Articles | Volume 13, issue 1
https://doi.org/10.5194/esd-13-595-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-13-595-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Widespread greening suggests increased dry-season plant water availability in the Rio Santa valley, Peruvian Andes
Lorenz Hänchen
CORRESPONDING AUTHOR
Department of Ecology, University of Innsbruck, Innsbruck, Austria
Cornelia Klein
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
UK Centre for Ecology & Hydrology, Wallingford, UK
Fabien Maussion
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Wolfgang Gurgiser
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Pierluigi Calanca
Climate and Agriculture, Department of Agroecology and Environment, Agroscope Institute for Sustainability Sciences ISS, Zurich, Switzerland
Georg Wohlfahrt
Department of Ecology, University of Innsbruck, Innsbruck, Austria
Related authors
Lorenz Hänchen, Emily Potter, Cornelia Klein, Pierluigi Calanca, Fabien Maussion, Wolfgang Gurgiser, and Georg Wohlfahrt
Hydrol. Earth Syst. Sci., 29, 2727–2747, https://doi.org/10.5194/hess-29-2727-2025, https://doi.org/10.5194/hess-29-2727-2025, 2025
Short summary
Short summary
In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture. This study introduces a new framework for improving estimations of the onset and end of the rainy season by testing how well they fit local vegetation data. We improve the performance of existing methods and present a new one with higher performance. Our findings can help us to make informed decisions about water usage, and the framework can be applied to other regions as well.
Patrick Schmitt, Fabien Maussion, Daniel N. Goldberg, and Philipp Gregor
EGUsphere, https://doi.org/10.5194/egusphere-2025-3401, https://doi.org/10.5194/egusphere-2025-3401, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
To improve large-scale understanding of glaciers, we developed a new data assimilation method that integrates available observations in a dynamically consistent way, while taking their timestamps into account. It is designed to flexibly include new glacier data as it becomes available. We tested the method with idealized experiments and found promising results in terms of accuracy and efficiency, showing strong potential for real-world applications.
Jakob Steiner, William Armstrong, Will Kochtitzky, Robert McNabb, Rodrigo Aguayo, Tobias Bolch, Fabien Maussion, Vibhor Agarwal, Iestyn Barr, Nathaniel R. Baurley, Mike Cloutier, Katelyn DeWater, Frank Donachie, Yoann Drocourt, Siddhi Garg, Gunjan Joshi, Byron Guzman, Stanislav Kutuzov, Thomas Loriaux, Caleb Mathias, Biran Menounos, Evan Miles, Aleksandra Osika, Kaleigh Potter, Adina Racoviteanu, Brianna Rick, Miles Sterner, Guy D. Tallentire, Levan Tielidze, Rebecca White, Kunpeng Wu, and Whyjay Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-315, https://doi.org/10.5194/essd-2025-315, 2025
Preprint under review for ESSD
Short summary
Short summary
Many mountain glaciers around the world flow into lakes – exactly how many however, has never been mapped. Across a large team of experts we have now identified all glaciers that end in lakes. Only about 1% do so, but they are generally larger than those which end on land. This is important to understand, as lakes can influence the behaviour of glacier ice, including how fast it disappears. This new dataset allows us to better model glaciers at a global scale, accounting for the effect of lakes.
Beatriz P. Cazorla, Ana Meijide, Javier Cabello, Julio Peñas, Rodrigo Vargas, Javier Martínez-López, Leonardo Montagnani, Alexander Knohl, Lukas Siebicke, Benimiano Gioli, Jiří Dušek, Ladislav Šigut, Andreas Ibrom, Georg Wohlfahrt, Eugénie Paul-Limoges, Kathrin Fuchs, Antonio Manco, Marian Pavelka, Lutz Merbold, Lukas Hörtnagl, Pierpaolo Duce, Ignacio Goded, Kim Pilegaard, and Domingo Alcaraz-Segura
EGUsphere, https://doi.org/10.5194/egusphere-2025-2835, https://doi.org/10.5194/egusphere-2025-2835, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
We assess whether satellite-derived Ecosystem Functional Types (EFTs) reflect spatial heterogeneity in carbon fluxes across Europe. Using Eddy Covariance data from 50 sites, we show that EFTs capture distinct Net Ecosystem Exchange dynamics and perform slightly better than PFTs. EFTs offer a scalable, annually updatable approach to monitor ecosystem functioning and its interannual variability.
Lorenz Hänchen, Emily Potter, Cornelia Klein, Pierluigi Calanca, Fabien Maussion, Wolfgang Gurgiser, and Georg Wohlfahrt
Hydrol. Earth Syst. Sci., 29, 2727–2747, https://doi.org/10.5194/hess-29-2727-2025, https://doi.org/10.5194/hess-29-2727-2025, 2025
Short summary
Short summary
In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture. This study introduces a new framework for improving estimations of the onset and end of the rainy season by testing how well they fit local vegetation data. We improve the performance of existing methods and present a new one with higher performance. Our findings can help us to make informed decisions about water usage, and the framework can be applied to other regions as well.
Finn Wimberly, Lizz Ultee, Lilian Schuster, Matthias Huss, David R. Rounce, Fabien Maussion, Sloan Coats, Jonathan Mackay, and Erik Holmgren
The Cryosphere, 19, 1491–1511, https://doi.org/10.5194/tc-19-1491-2025, https://doi.org/10.5194/tc-19-1491-2025, 2025
Short summary
Short summary
Glacier models have historically been used to understand glacier melt’s contribution to sea level rise. The capacity to project seasonal glacier runoff is a relatively recent development for these models. In this study we provide the first model intercomparison of runoff projections for the glacier evolution models capable of simulating future runoff globally. We compare model projections from 2000 to 2100 for all major river basins larger than 3000 km2 with over 30 km2 of initial glacier cover.
Lea Hartl, Patrick Schmitt, Lilian Schuster, Kay Helfricht, Jakob Abermann, and Fabien Maussion
The Cryosphere, 19, 1431–1452, https://doi.org/10.5194/tc-19-1431-2025, https://doi.org/10.5194/tc-19-1431-2025, 2025
Short summary
Short summary
We use regional observations of glacier area and volume change to inform glacier evolution modeling in the Ötztal and Stubai range (Austrian Alps) until 2100 in different climate scenarios. Glaciers in the region lost 23 % of their volume between 2006 and 2017. Under current warming trajectories, glacier loss in the region is expected to be near-total by 2075. We show that integrating regional calibration and validation data in glacier models is important to improve confidence in projections.
Kamilla Hauknes Sjursen, Jordi Bolibar, Marijn van der Meer, Liss Marie Andreassen, Julian Peter Biesheuvel, Thorben Dunse, Matthias Huss, Fabien Maussion, David R. Rounce, and Brandon Tober
EGUsphere, https://doi.org/10.5194/egusphere-2025-1206, https://doi.org/10.5194/egusphere-2025-1206, 2025
Short summary
Short summary
Understanding glacier mass changes is crucial for assessing freshwater availability in many regions of the world. We present the Mass Balance Machine, a machine learning model that learns from sparse measurements of glacier mass change to make predictions on unmonitored glaciers. Using data from Norway, we show that the model provides accurate estimates of mass changes at different spatiotemporal scales. Our findings show that machine learning can be a valuable tool to improve such predictions.
Rodrigo Aguayo, Fabien Maussion, Lilian Schuster, Marius Schaefer, Alexis Caro, Patrick Schmitt, Jonathan Mackay, Lizz Ultee, Jorge Leon-Muñoz, and Mauricio Aguayo
The Cryosphere, 18, 5383–5406, https://doi.org/10.5194/tc-18-5383-2024, https://doi.org/10.5194/tc-18-5383-2024, 2024
Short summary
Short summary
Predicting how much water will come from glaciers in the future is a complex task, and there are many factors that make it uncertain. Using a glacier model, we explored 1920 scenarios for each glacier in the Patagonian Andes. We found that the choice of the historical climate data was the most important factor, while other factors such as different data sources, climate models and emission scenarios played a smaller role.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Harry Zekollari, Matthias Huss, Lilian Schuster, Fabien Maussion, David R. Rounce, Rodrigo Aguayo, Nicolas Champollion, Loris Compagno, Romain Hugonnet, Ben Marzeion, Seyedhamidreza Mojtabavi, and Daniel Farinotti
The Cryosphere, 18, 5045–5066, https://doi.org/10.5194/tc-18-5045-2024, https://doi.org/10.5194/tc-18-5045-2024, 2024
Short summary
Short summary
Glaciers are major contributors to sea-level rise and act as key water resources. Here, we model the global evolution of glaciers under the latest generation of climate scenarios. We show that the type of observations used for model calibration can strongly affect the projections at the local scale. Our newly projected 21st century global mass loss is higher than the current community estimate as reported in the latest Intergovernmental Panel on Climate Change (IPCC) report.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary
Short summary
The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
Sarah Hanus, Lilian Schuster, Peter Burek, Fabien Maussion, Yoshihide Wada, and Daniel Viviroli
Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, https://doi.org/10.5194/gmd-17-5123-2024, 2024
Short summary
Short summary
This study presents a coupling of the large-scale glacier model OGGM and the hydrological model CWatM. Projected future increase in discharge is less strong while future decrease in discharge is stronger when glacier runoff is explicitly included in the large-scale hydrological model. This is because glacier runoff is projected to decrease in nearly all basins. We conclude that an improved glacier representation can prevent underestimating future discharge changes in large river basins.
Marin Kneib, Amaury Dehecq, Fanny Brun, Fatima Karbou, Laurane Charrier, Silvan Leinss, Patrick Wagnon, and Fabien Maussion
The Cryosphere, 18, 2809–2830, https://doi.org/10.5194/tc-18-2809-2024, https://doi.org/10.5194/tc-18-2809-2024, 2024
Short summary
Short summary
Avalanches are important for the mass balance of mountain glaciers, but few data exist on where and when they occur and which glaciers they affect the most. We developed an approach to map avalanches over large glaciated areas and long periods of time using satellite radar data. The application of this method to various regions in the Alps and High Mountain Asia reveals the variability of avalanches on these glaciers and provides key data to better represent these processes in glacier models.
Arianna Peron, Martin Graus, Marcus Striednig, Christian Lamprecht, Georg Wohlfahrt, and Thomas Karl
Atmos. Chem. Phys., 24, 7063–7083, https://doi.org/10.5194/acp-24-7063-2024, https://doi.org/10.5194/acp-24-7063-2024, 2024
Short summary
Short summary
The anthropogenic fraction of non-methane volatile organic compound (NMVOC) emissions associated with biogenic sources (e.g., terpenes) is investigated based on eddy covariance observations. The anthropogenic fraction of terpene emissions is strongly dependent on season. When analyzing volatile chemical product (VCP) emissions in urban environments, we caution that observations from short-term campaigns might over-/underestimate their significance depending on local and seasonal circumstances.
Joseph Kiem, Albin Hammerle, Leonardo Montagnani, and Georg Wohlfahrt
EGUsphere, https://doi.org/10.5194/egusphere-2024-881, https://doi.org/10.5194/egusphere-2024-881, 2024
Preprint archived
Short summary
Short summary
Albedo is the fraction of solar radiation that is reflected by some surface. The presence of a seasonal snow cover dramatically increases albedo. We made use of a novel snow depth dataset for Austria to investigate likely future changes in albedo up to 2100. In 5 out of the 6 investigated future scenarios a significant decline of albedo could be observed. The associated warming is equivalent to between 0.25 to 5 times the current annual CO2-equivalent emissions of Austria.
Larissa van der Laan, Anouk Vlug, Adam A. Scaife, Fabien Maussion, and Kristian Förster
EGUsphere, https://doi.org/10.5194/egusphere-2024-387, https://doi.org/10.5194/egusphere-2024-387, 2024
Short summary
Short summary
Usually, glacier models are supplied with climate information from long (e.g. 100 year) simulations by global climate models. In this paper, we test the feasibility of supplying glacier models with shorter simulations, to get more accurate information on 5–10 year time scales. Reliable information on these time scales is very important, especially for water management experts to know how much meltwater to expect, for rivers, agriculture and drinking water.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
Short summary
Short summary
We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Georg Wohlfahrt, Albin Hammerle, Felix M. Spielmann, Florian Kitz, and Chuixiang Yi
Biogeosciences, 20, 589–596, https://doi.org/10.5194/bg-20-589-2023, https://doi.org/10.5194/bg-20-589-2023, 2023
Short summary
Short summary
The trace gas carbonyl sulfide (COS), which is taken up by plant leaves in a process very similar to photosynthesis, is thought to be a promising proxy for the gross uptake of carbon dioxide by plants. Here we propose a new framework for estimating a key metric to that end, the so-called leaf relative uptake rate. The values we deduce by applying principles of plant optimality are considerably lower than published values and may help reduce the uncertainty of the global COS budget.
Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
Short summary
Short summary
We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463, https://doi.org/10.5194/bg-19-2427-2022, https://doi.org/10.5194/bg-19-2427-2022, 2022
Short summary
Short summary
A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Lisa Kaser, Arianna Peron, Martin Graus, Marcus Striednig, Georg Wohlfahrt, Stanislav Juráň, and Thomas Karl
Atmos. Chem. Phys., 22, 5603–5618, https://doi.org/10.5194/acp-22-5603-2022, https://doi.org/10.5194/acp-22-5603-2022, 2022
Short summary
Short summary
Biogenic volatile organic compounds (e.g., terpenoids) play an essential role in atmospheric chemistry. Urban greening activities need to consider the ozone- and aerosol-forming potential of these compounds released from vegetation. NMVOC emissions in urban environments are complex, and the biogenic component remains poorly quantified. For summer conditions biogenic emissions dominate terpene emissions and heat waves can significantly modulate urban biogenic terpenoid emissions.
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
Short summary
Short summary
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.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
Short summary
Short summary
Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
Short summary
Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Arianna Peron, Lisa Kaser, Anne Charlott Fitzky, Martin Graus, Heidi Halbwirth, Jürgen Greiner, Georg Wohlfahrt, Boris Rewald, Hans Sandén, and Thomas Karl
Biogeosciences, 18, 535–556, https://doi.org/10.5194/bg-18-535-2021, https://doi.org/10.5194/bg-18-535-2021, 2021
Short summary
Short summary
Drought events are expected to become more frequent with climate change. Along with these events atmospheric ozone is also expected to increase. Both can stress plants. Here we investigate to what extent these factors modulate the emission of volatile organic compounds (VOCs) from oak plants. We find an antagonistic effect between drought stress and ozone, impacting the emission of different BVOCs, which is indirectly controlled by stomatal opening, allowing plants to control their water budget.
Lilian Schuster, Fabien Maussion, Lukas Langhamer, and Gina E. Moseley
Weather Clim. Dynam., 2, 1–17, https://doi.org/10.5194/wcd-2-1-2021, https://doi.org/10.5194/wcd-2-1-2021, 2021
Short summary
Short summary
Precipitation and moisture sources over an arid region in northeast Greenland are investigated from 1979 to 2017 by a Lagrangian moisture source diagnostic driven by reanalysis data. Dominant winter moisture sources are the North Atlantic above 45° N. In summer local and north Eurasian continental sources dominate. In positive phases of the North Atlantic Oscillation, evaporation and moisture transport from the Norwegian Sea are stronger, resulting in more precipitation.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
Short summary
Short summary
We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Felix M. Spielmann, Albin Hammerle, Florian Kitz, Katharina Gerdel, and Georg Wohlfahrt
Biogeosciences, 17, 4281–4295, https://doi.org/10.5194/bg-17-4281-2020, https://doi.org/10.5194/bg-17-4281-2020, 2020
Short summary
Short summary
Carbonyl sulfide (COS) can be used as a proxy for plant photosynthesis on an ecosystem scale. However, the relationships between COS and CO2 fluxes and their dependence on daily to seasonal changes in environmental drivers are still poorly understood. We examined COS and CO2 ecosystem fluxes above an agriculturally used mountain grassland for 6 months. Harvesting of the grassland disturbed the otherwise stable COS-to-CO2 uptake ratio. We even found the canopy to release COS during those times.
Cited articles
Aide, T. M., Grau, H. R., Graesser, J., Andrade-Nuñez, M. J., Aráoz, E., Barros, A. P., Campos-Cerqueira, M., Chacon-Moreno, E., Cuesta, F., Espinoza, R., Peralvo, M., Polk, M. H., Rueda, X., Sanchez, A., Young, K. R., Zarbá, L., and Zimmerer, K. S.:
Woody vegetation dynamics in the tropical and subtropical Andes from 2001 to 2014: Satellite image interpretation and expert validation, Glob. Change Biol., 25, 2112–2126, https://doi.org/10.1111/gcb.14618, 2019. a
al Fahad, A., Burls, N. J., and Strasberg, Z.:
How will Southern Hemisphere subtropical anticyclones respond to global warming? Mechanisms and seasonality in CMIP5 and CMIP6 model projections, Clim. Dynam., 55, 703–718, https://doi.org/10.1007/s00382-020-05290-7, 2020. a
Anyamba, A. and Tucker, C. J.:
Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003, J. Arid Environ., 63, 596–614, https://doi.org/10.1016/j.jaridenv.2005.03.007, 2005. a
Arias, P. A., Garreaud, R., Poveda, G., Espinoza, J. C., Molina-Carpio, J., Masiokas, M., Viale, M., Scaff, L., and van Oevelen, P. J.:
Hydroclimate of the Andes Part II: Hydroclimate Variability and Sub-Continental Patterns, Front. Earth Sci., 8, p. 666, https://doi.org/10.3389/feart.2020.505467, 2021. a
Atzberger, C. and Eilers, P. H.:
A time series for monitoring vegetation activity and phenology at 10-daily time steps covering large parts of South America, Int. J. Digit. Earth, 4, 365–386, https://doi.org/10.1080/17538947.2010.505664, 2011. a
Baraer, M., Mark, B. G., Mckenzie, J. M., Condom, T., Bury, J., Huh, K. I., Portocarrero, C., Gómez, J., and Rathay, S.:
Glacier recession and water resources in Peru's Cordillera Blanca, J. Glaciol., 58, 134–150, https://doi.org/10.3189/2012JoG11J186, 2012. a
Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rödenbeck, C., Arain, M. A., Baldocchi, D., Bonan, G. B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K. W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F. I., and Papale, D.:
Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate, Science, 329, 834–838, https://doi.org/10.1126/science.1184984, 2010. a
Belda, S., Pipia, L., Morcillo-Pallarés, P., Rivera-Caicedo, J. P., Amin, E., De Grave, C., and Verrelst, J.:
DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection, Environ. Modell. Softw., 127, 104666, https://doi.org/10.1016/j.envsoft.2020.104666, 2020. a, b, c
Bonan, G. B. (2008). Forests and climate change: forcings, feedbacks, and the climate benefits of forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008. a
Bookhagen, B. and Strecker, M. R.:
Orographic barriers, high-resolution TRMM rainfall, and relief variations along the eastern Andes, Geophys. Res. Lett., 35, 6403, https://doi.org/10.1029/2007GL032011, 2008. a
Brandt, M., Hiernaux, P., Rasmussen, K., Tucker, C. J., Wigneron, J. P., Diouf, A. A., Herrmann, S. M., Zhang, W., Kergoat, L., Mbow, C., Abel, C., Auda, Y., and Fensholt, R.:
Changes in rainfall distribution promote woody foliage production in the Sahel, Communications Biology, 2, 1–10, https://doi.org/10.1038/s42003-019-0383-9, 2019. a
Bury, J., Mark, B. G., Carey, M., Young, K. R., McKenzie, J. M., Baraer, M., French, A., and Polk, M. H.:
New Geographies of Water and Climate Change in Peru: Coupled Natural and Social Transformations in the Santa River Watershed, Ann. Assoc. Am. Geogr., 103, 363–374, https://doi.org/10.1080/00045608.2013.754665, 2013. a, b
Buytaert, W. and De Bièvre, B.:
Water for cities: The impact of climate change and demographic growth in the tropical Andes, Water Resour. Res., 48, 8503, https://doi.org/10.1029/2011WR011755, 2012. a
Camberlin, P., Martiny, N., Philippon, N., and Richard, Y.:
Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa, Remote Sens. Environ., 106, 199–216, https://doi.org/10.1016/j.rse.2006.08.009, 2007. a
Campozano, L., Robaina, L., and Samaniego, E.:
The Pacific decadal oscillation modulates the relation of ENSO with the rainfall variability in coast of Ecuador, Int. J. Climatol., 40, 5801–5812, https://doi.org/10.1002/joc.6525, 2020. a
Carey, M., Baraer, M., Mark, B. G., French, A., Bury, J., Young, K. R., and McKenzie, J. M.:
Toward hydro-social modeling: Merging human variables and the social sciences with climate-glacier runoff models (Santa River, Peru), J. Hydrol., 518, 60–70, https://doi.org/10.1016/j.jhydrol.2013.11.006, 2014. a
Condom, T., Escobar, M., Purkey, D., Pouget, J. C., Suarez, W., Ramos, C., Apaestegui, J., Tacsi, A., and Gomez, J.:
Simulating the implications of glaciers' retreat for water management: a case study in the Rio Santa basin, Peru, Water Int., 37, 442–459, https://doi.org/10.1080/02508060.2012.706773, 2012. a
Crabtree, J.:
The impact of neo-liberal economics on Peruvian peasant agriculture in the 1990s, J. Peasant Stud., 29, 131–161, https://doi.org/10.1080/03066150412331311049, 2002. a
Dardel, C., Kergoat, L., Hiernaux, P., Mougin, E., Grippa, M., and Tucker, C. J.:
Re-greening Sahel: 30 years of remote sensing data and field observations (Mali, Niger), Remote Sens. Environ., 140, 350–364, https://doi.org/10.1016/j.rse.2013.09.011, 2014. a
de Jong, R., Schaepman, M. E., Furrer, R., de Bruin, S., and Verburg, P. H.:
Spatial relationship between climatologies and changes in global vegetation activity, Glob. Change Biol., 19, 1953–1964, https://doi.org/10.1111/gcb.12193, 2013. a
Didan, K.:
MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250 m SIN grid V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MOD13Q1.006, 2015a. a
Didan, K.:
MYD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250 m SIN grid V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MYD13Q1.006, 2015b. a
Donohue, R. J., Mcvicar, T. R., and Roderick, M. L.:
Climate-related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006, Glob. Change Biol., 15, 1025–1039, https://doi.org/10.1111/j.1365-2486.2008.01746.x, 2009. a
Eklundh, L. and Olsson, L.:
Vegetation index trends for the African Sahel 1982–1999, Geophys. Res. Lett., 30, 1430-1433, https://doi.org/10.1029/2002GL016772, 2003. a
Espinoza, J. C., Chavez, S., Ronchail, J., Junquas, C., Takahashi, K., and Lavado, W.:
Rainfall hotspots over the southern tropical Andes: Spatial distribution, rainfall intensity, and relations with large-scale atmospheric circulation, Water Resour. Res., 51, 3459–3475, https://doi.org/10.1002/2014WR016273, 2015. a
Fensholt, R., Langanke, T., Rasmussen, K., Reenberg, A., Prince, S. D., Tucker, C., Scholes, R. J., Le, Q. B., Bondeau, A., Eastman, R., Epstein, H., Gaughan, A. E., Hellden, U., Mbow, C., Olsson, L., Paruelo, J., Schweitzer, C., Seaquist, J., and Wessels, K.:
Greenness in semi-arid areas across the globe 1981–2007 – an Earth Observing Satellite based analysis of trends and drivers, Remote Sens. Environ., 121, 144–158, https://doi.org/10.1016/j.rse.2012.01.017, 2012. a, b
Forzieri, G., Feyen, L., Cescatti, A., and Vivoni, E. R.:
Spatial and temporal variations in ecosystem response to monsoon precipitation variability in southwestern North America, J. Geophys. Res.-Biogeo., 119, 1999–2017, https://doi.org/10.1002/2014JG002710, 2014. a
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., and Michaelsen, J.:
The climate hazards infrared precipitation with stations – A new environmental record for monitoring extremes, Scientific Data, 2, 1–21, https://doi.org/10.1038/sdata.2015.66, 2015. a
Garreaud, R. D.:
The Andes climate and weather, Adv. Geosci., 22, 3–11, https://doi.org/10.5194/adgeo-22-3-2009, 2009. a, b
Gray, S. B., Dermody, O., Klein, S. P., Locke, A. M., McGrath, J. M., Paul, R. E., Rosenthal, D. M., Ruiz-Vera, U. M., Siebers, M. H., Strellner, R., Ainsworth, E. A., Bernacchi, C. J., Long, S. P., Ort, D. R., and Leakey, A. D.:
Intensifying drought eliminates the expected benefits of elevated carbon dioxide for soybean, Nature Plants, 2, 1–8, https://doi.org/10.1038/nplants.2016.132, 2016. a
Gurgiser, W., Juen, I., Singer, K., Neuburger, M., Schauwecker, S., Hofer, M., and Kaser, G.:
Comparing peasants' perceptions of precipitation change with precipitation records in the tropical Callejón de Huaylas, Peru, Earth Syst. Dynam., 7, 499–515, https://doi.org/10.5194/esd-7-499-2016, 2016. a, b, c, d, e
Herrmann, S. M., Anyamba, A., and Tucker, C. J.:
Recent trends in vegetation dynamics in the African Sahel and their relationship to climate, Global Environ. Chang., 15, 394–404, https://doi.org/10.1016/j.gloenvcha.2005.08.004, 2005. a
Hickler, T., Eklundh, L., Seaquist, J. W., Smith, B., Ardö, J., Olsson, L., Sykes, M. T., and Sjöström, M.:
Precipitation controls Sahel greening trend, Geophys. Res. Lett., 32, L21415, https://doi.org/10.1029/2005GL024370, 2005. a
Huber, S., Fensholt, R., and Rasmussen, K.:
Water availability as the driver of vegetation dynamics in the African Sahel from 1982 to 2007, Global Planet. Change, 76, 186–195, https://doi.org/10.1016/j.gloplacha.2011.01.006, 2011. a
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG Final Precipitation L3 1 month 0.1 degree × 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], last access: 8 March 2021, https://doi.org/10.5067/GPM/IMERG/3B-MONTH/06, 2019. a
Huxman, T. E., Smith, M. D., Fay, P. A., Knapp, A. K., Shaw, M. R., Lolk, M. E., Smith, S. D., Tissue, D. T., Zak, J. C., Weltzin, J. F., Pockman, W. T., Sala, O. E., Haddad, B. M., Harte, J., Koch, G. W., Schwinning, S., Small, E. E., and Williams, D. G.:
Convergence across biomes to a common rain-use efficiency, Nature, 429, 651–654, https://doi.org/10.1038/nature02561, 2004. a
Karnieli, A., Agam, N., Pinker, R. T., Anderson, M., Imhoff, M. L., Gutman, G. G., Panov, N., and Goldberg, A.:
Use of NDVI and land surface temperature for drought assessment: Merits and limitations, J. Climate, 23, 618–633, https://doi.org/10.1175/2009JCLI2900.1, 2010. a
Kaser, G., Juen, I., Georges, C., Gómez, J., and Tamayo, W.:
The impact of glaciers on the runoff and the reconstruction of mass balance history from hydrological data in the tropical Cordillera Bianca, Perú, J. Hydrol., 282, 130–144, https://doi.org/10.1016/S0022-1694(03)00259-2, 2003. a, b
Killeen, T. J., Douglas, M., Consiglio, T., Jørgensen, P. M., and Mejia, J.:
Dry spots and wet spots in the Andean hotspot, J. Biogeogr., 34, 1357–1373, https://doi.org/10.1111/j.1365-2699.2006.01682.x, 2007. a
Knapp, A. K. and Smith, M. D.:
Variation among biomes in temporal dynamics of aboveground primary production, Science, 291, 481–484, https://doi.org/10.1126/science.291.5503.481, 2001. a
Kogan, F. N.:
Satellite-observed sensitivity of world land ecosystems to El Niño/La Niña, Remote Sens. Environ., 74, 445–462, https://doi.org/10.1016/S0034-4257(00)00137-1, 2000. a
Mark, B. G., Bury, J., McKenzie, J. M., French, A., and Baraer, M.:
Climate Change and Tropical Andean Glacier Recession: Evaluating Hydrologic Changes and Livelihood Vulnerability in the Cordillera Blanca, Peru, Ann. Assoc. Am. Geogr., 100, 794–805, https://doi.org/10.1080/00045608.2010.497369, 2010. a
Mateo-Sanchis, A., Muñoz-Marí, J., Campos-Taberner, M., García-Haro, J., and Camps-Valls, G.: Gap filling of biophysical parameter time series with multi-output Gaussian Processes, in: Proceedings of the IGARSS 2018–2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22–27 July 2018, 4039–4042, https://doi.org/10.1109/IGARSS.2018.8519254, 2018. a
Maussion, F., Gurgiser, W., Großhauser, M., Kaser, G., and Marzeion, B.:
ENSO influence on surface energy and mass balance at Shallap Glacier, Cordillera Blanca, Peru, The Cryosphere, 9, 1663–1683, https://doi.org/10.5194/tc-9-1663-2015, 2015. a, b, c
Miralles, D. G., Van Den Berg, M. J., Gash, J. H., Parinussa, R. M., De Jeu, R. A., Beck, H. E., Holmes, T. R., Jiménez, C., Verhoest, N. E., Dorigo, W. A., Teuling, A. J., and Johannes Dolman, A.:
El Niño-La Niña cycle and recent trends in continental evaporation, Nat. Clim. Change, 4, 122–126, https://doi.org/10.1038/nclimate2068, 2014. a
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker, C. J., Myneni, R. B., and Running, S. W.:
Climate-driven increases in global terrestrial net primary production from 1982 to 1999, Science, 300, 1560–1563, https://doi.org/10.1126/science.1082750, 2003. a
O'Neill, P., Chan, S., Njoku, E., Jackson, T., Bindlish, R., Chaubell, J., and Colliander, A.:
SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture, Version 5, National Snow and Ice Data Center (subset of Rio Santa basin), https://doi.org/10.5067/4DQ54OUIJ9DL, 2021. a
Pipia, L., Muñoz-Marí, J., Amin, E., Belda, S., Camps-Valls, G., and Verrelst, J.:
Fusing optical and SAR time series for LAI gap fillingwith multioutput Gaussian processes, Remote Sens. Environ., 235, 111452, https://doi.org/10.1016/j.rse.2019.111452, 2019. a
Polk, M. H., Mishra, N. B., Young, K. R., and Mainali, K.:
Greening and browning trends across Peru's diverse environments, Remote Sens.-Basel, 12, 2418, https://doi.org/10.3390/rs12152418, 2020. a
Potter, C. S. and Brooks, V.:
Global analysis of empirical relations between annual climate and seasonality of NDVI, Int. J. Remote Sens., 19, 2921–2948, https://doi.org/10.1080/014311698214352, 1998. a
Rabatel, A., Francou, B., Soruco, A., Gomez, J., Cáceres, B., Ceballos, J. L., Basantes, R., Vuille, M., Sicart, J.-E., Huggel, C., Scheel, M., Lejeune, Y., Arnaud, Y., Collet, M., Condom, T., Consoli, G., Favier, V., Jomelli, V., Galarraga, R., Ginot, P., Maisincho, L., Mendoza, J., Ménégoz, M., Ramirez, E., Ribstein, P., Suarez, W., Villacis, M., and Wagnon, P.:
Current state of glaciers in the tropical Andes: a multi-century perspective on glacier evolution and climate change, The Cryosphere, 7, 81–102, https://doi.org/10.5194/tc-7-81-2013, 2013. a
Rasmussen, C. E.:
Gaussian Processes in machine learning, Lect. Note. Comput. Sc., 3176, 63–71, https://doi.org/10.1007/978-3-540-28650-9_4, 2004. a
Rau, P., Bourrel, L., Labat, D., Melo, P., Dewitte, B., Frappart, F., Lavado, W., and Felipe, O.:
Regionalization of rainfall over the Peruvian Pacific slope and coast, Int. J. Climatol., 37, 143–158, https://doi.org/10.1002/joc.4693, 2017. a, b
Reich, P. B., Hobbie, S. E., and Lee, T. D.:
Plant growth enhancement by elevated CO2 eliminated by joint water and nitrogen limitation, Nat. Geosci., 7, 920–924, https://doi.org/10.1038/ngeo2284, 2014. a
Richard, Y. and Poccard, I.:
A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa, Int. J. Remote Sens., 19, 2907–2920, https://doi.org/10.1080/014311698214343, 1998. a
Richardson, A. D., Keenan, T. F., Migliavacca, M., Ryu, Y., Sonnentag, O., and Toomey, M.: Climate change, phenology, and phenological control of vegetation feedbacks to the climate system, Agr. Forest Meteorol., 169, 156–173, https://doi.org/10.1016/j.agrformet.2012.09.012, 2013. a
Richardson, A. D., Hufkens, K., Milliman, T., Aubrecht, D. M., Furze, M. E., Seyednasrollah, B., Krassovski, M. B., Latimer, J. M., Nettles, W. R., Heiderman, R. R., Warren, J. M., and Hanson, P. J.:
Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures, Nature, 560, 368–371, https://doi.org/10.1038/s41586-018-0399-1, 2018. a
Rivera, J. A., Marianetti, G., and Hinrichs, S.:
Validation of CHIRPS precipitation dataset along the Central Andes of Argentina, Atmos. Res., 213, 437–449, https://doi.org/10.1016/j.atmosres.2018.06.023, 2018. a
Rodriguez-Iturbe, I., D'Odorico, P., Porporato, A., and Ridolfi, L.:
On the spatial and temporal links between vegetation, climate, and soil moisture, Water Resour. Res., 35, 3709–3722, https://doi.org/10.1029/1999WR900255, 1999. a
Rouse, J. W. J., Haas, R. H., Schell, J. A., and Deering, D. W.: Monitoring vegetation systems in the Great Plains with ERTS, in: Third ERTS Symposium, NASA SP-351, Washington DC, 10 December 1973, 309–317, 1974. a
Sanabria, J., Bourrel, L., Dewitte, B., Frappart, F., Rau, P., Solis, O., and Labat, D.:
Rainfall along the coast of Peru during strong El Niño events, Int. J. Climatol., 38, 1737–1747, https://doi.org/10.1002/joc.5292, 2018. a
Sanabria, J., Carrillo, C. M., and Labat, D.:
Unprecedented Rainfall and Moisture Patterns during El Niño 2016 in the Eastern Pacific and Tropical Andes: Northern Perú and Ecuador, Atmosphere, 10, 768, https://doi.org/10.3390/atmos10120768, 2019. a
Schauwecker, S., Rohrer, M., Acuña, D., Cochachin, A., Dávila, L., Frey, H., Giráldez, C., Gómez, J., Huggel, C., Jacques-Coper, M., Loarte, E., Salzmann, N., and Vuille, M.:
Climate trends and glacier retreat in the Cordillera Blanca, Peru, revisited, Global Planet. Change, 119, 85–97, https://doi.org/10.1016/j.gloplacha.2014.05.005, 2014. a, b, c, d
Schwinning, S., Sala, O. E., Loik, M. E., and Ehleringer, J. R.:
Thresholds, memory, and seasonality: understanding pulse dynamics in arid/semi-arid ecosystems, Oecologia, 141, 191–193, https://doi.org/10.1007/s00442-004-1683-3, 2004. a
Segura, H., Junquas, C., Espinoza, J. C., Vuille, M., Jauregui, Y. R., Rabatel, A., Condom, T., and Lebel, T.:
New insights into the rainfall variability in the tropical Andes on seasonal and interannual time scales, Clim. Dynam., 53, 405–426, https://doi.org/10.1007/s00382-018-4590-8, 2019. a, b, c
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.:
Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015. a
Spracklen, D. V., Arnold, S. R., and Taylor, C. M.:
Observations of increased tropical rainfall preceded by air passage over forests, Nature, 489, 282–285, https://doi.org/10.1038/nature11390, 2012. a
Svoray, T. and Karnieli, A.:
Rainfall, topography and primary production relationships in a semiarid ecosystem, Ecohydrology, 4, 56–66, https://doi.org/10.1002/eco.123, 2011. a
Torres-Batlló, J. and Martí-Cardona, B.:
Precipitation trends over the southern Andean Altiplano from 1981 to 2018, J. Hydrol., 590, 125485, https://doi.org/10.1016/j.jhydrol.2020.125485, 2020. a, b
Tote, C., Beringhs, K., Swinnen, E., and Govers, G.:
Monitoring environmental change in the Andes based on SPOT-VGT and NOAA-AVHRR time series analysis, in: 2011 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, Multi-Temp 2011 – Proceedings, Trento, Italy, 12–14 July 2011, 268–272, 2011. a
Trenberth, K. E.:
The definition of El Nino, B. Am. Meteorol. Soc., 78, 2771–2778, https://doi.org/10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2, 1997. a, b
Urrutia, R. and Vuille, M.: Climate change projections for the tropical Andes using a regional climate model: Temperature and precipitation simulations for the end of the 21st century, J. Geophys. Res., 114, D02108, https://doi.org/10.1029/2008JD011021, 2009. a
USGS EROS Archive: Digital Elevation – Shuttle Radar Topography Mission (SRTM) 1 Arc-second Global, USGS EROS Archive [data set], https://www.usgs.gov/centers/eros, last access: January 2021. a
Verstraete, M. M., Gobron, N., Aussedat, O., Robustelli, M., Pinty, B., Widlowski, J. L., and Taberner, M.:
An automatic procedure to identify key vegetation phenology events using the JRC-FAPAR products, Adv. Space Res., 41, 1773–1783, https://doi.org/10.1016/j.asr.2007.05.066, 2008. a
Vrieling, A., de Leeuw, J., and Said, M.:
Length of Growing Period over Africa: Variability and Trends from 30 Years of NDVI Time Series, Remote Sens.-Basel, 5, 982–1000, https://doi.org/10.3390/rs5020982, 2013.
a
Vuille, M., Kaser, G., and Juen, I.:
Glacier mass balance variability in the Cordillera Blanca, Peru and its relationship with climate and the large-scale circulation, Global Planet. Change, 62, 14–28, https://doi.org/10.1016/j.gloplacha.2007.11.003, 2008. a, b
Whittaker, E. T.:
On a new method of graduation, P. Edinburgh Math. Soc., 41, 63–75, https://doi.org/10.1017/s0013091500077853, 1922. a
Wu, D., Zhao, X., Liang, S., Zhou, T., Huang, K., Tang, B., and Zhao, W.:
Time-lag effects of global vegetation responses to climate change, Glob. Change Biol., 21, 3520–3531, https://doi.org/10.1111/gcb.12945, 2015. a
Xu, C., Liu, H., Williams, A. P., Yin, Y., and Wu, X.:
Trends toward an earlier peak of the growing season in Northern Hemisphere mid-latitudes, Glob. Change Biol., 22, 2852–2860, https://doi.org/10.1111/gcb.13224, 2016. a
Yang, J., Tian, H., Pan, S., Chen, G., Zhang, B., and Dangal, S.:
Amazon drought and forest response: Largely reduced forest photosynthesis but slightly increased canopy greenness during the extreme drought of 2015/2016, Glob. Change Biol., 24, 1919–1934, https://doi.org/10.1111/gcb.14056, 2018. a
Young, K. R., Ponette-González, A. G., Polk, M. H., and Lipton, J. K.:
Snowlines and Treelines in the Tropical Andes, Ann. Am. Assoc. Geogr., 107, 429–440, https://doi.org/10.1080/24694452.2016.1235479, 2017. a
Zhang, X.:
Monitoring the response of vegetation phenology to precipitation in Africa by coupling MODIS and TRMM instruments, J. Geophys. Res., 110, D12103, https://doi.org/10.1029/2004JD005263, 2005. a
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais, P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E., Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., Pan, Y., Peng, S., Peuelas, J., Poulter, B., Pugh, T. A., Stocker, B. D., Viovy, N., Wang, X., Wang, Y., Xiao, Z., Yang, H., Zaehle, S., and Zeng, N.:
Greening of the Earth and its drivers, Nat. Clim. Change, 6, 791–795, https://doi.org/10.1038/nclimate3004, 2016. a
Short summary
To date, farmers' perceptions of hydrological changes do not match analysis of meteorological data. In contrast to rainfall data, we find greening of vegetation, indicating increased water availability in the past decades. The start of the season is highly variable, making farmers' perceptions comprehensible. We show that the El Niño–Southern Oscillation has complex effects on vegetation seasonality but does not drive the greening we observe. Improved onset forecasts could help local farmers.
To date, farmers' perceptions of hydrological changes do not match analysis of meteorological...
Altmetrics
Final-revised paper
Preprint