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Kahru, M, Lee ZP, Mitchell BG.  2017.  Contemporaneous disequilibrium of bio-optical properties in the Southern Ocean. Geophysical Research Letters. 44:2835-2842.   10.1002/2016gl072453   AbstractWebsite

Significant changes in satellite-detected net primary production (NPP, mgCm(-2)d(-1)) were observed in the Southern Ocean during 2011-2016: an increase in the Pacific sector and a decrease in the Atlantic sector. While no clear physical forcing was identified, we hypothesize that the changes in NPP were associated with changes in the phytoplankton community and reflected in the concomitant bio-optical properties. Satellite algorithms for chlorophyll a concentration (Chl a, mgm(-3)) use a combination of estimates of the remote sensing reflectance Rrs() that are statistically fitted to a global reference data set. In any particular region or point in space/time the estimate produced by the global mean algorithm can deviate from the true value. Reflectance anomaly (RA) is supposed to remove the first-order variability in Rrs() associated with Chl a and reveal bio-optical properties that are due to the composition of phytoplankton and associated materials. Time series of RA showed variability at multiple scales, including the life span of the sensor, multiyear and annual. Models of plankton functional types using estimated Chl a as input cannot be expected to correctly resolve regional and seasonal anomalies due to biases in the Chl a estimate that they are based on. While a statistical model using RA() time series can predict the times series of NPP with high accuracy (R-2=0.82) in both Pacific and Atlantic regions, the underlying mechanisms in terms of phytoplankton groups and the associated materials remain elusive.

Lin, JF, Lee Z, Ondrusek M, Kahru M.  2016.  Attenuation coefficient of usable solar radiation of the global oceans. Journal of Geophysical Research-Oceans. 121:3228-3236.   10.1002/2015jc011528   AbstractWebsite

Usable solar radiation (USR) represents spectrally integrated solar energy in the spectral range of 400-560 nm, a domain where photons penetrate the most in oceanic waters and thus contribute to photosynthesis and heating at deeper depths. Through purely numerical simulations, it was found that the diffuse attenuation coefficient of downwelling USR (K-d(USR), m(-1)) is nearly a constant vertically in the upper water column for clear waters and most turbid waters. Subsequently an empirical model was developed to estimate Kd(USR) based on the diffuse attenuation coefficient at 490 nm (Kd(490), m(-1)). We here evaluate this relationship using data collected from a wide range of oceanic and coastal environments and found that the relationship between Kd(490) and Kd(USR) developed via the numerical simulation is quite robust. We further refined this relationship to extend the applicability to "clearest" natural waters. This refined relationship was then used to produce sample distribution of Kd(USR) of global oceans. As expected, extremely low Kd(USR) (similar to 0.02 m(-1)) was observed in ocean gyres, while significantly higher Kd(USR) (similar to 5.2 m(-1)) was found in very turbid coastal regions. A useful application of Kd(USR) is to easily and accurately propagate surface USR to deeper depths, potentially to significantly improve the estimation of basin scale primary production and heat fluxes in the upper water column.

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.

Jacox, MG, Edwards CA, Kahru M, Rudnick DL, Kudela RM.  2015.  The potential for improving remote primary productivity estimates through subsurface chlorophyll and irradiance measurement. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 112:107-116.   10.1016/j.dsr2.2013.12.008   AbstractWebsite

A 26-year record of depth integrated primary productivity (PP) in the Southern California Current System (SCCS) is analyzed with the goal of improving satellite net primary productivity (PP) estimates. Modest improvements in PP model performance are achieved by tuning existing algorithms for the SCCS, particularly by parameterizing carbon fixation rate in the vertically generalized production model as a function of surface chlorophyll concentration and distance from shore. Much larger improvements are enabled by improving the accuracy of subsurface chlorophyll and light profiles. In a simple vertically resolved production model for the SCCS (VRPM-SC), substitution of in situ surface data for remote sensing estimates offers only marginal improvements in model r(2) (from 0.54 to 0.56) and total log(10) root mean squared difference (from 0.22 to 0.21), while inclusion of in situ chlorophyll and light profiles improves these metrics to 0.77 and 0.15, respectively. Autonomous underwater gliders, capable of measuring subsurface properties on long-term, long-range deployments, significantly improve PP model fidelity in the SCCS. We suggest their use (and that of other autonomous profilers such as Argo floats) in conjunction with satellites as a way forward for large-scale improvements in PP estimation. (C) 2013 Elsevier Ltd. All rights reserved.

Stramski, D, Reynolds RA, Kahru M, Mitchell BG.  1999.  Estimation of particulate organic carbon in the ocean from satellite remote sensing. Science. 285:239-242.   10.1126/science.285.5425.239   AbstractWebsite

Measurements from the Southern Ocean show that particulate organic carbon (POC) concentration is welt correlated with the optical backscattering by particles suspended in seawater. This relation, in conjunction with retrieval of the backscattering coefficient from remote-sensing reflectance, provides an algorithm for estimating surface POC from Satellite data of ocean color. Satellite imagery from SeaWiFS reveals the seasonal progression of POC, with a zonal band of elevated POC concentrations in December coinciding with the Antarctic Polar Front Zone. At that time, the POC pool within the top 100 meters of the entire Southern Ocean south of 40 degrees S exceeded 0.8 gigatons.

Kahru, M, Mitchell BG.  1998.  Spectral reflectance and absorption of a massive red tide off southern California. Journal of Geophysical Research-Oceans. 103:21601-21609.   10.1029/98jc01945   AbstractWebsite

Spectral reflectance and absorption of a massive Lingulodinium (Gonyaulax) polyedra red tide in March 1995 off southern California are compared to a "baseline" of biooptical measurements from the California Cooperative Oceanic Fisheries Investigations. The red tide was characterized by increased absorption and therefore reduced remote sensing reflectance (R(rs)) in the 340-400 nm spectral range. The increased ultraviolet absorption was probably caused by mycosporine-like amino acids in the particulate fraction as well as increased absorption by dissolved organic matter. The chlorophyll a (chl a) specific particulate absorption of the L. polyedra bloom in the visible spectral range remained relatively constant for the chi a range 1-150 mg m(-3) indicating accumulation of cells with similar optical characteristics. The difference in the R(rs) versus chl a relationship of the red tide and "normal" California Current phytoplankton diminished with increasing wavelength from 340 nm and disappeared at 412 nm. Ratios of R(rs) at 340 nm (or 380 nm) and 412 nm (or 443 nm) provided differentiation of the red tide starting at chi a concentration of 1-2 mg m(-3). The forthcoming Japanese Global Imager (GLI) satellite sensor has, among others, the 380 nm band. If the signal to noise ratio and atmospheric correction for the 380 nm band are sufficient to retrieve the dynamic range of the water leaving radiance, then it might be possible to differentiate red tides from other phytoplankton bloods with the algorithm described here.