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  • Author or Editor: M. J. Atkinson x
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J. D. Fuentes, M. Lerdau, R. Atkinson, D. Baldocchi, J. W. Bottenheim, P. Ciccioli, B. Lamb, C. Geron, L. Gu, A. Guenther, T. D. Sharkey, and W. Stockwell

Nonmethane hydrocarbons are ubiquitous trace atmospheric constituents yet they control the oxidation capacity of the atmosphere. Both anthropogenic and biogenic processes contribute to the release of hydrocarbons to the atmosphere. In this manuscript, the state of the science concerning biosynthesis, transport, and chemical transformation of hydrocarbons emitted by the terrestrial biosphere is reviewed. In particular, the focus is on isoprene, monoterpenes, and oxygenated hydrocarbons. The generated science during the last 10 years is reviewed to explain and quantify hydrocarbon emissions from vegetation and to discern impacts of biogenic hydrocarbons on local and regional atmospheric chemistry. Furthermore, the physiological and environmental processes controlling biosynthesis and production of hydrocarbon compounds are reported on. Many advances have been made on measurement and modeling approaches developed to quantify hydrocarbon emissions from leaves and forest ecosystems. A synthesis of the atmospheric chemistry of biogenic hydrocarbons and their role in the formation of oxidants and aerosols is presented. The integration of biogenic hydrocarbon kinetics and atmospheric physics into mathematical modeling systems is examined to assess the contribution of biogenic hydrocarbons to the formation of oxidants and aerosols, thereby allowing us to study their impacts on the earth's climate system and to develop strategies to reduce oxidant precursors in affected regions.

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Elizabeth C. Kent, John J. Kennedy, Thomas M. Smith, Shoji Hirahara, Boyin Huang, Alexey Kaplan, David E. Parker, Christopher P. Atkinson, David I. Berry, Giulia Carella, Yoshikazu Fukuda, Masayoshi Ishii, Philip D. Jones, Finn Lindgren, Christopher J. Merchant, Simone Morak-Bozzo, Nick A. Rayner, Victor Venema, Souichiro Yasui, and Huai-Min Zhang


Global surface temperature changes are a fundamental expression of climate change. Recent, much-debated variations in the observed rate of surface temperature change have highlighted the importance of uncertainty in adjustments applied to sea surface temperature (SST) measurements. These adjustments are applied to compensate for systematic biases and changes in observing protocol. Better quantification of the adjustments and their uncertainties would increase confidence in estimated surface temperature change and provide higher-quality gridded SST fields for use in many applications.

Bias adjustments have been based on either physical models of the observing processes or the assumption of an unchanging relationship between SST and a reference dataset, such as night marine air temperature. These approaches produce similar estimates of SST bias on the largest space and time scales, but regional differences can exceed the estimated uncertainty. We describe challenges to improving our understanding of SST biases. Overcoming these will require clarification of past observational methods, improved modeling of biases associated with each observing method, and the development of statistical bias estimates that are less sensitive to the absence of metadata regarding the observing method.

New approaches are required that embed bias models, specific to each type of observation, within a robust statistical framework. Mobile platforms and rapid changes in observation type require biases to be assessed for individual historic and present-day platforms (i.e., ships or buoys) or groups of platforms. Lack of observational metadata and high-quality observations for validation and bias model development are likely to remain major challenges.

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