Geostatistical analysis of mesoscale spatial variability and error in SeaWiFS and MODIS/Aqua global ocean color data Glover, David M. Doney, Scott C. Oestreich, William K. Tullo, Alisdair W. 2018-03-15T19:21:41Z 2018-03-15T19:21:41Z 2018-01-05
dc.description © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 123 (2018): 22–39, doi:10.1002/2017JC013023. en_US
dc.description.abstract Mesoscale (10–300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998–2010) and 8 year MODIS/Aqua (2003–2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation. en_US
dc.description.sponsorship NASA's Ocean Biology and Biogeochemistry Grant Numbers: NNG05GG30G, NNG05GR34G, NNX14AM36G, NNX14AL86G, NNX15AE65G; Ocean Biology Processing Group (OBPG) at NASA's Goddard Space Flight Center en_US
dc.identifier.citation Journal of Geophysical Research: Oceans 123 (2018): 22–39 en_US
dc.identifier.doi 10.1002/2017JC013023
dc.language.iso en_US en_US
dc.publisher John Wiley & Sons en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri *
dc.subject Variogram en_US
dc.subject Geostatistics en_US
dc.subject SeaWiFS en_US
dc.subject MODIS en_US
dc.subject Error en_US
dc.subject Patchiness en_US
dc.title Geostatistical analysis of mesoscale spatial variability and error in SeaWiFS and MODIS/Aqua global ocean color data en_US
dc.type Article en_US
dspace.entity.type Publication
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