Articles | Volume 29, issue 3
https://doi.org/10.5194/hess-29-701-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-701-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Feb 2025
Research article |
| 05 Feb 2025
| 05 Feb 2025
Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Gerald F. M. Page
School of Environmental and Conservation Sciences, Murdoch University, Murdoch, WA 6150, Australia
Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
Frank Zurek
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Christopher Still
Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
Mariah S. Carbone
Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ 86011, USA
Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
William Talavera
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Laura Hildebrand
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
James Byron
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Kyle Inthabandith
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Angellica Kucinski
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Melissa Carlson
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Kelsey Foss
Department of Earth and Environmental Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
Wendy Brown
Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
Rosemary W. H. Carroll
Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA
Austin Simonpietri
Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ 86011, USA
Marshall Worsham
Energy and Resources Group, University of California, Berkeley, Berkeley, CA 94720, USA
Ian Breckheimer
Clark Family School of Environment and Sustainability, Western Colorado University, Gunnison, CO 81231, USA
Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
Anna Ryken
Hydrologic Science and Engineering, Colorado School of Mines, Golden, CO 80401, USA
Reed Maxwell
High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA
David Gochis
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO 80305, USA
Mark S. Raleigh
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA
Eric Small
Department of Geological Sciences, University of Colorado Boulder, Boulder, CO 80309, USA
Kenneth H. Williams
Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Rocky Mountain Biological Laboratory, Crested Butte, CO 81224, USA
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Manuscript not accepted for further review
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The Canadian Arctic Archipelago (CAA) is characterized by advection from the Pacific (PW) and Atlantic waters (AW), ice melt, local river discharge and net precipitation. In a changing Arctic, it is crucial to monitor the hydrography of this Region. We combined chemical and physical parameters into an Optimal MultiParameter Analysis, for the detection of the source water fractions characterizing the CAA. The outcome was effective about the PW and AW, and discriminated the meltwaters origin.
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Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
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Trina Merrick, Stephanie Pau, Matteo Detto, Eben N. Broadbent, Stephanie A. Bohlman, Christopher J. Still, and Angelica M. Almeyda Zambrano
Biogeosciences, 18, 6077–6091, https://doi.org/10.5194/bg-18-6077-2021, https://doi.org/10.5194/bg-18-6077-2021, 2021
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Remote sensing measurements of forest structure promise to improve monitoring of tropical forest health. We investigated drone-based vegetation measurements' abilities to capture different structural and functional elements of a tropical forest. We found that emerging vegetation indices captured greater variability than traditional indices and one new index trends with daily change in carbon flux. These new tools can help improve understanding of tropical forest structure and function.
Trude Eidhammer, Adam Booth, Sven Decker, Lu Li, Michael Barlage, David Gochis, Roy Rasmussen, Kjetil Melvold, Atle Nesje, and Stefan Sobolowski
Hydrol. Earth Syst. Sci., 25, 4275–4297, https://doi.org/10.5194/hess-25-4275-2021, https://doi.org/10.5194/hess-25-4275-2021, 2021
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We coupled a detailed snow–ice model (Crocus) to represent glaciers in the Weather Research and Forecasting (WRF)-Hydro model and tested it on a well-studied glacier. Several observational systems were used to evaluate the system, i.e., satellites, ground-penetrating radar (used over the glacier for snow depth) and stake observations for glacier mass balance and discharge measurements in rivers from the glacier. Results showed improvements in the streamflow projections when including the model.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279, https://doi.org/10.5194/essd-13-3263-2021, https://doi.org/10.5194/essd-13-3263-2021, 2021
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Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
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Short summary
Warming in montane systems is affecting the snowmelt input amount. At the global scale, this will impact subalpine forests that rely on spring snowmelt to support their water demands. We use a network of sensors across a hillslope in the Upper Colorado Basin to show that the changing spring snowpack has a more pronounced impact on dense forest stands, while open stands show a higher reliance on summer rain and are less sensitive to significant changes in snow.
Warming in montane systems is affecting the snowmelt input amount. At the global scale, this...
