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  • Author or Editor: Eugenie S. Euskirchen x
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Joy Clein, A. David McGuire, Eugenie S. Euskirchen, and Monika Calef

Abstract

As part of the Western Arctic Linkage Experiment (WALE), simulations of carbon dynamics in the western Arctic (WALE region) were conducted during two recent decades by driving the Terrestrial Ecosystem Model (TEM) with three alternative climate datasets. Among the three TEM simulations, we compared the mean monthly and interannual variability of three carbon fluxes: 1) net primary production (NPP), 2) heterotrophic respiration (Rh), and 3) net ecosystem production (NEP). Cumulative changes in vegetation, soil, and total carbon storage among the simulations were also compared. This study supports the conclusion that the terrestrial carbon cycle is accelerating in the WALE region, with more rapid turnover of carbon for simulations driven by two of the three climates. The temperature differences among the climate datasets resulted in annual estimates of NPP and Rh that varied by a factor of 2.5 among the simulations. There is much spatial variability in the temporal trends of NPP and Rh across the region in the simulations driven by different climates, and the spatial pattern of trends is quite different among simulations. Thus, this study indicates that the overall response of NEP in simulations with TEM across the WALE region depends substantially on the temporal trends in the climate dataset used to drive the model. Similar to the recommendations of other studies in the WALE project, this study indicates that coupling methodologies should use anomalies of future climate model simulations to alter the climate of more trusted datasets for purposes of driving ecosystem models of carbon dynamics.

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John E. Walsh, Peter A. Bieniek, Brian Brettschneider, Eugénie S. Euskirchen, Rick Lader, and Richard L. Thoman

Abstract

Alaska experienced record-setting warmth during the 2015/16 cold season (October–April). Statewide average temperatures exceeded the period-of-record mean by more than 4°C over the 7-month cold season and by more than 6°C over the 4-month late-winter period, January–April. The record warmth raises two questions: 1) Why was Alaska so warm during the 2015/16 cold season? 2) At what point in the future might this warmth become typical if greenhouse warming continues? On the basis of circulation analogs computed from sea level pressure and 850-hPa geopotential height fields, the atmospheric circulation explains less than half of the anomalous warmth. The warming signal forced by greenhouse gases in climate models accounts for about 1°C of the anomalous warmth. A factor that is consistent with the seasonal and spatial patterns of the warmth is the anomalous surface state. The surface anomalies include 1) above-normal ocean surface temperatures and below-normal sea ice coverage in the surrounding seas from which air advects into Alaska and 2) the deficient snowpack over Alaska itself. The location of the maximum of anomalous warmth over Alaska and the late-winter–early-spring increase of the anomalous warmth unexplained by the atmospheric circulation implicates snow cover and its albedo effect, which is supported by observational measurements in the boreal forest and tundra biomes. Climate model simulations indicate that warmth of this magnitude will become the norm by the 2050s if greenhouse gas emissions follow their present scenario.

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Sara H. Knox, Robert B. Jackson, Benjamin Poulter, Gavin McNicol, Etienne Fluet-Chouinard, Zhen Zhang, Gustaf Hugelius, Philippe Bousquet, Josep G. Canadell, Marielle Saunois, Dario Papale, Housen Chu, Trevor F. Keenan, Dennis Baldocchi, Margaret S. Torn, Ivan Mammarella, Carlo Trotta, Mika Aurela, Gil Bohrer, David I. Campbell, Alessandro Cescatti, Samuel Chamberlain, Jiquan Chen, Weinan Chen, Sigrid Dengel, Ankur R. Desai, Eugenie Euskirchen, Thomas Friborg, Daniele Gasbarra, Ignacio Goded, Mathias Goeckede, Martin Heimann, Manuel Helbig, Takashi Hirano, David Y. Hollinger, Hiroki Iwata, Minseok Kang, Janina Klatt, Ken W. Krauss, Lars Kutzbach, Annalea Lohila, Bhaskar Mitra, Timothy H. Morin, Mats B. Nilsson, Shuli Niu, Asko Noormets, Walter C. Oechel, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Karina V. R. Schäfer, Hans Peter Schmid, Narasinha Shurpali, Oliver Sonnentag, Angela C. I. Tang, Masahito Ueyama, Rodrigo Vargas, Timo Vesala, Eric J. Ward, Lisamarie Windham-Myers, Georg Wohlfahrt, and Donatella Zona

Abstract

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m–2 yr–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.

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