Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2605-2024
© 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-16-2605-2024
© 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
| 
04 Jun 2024
Data description paper |
| 04 Jun 2024
| 04 Jun 2024
The ABoVE L-band and P-band airborne synthetic aperture radar surveys
Charles E. Miller
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Peter C. Griffith
NASA Goddard Space Flight Center/SSAI, Greenbelt, MD, USA
Elizabeth Hoy
NASA Goddard Space Flight Center/GST, Inc., Greenbelt, MD, USA
Naiara S. Pinto
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Yunling Lou
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Scott Hensley
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Bruce D. Chapman
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Jennifer Baltzer
Department of Biology, Wilfrid Laurier University, Waterloo, Ontario, Canada
Kazem Bakian-Dogaheh
Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA
W. Robert Bolton
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775-7340, USA
Biological and Environmental Systems Science Directorate, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Laura Bourgeau-Chavez
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI 48105, USA
Richard H. Chen
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Byung-Hun Choe
Canada Centre for Remote Sensing, Ottawa, Ontario K1A 0E4, Canada
Leah K. Clayton
Department of Earth & Planetary Sciences, Yale University, New Haven, CT, USA
Thomas A. Douglas
U.S. Army Cold Regions Research and Engineering Laboratory, Fort Wainwright, AK 99709, USA
Nancy French
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI 48105, USA
Jean E. Holloway
Department of Geography, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
Gang Hong
Canada Centre for Remote Sensing, Ottawa, Ontario K1A 0E4, Canada
Lingcao Huang
National Snow and Ice Data Center (NSIDC), University of Colorado Boulder, Boulder, CO 80309-0449, USA
Go Iwahana
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775-7340, USA
Liza Jenkins
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI 48105, USA
John S. Kimball
NTSG, WA Franke College of Forestry & Conservation, The University of Montana, Missoula, MT, USA
Tatiana Loboda
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Michelle Mack
Center for Ecosystem Science and Society and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ 86011, USA
Philip Marsh
Department of Geography and Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, Ontario, Canada
Roger J. Michaelides
Department of Geophysics, Colorado School of Mines, Golden, CO, USA
Mahta Moghaddam
Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA
Andrew Parsekian
Department of Geology & Geophysics, University of Wyoming, 1000 E University Ave., Laramie, WY, USA
Kevin Schaefer
National Snow and Ice Data Center (NSIDC), University of Colorado Boulder, Boulder, CO 80309-0449, USA
Paul R. Siqueira
Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, MA 01003-9284, USA
Debjani Singh
Biological and Environmental Systems Science Directorate, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Alireza Tabatabaeenejad
Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA
Merritt Turetsky
Ecology and Evolutionary Biology Department, University of Colorado Boulder, Boulder, CO, USA
Ridha Touzi
Canada Centre for Remote Sensing, Ottawa, Ontario K1A 0E4, Canada
Elizabeth Wig
Department of Geophysics, Stanford University, Stanford, CA, USA
Cathy J. Wilson
Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA
Paul Wilson
Canada Centre for Remote Sensing, Ottawa, Ontario K1A 0E4, Canada
Stan D. Wullschleger
Biological and Environmental Systems Science Directorate, Oak Ridge National Laboratory, Oak Ridge, TN, USA
Yonghong Yi
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Joint Institute for Regional Earth System Science & Engineering, The University of California, Los Angeles, CA 90095-7228, USA
Howard A. Zebker
Department of Geophysics, Stanford University, Stanford, CA, USA
Canada Centre for Remote Sensing, Ottawa, Ontario K1A 0E4, Canada
Yuhuan Zhao
Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA
Scott J. Goetz
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA
Related authors
Raphaël Savelli, Dustin Carroll, Dimitris Menemenlis, Jonathan Lauderdale, Clément Bertin, Stephanie Dutkiewicz, Manfredi Manizza, Anthony Bloom, Karel Castro-Morales, Charles E. Miller, Marc Simard, Kevin W. Bowman, and Hong Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1707, https://doi.org/10.5194/egusphere-2025-1707, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Accounting for carbon and nutrients in rivers is essential for resolving carbon dioxide (CO2) exchanges between the ocean and the atmosphere. In this study, we add the effect of present-day rivers to a pioneering global-ocean biogeochemistry model. This study highlights the challenge for global ocean numerical models to cover the complexity of the flow of water and carbon across the Land-to-Ocean Aquatic Continuum.
Clement Bertin, Vincent Le Fouest, Dustin Carroll, Stephanie Dutkiewicz, Dimitris Menemenlis, Atsushi Matsuoka, Manfredi Manizza, and Charles E. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-973, https://doi.org/10.5194/egusphere-2025-973, 2025
Short summary
Short summary
We adjusted a model of the Mackenzie River region to account for the riverine export of organic matter that affects light in the water. We show that such export causes a delay in the phytoplankton growth by two weeks and raises the water surface temperature by 1.7 °C. We found that temperature increase turns this coastal region from a sink of carbon dioxide to an emitter. Our findings suggest that rising exports of organic matter can significantly affect the carbon cycle in Arctic coastal areas.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
Short summary
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Daniel H. Cusworth, Andrew K. Thorpe, Charles E. Miller, Alana K. Ayasse, Ralph Jiorle, Riley M. Duren, Ray Nassar, Jon-Paul Mastrogiacomo, and Robert R. Nelson
Atmos. Chem. Phys., 23, 14577–14591, https://doi.org/10.5194/acp-23-14577-2023, https://doi.org/10.5194/acp-23-14577-2023, 2023
Short summary
Short summary
Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we tasked two satellites to routinely observe CO2 emissions at 30 coal-fired power plants between 2021 and 2022. These results present the largest dataset of space-based CO2 emission estimates to date.
Jinsol Kim, John B. Miller, Charles E. Miller, Scott J. Lehman, Sylvia E. Michel, Vineet Yadav, Nick E. Rollins, and William M. Berelson
Atmos. Chem. Phys., 23, 14425–14436, https://doi.org/10.5194/acp-23-14425-2023, https://doi.org/10.5194/acp-23-14425-2023, 2023
Short summary
Short summary
In this study, we present the partitioning of CO2 signals from biogenic, petroleum and natural gas sources by combining CO, 13CO2 and 14CO2 measurements. Using measurements from flask air samples at three sites in the greater Los Angeles region, we find larger and positive contributions of biogenic signals in winter and smaller and negative contributions in summer. The largest contribution of natural gas combustion generally occurs in summer.
Vineet Yadav, Subhomoy Ghosh, and Charles E. Miller
Geosci. Model Dev., 16, 5219–5236, https://doi.org/10.5194/gmd-16-5219-2023, https://doi.org/10.5194/gmd-16-5219-2023, 2023
Short summary
Short summary
Measuring the performance of inversions in linear Bayesian problems is crucial in real-life applications. In this work, we provide analytical forms of the local and global sensitivities of the estimated fluxes with respect to various inputs. We provide methods to uniquely map the observational signal to spatiotemporal domains. Utilizing this, we also show techniques to assess correlations between the Jacobians that naturally translate to nonstationary covariance matrix components.
Broghan M. Erland, Cristen Adams, Andrea Darlington, Mackenzie L. Smith, Andrew K. Thorpe, Gregory R. Wentworth, Steve Conley, John Liggio, Shao-Meng Li, Charles E. Miller, and John A. Gamon
Atmos. Meas. Tech., 15, 5841–5859, https://doi.org/10.5194/amt-15-5841-2022, https://doi.org/10.5194/amt-15-5841-2022, 2022
Short summary
Short summary
Accurately estimating greenhouse gas (GHG) emissions is essential to reaching net-zero goals to combat the climate crisis. Airborne box-flights are ideal for assessing regional GHG emissions, as they can attain small error. We compare two box-flight algorithms and found they produce similar results, but daily variability must be considered when deriving emissions inventories. Increasing the consistency and agreement between airborne methods moves us closer to achieving more accurate estimates.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
Short summary
Short summary
Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Elizabeth B. Wiggins, Arlyn Andrews, Colm Sweeney, John B. Miller, Charles E. Miller, Sander Veraverbeke, Roisin Commane, Steven Wofsy, John M. Henderson, and James T. Randerson
Atmos. Chem. Phys., 21, 8557–8574, https://doi.org/10.5194/acp-21-8557-2021, https://doi.org/10.5194/acp-21-8557-2021, 2021
Short summary
Short summary
We analyzed high-resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires. Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires.
Jakob Borchardt, Konstantin Gerilowski, Sven Krautwurst, Heinrich Bovensmann, Andrew K. Thorpe, David R. Thompson, Christian Frankenberg, Charles E. Miller, Riley M. Duren, and John Philip Burrows
Atmos. Meas. Tech., 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, https://doi.org/10.5194/amt-14-1267-2021, 2021
Short summary
Short summary
The AVIRIS-NG hyperspectral imager has been used successfully to identify and quantify anthropogenic methane sources utilizing different retrieval and inversion methods. Here, we examine the adaption and application of the WFM-DOAS algorithm to AVIRIS-NG measurements to retrieve local methane column enhancements, compare the results with other retrievals, and quantify the uncertainties resulting from the retrieval method. Additionally, we estimate emissions from five detected methane plumes.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
Short summary
Short summary
We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Jinyang Du, K. Arthur Endsley, Kazem Bakian Dogaheh, John Kimball, Mahta Moghaddam, Tom Douglas, Asem Melebari, Sepehr Eskandari, Jinhyuk Kim, Jane Whitcomb, Yuhuan Zhao, and Sophia Henze
EGUsphere, https://doi.org/10.5194/egusphere-2025-3236, https://doi.org/10.5194/egusphere-2025-3236, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Active layer thickness (ALT) is a sensitive indicator of the thawing Alaskan frozen soil, which may lead to increased greenhouse gas emissions, vegetation changes, and infrastructure damage. This study represents a multi-scale assessment of ALT spatial variations using observations including intensive field sampling, and drone, airborne and satellite remote sensing. Our study allows for improved interpretation of remote sensing and process-based ALT simulations for the changing Arctic.
Caleb G. Pan, Kristofer Lasko, Sean P. Griffin, John S. Kimball, Jinyang Du, Tate G. Meehan, and Peter B. Kirchner
The Cryosphere, 19, 2797–2819, https://doi.org/10.5194/tc-19-2797-2025, https://doi.org/10.5194/tc-19-2797-2025, 2025
Short summary
Short summary
This study examines 35 years of snow cover changes in Alaska’s Yukon River Basin using machine learning to track snowmelt timing and disappearance. Results show snow is melting earlier and disappearing faster due to rising temperatures, highlighting the effects of climate change on water resources, ecosystems, and communities. The findings improve understanding of snow dynamics and provide critical insights for addressing climate-driven challenges in the region.
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025, https://doi.org/10.5194/essd-17-2887-2025, 2025
Short summary
Short summary
Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a dataset of permafrost thaw depth measurements from burned and unburned sites contributed by researchers from across the northern high-latitude region. We estimated maximum thaw depth for each measurement, which addresses a key challenge: the ability to assess impacts of wildfire on maximum thaw depth when measurement timing varies.
Raphaël Savelli, Dustin Carroll, Dimitris Menemenlis, Jonathan Lauderdale, Clément Bertin, Stephanie Dutkiewicz, Manfredi Manizza, Anthony Bloom, Karel Castro-Morales, Charles E. Miller, Marc Simard, Kevin W. Bowman, and Hong Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1707, https://doi.org/10.5194/egusphere-2025-1707, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Accounting for carbon and nutrients in rivers is essential for resolving carbon dioxide (CO2) exchanges between the ocean and the atmosphere. In this study, we add the effect of present-day rivers to a pioneering global-ocean biogeochemistry model. This study highlights the challenge for global ocean numerical models to cover the complexity of the flow of water and carbon across the Land-to-Ocean Aquatic Continuum.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
EGUsphere, https://doi.org/10.5194/egusphere-2025-1498, https://doi.org/10.5194/egusphere-2025-1498, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
The impact of uncertainties in the simulation of snow density and SSA by the snow model Crocus (embedded within the Soil, Vegetation and Snow version 2 land surface model) on the simulation of snow backscatter (13.5 GHz) using the Snow Microwave Radiative Transfer model were quantified. The simulation of SSA was found to be a key model uncertainty. Underestimated SSA values lead to high errors in the simulation of snow backscatter, reduced by implementing a minimum SSA value (8.7 m2 kg-1).
Clement Bertin, Vincent Le Fouest, Dustin Carroll, Stephanie Dutkiewicz, Dimitris Menemenlis, Atsushi Matsuoka, Manfredi Manizza, and Charles E. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2025-973, https://doi.org/10.5194/egusphere-2025-973, 2025
Short summary
Short summary
We adjusted a model of the Mackenzie River region to account for the riverine export of organic matter that affects light in the water. We show that such export causes a delay in the phytoplankton growth by two weeks and raises the water surface temperature by 1.7 °C. We found that temperature increase turns this coastal region from a sink of carbon dioxide to an emitter. Our findings suggest that rising exports of organic matter can significantly affect the carbon cycle in Arctic coastal areas.
David Brodylo, Lauren V. Bosche, Ryan R. Busby, Elias J. Deeb, Thomas A. Douglas, and Juha Lemmetyinen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3936, https://doi.org/10.5194/egusphere-2024-3936, 2025
Short summary
Short summary
We combined field-based snow depth and snow water equivalent (SWE) measurements, remote sensing data, and machine learning to estimate snow depth and SWE over a 10 km2 local scale area in Sodankylä, Finland. Associations were found for snow depth and SWE with carbon- and mineral-based forest surface soils, alongside dry and wet peatbogs. This approach to upscale field-based snow depth and SWE measurements to a local scale can be used in regions that regularly experience snowfall.
Thomas Douglas, Mark Jorgenson, Taylor Sullivan, and Caiyun Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3997, https://doi.org/10.5194/egusphere-2024-3997, 2025
Short summary
Short summary
Permafrost thaw across earth’s high latitudes is leading to dramatic changes in vegetation and hydrology. We undertook a two-decade long study on the Tanana Flats near Fairbanks, Alaska to measure permafrost thaw and associated ground surface subsidence via field-based and remote-sensing techniques. The study identified strengths and limitations of the three methods we used to quantify permafrost thaw degradation.
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024, https://doi.org/10.5194/tc-18-5685-2024, 2024
Short summary
Short summary
Parameterisations of Arctic snow processes were implemented into the multi-physics ensemble version of the snow model Crocus (embedded within the Soil, Vegetation, and Snow version 2 land surface model) and evaluated at an Arctic tundra site. Optimal combinations of parameterisations that improved the simulation of density and specific surface area featured modifications that raise wind speeds to increase compaction in surface layers, prevent snowdrift, and increase viscosity in basal layers.
Noriaki Ohara, Andrew D. Parsekian, Benjamin M. Jones, Rodrigo C. Rangel, Kenneth M. Hinkel, and Rui A. P. Perdigão
The Cryosphere, 18, 5139–5152, https://doi.org/10.5194/tc-18-5139-2024, https://doi.org/10.5194/tc-18-5139-2024, 2024
Short summary
Short summary
Snow distribution characterization is essential for accurate snow water estimation for water resource prediction from existing in situ observations and remote-sensing data at a finite spatial resolution. Four different observed snow distribution datasets were analyzed for Gaussianity. We found that non-Gaussianity of snow distribution is a signature of the wind redistribution effect. Generally, seasonal snowpack can be approximated well by a Gaussian distribution for a fully snow-covered area.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
The Cryosphere, 18, 3765–3785, https://doi.org/10.5194/tc-18-3765-2024, https://doi.org/10.5194/tc-18-3765-2024, 2024
Short summary
Short summary
Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA, to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
Short summary
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Gaïa Michel, Julien Crétat, Olivier Mathieu, Mathieu Thévenot, Andrey Dara, Robert Granat, Zhendong Wu, Clément Bonnefoy-Claudet, Julianne Capelle, Jean Cacot, and John S. Kimball
EGUsphere, https://doi.org/10.5194/egusphere-2024-1758, https://doi.org/10.5194/egusphere-2024-1758, 2024
Short summary
Short summary
This study questions the usefulness of state-ot-the-art models to characterize the temporal variability of atmosphere-ecosystem CO2 exchanges in western European forests. Their mean annual cycle and annual budget are better captured by statistical than physical models, while their interannual variability and long-term trend are better captured by models forced by climate variability. Accounting for both forest stands and climate variability is thus key for properly assessing CO2 fluxes.
Yiming Xu, Qianlai Zhuang, Bailu Zhao, Michael Billmire, Christopher Cook, Jeremy Graham, Nancy French, and Ronald Prinn
EGUsphere, https://doi.org/10.5194/egusphere-2024-1324, https://doi.org/10.5194/egusphere-2024-1324, 2024
Preprint archived
Short summary
Short summary
We use a process-based model to simulate the fire impacts on soil thermal and hydrological dynamics and carbon budget of forest ecosystems in Northern Eurasia based on satellite-derived burn severity data. We find that fire severity generally increases in this region during the study period. Simulations indicate that fires increase soil temperature and water runoff. Fires lead the forest ecosystems to lose 2.3 Pg C, shifting the forests from a carbon sink to a source in this period.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
Short summary
Short summary
We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Kevin R. Barry, Thomas C. J. Hill, Marina Nieto-Caballero, Thomas A. Douglas, Sonia M. Kreidenweis, Paul J. DeMott, and Jessie M. Creamean
Atmos. Chem. Phys., 23, 15783–15793, https://doi.org/10.5194/acp-23-15783-2023, https://doi.org/10.5194/acp-23-15783-2023, 2023
Short summary
Short summary
Ice-nucleating particles (INPs) are important for the climate due to their influence on cloud properties. To understand potential land-based sources of them in the Arctic, we carried out a survey near the northernmost point of Alaska, a landscape connected to the permafrost (thermokarst). Permafrost contained high concentrations of INPs, with the largest values near the coast. The thermokarst lakes were found to emit INPs, and the water contained elevated concentrations.
Daniel H. Cusworth, Andrew K. Thorpe, Charles E. Miller, Alana K. Ayasse, Ralph Jiorle, Riley M. Duren, Ray Nassar, Jon-Paul Mastrogiacomo, and Robert R. Nelson
Atmos. Chem. Phys., 23, 14577–14591, https://doi.org/10.5194/acp-23-14577-2023, https://doi.org/10.5194/acp-23-14577-2023, 2023
Short summary
Short summary
Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we tasked two satellites to routinely observe CO2 emissions at 30 coal-fired power plants between 2021 and 2022. These results present the largest dataset of space-based CO2 emission estimates to date.
Jinsol Kim, John B. Miller, Charles E. Miller, Scott J. Lehman, Sylvia E. Michel, Vineet Yadav, Nick E. Rollins, and William M. Berelson
Atmos. Chem. Phys., 23, 14425–14436, https://doi.org/10.5194/acp-23-14425-2023, https://doi.org/10.5194/acp-23-14425-2023, 2023
Short summary
Short summary
In this study, we present the partitioning of CO2 signals from biogenic, petroleum and natural gas sources by combining CO, 13CO2 and 14CO2 measurements. Using measurements from flask air samples at three sites in the greater Los Angeles region, we find larger and positive contributions of biogenic signals in winter and smaller and negative contributions in summer. The largest contribution of natural gas combustion generally occurs in summer.
Nathan Alec Conroy, Jeffrey M. Heikoop, Emma Lathrop, Dea Musa, Brent D. Newman, Chonggang Xu, Rachael E. McCaully, Carli A. Arendt, Verity G. Salmon, Amy Breen, Vladimir Romanovsky, Katrina E. Bennett, Cathy J. Wilson, and Stan D. Wullschleger
The Cryosphere, 17, 3987–4006, https://doi.org/10.5194/tc-17-3987-2023, https://doi.org/10.5194/tc-17-3987-2023, 2023
Short summary
Short summary
This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
Vineet Yadav, Subhomoy Ghosh, and Charles E. Miller
Geosci. Model Dev., 16, 5219–5236, https://doi.org/10.5194/gmd-16-5219-2023, https://doi.org/10.5194/gmd-16-5219-2023, 2023
Short summary
Short summary
Measuring the performance of inversions in linear Bayesian problems is crucial in real-life applications. In this work, we provide analytical forms of the local and global sensitivities of the estimated fluxes with respect to various inputs. We provide methods to uniquely map the observational signal to spatiotemporal domains. Utilizing this, we also show techniques to assess correlations between the Jacobians that naturally translate to nonstationary covariance matrix components.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
Short summary
Short summary
This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
Preprint archived
Short summary
Short summary
Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Stefano Potter, Sol Cooperdock, Sander Veraverbeke, Xanthe Walker, Michelle C. Mack, Scott J. Goetz, Jennifer Baltzer, Laura Bourgeau-Chavez, Arden Burrell, Catherine Dieleman, Nancy French, Stijn Hantson, Elizabeth E. Hoy, Liza Jenkins, Jill F. Johnstone, Evan S. Kane, Susan M. Natali, James T. Randerson, Merritt R. Turetsky, Ellen Whitman, Elizabeth Wiggins, and Brendan M. Rogers
Biogeosciences, 20, 2785–2804, https://doi.org/10.5194/bg-20-2785-2023, https://doi.org/10.5194/bg-20-2785-2023, 2023
Short summary
Short summary
Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m−2. We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.
Evan J. Wilcox, Brent B. Wolfe, and Philip Marsh
Hydrol. Earth Syst. Sci., 27, 2173–2188, https://doi.org/10.5194/hess-27-2173-2023, https://doi.org/10.5194/hess-27-2173-2023, 2023
Short summary
Short summary
The Arctic is warming quickly and influencing lake water balances. We used water isotope concentrations taken from samples of 25 lakes in the Canadian Arctic and estimated the average ratio of evaporation to inflow (E / I) for each lake. The ratio of watershed area (the area that flows into the lake) to lake area (WA / LA) strongly predicted E / I, as lakes with relatively smaller watersheds received less inflow. The WA / LA could be used to predict the vulnerability of Arctic lakes to future change.
Luke D. Schiferl, Jennifer D. Watts, Erik J. L. Larson, Kyle A. Arndt, Sébastien C. Biraud, Eugénie S. Euskirchen, Jordan P. Goodrich, John M. Henderson, Aram Kalhori, Kathryn McKain, Marikate E. Mountain, J. William Munger, Walter C. Oechel, Colm Sweeney, Yonghong Yi, Donatella Zona, and Róisín Commane
Biogeosciences, 19, 5953–5972, https://doi.org/10.5194/bg-19-5953-2022, https://doi.org/10.5194/bg-19-5953-2022, 2022
Short summary
Short summary
As the Arctic rapidly warms, vast stores of thawing permafrost could release carbon dioxide (CO2) into the atmosphere. We combined observations of atmospheric CO2 concentrations from aircraft and a tower with observed CO2 fluxes from tundra ecosystems and found that the Alaskan North Slope in not a consistent source nor sink of CO2. Our study shows the importance of using both site-level and atmospheric measurements to constrain regional net CO2 fluxes and improve biogenic processes in models.
Evan J. Wilcox, Brent B. Wolfe, and Philip Marsh
Hydrol. Earth Syst. Sci., 26, 6185–6205, https://doi.org/10.5194/hess-26-6185-2022, https://doi.org/10.5194/hess-26-6185-2022, 2022
Short summary
Short summary
We estimated how much of the water flowing into lakes during snowmelt replaced the pre-snowmelt lake water. Our data show that, as lake depth increases, the amount of water mixed into lakes decreased, because vertical mixing is reduced as lake depth increases. Our data also show that the water mixing into lakes is not solely snow-sourced but is a mixture of snowmelt and soil water. These results are relevant for lake biogeochemistry given the unique properties of snowmelt runoff.
Broghan M. Erland, Cristen Adams, Andrea Darlington, Mackenzie L. Smith, Andrew K. Thorpe, Gregory R. Wentworth, Steve Conley, John Liggio, Shao-Meng Li, Charles E. Miller, and John A. Gamon
Atmos. Meas. Tech., 15, 5841–5859, https://doi.org/10.5194/amt-15-5841-2022, https://doi.org/10.5194/amt-15-5841-2022, 2022
Short summary
Short summary
Accurately estimating greenhouse gas (GHG) emissions is essential to reaching net-zero goals to combat the climate crisis. Airborne box-flights are ideal for assessing regional GHG emissions, as they can attain small error. We compare two box-flight algorithms and found they produce similar results, but daily variability must be considered when deriving emissions inventories. Increasing the consistency and agreement between airborne methods moves us closer to achieving more accurate estimates.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
Short summary
Short summary
Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Zhuoxuan Xia, Lingcao Huang, Chengyan Fan, Shichao Jia, Zhanjun Lin, Lin Liu, Jing Luo, Fujun Niu, and Tingjun Zhang
Earth Syst. Sci. Data, 14, 3875–3887, https://doi.org/10.5194/essd-14-3875-2022, https://doi.org/10.5194/essd-14-3875-2022, 2022
Short summary
Short summary
Retrogressive thaw slumps are slope failures resulting from abrupt permafrost thaw, and are widely distributed along the Qinghai–Tibet Engineering Corridor. The potential damage to infrastructure and carbon emission of thaw slumps motivated us to obtain an inventory of thaw slumps. We used a semi-automatic method to map 875 thaw slumps, filling the knowledge gap of thaw slump locations and providing key benchmarks for analysing the distribution features and quantifying spatio-temporal changes.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
Short summary
Short summary
In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Rachael E. McCaully, Carli A. Arendt, Brent D. Newman, Verity G. Salmon, Jeffrey M. Heikoop, Cathy J. Wilson, Sanna Sevanto, Nathan A. Wales, George B. Perkins, Oana C. Marina, and Stan D. Wullschleger
The Cryosphere, 16, 1889–1901, https://doi.org/10.5194/tc-16-1889-2022, https://doi.org/10.5194/tc-16-1889-2022, 2022
Short summary
Short summary
Degrading permafrost and shrub expansion are critically important to tundra biogeochemistry. We observed significant variability in soil pore water NO3-N in an alder-dominated permafrost hillslope in Alaska. Proximity to alder shrubs and the presence or absence of topographic gradients and precipitation events strongly influence NO3-N availability and mobility. The highly dynamic nature of labile N on small spatiotemporal scales has implications for nutrient responses to a warming Arctic.
Noriaki Ohara, Benjamin M. Jones, Andrew D. Parsekian, Kenneth M. Hinkel, Katsu Yamatani, Mikhail Kanevskiy, Rodrigo C. Rangel, Amy L. Breen, and Helena Bergstedt
The Cryosphere, 16, 1247–1264, https://doi.org/10.5194/tc-16-1247-2022, https://doi.org/10.5194/tc-16-1247-2022, 2022
Short summary
Short summary
New variational principle suggests that a semi-ellipsoid talik shape (3D Stefan equation) is optimum for incoming energy. However, the lake bathymetry tends to be less ellipsoidal due to the ice-rich layers near the surface. Wind wave erosion is likely responsible for the elongation of lakes, while thaw subsidence slows the wave effect and stabilizes the thermokarst lakes. The derived 3D Stefan equation was compared to the field-observed talik thickness data using geophysical methods.
Elchin E. Jafarov, Daniil Svyatsky, Brent Newman, Dylan Harp, David Moulton, and Cathy Wilson
The Cryosphere, 16, 851–862, https://doi.org/10.5194/tc-16-851-2022, https://doi.org/10.5194/tc-16-851-2022, 2022
Short summary
Short summary
Recent research indicates the importance of lateral transport of dissolved carbon in the polygonal tundra, suggesting that the freeze-up period could further promote lateral carbon transport. We conducted subsurface tracer simulations on high-, flat-, and low-centered polygons to test the importance of the freeze–thaw cycle and freeze-up time for tracer mobility. Our findings illustrate the impact of hydraulic and thermal gradients on tracer mobility, as well as of the freeze-up time.
Karis J. McFarlane, Heather M. Throckmorton, Jeffrey M. Heikoop, Brent D. Newman, Alexandra L. Hedgpeth, Marisa N. Repasch, Thomas P. Guilderson, and Cathy J. Wilson
Biogeosciences, 19, 1211–1223, https://doi.org/10.5194/bg-19-1211-2022, https://doi.org/10.5194/bg-19-1211-2022, 2022
Short summary
Short summary
Planetary warming is increasing seasonal thaw of permafrost, making this extensive old carbon stock vulnerable. In northern Alaska, we found more and older dissolved organic carbon in small drainages later in summer as more permafrost was exposed by deepening thaw. Younger and older carbon did not differ in chemical indicators related to biological lability suggesting this carbon can cycle through aquatic systems and contribute to greenhouse gas emissions as warming increases permafrost thaw.
Julien Meloche, Alexandre Langlois, Nick Rutter, Alain Royer, Josh King, Branden Walker, Philip Marsh, and Evan J. Wilcox
The Cryosphere, 16, 87–101, https://doi.org/10.5194/tc-16-87-2022, https://doi.org/10.5194/tc-16-87-2022, 2022
Short summary
Short summary
To estimate snow water equivalent from space, model predictions of the satellite measurement (brightness temperature in our case) have to be used. These models allow us to estimate snow properties from the brightness temperature by inverting the model. To improve SWE estimate, we proposed incorporating the variability of snow in these model as it has not been taken into account yet. A new parameter (coefficient of variation) is proposed because it improved simulation of brightness temperature.
Anton Jitnikovitch, Philip Marsh, Branden Walker, and Darin Desilets
The Cryosphere, 15, 5227–5239, https://doi.org/10.5194/tc-15-5227-2021, https://doi.org/10.5194/tc-15-5227-2021, 2021
Short summary
Short summary
Conventional methods used to measure snow have many limitations which hinder our ability to document annual cycles, test predictive models, or analyze the impact of climate change. A modern snow measurement method using in situ cosmic ray neutron sensors demonstrates the capability of continuously measuring spatially variable snowpacks with considerable accuracy. These sensors can provide important data for testing models, validating remote sensing, and water resource management applications.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
Short summary
Short summary
The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
McKenzie A. Kuhn, Ruth K. Varner, David Bastviken, Patrick Crill, Sally MacIntyre, Merritt Turetsky, Katey Walter Anthony, Anthony D. McGuire, and David Olefeldt
Earth Syst. Sci. Data, 13, 5151–5189, https://doi.org/10.5194/essd-13-5151-2021, https://doi.org/10.5194/essd-13-5151-2021, 2021
Short summary
Short summary
Methane (CH4) emissions from the boreal–Arctic region are globally significant, but the current magnitude of annual emissions is not well defined. Here we present a dataset of surface CH4 fluxes from northern wetlands, lakes, and uplands that was built alongside a compatible land cover dataset, sharing the same classifications. We show CH4 fluxes can be split by broad land cover characteristics. The dataset is useful for comparison against new field data and model parameterization or validation.
Dylan R. Harp, Vitaly Zlotnik, Charles J. Abolt, Bob Busey, Sofia T. Avendaño, Brent D. Newman, Adam L. Atchley, Elchin Jafarov, Cathy J. Wilson, and Katrina E. Bennett
The Cryosphere, 15, 4005–4029, https://doi.org/10.5194/tc-15-4005-2021, https://doi.org/10.5194/tc-15-4005-2021, 2021
Short summary
Short summary
Polygon-shaped landforms present in relatively flat Arctic tundra result in complex landscape-scale water drainage. The drainage pathways and the time to transition from inundated conditions to drained have important implications for heat and carbon transport. Using fundamental hydrologic principles, we investigate the drainage pathways and timing of individual polygons, providing insights into the effects of polygon geometry and preferential flow direction on drainage pathways and timing.
Thomas A. Douglas, Christopher A. Hiemstra, John E. Anderson, Robyn A. Barbato, Kevin L. Bjella, Elias J. Deeb, Arthur B. Gelvin, Patricia E. Nelsen, Stephen D. Newman, Stephanie P. Saari, and Anna M. Wagner
The Cryosphere, 15, 3555–3575, https://doi.org/10.5194/tc-15-3555-2021, https://doi.org/10.5194/tc-15-3555-2021, 2021
Short summary
Short summary
Permafrost is actively degrading across high latitudes due to climate warming. We combined thousands of end-of-summer active layer measurements, permafrost temperatures, geophysical surveys, deep borehole drilling, and repeat airborne lidar to quantify permafrost warming and thawing at sites across central Alaska. We calculate the mass of permafrost soil carbon potentially exposed to thaw over the past 7 years (0.44 Pg) is similar to the yearly carbon dioxide emissions of Australia.
Elizabeth B. Wiggins, Arlyn Andrews, Colm Sweeney, John B. Miller, Charles E. Miller, Sander Veraverbeke, Roisin Commane, Steven Wofsy, John M. Henderson, and James T. Randerson
Atmos. Chem. Phys., 21, 8557–8574, https://doi.org/10.5194/acp-21-8557-2021, https://doi.org/10.5194/acp-21-8557-2021, 2021
Short summary
Short summary
We analyzed high-resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires. Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires.
William R. Wieder, Derek Pierson, Stevan Earl, Kate Lajtha, Sara G. Baer, Ford Ballantyne, Asmeret Asefaw Berhe, Sharon A. Billings, Laurel M. Brigham, Stephany S. Chacon, Jennifer Fraterrigo, Serita D. Frey, Katerina Georgiou, Marie-Anne de Graaff, A. Stuart Grandy, Melannie D. Hartman, Sarah E. Hobbie, Chris Johnson, Jason Kaye, Emily Kyker-Snowman, Marcy E. Litvak, Michelle C. Mack, Avni Malhotra, Jessica A. M. Moore, Knute Nadelhoffer, Craig Rasmussen, Whendee L. Silver, Benjamin N. Sulman, Xanthe Walker, and Samantha Weintraub
Earth Syst. Sci. Data, 13, 1843–1854, https://doi.org/10.5194/essd-13-1843-2021, https://doi.org/10.5194/essd-13-1843-2021, 2021
Short summary
Short summary
Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Here we present the SOils DAta Harmonization database (SoDaH), a flexible database designed to harmonize diverse SOM datasets from multiple research networks.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Jakob Borchardt, Konstantin Gerilowski, Sven Krautwurst, Heinrich Bovensmann, Andrew K. Thorpe, David R. Thompson, Christian Frankenberg, Charles E. Miller, Riley M. Duren, and John Philip Burrows
Atmos. Meas. Tech., 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, https://doi.org/10.5194/amt-14-1267-2021, 2021
Short summary
Short summary
The AVIRIS-NG hyperspectral imager has been used successfully to identify and quantify anthropogenic methane sources utilizing different retrieval and inversion methods. Here, we examine the adaption and application of the WFM-DOAS algorithm to AVIRIS-NG measurements to retrieve local methane column enhancements, compare the results with other retrievals, and quantify the uncertainties resulting from the retrieval method. Additionally, we estimate emissions from five detected methane plumes.
Kazuyuki Saito, Hirokazu Machiya, Go Iwahana, Tokuta Yokohata, and Hiroshi Ohno
Geosci. Model Dev., 14, 521–542, https://doi.org/10.5194/gmd-14-521-2021, https://doi.org/10.5194/gmd-14-521-2021, 2021
Short summary
Short summary
Soil organic carbon (SOC) and ground ice (ICE) are essential but under-documented information to assess the circum-Arctic permafrost degradation impacts. A simple numerical model of essential SOC and ICE dynamics, developed and integrated north of 50° N for 125,000 years since the last interglacial, reconstructed the history and 1° distribution of SOC and ICE consistent with current knowledge, together with successful demonstration of climatic and topographical controls on SOC evolution.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller
Biogeosciences, 17, 5861–5882, https://doi.org/10.5194/bg-17-5861-2020, https://doi.org/10.5194/bg-17-5861-2020, 2020
Short summary
Short summary
We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO2 seasonal cycles.
Seyedmohammad Mousavi, Andreas Colliander, Julie Z. Miller, and John S. Kimball
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-297, https://doi.org/10.5194/tc-2020-297, 2020
Manuscript not accepted for further review
A. D. Collins, C. G. Andresen, L. M. Charsley-Groffman, T. Cochran, J. Dann, E. Lathrop, G. J. Riemersma, E. M. Swanson, A. Tapadinhas, and C. J. Wilson
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-M-2-2020, 1–8, https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-1-2020, https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-1-2020, 2020
Eleanor J. Burke, Yu Zhang, and Gerhard Krinner
The Cryosphere, 14, 3155–3174, https://doi.org/10.5194/tc-14-3155-2020, https://doi.org/10.5194/tc-14-3155-2020, 2020
Short summary
Short summary
Permafrost will degrade under future climate change. This will have implications locally for the northern high-latitude regions and may well also amplify global climate change. There have been some recent improvements in the ability of earth system models to simulate the permafrost physical state, but further model developments are required. Models project the thawed volume of soil in the top 2 m of permafrost will increase by 10 %–40 % °C−1 of global mean surface air temperature increase.
Inge Grünberg, Evan J. Wilcox, Simon Zwieback, Philip Marsh, and Julia Boike
Biogeosciences, 17, 4261–4279, https://doi.org/10.5194/bg-17-4261-2020, https://doi.org/10.5194/bg-17-4261-2020, 2020
Short summary
Short summary
Based on topsoil temperature data for different vegetation types at a low Arctic tundra site, we found large small-scale variability. Winter temperatures were strongly influenced by vegetation through its effects on snow. Summer temperatures were similar below most vegetation types and not consistently related to late summer permafrost thaw depth. Given that vegetation type defines the relationship between winter and summer soil temperature and thaw depth, it controls permafrost vulnerability.
Cited articles
Allen, B. D., Braun, S. A., Crawford, J. H., Jensen, E. J., Miller, C. E., Moghaddam, M., and Maring, H.: Proposed investigations from NASA's Earth Venture-1 (EV-1) airborne science selections, in: 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, HI, USA, 2010, 2575–2578, https://doi.org/10.1109/IGARSS.2010.5651920, 2010.
Altenau, E. H., Pavelsky, T. M., Moller, D., Lion, C., Pitcher, L. H., Allen, G. H., Bates, P. D., Calmant, S., Durand, M., and Smith, L. C.: AirSWOT measurements of river water surface elevation and slope: Tanana River, AK, Geophys. Res. Lett., 44, 181–189, https://doi.org/10.1002/2016GL071577, 2017.
Bakian-Dogaheh, K., Chen, R. H., Moghaddam, M., Yi, Y., and Tabatabaeenejad, A.: ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1759, 2020a.
Bakian-Dogaheh, K., Chen, R. H., Moghaddam, M., and Tabatabaeenejad, A.: Electromagnetic scattering behavior of a new organic soil dielectric model for long-wavelength radar retrieval of permafrost active layer soil properties, 2020 IEEE International Geoscience and Remote Sensing Symposium, Virtual Symposium, 26 September–2 October 2020b.
Blair, J. B. and Hofton, M. A.: Modeling laser altimeter return waveforms over complex vegetation using high‐resolution elevation data, Geophy. Res. Lett., 26, 2509–2512, https://doi.org/10.1029/1999GL010484, 1999.
Blair, J. B. and Hofton, M.: ABoVE LVIS L1B Geolocated Return Energy Waveforms, Version 1,NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado USA [data set], https://doi.org/10.5067/UMRAWS57QAFU, 2018a.
Blair, J. B. and Hofton, M.: ABoVE LVIS L2 Geolocated Surface Elevation Product, Version 1, National Snow and Ice Data Center (NSIDC), the LVIS DAAC [data set], https://doi.org/10.5067/IA5WAX7K3YGY, 2018b.
Blair, J. B., Rabine, D. L., and Hofton, M. A.: The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography, ISPRS J. Photogramm., 54, 115–122, https://doi.org/10.1016/S0924-2716(99)00002-7, 1999.
Bourgeau-Chavez, L. L., Battaglia, M., Kane, E. S., Cohen, L. M., and Tanzer, D.: ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1703, 2019a.
Bourgeau-Chavez, L. L., Graham, J. A., Grelick, S. E., French, N. H. F., Battaglia, M., Hansen, D., and Tanzer, D.: ABoVE: Ecosystem Map, Great Slave Lake Area, Northwest Territories, Canada, 1997–2011, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1695, 2019b.
Chapin, E., Chau, A., Chen, J., Heavey, B., Hensley, S., Lou, Y., Machuzak, R., and Moghaddam, M.: AirMOSS: An Airborne P-band SAR to measure root-zone soil moisture, in: 2012 IEEE Radar Conference, Atlanta, GA, USA, 7–11 May 2012, 0693–0698, https://doi.org/10.1109/RADAR.2012.6212227, 2012.
Chapin, E., Flores, S., Harcke, L., Hawkins, B. P., Hensley, S., Michel, T. R., Muellerschoen, R. J., Shimada, J. G., Tung, W. W., and Veeramachaneni, C.: AirMOSS: L1 S-0 Polarimetric Data from AirMOSS P-band SAR, BERMS, Canada, 2012–2015, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1406, 2018.
Chen, R. H., Bakian-Dogaheh, K., Tabatabaeenejad, A., and Moghaddam, M.: Modeling and Retrieving Soil Moisture and Organic Matter Profiles in the Active Layer of Permafrost Soils From P-Band Radar Observations, IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, 10095–10098, https://doi.org/10.1109/IGARSS.2019.8899802, 2019a.
Chen, R. H., Tabatabaeenejad, A., and Moghaddam, M.: ABoVE: Active Layer and Soil Moisture Properties from AirMOSS P-band SAR in Alaska, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1657, 2019b.
Chen, R. H., Michaelides, R. J., Zhao, Y., Huang, L., Wig, E., Sullivan, T. D., Parsekian, A. D., Zebker, H. A., Moghaddam, M., and Schaefer, K. M.: Permafrost Dynamics Observatory: Retrieval of Active Layer Thickness and Soil Moisture from Airborne Insar and Polsar Data, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 2021, https://doi.org/10.1109/IGARSS47720.2021.9554288, 1444–1447, 2021.
Chen, R. H., Michaelides, R. J., Zhao, Y., Huang, L., Wig, E., Sullivan, T. D., Parsekian, A. D., Zebker, H. A., Moghaddam, M., and Schaefer, K. M.: Permafrost Dynamics Observatory (PDO): 2. Joint Retrieval of Permafrost Active Layer Thickness and Soil Moisture From L‐Band InSAR and P‐Band PolSAR, Earth and Space Science, 10, e2022EA002453, https://doi.org/10.1029/2022EA002453, 2023.
Clayton, L. K., Schaefer, K., Battaglia, M. J., Bourgeau-Chavez, L., Chen, J., Chen, R. H., Chen, A., Bakian-Dogaheh, K., Grelik, S., Jafarov, E., and Liu, L.: Active layer thickness as a function of soil water content, Environ. Res. Lett., 16, 055028, https://doi.org/10.1088/1748-9326/abfa4c, 2021.
Cook, B. D., Corp, L. W., Nelson, R. F., Middleton, E. M., Morton, D. C., McCorkel, J. T., Masek, J. G., Ranson, K. J., Ly, V., and Montesano, P. M.: NASA Goddard's Lidar, Hyperspectral and Thermal (G-LiHT) airborne imager, Remote Sens.-Basel, 5, 4045–4066, https://doi.org/10.3390/rs5084045, 2013.
Dann, J., Bennett, K. E., Bolton, W. R., and Wilson, C. J.: Factors Controlling a Synthetic Aperture Radar (SAR) Derived Root-Zone Soil Moisture Product over The Seward Peninsula of Alaska, Remote Sens.-Basel, 14, 4927, https://doi.org/10.3390/rs14194927, 2022.
Du, J., Kimball, J. S., and Moghaddam, M.: Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations, Remote Sens.-Basel, 7, 9450–9472, https://doi.org/10.3390/rs70709450, 2015.
French, N. H. F., Graham, J. A., Bourgeau-Chavez, L. L., and Whitman, E.: ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014–2015, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1694, 2020.
Goetz, S. J., Miller, C. E., Griffith, P. C., Chatterjee, A., Boelman, N., Bourgeau-Chavez, L., Butman, D., Epstein, H., Fisher, J., French, N., Hoy, E., Kimball, J. S., Larson, E., Loboda, T., Mack, M., Moghaddam, M., Montesano, P., Prugh, L., Rawlins, M., Rocha, A. V., Rogers, B. M., and Schaefer, K.: An overview of NASA’s Arctic Boreal Vulnerability Experiment (ABoVE): An integrated research campaign to assess ecosystem vulnerability and its implications within the Arctic and boreal domain, Environmental Research Letters (ABoVE Special Collection), Manuscript ERL-112259, in review, 2022.
Hensley, S., Oveisgharan, S., Saatchi, S., Simard, M., Ahmed, R., and Haddad, Z.: An error model for biomass estimates derived from polarimetric radar backscatter, IEEE T. Geosci. Remote, 52, 4065–4082, 2014.
Hensley, S., Lou, Y., Michel, T., Muellerschoen, R., Hawkins, B., Lavalle, M., Pinto, N., Reigber, A., and Pardini, M.: UAVSAR PolInSAR and tomographic experiments in Germany, in: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, July 2016, 7517–7520, https://doi.org/10.1109/IGARSS.2016.7730960, 2016.
Hensley, S., Chapman, B., Lavalle, M., Hawkins, B., Riel, B., Michel, T., Muellerschoen, R., Lou, Y., and Simard, M.: UAVSAR L-Band and P-Band Tomographic Experiments in Boreal Forests, IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018, 8679–8682, https://doi.org/10.1109/IGARSS.2018.8518784, 2018.
Hensley, S., Ahmed, R., Chapman, B., Hawkins, B., Lavalle, M., Pinto, N., Pardini, M., Papathanassiou, K., Siqueria, P., and Treuhaft, R.: Boreal Forest Radar Tomography at P, L and S-Bands at Berms and Delta Junction, IGARSS 2020 – 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, 96–99, https://doi.org/10.1109/IGARSS39084.2020.9323337, 2020.
Hinzman, L. D., Deal, C. J., McGuire, A. D., Mernild, S. H., Polyakov, I. V., and Walsh, J. E.: Trajectory of the Arctic as an integrated system, Ecol. Appl., 23, 1837–1868, https://doi.org/10.1890/11-1498.1, 2013.
Holloway, J. E., Lewkowicz, A. G., Douglas, T. A., Li, X., Turetsky, M. R., Baltzer, J. L., and Jin, H.: Impact of wildfire on permafrost landscapes: A review of recent advances and future prospects, Permafrost Periglac., 31, 371–382, https://doi.org/10.1002/ppp.2048, 2020.
Hoy, E. E., Griffith, P., Miller, C. E., and ABoVE Science Team: ABoVE: Directory of Field Sites Associated with 2017 ABoVE Airborne Campaign, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1582, 2018.
Kokelj, S. V., Lacelle, D., Lantz, T. C., Tunnicliffe, J., Malone, L., Clark, I. D., and Chin, K. S.: Thawing of massive ground ice in mega slumps drives increases in stream sediment and solute flux across a range of watershed scales, J. Geophys. Res.-Earth, 118, 681–692, https://doi.org/10.1002/jgrf.20063, 2013.
Kokelj, S. V., Tunnicliffe, J., Lacelle, D., Lantz, T. C., Chin, K. S., and Fraser, R.: Increased precipitation drives mega slump development and destabilization of ice-rich permafrost terrain, northwestern Canada, Glob. Planet. Change, 129, 56–68, https://doi.org/10.1016/j.gloplacha.2015.02.008, 2015.
Kyzivat, E. D., Smith, L. C., Pitcher, L. H., Fayne, J. V., Cooley, S. W., Cooper, M. G., Topp, S. N., Langhorst, T., Harlan, M. E., Horvat, C., Gleason, C. J., and Pavelsky, T. M.: A High-Resolution Airborne Color-Infrared Camera Water Mask for the NASA ABoVE Campaign, Remote Sens.-Basel, 11, 2163, https://doi.org/10.3390/rs11182163, 2019.
Kyzivat, E. D., Smith, L. C., Pitcher, L. H., Fayne, J. V., Cooley, S. W., Cooper, M. G., Topp, S., Langhorst, T., Harlan, M. E., Gleason, C. J., and Pavelsky, T. M.: ABoVE: AirSWOT Water Masks from Color-Infrared Imagery over Alaska and Canada, 2017, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1707, 2020.
Lantz, T. C. and Turner, K. W.: Changes in lake area in response to thermokarst processes and climate in Old Crow Flats, Yukon, J. Geophys. Res.-Biogeo., 120, 513–524, https://doi.org/10.1002/2014JG002744, 2015.
Lathrop, E., Nutt, M., Wilson, C., Bolton, R., Perkins, G., and Harris, R.: Soil moisture, physical and chemical properties coincident with airborne SAR data collections for 2017 and 2019, Seward Peninsula, Alaska, Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.5440/1854940, 2022.
Le Toan, T., Quegan, S., Davidson, M. W. J., Balzter, H., Paillou, P., Papathanassiou, K., Plummer, S., Rocca, F., Saatchi, S., Shugart, H., and Ulander, L.: The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle, Remote Sens. Environ., 115, 2850–2860, https://doi.org/10.1016/j.rse.2011.03.020, 2011.
Loboda, T. V., Jenkins, L. K., Chen, D., He, J., and Baer, A.: Burned and Unburned Field Site Data, Noatak, Seward, and North Slope, AK, 2016–2018, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1919, 2022.
Magagi, R., Berg, A. A., Goita, K., Belair, S., Jackson, T. J., Toth, B., Walker, A., McNairn, H., O'Neill, P. E., Moghaddam, M., Gherboudj, I., Colliander, A., Cosh, M. H., Burgin, M., Fisher, J. B., Kim, S.-B., Mladenova, I., Djamai, N., Rousseau, L.-P. B., Belanger, J., Shang, J., and Merzouki, A.: Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10): Overview and Preliminary Results, IEEE T. Geosci. Remote, 51, 347–363, https://doi.org/10.1109/TGRS.2012.2198920, 2013.
McGuire, A. D., Anderson, L. G., Christensen, T. R., Dallimore, S., Guo, L., Hayes, D. J., Heimann, M., Lorenson, T. D., Macdonald, R. W., and Roulet, N.: Sensitivity of the carbon cycle in the Arctic to climate change, Ecol. Monogr., 79, 523–555, https://doi.org/10.1890/08-2025.1, 2009.
Meddens, A. J. H., Vierling, L. A., Eitel, J. U. H., Jennewein, J. S., White, J. C., and Wulder, M. A.: Developing 5 m resolution canopy height and digital terrain models from WorldView and ArcticDEM data, Remote Sens. Environ., 218, 174–188, https://doi.org/10.1016/j.rse.2018.09.010, 2018.
Mehra, R. and Ramanujam, V. M.: L S Band Airborne SAR Data Products Calibration, in: 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), New Delhi, India, 9–15 March 2019, https://doi.org/10.23919/URSIAP-RASC.2019.8738681, 2019.
Meyer, G., Humphreys, E. R., Melton, J. R., Cannon, A. J., and Lafleur, P. M.: Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC), Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, 2021.
Michaelides, R. J., Chen, R. H., Zhao, Y., Schaefer, K., Parsekian, A. D., Sullivan, T., Moghaddam, M., Zebker, H. A., Liu, L., Xu, X., and Chen, J.: Permafrost Dynamics Observatory – part I: Postprocessing and calibration methods of UAVSAR L-band InSAR data for seasonal subsidence estimation, Earth Space Sci., 8, e2020EA001630, https://doi.org/10.1029/2020EA001630, 2021.
Miller, C. E., Griffith, P. C., Goetz, S. J., Hoy, E. E., Pinto, N., McCubbin, I. B., Thorpe, A. K., Hofton, M., Hodkinson, D., Hansen, C., Woods, J., Larson, E., Kasischke, E. S., and Margolis, H. A.: An overview of ABoVE airborne campaign data acquisitions and science opportunities, Environ. Res. Lett., 14, 080201, https://doi.org/10.1088/1748-9326/ab0d44, 2019.
Miller, C. E., Griffith, P., Hoy, E. E., Pinto, N., Lou, Y., Hensley, S., Chapman, B., Baltzer, J. L., Bakian-Dogaheh, K., Bolton, W. R., Bourgeau-Chavez, L. L., Chen, R. H., Choe, B.-H., Clayton, L. K., Douglas, T. A., French, N. H. F., Holloway, J. E., Hong, G., Huang, L., Iwahana, G., Jenkins, L. K., Kimball, J. S., Loboda, T. V., Mack, M. C., Marsh, P., Michaelides, R. J., Moghaddam, M., Parsekian, A. D., Schaefer, K., Siqueira, P., Singh, D., Tabatabaeenejad, A., Turetsky, M. R., Touzi, R., Wig, E., Wilson, P., Wilson, C. J., Wullschleger, S. D., Yi, Y., Zebker, H. A., Zhang, Y., Zhao, Y., and Goetz, S. J.: Summary of the ABoVE L-band and P-band Airborne SAR Surveys, ORNL DAAC, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/2150, 2023.
Moghaddam, M., Tabatabaeenejad, A., Chen, R. H., Saatchi, S. S., Jaruwatanadilok, S., Burgin, M., Duan, X., and Truong-Loi, M. L.: AirMOSS: L2/3 Volumetric Soil Moisture Profiles Derived From Radar, 2012–2015, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1418, 2016.
Montesano, P. M., Sun, G., Dubayah, R. O., and Ranson, K. J.: Spaceborne potential for examining taiga–tundra ecotone form and vulnerability, Biogeosciences, 13, 3847–3861, https://doi.org/10.5194/bg-13-3847-2016, 2016.
National Research Council (NRC): Opportunities to Use Remote Sensing in Understanding Permafrost and Related Ecological Characteristics: Report of a Workshop, The National Academies Press, Washington, DC, https://doi.org/10.17226/18711, 2014.
Pitcher, L. H., Pavelsky, T. M., Smith, L. C., Moller, D. K., Altenau, E. H., Allen, G. H., Lion, C., Butman, D., Cooley, S. W., Fayne, J. V., and Bertram, M.: AirSWOT InSAR Mapping of Surface Water Elevations and Hydraulic Gradients Across the Yukon Flats Basin, Alaska, Water Resour. Res., 55, 937–953, https://doi.org/10.1029/2018WR023274, 2019a.
Pitcher, L. H., Smith, L. C., Pavelsky, T. M., Fayne, J. V., Cooley, S. W., Altenau, E. H., Moller, D. K., and Arvesen, J.: ABoVE: AirSWOT Radar, Orthomosaic, and Water Masks, Yukon Flats Basin, Alaska, 2015, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1655, 2019b.
Pitcher, L. H., Smith, L. C., Cooley, S. W., Zaino, A., Carlson, R., Pettit, J., Gleason, C. J., Minear, J. T., Fayne, J. V., Willis, M. J., Hansen, J. S., Easterday, K. J., Harlan, M. E., Langhorst, T., Topp, S. N., Dolan, W., Kyzivat, E. D., Pietroniro, A., Marsh, P., Yang, D., Carter, T., Onclin, C., Hosseini, N., Wilcox, E., Moreira, D., Berge-Nguyen, M., Cretaux, J.-F., and Pavelsky, T. M.: Advancing Field-Based GNSS Surveying for Validation of Remotely Sensed Water Surface Elevation Products, Front. Earth Sci., 8, 278, https://doi.org/10.3389/feart.2020.00278, 2020.
Porter, C., Morin, P., Howat, I., Noh, M.-J., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., Tomko, K., Willis, M., Kelleher, C., Cloutier, M., Husby, E., Foga, S., Nakamura, H., Platson, M., Wethington, M., Williamson, C., Bauer, G., Enos, J., Arnold, G., Kramer, W., Becker, P., Doshi, A., D'Souza, C., Cummens, P., Laurier, F., and Bojesen, M.: ArcticDEM, https://doi.org/10.7910/DVN/OHHUKH, 2018.
Quegan, S., Le Toan, T., Chave, J., Dall, J., Exbrayat, J.-F., Minh, D. H. T., Lomas, M., D'Alessandro, M. M., Paillou, P., Papathanassiou, K., Rocca, F., Saatchi, S., Scipal, K., Shugart, H., Smallman, T. L., Soja, M. J., Tebaldini, S., Ulander, L., Villard, L., and Williams, M.: The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space, Remote Sens. Environ., 227, 44–60, https://doi.org/10.1016/j.rse.2019.03.032, 2019.
Quinton, W., Berg, A., Braverman, M., Carpino, O., Chasmer, L., Connon, R., Craig, J., Devoie, É., Hayashi, M., Haynes, K., Olefeldt, D., Pietroniro, A., Rezanezhad, F., Schincariol, R., and Sonnentag, O.: A synthesis of three decades of hydrological research at Scotty Creek, NWT, Canada, Hydrol. Earth Syst. Sci., 23, 2015–2039, https://doi.org/10.5194/hess-23-2015-2019, 2019.
Ramanujam, V. M. and Mehra, R.: L&S Band SAR Data Processing and Products, in: 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), New Delhi, India, 2019, https://doi.org/10.23919/URSIAP-RASC.2019.8738235, 2019.
Ramanujam, V. M., Suneela, T. J. V. D., and Bhan, R.: ISRO's dual frequency airborne SAR pre-cursor to NISAR, in: Earth Observing Missions and Sensors: Development, Implementation, and Characterization IV, 98810A, https://doi.org/10.1117/12.2228086, 2016.
Reigber, A., Papathanassiou, K., Jger, M., and Scheiber, R.: First results of multispectral polarimetry and single-pass PolInSAR with the F-SAR airborne SAR instrument, in: 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, IEEE, 2305–2308, https://doi.org/10.1109/IGARSS.2013.6723279, 2013.
Rosen, P. A., Kim, Y., Kumar, R., Misra, T., Bhan, R., and Sagi, V. R.: Global persistent SAR sampling with the NASA-ISRO SAR (NISAR) mission, in; 2017 IEEE Radar Conference (RadarConf), Seattle, WA, USA, 2017, 0410–0414, https://doi.org/10.1109/RADAR.2017.7944237, 2017.
Saatchi, S., Xu, L., Yang, Y., and Yu, Y.: Evaluation of NISAR Biomass Algorithm in Temperate and Boreal Forests, IGARSS 2019–2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, 7363–7366, https://doi.org/10.1109/IGARSS.2019.8898657, 2019.
Saatchi, S. S. and Moghaddam, M.: Estimation of crown and stem water content and biomass of boreal forest using polarimetric SAR imagery, IEEE T. Geosci. Remote, 38, 697–709, https://doi.org/10.1109/36.841999, 2000.
Schaefer, K., Liu, L., Parsekian, A., Jafarov, E., Chen, A., Zhang, T., Gusmeroli, A., Panda, S., Zebker, H. A., and Schaefer, T.: Remotely sensed active layer thickness (ReSALT) at Barrow, Alaska using interferometric synthetic aperture radar, Remote sensing, 7, 3735–3759, https://doi.org/10.3390/rs70403735, 2015.
Schaefer, K., Michaelides, R. J., Chen, R. H., Sullivan, T. D., Parsekian, A. D., Bakian-Dogaheh, K., Tabatabaeenejad, A., Moghaddam, M., Chen, J., Chen, A. C., Liu, L., and Zebker, H. A.: ABoVE: Active Layer Thickness Derived from Airborne L- and P-band SAR, Alaska, 2017, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1676, 2019.
Schaefer, K., Clayton, L. K., Battaglia, M. J., Bourgeau-Chavez, L. L., Chen, R. H., Chen, A. C., Chen, J., Bakian-Dogaheh, K., Douglas, T. A., Grelick, S. E., Iwahana, G., Jafarov, E., Liu, L., Ludwig, S., Michaelides, R. J., Moghaddam, M., Natali, S., Panda, S. K., Parsekian, A. D., Rocha, A. V., Schaefer, S. R., Sullivan, T. D., Tabatabaeenejad, A., Wang, K., Wilson, C. J., Zebker, H. A., Zhang, T., and Zhao, Y.: ABoVE: Soil Moisture and Active Layer Thickness in Alaska and NWT, Canada, 2008–2020, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1903, 2021a.
Schaefer, K., Michaelides, R. J., Chen, R. H., Sullivan, T. D., Parsekian, A. D., Zhao, Y., Bakian-Dogaheh, K., Tabatabaeenejad, A., Moghaddam, M., Chen, J., Chen, A. C., Liu, L., and Zebker, H. A.: ABoVE: Active Layer Thickness Derived from Airborne L- and P-band SAR, Alaska, 2017, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1796, 2021b.
Sellers, P., Hall, F., Margolis, H., Kelly, B., Baldocchi, D., den Hartog, G., Cihlar, J., Ryan, M. G., Goodison, B., Crill, P., Ranson, K. J., Lettenmaier, D., and Wickland, D. E.: The Boreal Ecosystem–Atmosphere Study (BOREAS): An Overview and Early Results from the 1994 Field Year, B. Am. Meteorol. Soc., 76, 1549–1577, https://doi.org/10.1175/1520-0477(1995)076<1549:TBESAO>2.0.CO;2, 1995.
Sellers, P. J., Hall, F. G., Kelly, R. D., Black, A., Baldocchi, D., Berry, J., Ryan, M., Ranson, K. J., Crill, P. M., Lettenmaier, D. P., Margolis, H., Cihlar, J., Newcomer, J., Fitzjarrald, D., Jarvis, P. G., Gower, S. T., Halliwell, D., Williams, D., Goodison, B., Wickland, D. E., and Guertin, F. E.: BOREAS in 1997: Experiment overview, scientific results, and future directions, J. Geophys. Res.-Atmos., 102, 28731–28769, https://doi.org/10.1029/97JD03300, 1997.
Silva, C. A., Duncanson, L., Hancock, S., Neuenschwander, A., Thomas, N., Hofton, M., Fatoyinbo, L., Simard, M., Marshak, C. Z., Armston, J., Lutchke, S., and Dubayah, R.: Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping, Remote Sens. Environ., 253, 112234, https://doi.org/10.1016/j.rse.2020.112234, 2021.
Tabatabaeenejad, A., Burgin, M., and Moghaddam, M.: Potential of L-band radar for retrieval of canopy and subcanopy parameters of boreal forests, IEEE T. Geosci. Remote, 50, 2150–2160, https://doi.org/10.1109/TGRS.2011.2173349, 2011.
Tabatabaeenejad, A., Burgin, M., Duan, X., and Moghaddam, M.: P-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First AirMOSS Results, IEEE T. Geosci. Remote, 53, 645–658, https://doi.org/10.1109/TGRS.2014.2326839, 2015.
Tabatabaeenejad, A., Chen, R. H., Burgin, M. S., Duan, X., Cuenca, R. H., Cosh, M. H., Scott, R. L., and Moghaddam, M.: Assessment and Validation of AirMOSS P-Band Root-Zone Soil Moisture Products, IEEE T. Geosci. Remote, 58, 6181–6196, https://doi.org/10.1109/TGRS.2020.2974976, 2020.
Tank, S. E., Olefeldt, D., Quinton, W. L., Spence, C., Dion, N., Ackley, C., Burd, K., Hutchins, R., and Mengistu, S.: Fire in the Arctic: The effect of wildfire across diverse aquatic ecosystems of the Northwest Territories, Polar Knowledge: Aqhaliat, 1, 31–38, 2018.
Vincent, W. F., Callaghan, T. V., Dahl-Jensen, D., Johansson, M., Kovacs, K. M., Michel, C., Prowse, T., Reist, J. D., and Sharp, M.: Ecological Implications of Changes in the Arctic Cryosphere, AMBIO, 40, 87–99, https://doi.org/10.1007/s13280-011-0218-5, 2011.
Walker, X. J., Rogers, B. M., Baltzer, J. L., Cumming, S. G., Day, N. J., Goetz, S. J., Johnstone, J. F., Schuur, E. A. G., Turetsky, M. R., and Mack, M. C.: Cross-scale controls on carbon emissions from boreal forest megafires, Glob. Change Biol., 24, 4251–4265, https://doi.org/10.1111/gcb.14287, 2018a.
Walker, X. J., Rogers, B. M., Baltzer, J. L., Cummings, S. R., Day, N. J., Goetz, S. J., Johnstone, J. F., Turetsky, M. R., and Mack, M. C.: ABoVE: Wildfire Carbon Emissions and Burned Plot Characteristics, NWT, CA, 2014–2016, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1561, 2018b.
Walker, X. J., Baltzer, J. L., Cumming, S. G., Day, N. J., Ebert, C., Goetz, S., Johnstone, J. F., Potter, S., Rogers, B. M., Schuur, E. A. G., Turetsky, M. R., and Mack, M. C.: Increasing wildfires threaten historic carbon sink of boreal forest soils, Nature, 572, 520–523, https://doi.org/10.1038/s41586-019-1474-y, 2019a.
Walker, X. J., Baltzer, J. L., Laurier, W., Cumming, S. G., Day, N. J., Goetz, S. J., Johnstone, J. F., Potter, S., Rogers, B. M., Schuur, E. A. G., Turetsky, M. R., and Mack, M. C.: ABoVE: Characterization of Carbon Dynamics in Burned Forest Plots, NWT, Canada, 2014, ORNL DAAC, https://doi.org/10.3334/ORNLDAAC/1664, 2019b.
Wilson, C., Dann, J., Bolton, R., Charsley-Groffman, L., Jafarov, E., Musa, D., and Wullschleger, S.: In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Barrow and Seward Peninsulas, Alaska, 2017, Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.5440/1423892, 2018.
Wilson, C., Dann, J., Bolton, R., Charsley-Groffman, L., Jafarov, E., Musa, D., and Wullschleger, S.: In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Barrow and Seward Peninsulas, Alaska, 2017, United States, Version 2, U.S. Department of Energy, Oak Ridge, Tennessee, USA [data set], https://www.osti.gov/biblio/1423892 (last access: 19 April 2024), 2021.
Wilson, C., Lathrop, E., Bolton, R., Jin, X., Nutt, M., and Dann, J.: In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Seward Peninsula, Alaska, 2019, Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.5440/1856042, 2022.
Zhao, Y., Chen, R. H., Bakina-Dogaheh, K., Whitcomb, J., Yi, Y., Kimball, J. S., and Moghaddam, M.: Mapping Boreal Forest Species and Canopy Height using Airborne SAR and Lidar Data in Interior Alaska, IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022, 4955–4958, https://doi.org/10.1109/IGARSS46834.2022.9883311, 2022.
Short summary
NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture...
Altmetrics
Final-revised paper
Preprint