The mapping result coincides well with widely used datasets at present. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The dataset will be valuable for long-term simulations and precise analyses. The framework can be extended to specific regions or other land use types.
Diyang Cui, Shunlin Liang, Dongdong Wang, and Zheng Liu
Earth Syst. Sci. Data, 13, 5087–5114, https://doi.org/10.5194/essd-13-5087-2021, https://doi.org/10.5194/essd-13-5087-2021, 2021
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Large portions of the Earth's surface are expected to experience changes in climatic conditions. The rearrangement of climate distributions can lead to serious impacts on ecological and social systems. Major climate zones are distributed in a predictable pattern and are largely defined following the Köppen climate classification. This creates an urgent need to compile a series of Köppen climate classification maps with finer spatial and temporal resolutions and improved accuracy.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
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The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Samuel J. Tomlinson, Edward J. Carnell, Anthony J. Dore, and Ulrike Dragosits
Earth Syst. Sci. Data, 13, 4677–4692, https://doi.org/10.5194/essd-13-4677-2021, https://doi.org/10.5194/essd-13-4677-2021, 2021
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Nitrogen (N) may impact the environment in many ways, and estimation of its deposition to the terrestrial surface is of interest. N deposition data have not been generated at a high resolution (1 km × 1 km) over a long time series in the UK before now. This study concludes that N deposition has reduced by ~ 40 % from 1990. The impact of these results allows analysis of environmental impacts at a high spatial and temporal resolution, using a consistent methodology and consistent set of input data.
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, https://doi.org/10.5194/essd-13-4349-2021, 2021
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The creation of ERA5-Land responds to a growing number of applications requiring global land datasets at a resolution higher than traditionally reached. ERA5-Land provides operational, global, and hourly key variables of the water and energy cycles over land surfaces, at 9 km resolution, from 1981 until the present. This work provides evidence of an overall improvement of the water cycle compared to previous reanalyses, whereas the energy cycle variables perform as well as those of ERA5.
Yan Chen, Shunlin Liang, Han Ma, Bing Li, Tao He, and Qian Wang
Earth Syst. Sci. Data, 13, 4241–4261, https://doi.org/10.5194/essd-13-4241-2021, https://doi.org/10.5194/essd-13-4241-2021, 2021
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This study used remotely sensed and assimilated data to estimate all-sky land surface air temperature (Ta) using a machine learning method, and developed an all-sky 1 km daily mean land Ta product for 2003–2019 over mainland China. Validation results demonstrated that this dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in studies of climate change and the hydrological cycle.
Guoqing Zhang, Youhua Ran, Wei Wan, Wei Luo, Wenfeng Chen, Fenglin Xu, and Xin Li
Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, https://doi.org/10.5194/essd-13-3951-2021, 2021
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Lakes can be effective indicators of climate change, especially over the Qinghai–Tibet Plateau. Here, we provide the most comprehensive lake mapping covering the past 100 years. The new features of this data set are (1) its temporal length, providing the longest period of lake observations from maps, (2) the data set provides a state-of-the-art lake inventory for the Landsat era (from the 1970s to 2020), and (3) it provides the densest lake observations for lakes with areas larger than 1 km2.
Jie Yang and Xin Huang
Earth Syst. Sci. Data, 13, 3907–3925, https://doi.org/10.5194/essd-13-3907-2021, https://doi.org/10.5194/essd-13-3907-2021, 2021
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We produce the 30 m annual China land cover dataset (CLCD), with an accuracy reaching 79.31 %. Trends and patterns of land cover changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and increase in forest (+4.34 %). The CLCD generally reflected the rapid urbanization and a series of ecological projects in China and revealed the anthropogenic implications on LC under the condition of climate change.
Richard Porter-Smith, John McKinlay, Alexander D. Fraser, and Robert A. Massom
Earth Syst. Sci. Data, 13, 3103–3114, https://doi.org/10.5194/essd-13-3103-2021, https://doi.org/10.5194/essd-13-3103-2021, 2021
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This study quantifies the characteristic complexity
signaturesaround the Antarctic outer coastal margin, giving a multiscale estimate of the magnitude and direction of undulation or complexity at each point location along the entire coastline. It has numerous applications for both geophysical and biological studies and will contribute to Antarctic research requiring quantitative information about this important interface.
Gonçalo Vieira, Carla Mora, Pedro Pina, Ricardo Ramalho, and Rui Fernandes
Earth Syst. Sci. Data, 13, 3179–3201, https://doi.org/10.5194/essd-13-3179-2021, https://doi.org/10.5194/essd-13-3179-2021, 2021
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Fogo in Cabo Verde is one of the most active ocean island volcanoes on Earth, posing important hazards to local populations and at a regional level. The last eruption occurred from November 2014 to February 2015. A survey of the Chã das Caldeiras area was conducted using a fixed-wing unmanned aerial vehicle. A point cloud, digital surface model and orthomosaic with 10 and 25 cm resolutions are provided, together with the full aerial survey projects and datasets.
Clara Betancourt, Timo Stomberg, Ribana Roscher, Martin G. Schultz, and Scarlet Stadtler
Earth Syst. Sci. Data, 13, 3013–3033, https://doi.org/10.5194/essd-13-3013-2021, https://doi.org/10.5194/essd-13-3013-2021, 2021
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With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in the field of environmental science. The AQ-Bench dataset contains air quality data and metadata from more than 5500 air quality observation stations all over the world. The dataset offers a low-threshold entrance to machine learning on a real-world environmental dataset. AQ-Bench thus provides a blueprint for environmental benchmark datasets.
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021, https://doi.org/10.5194/essd-13-2701-2021, 2021
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Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Lilu Sun and Yunfei Fu
Earth Syst. Sci. Data, 13, 2293–2306, https://doi.org/10.5194/essd-13-2293-2021, https://doi.org/10.5194/essd-13-2293-2021, 2021
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Multi-source dataset use is hampered by use of different spatial and temporal resolutions. We merged Tropical Rainfall Measuring Mission precipitation radar and visible and infrared scanner measurements with ERA5 reanalysis. The statistical results indicate this process has no unacceptable influence on the original data. The merged dataset can help in studying characteristics of and changes in cloud and precipitation systems and provides an opportunity for data analysis and model simulations.
Yongyong Fu, Jinsong Deng, Hongquan Wang, Alexis Comber, Wu Yang, Wenqiang Wu, Shixue You, Yi Lin, and Ke Wang
Earth Syst. Sci. Data, 13, 1829–1842, https://doi.org/10.5194/essd-13-1829-2021, https://doi.org/10.5194/essd-13-1829-2021, 2021
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Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the first time. It was found to cover a total area of ~1100 km2, of which more than 85 % is marine plant culture areas, with 87 % found in four coastal provinces. The results confirm the applicability and effectiveness of deep learning when applied to GF-1 data at the national scale, identifying the detailed spatial distributions and supporting the sustainable management of coastal resources in China.
Sebastian Weinert, Kristian Bär, and Ingo Sass
Earth Syst. Sci. Data, 13, 1441–1459, https://doi.org/10.5194/essd-13-1441-2021, https://doi.org/10.5194/essd-13-1441-2021, 2021
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Physical rock properties are a key element for resource exploration, the interpretation of results from geophysical methods or the parameterization of physical or geological models. Despite the need for physical rock properties, data are still very scarce and often not available for the area of interest. The database presented aims to provide easy access to physical rock properties measured at 224 locations in Bavaria, Hessen, Rhineland-Palatinate and Thuringia (Germany).
Claire E. Simpson, Christopher D. Arp, Yongwei Sheng, Mark L. Carroll, Benjamin M. Jones, and Laurence C. Smith
Earth Syst. Sci. Data, 13, 1135–1150, https://doi.org/10.5194/essd-13-1135-2021, https://doi.org/10.5194/essd-13-1135-2021, 2021
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Sonar depth point measurements collected at 17 lakes on the Arctic Coastal Plain of Alaska are used to train and validate models to map lake bathymetry. These models predict depth from remotely sensed lake color and are able to explain 58.5–97.6 % of depth variability. To calculate water volumes, we integrate this modeled bathymetry with lake surface area. Knowledge of Alaskan lake bathymetries and volumes is crucial to better understanding water storage, energy balance, and ecological habitat.
Fei Feng and Kaicun Wang
Earth Syst. Sci. Data, 13, 907–922, https://doi.org/10.5194/essd-13-907-2021, https://doi.org/10.5194/essd-13-907-2021, 2021
Els Knaeps, Sindy Sterckx, Gert Strackx, Johan Mijnendonckx, Mehrdad Moshtaghi, Shungudzemwoyo P. Garaba, and Dieter Meire
Earth Syst. Sci. Data, 13, 713–730, https://doi.org/10.5194/essd-13-713-2021, https://doi.org/10.5194/essd-13-713-2021, 2021
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This paper describes a dataset consisting of 47 hyperspectral-reflectance measurements of plastic litter samples. The plastic litter samples include virgin and real samples. They were measured in dry conditions, and a selection of the samples were also measured in wet conditions and submerged in a water tank. The dataset can be used to better understand the effect of water absorption on the plastics and develop algorithms to detect and characterize marine plastics.
Susannah Rennie, Klaus Goergen, Christoph Wohner, Sander Apweiler, Johannes Peterseil, and John Watkins
Earth Syst. Sci. Data, 13, 631–644, https://doi.org/10.5194/essd-13-631-2021, https://doi.org/10.5194/essd-13-631-2021, 2021
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This paper describes a pan-European climate service data product intended for ecological researchers. Access to regional climate scenario data will save ecologists time, and, for many, it will allow them to work with data resources that they will not previously have used due to a lack of knowledge and skills to access them. Providing easy access to climate scenario data in this way enhances long-term ecological research, for example in general regional climate change or impact assessments.
Martin Strohmeier, Xavier Olive, Jannis Lübbe, Matthias Schäfer, and Vincent Lenders
Earth Syst. Sci. Data, 13, 357–366, https://doi.org/10.5194/essd-13-357-2021, https://doi.org/10.5194/essd-13-357-2021, 2021
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Flight data have been used widely for research by academic researchers and (supra)national institutions. Example domains range from epidemiology (e.g. examining the spread of COVID-19 via air travel) to economics (e.g. use as proxy for immediate forecasting of the state of a country's economy) and Earth sciences (climatology in particular). Until now, accurate flight data have been available only in small pieces from closed, proprietary sources. This work changes this with a crowdsourced effort.
Jinshi Jian, Rodrigo Vargas, Kristina Anderson-Teixeira, Emma Stell, Valentine Herrmann, Mercedes Horn, Nazar Kholod, Jason Manzon, Rebecca Marchesi, Darlin Paredes, and Ben Bond-Lamberty
Earth Syst. Sci. Data, 13, 255–267, https://doi.org/10.5194/essd-13-255-2021, https://doi.org/10.5194/essd-13-255-2021, 2021
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Field soil-to-atmosphere CO2 flux (soil respiration, Rs) observations were compiled into a global database (SRDB) a decade ago. Here, we restructured and updated the database to the fifth version, SRDB-V5, with data published through 2017 included. SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field Rs measurements, and it provides opportunities for the scientific community to better understand the spatial and temporal variability of Rs.
Robert A. Rohde and Zeke Hausfather
Earth Syst. Sci. Data, 12, 3469–3479, https://doi.org/10.5194/essd-12-3469-2020, https://doi.org/10.5194/essd-12-3469-2020, 2020
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A global land and ocean temperature record was created by combining the Berkeley Earth monthly land temperature field with a newly interpolated version of the HadSST3 ocean dataset. The resulting dataset covers the period from 1850 to present.
This paper describes the methods used to create that combination and compares the results to other estimates of global temperature and the associated recent climate change, giving similar results.
Igor Savin, Valery Mironov, Konstantin Muzalevskiy, Sergey Fomin, Andrey Karavayskiy, Zdenek Ruzicka, and Yuriy Lukin
Earth Syst. Sci. Data, 12, 3481–3487, https://doi.org/10.5194/essd-12-3481-2020, https://doi.org/10.5194/essd-12-3481-2020, 2020
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This article presents a dielectric database of organic Arctic soils. This database was created based on dielectric measurements of seven samples of organic soils collected in various parts of the Arctic tundra. The created database can serve not only as a source of experimental data for the development of new soil dielectric models for the Arctic tundra but also as a source of training data for artificial intelligence satellite algorithms of soil moisture retrievals based on neural networks.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jin Ma, Ji Zhou, Frank-Michael Göttsche, Shunlin Liang, Shaofei Wang, and Mingsong Li
Earth Syst. Sci. Data, 12, 3247–3268, https://doi.org/10.5194/essd-12-3247-2020, https://doi.org/10.5194/essd-12-3247-2020, 2020
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Land surface temperature is an important parameter in the research of climate change and many land surface processes. This article describes the development and testing of an algorithm for generating a consistent global long-term land surface temperature product from 20 years of NOAA AVHRR radiance data. The preliminary validation results indicate good accuracy of this new long-term product, which has been designed to simplify applications and support the scientific research community.
Clara Lázaro, Maria Joana Fernandes, Telmo Vieira, and Eliana Vieira
Earth Syst. Sci. Data, 12, 3205–3228, https://doi.org/10.5194/essd-12-3205-2020, https://doi.org/10.5194/essd-12-3205-2020, 2020
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In satellite altimetry (SA), the wet tropospheric correction (WTC) accounts for the path delay induced mainly by atmospheric water vapour. In coastal regions, the accuracy of the WTC determined by the on-board radiometer deteriorates. The GPD+ methodology, developed by the University of Porto in the remit of ESA-funded projects, computes improved WTCs for SA. Global enhanced products are generated for all past and operational altimetric missions, forming a relevant dataset for coastal altimetry.
Cited articles
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Short summary
Observations of cloud properties are necessary to understand and model clouds. Observations are frequently retrieved using remotely sensed measurements of infrared cloud emission. To support development and validation of the retrieval algorithms, this work produced a synthetic high-spectral-resolution infrared data set based on atmospheric conditions typical of the Arctic. Advantages of the data set include a priori knowledge of cloud properties and control over measurement uncertainties.
Observations of cloud properties are necessary to understand and model clouds. Observations are...
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