Articles | Volume 25, issue 4
https://doi.org/10.5194/hess-25-2279-2021
© Author(s) 2021. 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-25-2279-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Apr 2021
Research article |
| 28 Apr 2021
| 28 Apr 2021
Evapotranspiration in the Amazon: spatial patterns, seasonality, and recent trends in observations, reanalysis, and climate models
Jessica C. A. Baker
CORRESPONDING AUTHOR
School of Earth and Environment, University of Leeds, Leeds, UK
Luis Garcia-Carreras
Department of Earth and Environmental Sciences, University of Manchester, Manchester, UK
Manuel Gloor
School of Geography, University of Leeds, Leeds, UK
John H. Marsham
School of Earth and Environment, University of Leeds, Leeds, UK
Wolfgang Buermann
Institut für Geographie, Universität Augsburg, 86135 Augsburg, Germany
Humberto R. da Rocha
Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
Antonio D. Nobre
Earth System Science Center, INPE, São José dos Campos, São Paulo, Brazil
Alessandro Carioca de Araujo
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA),
Belém, Pará, Brazil
Dominick V. Spracklen
School of Earth and Environment, University of Leeds, Leeds, UK
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EGUsphere, https://doi.org/10.5194/egusphere-2025-4278, https://doi.org/10.5194/egusphere-2025-4278, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We studied how airborne particles like smoke affect a pristine Amazon rainforest. Using long-term data, we found that high aerosol pollution reduces the heat and water vapor released by the forest, causing a cooling effect. Surprisingly, it also substantially boosts the forest's carbon dioxide absorption by scattering sunlight, which helps plants with photosynthesis. This shows that aerosols significantly alter the Amazon's microclimate and its crucial role in the global carbon and water cycles.
Rafaela Cruz Alves Alberti, Thomas Lauvaux, Angel Liduvino Vara-Vela, Ricard Segura Barrero, Christoffer Karoff, Maria de Fátima Andrade, Márcia Talita Amorim Marques, Noelia Rojas Benavente, Osvaldo Machado Rodrigues Cabral, Humberto Ribeiro da Rocha, and Rita Yuri Ynoue
Atmos. Chem. Phys., 25, 9803–9829, https://doi.org/10.5194/acp-25-9803-2025, https://doi.org/10.5194/acp-25-9803-2025, 2025
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This study addresses uncertainties in atmospheric models by analyzing CO2 dynamics in a complex urban environment characterized by a dense population and tropical vegetation. High-accuracy sensors were deployed, and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was utilized to simulate CO2 transport, capturing variations and assessing contributions from both anthropogenic and biogenic sources.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid T. Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
Atmos. Chem. Phys., 25, 6219–6255, https://doi.org/10.5194/acp-25-6219-2025, https://doi.org/10.5194/acp-25-6219-2025, 2025
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This study uses dry CO2 mole fractions from the Amazon Tall Tower Observatory together with airborne profiles to estimate net carbon exchange in tropical South America. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. Finally, to further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon–Andes foothills.
Carlos A. Sierra, Ingrid Chanca, Meinrat Andreae, Alessandro Carioca de Araújo, Hella van Asperen, Lars Borchardt, Santiago Botía, Luiz Antonio Candido, Caio S. C. Correa, Cléo Quaresma Dias-Junior, Markus Eritt, Annica Fröhlich, Luciana V. Gatti, Marcus Guderle, Samuel Hammer, Martin Heimann, Viviana Horna, Armin Jordan, Steffen Knabe, Richard Kneißl, Jost Valentin Lavric, Ingeborg Levin, Kita Macario, Juliana Menger, Heiko Moossen, Carlos Alberto Quesada, Michael Rothe, Christian Rödenbeck, Yago Santos, Axel Steinhof, Bruno Takeshi, Susan Trumbore, and Sönke Zaehle
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-151, https://doi.org/10.5194/essd-2025-151, 2025
Revised manuscript under review for ESSD
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We present here a unique dataset of atmospheric observations of greenhouse gases and isotopes that provide key information on land-atmosphere interactions for the Amazon forests of central Brazil. The data show a relatively large level of variability, but also important trends in greenhouse gases, and signals from fires as well as seasonal biological activity.
Jamie Robert Cameron Brown, Ross Woods, Humberto Ribeiro da Rocha, Debora Regina Roberti, and Rafael Rosolem
EGUsphere, https://doi.org/10.5194/egusphere-2025-883, https://doi.org/10.5194/egusphere-2025-883, 2025
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In recent years, global and regional weather datasets have emerged, but validation with real-world data is crucial, especially in diverse regions like Brazil. This study compares seven key weather variables from five datasets with measurements from 11 sites across Brazil’s main biomes. Results show varying performance across variables and timescales, with one reanalysis product outperforming others overall. Findings suggest it may be a strong choice for multi-variable studies in Brazil.
Ingrid Chanca, Ingeborg Levin, Susan Trumbore, Kita Macario, Jost Lavric, Carlos Alberto Quesada, Alessandro Carioca de Araújo, Cléo Quaresma Dias Júnior, Hella van Asperen, Samuel Hammer, and Carlos A. Sierra
Biogeosciences, 22, 455–472, https://doi.org/10.5194/bg-22-455-2025, https://doi.org/10.5194/bg-22-455-2025, 2025
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Assessing the net carbon (C) budget of the Amazon entails considering the magnitude and timing of C absorption and losses through respiration (transit time of C). Radiocarbon-based estimates of the transit time of C in the Amazon Tall Tower Observatory (ATTO) suggest a change in the transit time from 6 ± 2 years and 18 ± 4 years within 2 years (October 2019 and December 2021, respectively). This variability indicates that only a fraction of newly fixed C can be stored for decades or longer.
Akima Ringsdorf, Achim Edtbauer, Bruna Holanda, Christopher Poehlker, Marta O. Sá, Alessandro Araújo, Jürgen Kesselmeier, Jos Lelieveld, and Jonathan Williams
Atmos. Chem. Phys., 24, 11883–11910, https://doi.org/10.5194/acp-24-11883-2024, https://doi.org/10.5194/acp-24-11883-2024, 2024
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We show the average height distribution of separately observed aldehydes and ketones over a day and discuss their rainforest-specific sources and sinks as well as their seasonal changes above the Amazon. Ketones have much longer atmospheric lifetimes than aldehydes and thus different implications for atmospheric chemistry. However, they are commonly observed together, which we overcome by measuring with a NO+ chemical ionization mass spectrometer for the first time in the Amazon rainforest.
Luiz A. T. Machado, Jürgen Kesselmeier, Santiago Botía, Hella van Asperen, Meinrat O. Andreae, Alessandro C. de Araújo, Paulo Artaxo, Achim Edtbauer, Rosaria R. Ferreira, Marco A. Franco, Hartwig Harder, Sam P. Jones, Cléo Q. Dias-Júnior, Guido G. Haytzmann, Carlos A. Quesada, Shujiro Komiya, Jost Lavric, Jos Lelieveld, Ingeborg Levin, Anke Nölscher, Eva Pfannerstill, Mira L. Pöhlker, Ulrich Pöschl, Akima Ringsdorf, Luciana Rizzo, Ana M. Yáñez-Serrano, Susan Trumbore, Wanda I. D. Valenti, Jordi Vila-Guerau de Arellano, David Walter, Jonathan Williams, Stefan Wolff, and Christopher Pöhlker
Atmos. Chem. Phys., 24, 8893–8910, https://doi.org/10.5194/acp-24-8893-2024, https://doi.org/10.5194/acp-24-8893-2024, 2024
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Composite analysis of gas concentration before and after rainfall, during the day and night, gives insight into the complex relationship between trace gas variability and precipitation. The analysis helps us to understand the sources and sinks of trace gases within a forest ecosystem. It elucidates processes that are not discernible under undisturbed conditions and contributes to a deeper understanding of the trace gas life cycle and its intricate interactions with cloud dynamics in the Amazon.
Hella van Asperen, Thorsten Warneke, Alessandro Carioca de Araújo, Bruce Forsberg, Sávio José Filgueiras Ferreira, Thomas Röckmann, Carina van der Veen, Sipko Bulthuis, Leonardo Ramos de Oliveira, Thiago de Lima Xavier, Jailson da Mata, Marta de Oliveira Sá, Paulo Ricardo Teixeira, Julie Andrews de França e Silva, Susan Trumbore, and Justus Notholt
Biogeosciences, 21, 3183–3199, https://doi.org/10.5194/bg-21-3183-2024, https://doi.org/10.5194/bg-21-3183-2024, 2024
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Carbon monoxide (CO) is regarded as an important indirect greenhouse gas. Soils can emit and take up CO, but, until now, uncertainty remains as to which process dominates in tropical rainforests. We present the first soil CO flux measurements from a tropical rainforest. Based on our observations, we report that tropical rainforest soils are a net source of CO. In addition, we show that valley streams and inundated areas are likely additional hot spots of CO in the ecosystem.
Matthias Fischer, Peter Knippertz, Roderick van der Linden, Alexander Lemburg, Gregor Pante, Carsten Proppe, and John H. Marsham
Weather Clim. Dynam., 5, 511–536, https://doi.org/10.5194/wcd-5-511-2024, https://doi.org/10.5194/wcd-5-511-2024, 2024
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Our research enhances the understanding of the complex dynamics within the West African monsoon system by analyzing the impact of specific model parameters on its characteristics. Employing surrogate models, we identified critical factors such as the entrainment rate and the fall velocity of ice. Precise definition of these parameters in weather models could improve forecast accuracy, thus enabling better strategies to manage and reduce the impact of weather events.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
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We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Joseph Smith, Cathryn Birch, John Marsham, Simon Peatman, Massimo Bollasina, and George Pankiewicz
Nat. Hazards Earth Syst. Sci., 24, 567–582, https://doi.org/10.5194/nhess-24-567-2024, https://doi.org/10.5194/nhess-24-567-2024, 2024
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Nowcasting uses observations to make predictions of the atmosphere on short timescales and is particularly applicable to the Maritime Continent, where storms rapidly develop and cause natural disasters. This paper evaluates probabilistic and deterministic satellite nowcasting algorithms over the Maritime Continent. We show that the probabilistic approach is most skilful at small scales (~ 60 km), whereas the deterministic approach is most skilful at larger scales (~ 200 km).
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
Amelie U. Schmitt, Felix Ament, Alessandro C. de Araújo, Marta Sá, and Paulo Teixeira
Atmos. Chem. Phys., 23, 9323–9346, https://doi.org/10.5194/acp-23-9323-2023, https://doi.org/10.5194/acp-23-9323-2023, 2023
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Tall vegetation in forests affects the exchange of heat and moisture between the atmosphere and the land surface. We compared measurements from the Amazon Tall Tower Observatory to results from a land surface model to identify model shortcomings. Our results suggest that soil temperatures in the model could be improved by incorporating a separate canopy layer which represents the heat storage within the forest.
Emily Dowd, Chris Wilson, Martyn P. Chipperfield, Emanuel Gloor, Alistair Manning, and Ruth Doherty
Atmos. Chem. Phys., 23, 7363–7382, https://doi.org/10.5194/acp-23-7363-2023, https://doi.org/10.5194/acp-23-7363-2023, 2023
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Surface observations of methane show that the seasonal cycle amplitude (SCA) of methane is decreasing in the northern high latitudes (NHLs) but increased globally (1995–2020). The NHL decrease is counterintuitive, as we expect the SCA to increase with increasing concentrations. We use a chemical transport model to investigate changes in SCA in the NHLs. We find well-mixed methane and changes in emissions from Canada, the Middle East, and Europe are the largest contributors to the SCA in NHLs.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
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We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Hannah Walker, Daniel Stone, Trevor Ingham, Sina Hackenberg, Danny Cryer, Shalini Punjabi, Katie Read, James Lee, Lisa Whalley, Dominick V. Spracklen, Lucy J. Carpenter, Steve R. Arnold, and Dwayne E. Heard
Atmos. Chem. Phys., 22, 5535–5557, https://doi.org/10.5194/acp-22-5535-2022, https://doi.org/10.5194/acp-22-5535-2022, 2022
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Glyoxal is a ubiquitous reactive organic compound in the atmosphere, which may form organic aerosol and impact the atmosphere's oxidising capacity. There are limited measurements of glyoxal's abundance in the remote marine atmosphere. We made new measurements of glyoxal using a highly sensitive technique over two 4-week periods in the tropical Atlantic atmosphere. We show that daytime measurements are mostly consistent with our chemical understanding but a potential missing source at night.
Marco A. Franco, Florian Ditas, Leslie A. Kremper, Luiz A. T. Machado, Meinrat O. Andreae, Alessandro Araújo, Henrique M. J. Barbosa, Joel F. de Brito, Samara Carbone, Bruna A. Holanda, Fernando G. Morais, Janaína P. Nascimento, Mira L. Pöhlker, Luciana V. Rizzo, Marta Sá, Jorge Saturno, David Walter, Stefan Wolff, Ulrich Pöschl, Paulo Artaxo, and Christopher Pöhlker
Atmos. Chem. Phys., 22, 3469–3492, https://doi.org/10.5194/acp-22-3469-2022, https://doi.org/10.5194/acp-22-3469-2022, 2022
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In Central Amazonia, new particle formation in the planetary boundary layer is rare. Instead, there is the appearance of sub-50 nm aerosols with diameters larger than about 20 nm that eventually grow to cloud condensation nuclei size range. Here, 254 growth events were characterized which have higher predominance in the wet season. About 70 % of them showed direct relation to convective downdrafts, while 30 % occurred partly under clear-sky conditions, evidencing still unknown particle sources.
Maria Prass, Meinrat O. Andreae, Alessandro C. de Araùjo, Paulo Artaxo, Florian Ditas, Wolfgang Elbert, Jan-David Förster, Marco Aurélio Franco, Isabella Hrabe de Angelis, Jürgen Kesselmeier, Thomas Klimach, Leslie Ann Kremper, Eckhard Thines, David Walter, Jens Weber, Bettina Weber, Bernhard M. Fuchs, Ulrich Pöschl, and Christopher Pöhlker
Biogeosciences, 18, 4873–4887, https://doi.org/10.5194/bg-18-4873-2021, https://doi.org/10.5194/bg-18-4873-2021, 2021
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Bioaerosols in the atmosphere over the Amazon rain forest were analyzed by molecular biological staining and microscopy. Eukaryotic, bacterial, and archaeal aerosols were quantified in time series and altitude profiles which exhibited clear differences in number concentrations and vertical distributions. Our results provide insights into the sources and dispersion of different Amazonian bioaerosol types as a basis for a better understanding of biosphere–atmosphere interactions.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
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Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Eva Y. Pfannerstill, Nina G. Reijrink, Achim Edtbauer, Akima Ringsdorf, Nora Zannoni, Alessandro Araújo, Florian Ditas, Bruna A. Holanda, Marta O. Sá, Anywhere Tsokankunku, David Walter, Stefan Wolff, Jošt V. Lavrič, Christopher Pöhlker, Matthias Sörgel, and Jonathan Williams
Atmos. Chem. Phys., 21, 6231–6256, https://doi.org/10.5194/acp-21-6231-2021, https://doi.org/10.5194/acp-21-6231-2021, 2021
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Tropical forests are globally significant for atmospheric chemistry. However, the mixture of reactive organic gases emitted by these ecosystems is poorly understood. By comprehensive observations at an Amazon forest site, we show that oxygenated species were previously underestimated in their contribution to the tropical-forest reactant mix. Our results show rain and temperature effects and have implications for models and the understanding of ozone and particle formation above tropical forests.
Hella van Asperen, João Rafael Alves-Oliveira, Thorsten Warneke, Bruce Forsberg, Alessandro Carioca de Araújo, and Justus Notholt
Biogeosciences, 18, 2609–2625, https://doi.org/10.5194/bg-18-2609-2021, https://doi.org/10.5194/bg-18-2609-2021, 2021
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Termites are insects that are highly abundant in tropical ecosystems. It is known that termites emit CH4, an important greenhouse gas, but their absolute emission remains uncertain. In the Amazon rainforest, we measured CH4 emissions from termite nests and groups of termites. In addition, we tested a fast and non-destructive field method to estimate termite nest colony size. We found that termites play a significant role in an ecosystem's CH4 budget and probably emit more than currently assumed.
Thomas Thorp, Stephen R. Arnold, Richard J. Pope, Dominick V. Spracklen, Luke Conibear, Christoph Knote, Mikhail Arshinov, Boris Belan, Eija Asmi, Tuomas Laurila, Andrei I. Skorokhod, Tuomo Nieminen, and Tuukka Petäjä
Atmos. Chem. Phys., 21, 4677–4697, https://doi.org/10.5194/acp-21-4677-2021, https://doi.org/10.5194/acp-21-4677-2021, 2021
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We compare modelled near-surface pollutants with surface and satellite observations to better understand the controls on the regional concentrations of pollution in western Siberia for late spring and summer in 2011. We find two commonly used emission inventories underestimate human emissions when compared to observations. Transport emissions are the main source of pollutants within the region during this period, whilst fire emissions peak during June and are only significant south of 60° N.
Guilherme F. Camarinha-Neto, Julia C. P. Cohen, Cléo Q. Dias-Júnior, Matthias Sörgel, José Henrique Cattanio, Alessandro Araújo, Stefan Wolff, Paulo A. F. Kuhn, Rodrigo A. F. Souza, Luciana V. Rizzo, and Paulo Artaxo
Atmos. Chem. Phys., 21, 339–356, https://doi.org/10.5194/acp-21-339-2021, https://doi.org/10.5194/acp-21-339-2021, 2021
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It was observed that friagem phenomena (incursion of cold waves from the high latitudes of the Southern Hemisphere to the Amazon region), very common in the dry season of the Amazon region, produced significant changes in microclimate and atmospheric chemistry. Moreover, the effects of the friagem change the surface O3 and CO2 mixing ratios and therefore interfere deeply in the microclimatic conditions and the chemical composition of the atmosphere above the rainforest.
Robbie Ramsay, Chiara F. Di Marco, Matthias Sörgel, Mathew R. Heal, Samara Carbone, Paulo Artaxo, Alessandro C. de Araùjo, Marta Sá, Christopher Pöhlker, Jost Lavric, Meinrat O. Andreae, and Eiko Nemitz
Atmos. Chem. Phys., 20, 15551–15584, https://doi.org/10.5194/acp-20-15551-2020, https://doi.org/10.5194/acp-20-15551-2020, 2020
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The Amazon rainforest is a unique
laboratoryto study the processes which govern the exchange of gases and aerosols to and from the atmosphere. This study investigated these processes by measuring the atmospheric concentrations of trace gases and particles at the Amazon Tall Tower Observatory. We found that the long-range transport of pollutants can affect the atmospheric composition above the Amazon rainforest and that the gases ammonia and nitrous acid can be emitted from the rainforest.
Robinson I. Negrón-Juárez, Jennifer A. Holm, Boris Faybishenko, Daniel Magnabosco-Marra, Rosie A. Fisher, Jacquelyn K. Shuman, Alessandro C. de Araujo, William J. Riley, and Jeffrey Q. Chambers
Biogeosciences, 17, 6185–6205, https://doi.org/10.5194/bg-17-6185-2020, https://doi.org/10.5194/bg-17-6185-2020, 2020
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The temporal variability in the Landsat satellite near-infrared (NIR) band captured the dynamics of forest regrowth after disturbances in Central Amazon. This variability was represented by the dynamics of forest regrowth after disturbances were properly represented by the ELM-FATES model (Functionally Assembled Terrestrial Ecosystem Simulator (FATES) in the Energy Exascale Earth System Model (E3SM) Land Model (ELM)).
Nina Löbs, David Walter, Cybelli G. G. Barbosa, Sebastian Brill, Rodrigo P. Alves, Gabriela R. Cerqueira, Marta de Oliveira Sá, Alessandro C. de Araújo, Leonardo R. de Oliveira, Florian Ditas, Daniel Moran-Zuloaga, Ana Paula Pires Florentino, Stefan Wolff, Ricardo H. M. Godoi, Jürgen Kesselmeier, Sylvia Mota de Oliveira, Meinrat O. Andreae, Christopher Pöhlker, and Bettina Weber
Biogeosciences, 17, 5399–5416, https://doi.org/10.5194/bg-17-5399-2020, https://doi.org/10.5194/bg-17-5399-2020, 2020
Short summary
Short summary
Cryptogamic organisms, such as bryophytes, lichens, and algae, cover major parts of vegetation in the Amazonian rain forest, but their relevance in biosphere–atmosphere exchange, climate processes, and nutrient cycling is largely unknown.
Over the duration of 2 years we measured their water content, temperature, and light conditions to get better insights into their physiological activity patterns and thus their potential impact on local, regional, and even global biogeochemical processes.
Ben Silver, Luke Conibear, Carly L. Reddington, Christoph Knote, Steve R. Arnold, and Dominick V. Spracklen
Atmos. Chem. Phys., 20, 11683–11695, https://doi.org/10.5194/acp-20-11683-2020, https://doi.org/10.5194/acp-20-11683-2020, 2020
Short summary
Short summary
China suffers from serious air pollution, which is thought to cause millions of early deaths each year. Measurements on the ground show that overall air quality is improving. Air quality is also affected by weather conditions, which can vary from year to year. We conduct computer simulations to show it is the reduction of the amount of pollution emitted, rather than weather conditions, which caused air quality to improve during 2015–2017. We then estimate that 150 000 fewer people die early.
Cited articles
Ahlström, A., Canadell, J. G., Schurgers, G., Wu, M., Berry, J. A.,
Guan, K., and Jackson, R. B.: Hydrologic resilience and Amazon productivity,
Nat. Commun., 8, 387, https://doi.org/10.1038/s41467-017-00306-z, 2017.
Andreae, M. O., Acevedo, O. C., Araùjo, A., Artaxo, P., Barbosa, C. G. G., Barbosa, H. M. J., Brito, J., Carbone, S., Chi, X., Cintra, B. B. L., da Silva, N. F., Dias, N. L., Dias-Júnior, C. Q., Ditas, F., Ditz, R., Godoi, A. F. L., Godoi, R. H. M., Heimann, M., Hoffmann, T., Kesselmeier, J., Könemann, T., Krüger, M. L., Lavric, J. V., Manzi, A. O., Lopes, A. P., Martins, D. L., Mikhailov, E. F., Moran-Zuloaga, D., Nelson, B. W., Nölscher, A. C., Santos Nogueira, D., Piedade, M. T. F., Pöhlker, C., Pöschl, U., Quesada, C. A., Rizzo, L. V., Ro, C.-U., Ruckteschler, N., Sá, L. D. A., de Oliveira Sá, M., Sales, C. B., dos Santos, R. M. N., Saturno, J., Schöngart, J., Sörgel, M., de Souza, C. M., de Souza, R. A. F., Su, H., Targhetta, N., Tóta, J., Trebs, I., Trumbore, S., van Eijck, A., Walter, D., Wang, Z., Weber, B., Williams, J., Winderlich, J., Wittmann, F., Wolff, S., and Yáñez-Serrano, A. M.: The Amazon Tall Tower Observatory (ATTO): overview of pilot measurements on ecosystem ecology, meteorology, trace gases, and aerosols, Atmos. Chem. Phys., 15, 10723–10776, https://doi.org/10.5194/acp-15-10723-2015, 2015.
Baker, J. C. A.: Catchment-scale estimates of Amazon evapotranspiration (Version pre_publication), Zenodo [data set], https://doi.org/10.5281/zenodo.4271331, 2020.
Baker, J. C. A.: Error estimates of Amazon catchment-balance evapotranspiration, Zenodo [data set], https://doi.org/10.5281/zenodo.4580292, 2021a.
Baker, J. C. A.: amazon_et: Amazon evapotranspiration scripts for HESS (Version v1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.4580447, 2021b.
Baker, J. C. A. and Spracklen, D. V.: Climate Benefits of Intact Amazon
Forests and the Biophysical Consequences of Disturbance, Frontiers in
Forests and Global Change, 2, 47, https://doi.org/10.3389/ffgc.2019.00047, 2019.
Baker, J. C. A., Castilho de Souza, D., Kubota, P., Buermann, W., Coelho, C.
A. S., Andrews, M. B., Gloor, M., Garcia-Carreras, L., Figueroa, S. N., and
Spracklen, D. V.: An assessment of land-atmosphere interactions over South
America using satellites, reanalysis and two global climate models, J.
Hydrometeorol., 22, 905–922, 2021a.
Baker, J. C. A., Garcia-Carreras, L., Buermann, W., Castilho de Souza, D.,
Marsham, J. H., Kubota, P., Gloor, M., Coelho, C. A. S., and Spracklen, D.
V.: Robust Amazon precipitation projections in climate models that capture
realistic land-atmosphere interactions, Environ. Res. Lett., in review, 2021b.
Barlow, J., Berenguer, E., Carmenta, R., and França, F.: Clarifying
Amazonia's burning crisis, Glob. Change Biol., 26, 319–321,
https://doi.org/10.1111/gcb.14872, 2020.
Callède, J., Ronchail, J., Guyot, J.-L., and Oliveira, E. D.:
Déboisement amazonien: son influence sur le débit de l'Amazone à
Óbidos (Brésil), Revue des sciences de l'eau/Journal of Water
Science, 21, 59–72, 2008.
Christoffersen, B. O., Restrepo-Coupe, N., Arain, M. A., Baker, I. T.,
Cestaro, B. P., Ciais, P., Fisher, J. B., Galbraith, D., Guan, X. D.,
Gulden, L., van den Hurk, B., Ichii, K., Imbuzeiro, H., Jain, A., Levine,
N., Miguez-Machor, G., Poulter, B., Roberti, D. R., Sakaguchi, K., Sahoo,
A., Schaefer, K., Shi, M. J., Verbeeck, H., Yang, Z. L., Araujo, A. C.,
Kruijt, B., Manzi, A. O., da Rocha, H. R., von Randow, C., Muza, M. N.,
Borak, J., Costa, M. H., de Goncalves, L. G. G., Zeng, X. B., and Saleska,
S. R.: Mechanisms of water supply and vegetation demand govern the
seasonality and magnitude of evapotranspiration in Amazonia and Cerrado,
Agr. Forest Meteorol., 191, 33–50, https://doi.org/10.1016/j.agrformet.2014.02.008, 2014.
Costa, M. H., Souza-Filho, J. C., and Ribeiro, A.: Comments on “The
Regional Evapotranspiration of the Amazon”, J. Hydrometeorol., 5,
1279–1280, https://doi.org/10.1175/jhm-393.1, 2004.
Costa, M. H., Biajoli, M. C., Sanches, L., Malhado, A. C. M., Hutyra, L. R.,
da Rocha, H. R., Aguiar, R. G., and de Araújo, A. C.: Atmospheric versus
vegetation controls of Amazonian tropical rain forest evapotranspiration:
Are the wet and seasonally dry rain forests any different?, J. Geophys. Res., 115, G04021, https://doi.org/10.1029/2009jg001179, 2010.
Crowhurst, D. M., Dadson, S. J., and Washington, R.: Evaluation of
Evaporation Climatology for the Congo Basin Wet Seasons in 11 Global Climate
Models, J. Geophys. Res.-Atmos., 125, e2019JD030619, https://doi.org/10.1029/2019JD030619, 2020.
da Rocha, H. R., Goulden, M. L., Miller, S. D., Menton, M. C., Pinto, L. D.
V. O., de Freitas, H. C., and e Silva Figueira, A. M.: Seasonality of water
and heat fluxes over a tropical forest in eastern Amazonia, Ecol.
Appl., 14, 22–32, https://doi.org/10.1890/02-6001, 2004.
da Rocha, H. R., Manzi, A. O., Cabral, O. M., Miller, S. D., Goulden, M. L.,
Saleska, S. R., R.-Coupe, N., Wofsy, S. C., Borma, L. S., Artaxo, P.,
Vourlitis, G., Nogueira, J. S., Cardoso, F. L., Nobre, A. D., Kruijt, B.,
Freitas, H. C., von Randow, C., Aguiar, R. G., and Maia, J. F.: Patterns of
water and heat flux across a biome gradient from tropical forest to savanna
in Brazil, J. Geophys. Res., 114, G00B12,
https://doi.org/10.1029/2007jg000640, 2009a.
da Rocha, H. R., Manzi, A. O., and Shuttleworth, J.: Evapotranspiration, in:
Amazonia and Global Change, edited by: Keller, M., Bustamante, M., Gash, J., and Silva Dias, P., Geophysical Monograph Series, 186, 261–272, 2009b.
da Silva, H. J. F., Gonçalves, W. A., and Bezerra, B. G.: Comparative
analyzes and use of evapotranspiration obtained through remote sensing to
identify deforested areas in the Amazon, Int. J. Appl. Earth Obs., 78, 163–174, https://doi.org/10.1016/j.jag.2019.01.015, 2019.
de Oliveira, G., Brunsell, N. A., Moraes, E. C., Shimabukuro, Y. E.,
Bertani, G., dos Santos, T. V., and Aragao, L.: Evaluation of MODIS-based
estimates of water-use efficiency in Amazonia, Int. J. Remote Sens., 38, 5291–5309, https://doi.org/10.1080/01431161.2017.1339924, 2017.
Dingman, S. L.: Physical hydrology, Waveland press, Long Grove, Illinois, USA, 3rd edn., ISBN: 1-4786-1118-9, 2015.
Eltahir, E. A.: Role of vegetation in sustaining large-scale atmospheric
circulations in the tropics, J. Geophys. Res., 101, 4255–4268, 1996.
Eltahir, E. A. and Bras, R. L.: Precipitation recycling in the Amazon
basin, Q. J. Roy. Meteor. Soc., 120, 861–880, 1994.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016 (data available at: https://esgf-index1.ceda.ac.uk/search/cmip6-ceda/, last access: 1 June 2020).
Fearnside, P. M.: Viewpoint-Brazil's Madeira River Dams: A Setback for
Environmental Policy in Amazonian Development, Water Alternatives, 7, 256–269, 2014.
Fisher, J. B., Malhi, Y., Bonal, D., Da Rocha, H. R., De AraÚJo, A. C.,
Gamo, M., Goulden, M. L., Hirano, T., Huete, A. R., Kondo, H., Kumagai, T.
O., Loescher, H. W., Miller, S., Nobre, A. D., Nouvellon, Y., Oberbauer, S.
F., Panuthai, S., Roupsard, O., Saleska, S., Tanaka, K., Tanaka, N., Tu, K.
P., and Von Randow, C.: The land–atmosphere water flux in the tropics,
Glob. Change Biol., 15, 2694–2714, https://doi.org/10.1111/j.1365-2486.2008.01813.x,
2009.
Foken, T.: The Energy Balance Closure Problem: An Overview, Ecol.
Appl., 18, 1351–1367, https://doi.org/10.1890/06-0922.1, 2008.
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, 150066,
https://doi.org/10.1038/sdata.2015.66, 2015 (data available at: https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_monthly/netcdf/, last access: 1 June 2020).
Gat, J. R. and Matsui, E.: Atmospheric water balance in the Amazon basin:
An isotopic evapotranspiration model, J. Geophys. Res., 96, 13179–13188, https://doi.org/10.1029/91JD00054, 1991.
GDAL/OGR Contributors: Geospatial Data Abstraction software Library: https://gdal.org, last access: June 2020.
Gloor, M., Brienen, R. J. W., Galbraith, D., Feldpausch, T. R.,
Schöngart, J., Guyot, J. L., Espinoza, J. C., Lloyd, J., and Phillips,
O. L.: Intensification of the Amazon hydrological cycle over the last two
decades, Geophys. Res. Lett., 40, 1729–1733, https://doi.org/10.1002/grl.50377,
2013.
Good, S. P., Noone, D., and Bowen, G.: Hydrologic connectivity constrains
partitioning of global terrestrial water fluxes, Science, 349, 175–177,
https://doi.org/10.1126/science.aaa5931, 2015.
Guan, K., Pan, M., Li, H., Wolf, A., Wu, J., Medvigy, D., Caylor, K. K.,
Sheffield, J., Wood, E. F., Malhi, Y., Liang, M., Kimball, J., Saleska, S.,
Berry, J., Joiner, J., and Lyapustin, A.: Photosynthetic seasonality of
global tropical forests constrained by hydroclimate, Nature Geoscience, 8,
284-289, 2015.
Gutman, G. G.: On the monitoring of land surface temperatures with the
NOAA/AVHRR: Removing the effect of satellite orbit drift, Int.
J. Remote Sens., 20, 3407–3413, https://doi.org/10.1080/014311699211435, 1999.
Hasler, N. and Avissar, R.: What Controls Evapotranspiration in the Amazon
Basin?, J. Hydrometeorol., 8, 380–395, https://doi.org/10.1175/jhm587.1, 2007.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2019 (data available at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview, last access: 1 June 2020).
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
HidroWeb: HidroWeb, Brazilian Water Resources Database, Agência
Nacional de Águas, Water Resources National Agency, Brazil, available at: https://www.snirh.gov.br/hidroweb/serieshistoricas (last access: 1 June 2020), 2018.
Hodges, J. L.: The significance probability of the Smirnov two-sample test,
Arkiv för Matematik, 3, 469–486, 1958.
Huffman, G. J.: Estimates of root-mean-square random error for finite
samples of estimated precipitation, J. Appl. Meteorol., 36, 1191–1201, 1997.
Jasechko, S., Sharp, Z. D., Gibson, J., Birks, S. J., Yi, Y., and Fawcett,
P. J.: Terrestrial water fluxes dominated by transpiration, Nature, 496,
347–350, https://doi.org/10.1038/nature11983, 2013.
Jasechko, S.: Plants turn on the tap, Nat. Clim. Change, 8, 562–563,
https://doi.org/10.1038/s41558-018-0212-z, 2018.
Jung, M., Reichstein, M., Ciais, P., Seneviratne, S. I., Sheffield, J.,
Goulden, M. L., Bonan, G., Cescatti, A., Chen, J., de Jeu, R., Dolman, A.
J., Eugster, W., Gerten, D., Gianelle, D., Gobron, N., Heinke, J., Kimball,
J., Law, B. E., Montagnani, L., Mu, Q., Mueller, B., Oleson, K., Papale, D.,
Richardson, A. D., Roupsard, O., Running, S., Tomelleri, E., Viovy, N.,
Weber, U., Williams, C., Wood, E., Zaehle, S., and Zhang, K.: Recent decline
in the global land evapotranspiration trend due to limited moisture supply,
Nature, 467, 951–954, https://doi.org/10.1038/nature09396, 2010.
Karlsson, K.-G., Riihelä, A., Müller, R., Meirink, J. F., Sedlar, J., Stengel, M., Lockhoff, M., Trentmann, J., Kaspar, F., Hollmann, R., and Wolters, E.: CLARA-A1: CM SAF cLouds, Albedo and Radiation dataset from AVHRR data, Edition 1 – Monthly Means / Daily Means / Pentad Means / Monthly Histograms, Satellite Application Facility on Climate Monitoring (CM SAF) [data set], https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V001, 2012.
Karlsson, K.-G., Riihelä, A., Müller, R., Meirink, J. F., Sedlar, J., Stengel, M., Lockhoff, M., Trentmann, J., Kaspar, F., Hollmann, R., and Wolters, E.: CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data, Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, 2013.
Keller, M., Bustamante, M., Gash, J., and Dias, P. S.: Amazonia and global
change, Geophysical Monograph Series American Geophysical Union, Washington, DC, ISBN: 978-0-87590-476-4, 2009.
Kergoat, L., Lafont, S., Douville, H., Berthelot, B., Dedieu, G., Planton,
S., and Royer, J.-F.: Impact of doubled CO2 on global-scale leaf area index and evapotranspiration: Conflicting stomatal conductance and LAI responses, J. Geophys. Res., 107, 4808,
https://doi.org/10.1029/2001jd001245, 2002.
Khand, K., Numata, I., Kjaersgaard, J., and Vourlitis, G. L.: Dry season
evapotranspiration dynamics over human-impacted landscapes in the southern
Amazon using the Landsat-based METRIC model, Remote Sensing, 9, 706, https://doi.org/10.3390/rs9070706, 2017.
Kooperman, G. J., Chen, Y., Hoffman, F. M., Koven, C. D., Lindsay, K.,
Pritchard, M. S., Swann, A. L. S., and Randerson, J. T.: Forest response to
rising CO2 drives zonally asymmetric rainfall change over tropical land,
Nat. Clim. Change, 8, 434–440, https://doi.org/10.1038/s41558-018-0144-7, 2018.
Koren, G., Schaik, E. v., Araújo, A. C., Boersma, K. F., Gärtner,
A., Killaars, L., Kooreman, M. L., Kruijt, B., Laan-Luijkx, I. T. v. d.,
Randow, C. v., Smith, N. E., and Peters, W.: Widespread reduction in
sun-induced fluorescence from the Amazon during the 2015/2016 El
Niño, Philos. T. Roy. Soc. B, 373, 20170408, https://doi.org/10.1098/rstb.2017.0408, 2018.
Kunert, N., Aparecido, L. M. T., Wolff, S., Higuchi, N., Santos, J. d.,
Araujo, A. C. d., and Trumbore, S.: A revised hydrological model for the
Central Amazon: The importance of emergent canopy trees in the forest water
budget, Agr. Forest Meteorol., 239, 47–57, https://doi.org/10.1016/j.agrformet.2017.03.002, 2017.
Langenbrunner, B., Pritchard, M. S., Kooperman, G. J., and Randerson, J. T.:
Why Does Amazon Precipitation Decrease When Tropical Forests Respond to
Increasing CO2?, Earth's Future, 7, 450–468, https://doi.org/10.1029/2018ef001026, 2019.
Long, D., Longuevergne, L., and Scanlon, B. R.: Uncertainty in
evapotranspiration from land surface modeling, remote sensing, and GRACE
satellites, Water Resour. Res., 50, 1131–1151,
https://doi.org/10.1002/2013WR014581, 2014.
Lopes, A. P., Nelson, B. W., Wu, J., Graça, P. M. L. d. A., Tavares, J.
V., Prohaska, N., Martins, G. A., and Saleska, S. R.: Leaf flush drives dry
season green-up of the Central Amazon, Remote Sens. Environ., 182,
90–98, https://doi.org/10.1016/j.rse.2016.05.009, 2016.
Maeda, E. E., Ma, X., Wagner, F. H., Kim, H., Oki, T., Eamus, D., and Huete, A.: Evapotranspiration seasonality across the Amazon Basin, Earth Syst. Dynam., 8, 439–454, https://doi.org/10.5194/esd-8-439-2017, 2017.
Malhi, Y., Roberts, J. T., Betts, R. A., Killeen, T. J., Li, W., and Nobre,
C. A.: Climate change, deforestation, and the fate of the Amazon, Science,
319, 169–172, 2008.
Marengo, J. A.: On the hydrological cycle of the Amazon Basin: A historical
review and current state-of-the-art, Revista Brasileira de Meteorologia, 21,
1–19, 2006.
Martens, B., Miralles, D. G., Lievens, H., van der Schalie, R., de Jeu, R. A. M., Fernández-Prieto, D., Beck, H. E., Dorigo, W. A., and Verhoest, N. E. C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, 2017 (data available at: https://www.gleam.eu/#downloads, last access: 6 March 2020).
Martinelli, L. A., Victoria, R. L., Silveira Lobo Sternberg, L., Ribeiro,
A., and Zacharias Moreira, M.: Using stable isotopes to determine sources of
evaporated water to the atmosphere in the Amazon basin, J. Hydrol., 183, 191–204, https://doi.org/10.1016/0022-1694(95)02974-5, 1996.
Michel, D., Jiménez, C., Miralles, D. G., Jung, M., Hirschi, M., Ershadi, A., Martens, B., McCabe, M. F., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms, Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, 2016.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Miralles, D. G., Jiménez, C., Jung, M., Michel, D., Ershadi, A., McCabe, M. F., Hirschi, M., Martens, B., Dolman, A. J., Fisher, J. B., Mu, Q., Seneviratne, S. I., Wood, E. F., and Fernández-Prieto, D.: The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets, Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016, 2016.
Monteith, J.: Evaporation and environment. The state and movement of water
in living organisms, Symposium of the Society of Experimental Biology, 19,
205–234, 1965.
Moreira, M., Sternberg, L., Martinelli, L., Victoria, R., Barbosa, E.,
Bonates, L., and Nepstad, D.: Contribution of transpiration to forest
ambient vapour based on isotopic measurements, Glob. Change Biol., 3, 439–450, 1997.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a
global evapotranspiration algorithm based on MODIS and global meteorology
data, Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global
terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, https://doi.org/10.1016/j.rse.2011.02.019, 2011.
Mu, Q., Zhao, M., and Running, S. W.: MODIS global terrestrial
evapotranspiration (ET) product (NASA MOD16A2/A3), Algorithm Theoretical
Basis Document, NASA, Washinton, DC, Collection 5, 1–66, 2013.
Mueller, B. and Seneviratne, S. I.: Systematic land climate and evapotranspiration biases in CMIP5 simulations, Geophys. Res. Lett., 41, 128–134, https://doi.org/10.1002/2013gl058055, 2014.
Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I.: Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis, Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, 2013.
Myneni, R., Hoffman, S., Knyazikhin, Y., Privette, J., Glassy, J., Tian, Y.,
Wang, Y., Song, X., Zhang, Y., and Smith, G.: Global products of vegetation
leaf area and fraction absorbed PAR from year one of MODIS data, Remote
Sens. Environ., 83, 214–231, 2002.
Myneni, R., Knyazikhin, Y., and Park, T.: MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006, NASA EOSDIS Land Processes
DAAC [data set], https://doi.org/10.5067/MODIS/MOD15A2H.006, 2015 (data available at: https://lpdaac.usgs.gov/products/mod15a2hv006/, last access: 1 June 2020).
Myneni, R. B., Yang, W., Nemani, R. R., Huete, A. R., Dickinson, R. E.,
Knyazikhin, Y., Didan, K., Fu, R., Negrón Juárez, R. I., Saatchi, S.
S., Hashimoto, H., Ichii, K., Shabanov, N. V., Tan, B., Ratana, P.,
Privette, J. L., Morisette, J. T., Vermote, E. F., Roy, D. P., Wolfe, R. E.,
Friedl, M. A., Running, S. W., Votava, P., El-Saleous, N., Devadiga, S., Su,
Y., and Salomonson, V. V.: Large seasonal swings in leaf area of Amazon
rainforests, P. Natl. Acad. Sci. USA, 104, 4820–4823, https://doi.org/10.1073/pnas.0611338104, 2007.
Nepstad, D. C., Stickler, C. M., Soares-Filho, B., and Merry, F.: Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point, Philos. T. Roy. Soc. B, 363, 1737–1746, https://doi.org/10.1098/rstb.2007.0036, 2008.
Paca, V. H. d. M., Espinoza-Dávalos, G. E., Hessels, T. M., Moreira, D.
M., Comair, G. F., and Bastiaanssen, W. G. M.: The spatial variability of
actual evapotranspiration across the Amazon River Basin based on remote
sensing products validated with flux towers, Ecological Processes, 8, 6,
https://doi.org/10.1186/s13717-019-0158-8, 2019.
Pan, S., Pan, N., Tian, H., Friedlingstein, P., Sitch, S., Shi, H., Arora, V. K., Haverd, V., Jain, A. K., Kato, E., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Ottlé, C., Poulter, B., Zaehle, S., and Running, S. W.: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling, Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, 2020.
Paredes-Trejo, F. J., Barbosa, H. A., and Lakshmi Kumar, T. V.: Validating
CHIRPS-based satellite precipitation estimates in Northeast Brazil, J. Arid Environ., 139, 26–40, https://doi.org/10.1016/j.jaridenv.2016.12.009, 2017.
Pinzón, J. E., Brown, M. E., and Tucker, C. J.: EMD CORRECTION OF
ORBITAL DRIFT ARTIFACTS IN SATELLITE DATA STREAM, in: Hilbert-Huang
Transform and Its Applications, edited by: Huang, N. E., and Shen, S. S. P., World Scientific, Interdisciplinary Mathematical Sciences, 16, 167–186, 2005.
Priestley, C. and Taylor, R.: On the assessment of surface heat flux and
evaporation using large-scale parameters, Mon. Weather Rev., 100, 81–92, 1972.
Restrepo-Coupe, N., da Rocha, H. R., Hutyra, L. R., da Araujo, A. C., Borma,
L. S., Christoffersen, B., Cabral, O. M. R., de Camargo, P. B., Cardoso, F.
L., da Costa, A. C. L., Fitzjarrald, D. R., Goulden, M. L., Kruijt, B.,
Maia, J. M. F., Malhi, Y., Manzi, A. O., Miller, S. D., Nobre, A. D., von
Randow, C., Sá, L. D. A., Sakai, R. K., Tota, J., Wofsy, S. C., Zanchi,
F. B., and Saleska, S. R.: What drives the seasonality of photosynthesis
across the Amazon basin? A cross-site analysis of eddy flux tower
measurements from the Brasil flux network, Agr. Forest Meteorol., 182–183, 128–144, 2013.
Rodell, M. and Famiglietti, J. S.: Detectability of variations in
continental water storage from satellite observations of the time dependent
gravity field, Water Resour. Res., 35, 2705–2723,
https://doi.org/10.1029/1999WR900141, 1999.
Rodell, M., McWilliams, E. B., Famiglietti, J. S., Beaudoing, H. K., and
Nigro, J.: Estimating evapotranspiration using an observation based
terrestrial water budget, Hydrol. Process., 25, 4082–4092,
https://doi.org/10.1002/hyp.8369, 2011.
Ruhoff, A. L., Paz, A. R., Aragao, L., Mu, Q., Malhi, Y., Collischonn, W.,
Rocha, H. R., and Running, S. W.: Assessment of the MODIS global
evapotranspiration algorithm using eddy covariance measurements and
hydrological modelling in the Rio Grande basin, Hydrolog. Sci.
J., 58, 1658–1676, https://doi.org/10.1080/02626667.2013.837578, 2013.
Running, S. W., Mu, Q., Zhao, M., and Moreno, A.: MODIS Global Terrestrial Evapotranspiration (ET) Product (MOD16A2/A3 and Year-End Gap-Filled MOD16A2GF/A3GF) NASA Earth Observing System MODIS Land Algorithm (For Collection 6), National Aeronautics and Space Administration, Washington, DC, USA [data set], https://doi.org/10.5067/MODIS/MOD16A2.006, 2019 (data available at: https://lpdaac.usgs.gov/products/mod16a2v006/, last access: 1 June 2020).
Salati, E. and Vose, P. B.: Amazon Basin: A System in Equilibrium, Science,
225, 129–138, https://doi.org/10.1126/science.225.4658.129, 1984.
Salati, E., Dall'Olio, A., Matsui, E., and Gat, J. R.: Recycling of water in
the Amazon basin: an isotopic study, Water Resour. Res., 15, 1250–1258, 1979.
Saleska, S. R., Da Rocha, H. R., Huete, A. R., Nobre, A. D., Artaxo, P. E., and Shimabukuro, Y. E.: LBA-ECO CD-32 Flux Tower Network Data Compilation,
Brazilian Amazon: 1999–2006, Oak Ridge National Laboratory Distributed
Active Archive Center, Oak Ridge, Tennessee, USA [data set], https://doi.org/10.3334/ORNLDAAC/1174, 2013 (data available at: https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1174, last access: 1 January 2020).
Saleska, S. R., Wu, J., Guan, K., Araujo, A. C., Huete, A., Nobre, A. D.,
and Restrepo-Coupe, N.: Dry-season greening of Amazon forests, Nature, 531,
E4–E5, https://doi.org/10.1038/nature16457, 2016.
Schlesinger, W. H. and Jasechko, S.: Transpiration in the global water
cycle, Agr. Forest Meteorol., 189–190, 115–117, https://doi.org/10.1016/j.agrformet.2014.01.011, 2014.
Schwalm, C. R., Huntinzger, D. N., Michalak, A. M., Fisher, J. B., Kimball,
J. S., Mueller, B., Zhang, K., and Zhang, Y.: Sensitivity of inferred
climate model skill to evaluation decisions: a case study using CMIP5
evapotranspiration, Environ. Res. Lett., 8, 024028,
https://doi.org/10.1088/1748-9326/8/2/024028, 2013.
Seyler, F., Muller, F., Cochonneau, G., Guimarães, L., and Guyot, J. L.:
Watershed delineation for the Amazon sub-basin system using GTOPO30 DEM and
a drainage network extracted from JERS SAR images, Hydrol. Process., 23, 3173–3185, https://doi.org/10.1002/hyp.7397, 2009.
Shi, M., Liu, J., Worden, J. R., Bloom, A. A., Wong, S., and Fu, R.: The
2005 Amazon Drought Legacy Effect Delayed the 2006 Wet Season Onset,
Geophys. Res. Lett., 46, 9082–9090, https://doi.org/10.1029/2019gl083776, 2019.
Silvério, D. V., Brando, P. M., Macedo, M. N., Beck, P. S., Bustamante,
M., and Coe, M. T.: Agricultural expansion dominates climate changes in
southeastern Amazonia: the overlooked non-GHG forcing, Environ.
Res. Lett., 10, 104015, https://doi.org/10.1088/1748-9326/10/10/104015, 2015.
Skinner, C. B., Poulsen, C. J., Chadwick, R., Diffenbaugh, N. S., and
Fiorella, R. P.: The Role of Plant CO2 Physiological Forcing in Shaping
Future Daily-Scale Precipitation, J. Climate, 30, 2319–2340,
https://doi.org/10.1175/JCLI-D-16-0603.1, 2017.
Sörensson, A. A. and Ruscica, R. C.: Intercomparison and Uncertainty
Assessment of Nine Evapotranspiration Estimates Over South America, Water
Resour. Res., 54, 2891–2908, https://doi.org/10.1002/2017wr021682, 2018.
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.
Spracklen, D. V., Baker, J. C. A., Garcia-Carreras, L., and Marsham, J.: The
Effects of Tropical Vegetation On Rainfall, Annu. Rev. Env. Resour., 43, 14.11–14.26, https://doi.org/10.1146/annurev-environ-102017-030136, 2018.
Sun, L., Baker, J. C. A., Gloor, E., Spracklen, D., Boesch, H., Somkuti, P.,
Maeda, E., and Buermann, W.: Seasonal and Inter-annual Variation of
Evapotranspiration in Amazonia Based on Precipitation, River Discharge and
Gravity Anomaly Data, Frontiers in Earth Science, 7, 1–9,
https://doi.org/10.3389/feart.2019.00032, 2019.
Swann, A. L. S. and Koven, C. D.: A Direct Estimate of the Seasonal Cycle
of Evapotranspiration over the Amazon Basin, J. Hydrometeorol., 18, 2173–2185, https://doi.org/10.1175/jhm-d-17-0004.1, 2017.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/bams-d-11-00094.1, 2012 (data available at: https://esgf-index1.ceda.ac.uk/search/cmip5-ceda/, last access: 1 January 2020).
Teuling, A. J.: A Forest Evapotranspiration Paradox Investigated Using
Lysimeter Data, Vadose Zone J., 17, 1–7, https://doi.org/10.2136/vzj2017.01.0031, 2018.
Timpe, K. and Kaplan, D.: The changing hydrology of a dammed Amazon,
Science Advances, 3, e1700611, https://doi.org/10.1126/sciadv.1700611, 2017.
van der Ent, R. J., Savenije, H. H., Schaefli, B., and Steele-Dunne, S. C.:
Origin and fate of atmospheric moisture over continents, Water Resour. Res., 46, W09525, https://doi.org/10.1029/2010WR009127, 2010.
Victoria, R. L., Martinelli, L. A., Jefferson, M., and Jeffrey, R.:
Mechanisms of Water Recycling in the Amazon Basin: Isotopic Insights, Ambio,
20, 384–387, 1991.
von Randow, C., Manzi, A. O., Kruijt, B., de Oliveira, P. J., Zanchi, F. B.,
Silva, R. L., Hodnett, M. G., Gash, J. H. C., Elbers, J. A., Waterloo, M.
J., Cardoso, F. L., and Kabat, P.: Comparative measurements and seasonal
variations in energy and carbon exchange over forest and pasture in South
West Amazonia, Theor. Appl. Climatol., 78, 5–26,
https://doi.org/10.1007/s00704-004-0041-z, 2004.
Wang, K. and Dickinson, R. E.: A review of global terrestrial
evapotranspiration: Observation, modeling, climatology, and climatic
variability, Rev. Geophys., 50, RG2005, https://doi.org/10.1029/2011rg000373, 2012.
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., and Landerer, F. W.:
Improved methods for observing Earth's time variable mass distribution with
GRACE using spherical cap mascons, J. Geophys. Res.-Sol. Ea., 120, 2648–2671, https://doi.org/10.1002/2014jb011547, 2015.
Wei, Z., Yoshimura, K., Wang, L., Miralles, D. G., Jasechko, S., and Lee,
X.: Revisiting the contribution of transpiration to global terrestrial
evapotranspiration, Geophys. Res. Lett., 44, 2792–2801,
https://doi.org/10.1002/2016gl072235, 2017.
Werth, D. and Avissar, R.: The Regional Evapotranspiration of the Amazon,
J. Hydrometeorol., 5, 100–109, https://doi.org/10.1175/1525-7541(2004)005<0100:Treota>2.0.Co;2, 2004.
Wiese, D. N., Yuan, D.-N., Boening, C., Landerer, F. W., and Watkins, M. M.: JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height Coastal Resolution Improvement (CRI) Filtered Release 06 Version 02, PO.DAAC, CA, USA [data set], https://doi.org/10.5067/TEMSC-3JC62, 2019 (data available at: https://podaac-opendap.jpl.nasa.gov/opendap/allData/tellus/L3/mascon/RL06/JPL/v02/CRI/netcdf/, last access: 6 May 2020).
Wiese, D. N., Landerer, F. W., and Watkins, M. M.: Quantifying and reducing
leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res., 52, 7490–7502, https://doi.org/10.1002/2016wr019344, 2016.
Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier,
P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A., Ibrom,
A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R., Oechel,
W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at
FLUXNET sites, Agr. Forest Meteorol., 113, 223–243, https://doi.org/10.1016/S0168-1923(02)00109-0, 2002.
Wright, J. S., Fu, R., Worden, J. R., Chakraborty, S., Clinton, N. E., Risi,
C., Sun, Y., and Yin, L.: Rainforest-initiated wet season onset over the
southern Amazon, P. Natl. Acad. Sci. USA, 114,
8481–8486, https://doi.org/10.1073/pnas.1621516114, 2017.
Wu, J., Lakshmi, V., Wang, D., Lin, P., Pan, M., Cai, X., Wood, E. F., and
Zeng, Z.: The Reliability of Global Remote Sensing Evapotranspiration
Products over Amazon, Remote Sensing, 12, 2211, https://doi.org/10.3390/rs12142211, 2020.
Yan, K., Park, T., Yan, G., Chen, C., Yang, B., Liu, Z., Nemani, R. R.,
Knyazikhin, Y., and Myneni, R. B.: Evaluation of MODIS LAI/FPAR Product
Collection 6. Part 1: Consistency and Improvements, Remote Sensing, 8, 1–16, 2016a.
Yan, K., Park, T., Yan, G., Liu, Z., Yang, B., Chen, C., Nemani, R. R.,
Knyazikhin, Y., and Myneni, R. B.: Evaluation of MODIS LAI/FPAR product
collection 6. Part 2: Validation and intercomparison, Remote Sensing, 8,
460, https://doi.org/10.3390/rs8060460, 2016b.
Yin, L., Fu, R., Shevliakova, E., and Dickinson, R. E.: How well can CMIP5
simulate precipitation and its controlling processes over tropical South
America?, Clim. Dynam., 41, 3127–3143, https://doi.org/10.1007/s00382-012-1582-y, 2013.
Zemp, D. C., Schleussner, C.-F., Barbosa, H. M. J., van der Ent, R. J., Donges, J. F., Heinke, J., Sampaio, G., and Rammig, A.: On the importance of cascading moisture recycling in South America, Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, 2014.
Zemp, D. C., Schleussner, C.-F., Barbosa, H. M. J., Hirota, M., Montade, V.,
Sampaio, G., Staal, A., Wang-Erlandsson, L., and Rammig, A.: Self-amplified
Amazon forest loss due to vegetation-atmosphere feedbacks, Nat.
Commun., 8, 1–10, https://doi.org/10.1038/ncomms14681, 2017a.
Zemp, D. C., Schleussner, C.-F., Barbosa, H. M. J., and Rammig, A.:
Deforestation effects on Amazon forest resilience, Geophys. Res. Lett., 44, 6182–6190, https://doi.org/10.1002/2017gl072955, 2017b.
Zeng, Z., Piao, S., Lin, X., Yin, G., Peng, S., Ciais, P., and Myneni, R.
B.: Global evapotranspiration over the past three decades: estimation based
on the water balance equation combined with empirical models, Environ.
Res. Lett., 7, 014026, https://doi.org/10.1088/1748-9326/7/1/014026, 2012.
Zhang, K., Kimball, J. S., Nemani, R. R., and Running, S. W.: A continuous
satellite-derived global record of land surface evapotranspiration from 1983
to 2006, Water Resour. Res., 46, W09522, https://doi.org/10.1029/2009wr008800, 2010 (data available at: http://files.ntsg.umt.edu/data/ET_global_monthly/Global_8kmResolution/, last access: 1 June 2020).
Zhang, K., Almeida Castanho, A. D., Galbraith, D. R., Moghim, S., Levine, N.
M., Bras, R. L., Coe, M. T., Costa, M. H., Malhi, Y., and Longo, M.: The
fate of Amazonian ecosystems over the coming century arising from changes in
climate, atmospheric CO2, and land use, Glob. Change Biol., 21, 2569–2587, https://doi.org/10.1111/gcb.12903, 2015a.
Zhang, K., Kimball, J. S., Nemani, R. R., Running, S. W., Hong, Y., Gourley,
J. J., and Yu, Z.: Vegetation Greening and Climate Change Promote
Multidecadal Rises of Global Land Evapotranspiration, Scientific Reports, 5, 15956, https://doi.org/10.1038/srep15956, 2015b.
Zhang, K., Kimball, J. S., and Running, S. W.: A review of remote sensing
based actual evapotranspiration estimation, WIREs Water, 3, 834–853,
https://doi.org/10.1002/wat2.1168, 2016.
Zhang, L., Dawes, W. R., and Walker, G. R.: Response of mean annual
evapotranspiration to vegetation changes at catchment scale, Water Resour.
Res., 37, 701–708, https://doi.org/10.1029/2000wr900325, 2001.
Zhang, Y., Peña-Arancibia, J. L., McVicar, T. R., Chiew, F. H. S., Vaze,
J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y. Y., Miralles, D. G., and
Pan, M.: Multi-decadal trends in global terrestrial evapotranspiration and
its components, Scientific Reports, 6, 19124, https://doi.org/10.1038/srep19124,
2016.
Short summary
Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to...
