Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data. Issue 1 (5th January 2018)

• Record Type: Journal Article
• Authors: Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.
• Is Part Of: Journal of geophysical research. Volume 123:Issue 1(2018)
• Page Start: 22
• Page End: 39
• Publication Date: 2018-01-05
• Subjects: variogram -- geostatistics -- SeaWiFS -- MODIS -- error -- patchiness; Oceanography -- Periodicals; 551.4605
• DOI: 10.1002/2017JC013023
• Languages: English
• ISSNs: 2169-9275

Abstract

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. Key Points: Geostatistical techniques isolate mesoscale variability independent of satellite platform Unresolved variability scales proportional to surface chlorophyll except low‐chlorophyll regions Physical stirring of large‐scale gradient supports observed mesoscale variability in surface chlorophyll