Potential controls of isoprene in the surface ocean.

Isoprene surface ocean concentrations and vertical distribution, atmospheric mixing ratios and calculated sea-to-air fluxes spanning approximately 125 degrees of latitude (80 °N - 45 °S) over the Arctic and Atlantic Oceans are reported. Oceanic isoprene concentrations were associated with a number o...

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Bibliographic Details
Published in:Global Biogeochemical Cycles
Main Authors: Hackenberg, SC, Andrews, SJ, Chance, RJ, Brewin, RJW, Tarran, GA, Tilstone, GH, Manaeian, JK, Small, A, Bouman, H, Dall’Olmo, G, Reifel, KM, Airs, RL, Cummings, DG, Lewis, AC, Carpenter, LJ
Format: Article in Journal/Newspaper
Language:English
Published: 2017
Subjects:
Atmospheric Sciences
Biology
Chemistry
Ecology and Environment
Marine Sciences
Oceanography
Arctic
Online Access:http://plymsea.ac.uk/id/eprint/7419/
http://plymsea.ac.uk/id/eprint/7419/5/Published.pdf
https://doi.org/10.1002/2016GB005531
Description
Summary:Isoprene surface ocean concentrations and vertical distribution, atmospheric mixing ratios and calculated sea-to-air fluxes spanning approximately 125 degrees of latitude (80 °N - 45 °S) over the Arctic and Atlantic Oceans are reported. Oceanic isoprene concentrations were associated with a number of concurrently monitored biological variables including chlorophyll a (Chl a), photo-protective pigments, integrated primary production (intPP) and cyanobacterial cell counts, with higher isoprene concentrations relative to all respective variables found at sea surface temperatures greater than 20 °C. The correlation between isoprene and the sum of photo-protective carotenoids, which is reported here for the first time, was the most consistent across all cruises. Parameterisations based on linear regression analyses of these relationships perform well for Arctic and Atlantic data, producing a better fit to observations than an existing Chl a–based parameterisation. Global extrapolations of isoprene surface water concentrations using satellite-derived Chl a and intPP were able to reproduce general trends in the in situ data and absolute values within a factor of 2 between 60% and 85% of the time, depending on the data set and algorithm used.

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