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Kahru, M, Jacox MG, Ohman MD.  2018.  CCE1: Decrease in the frequency of oceanic fronts and surface chlorophyll concentration in the California Current System during the 2014-2016 northeast Pacific warm anomalies. Deep-Sea Research Part I-Oceanographic Research Papers. 140:4-13.   10.1016/j.dsr.2018.04.007   AbstractWebsite

Oceanic fronts are sites of increased vertical exchange that are often associated with increased primary productivity, downward flux of organic carbon, and aggregation of plankton and higher trophic levels. Given the influence of fronts on the functioning of marine ecosystems, an improved understanding of the spatial and temporal variability of frontal activity is desirable. Here, we document changes in the frequency of sea-surface fronts and the surface concentration of chlorophyll-a (Chla) in the California Current System that occurred during the Northeast Pacific anomalous warming of 2014-2015 and El Nino of 2015-2016, and place those anomalies in the context of two decades of variability. Frontal frequency was detected with the automated histogram method using datasets of sea-surface temperature (SST) and Chla from multiple satellite sensors. During the anomalous 2014-2016 period, a drop in the frequency of fronts coincided with the largest negative Chla anomalies and positive SST anomalies in the whole period of satellite observations (1997-2017 for Chla and 1982-2017 for SST). These recent reductions in frontal frequency ran counter to a previously reported increasing trend, though it remains to be seen if they represent brief interruptions in that trend or a reversal that will persist going forward.

Kahru, M, Jacox MG, Lee Z, Kudela RM, Manzano-Sarabia M, Mitchell BG.  2015.  Optimized multi-satellite merger of primary production estimates in the California Current using inherent optical properties. Journal of Marine Systems. 147:94-102.   10.1016/j.jmarsys.2014.06.003   AbstractWebsite

Building a multi-decadal time series of large-scale estimates of net primary production (NPP) requires merging data from multiple ocean color satellites. The primary product of ocean color sensors is spectral remote sensing reflectance (Rrs). We found significant differences (13-18% median absolute percent error) between Rrs estimates at 443 nm of different satellite sensors. These differences in Rrs are transferred to inherent optical properties and further on to estimates of NPP. We estimated NPP for the California Current region from three ocean color sensors (SeaWiFS, MODIS-Aqua and MERIS) using a regionally optimized absorption based primary production model (Aph-PP) of Lee et al. (2011). Optimization of the Aph-PP model was required for each individual satellite sensor in order to make NPP estimates from different sensors compatible with each other. While the concept of Aph-PP has advantages over traditional chlorophyll-based NPP models, in practical application even the optimized Aph-PP model explained less than 60% of the total variance in NPP which is similar to other NPP algorithms. Uncertainties in satellite Rrs estimates as well as uncertainties in parameters representing phytoplankton depth distribution and physiology are likely to be limiting our current capability to accurately estimate NPP from space. Introducing a generic vertical profile for phytoplankton improved slightly the skill of the Aph-PP model. (C) 2014 Elsevier B.V. All rights reserved.