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Jelle Treep, Gil Bohrer, Judy Shamoun-Baranes, Olivier Duriez, Renato Prata de Moraes Frasson, and Willem Bouten

Abstract

Bird flight is strongly influenced by local meteorological conditions. With increasing amounts of high-frequency GPS data of bird movement becoming available, as tags become cheaper and lighter, opportunities are created to obtain large datasets of quantitative meteorological information from observations conducted by bird-borne tags. In this article we propose a method for estimating wind velocity and convective velocity scale from tag-based high-frequency GPS data of soaring birds in flight.

The flight patterns of soaring birds are strongly influenced by the interactions between atmospheric boundary layer processes and the morphology of the bird; climb rates depend on vertical air motion, flight altitude depends on boundary layer height, and drift off the bird’s flight path depends on wind speed and direction. We combine aerodynamic theory of soaring bird flight, the bird’s morphological properties, and three-dimensional GPS measurements at 3-s intervals to estimate the convective velocity scale and horizontal wind velocity at the locations and times of flight.

We use wind speed and direction observations from meteorological ground stations and estimates of convective velocity from the Ocean–Land–Atmosphere Model (OLAM) to evaluate our findings. Although not collocated, our wind velocity estimates are consistent with ground station data, and convective velocity–scale estimates are consistent with the meteorological model. Our work demonstrates that biologging offers a novel alternative approach for estimating atmospheric conditions on a spatial and temporal scale that complements existing meteorological measurement systems.

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Renato Ramos da Silva, Gil Bohrer, David Werth, Martin J. Otte, and Roni Avissar

Abstract

Meteorological observations and model simulations are used to show that the catastrophic ice storm of 4–5 December 2002 in the southeastern United States resulted from the combination of a classic winter storm and a warm sea surface temperature (SST) anomaly in the western Atlantic Ocean. At the time of the storm, observations show that the Atlantic SST near the southeastern U.S. coast was 1.0°–1.5°C warmer than its multiyear mean. The impact of this anomalous SST on the ice accumulation of the ice storm was evaluated with the Regional Atmospheric Modeling System. The model shows that a warmer ocean leads to the conversion of more snow into freezing rain while not significantly affecting the inland surface temperature. Conversely, a cooler ocean produces mostly snowfall and less freezing rain. A similar trend is obtained by statistically comparing observations of ice storms in the last decade with weekly mean Atlantic SSTs. The SST during an ice storm is significantly and positively correlated with a deeper and warmer melting layer.

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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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