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Anderson, CR, Kudela RM, Kahru M, Chao Y, Rosenfeld LK, Bahr FL, Anderson DM, Norris TA.  2016.  Initial skill assessment of the California Harmful Algae Risk Mapping (C-HARM) system. Harmful Algae. 59:1-18.   10.1016/j.hal.2016.08.006   AbstractWebsite

Toxic algal events are an annual burden on aquaculture and coastal ecosystems of California. The threat of domoic acid (DA) toxicity to human and wildlife health is the dominant harmful algal bloom (HAB) concern for the region, leading to a strong focus on prediction and mitigation of these blooms and their toxic effects. This paper describes the initial development of the California Harmful Algae Risk Mapping (C-HARM) system that predicts the spatial likelihood of blooms and dangerous levels of DA using a unique blend of numerical models, ecological forecast models of the target group, Pseudo-nitzschia, and satellite ocean color imagery. Data interpolating empirical orthogonal functions (DINEOF) are applied to ocean color imagery to fill in missing data and then used in a multivariate mode with other modeled variables to forecast biogeochemical parameters. Daily predictions (nowcast and forecast maps) are run routinely at the Central and Northern California Ocean Observing System (CeNCOOS) and posted on its public website. Skill assessment of model output for the nowcast data is restricted to nearshore pixels that overlap with routine pier monitoring of HABs in California from 2014 to 2015. Model lead times are best correlated with DA measured with solid phase adsorption toxin tracking (SPATI') and marine mammal strandings from DA toxicosis, suggesting long-term benefits of the HAB predictions to decision making. Over the next three years, the C-HARM application system will be incorporated into the NOAA operational HAB forecasting system and HAB Bulletin. (C) 2016 Elsevier B.V. All rights reserved.

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Kahru, M, Mitchell BG.  1999.  Empirical chlorophyll algorithm and preliminary SeaWiFS validation for the California Current. International Journal of Remote Sensing. 20:3423-3429.   10.1080/014311699211453   AbstractWebsite

A new empirical chlorophyll algorithm is proposed for SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and other ocean colour sensors. The CAL-P6 algorithm uses a sixth-order polynomial of the ratio of normalized water leaving radiances (L-WN) at 490 nm and 555 nm and is based on 348 measurements of L-WN,, and chlorophyll-a in the California Current. Validation of the SeaWiFS-derived chlorophyll values with 27 concurrent in situ measurements showed high correlation (r(2) = 0.93 in the log-log space) but significant overestimation by SeaWiFS at high chlorophyll-a concentration. The problem was traced to significant underestimation of the SeaWiFS-derived L-WN,, (490) at high chlorophyll-a concentration (3-5mgm(-3)). Further refinement of the atmospheric correction is needed for SeaWiFS to attain its goal of 35% accuracy for chlorophyll retrieval in the coastal zone.

Kahru, M, Brotas V, Manzano-Sarabia M, Mitchell BG.  2011.  Are phytoplankton blooms occurring earlier in the Arctic? Global Change Biology. 17:1733-1739.   10.1111/j.1365-2486.2010.02312.x   AbstractWebsite

Time series of satellite-derived surface chlorophyll-a concentration (Chl) in 1997-2009 were used to examine for trends in the timing of the annual phytoplankton bloom maximum. Significant trends towards earlier phytoplankton blooms were detected in about 11% of the area of the Arctic Ocean with valid Chl data, e.g. in the Hudson Bay, Foxe Basin, Baffin Sea, off the coasts of Greenland, in the Kara Sea and around Novaya Zemlya. These areas roughly coincide with areas where ice concentration has decreased in early summer (June), thus making the earlier blooms possible. In the selected areas, the annual phytoplankton bloom maximum has advanced by up to 50 days which may have consequences for the Arctic food chain and carbon cycling. Outside the Arctic, the annual Chl maximum has become earlier in boreal North Pacific but later in the North Atlantic.

Kahru, M, Kudela RM, Anderson CR, Mitchell BG.  2015.  Optimized merger of ocean chlorophyll algorithms of MODIS-Aqua and VIIRS. Ieee Geoscience and Remote Sensing Letters. 12:2282-2285.   10.1109/lgrs.2015.2470250   AbstractWebsite

Standard ocean chlorophyll-a (Chla) products from currently operational satellite sensors Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Visible Infrared Imager Radiometer Suite (VIIRS) underestimate medium and high in situ Chla concentrations and have approximately 9% bias between each other in the California Current. By using the regional optimization approach of Kahru et al., we minimized the differences between satellite estimates and in situ match-ups as well as between estimates of the two satellite sensors and created improved empirical algorithms for both sensors. The regionally optimized Chla estimates from MODIS-Aqua and VIIRS have no bias between each other, have improved retrievals at medium to high in situ Chla, and can be merged to improve temporal frequency and spatial coverage and to extend the merged time series.

Kahru, M, Kudela R, Manzano-Sarabia M, Mitchell BG.  2009.  Trends in primary production in the California Current detected with satellite data. Journal of Geophysical Research-Oceans. 114   10.1029/2008jc004979   AbstractWebsite

Several ocean primary production algorithms using satellite data were evaluated on a large archive of net primary production (NPP) and chlorophyll-a (Chl-a) measurements collected by the California Cooperative Fisheries Investigations program in the California Current. The best algorithm matching in situ data was found by empirically adjusting the Behrenfeld-Falkowski Vertically Generalized Production Model. Satellite-derived time series of NPP were calculated for the California Current area. Significant increase in NPP and Chl-a annual peak levels, i.e., the "bloom magnitude,'' were found along the coasts of the California Current as well as other major eastern boundary currents for the period of modern ocean color data (1997-2007). The reasons for this increase are not clear but are associated with various environmental conditions.

Kahru, M, Kudela RM, Manzano-Sarabia M, Mitchell BG.  2012.  Trends in the surface chlorophyll of the California Current: Merging data from multiple ocean color satellites. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 77-80:89-98. Abstract

Standard remote sensing reflectance products from four ocean color sensors (OCTS, SeaWiFS, MODISA, MERIS) and over 10,000 in situ measurements of surface chlorophyll-a (Chl-a) concentration in the California Current were used to create empirical algorithms that are consistent with in situ data as well as between individual sensors. Using these algorithms, a merged multi-sensor time series of the surface Chl-a concentration in California Current region was created. The merged Oil-a time series (November 1996-December 2011) show a significant (P < 0.01) increasing trend off central California and significant (P < 0.01) decreasing trends in the central North Pacific gyre and off southern Baja California. Although this 15-year time series is too short to separate interannual and multidecadal cycles from climate trends, both of these trends are consistent with the predicted effects of global warming. The expected increase in vertical stratification of the water column and the resulting decreased vertical flux of nutrients would lead to lower Chl-a in the gyre but the increased upwelling-favorable winds leading to stronger upwelling off central California or the increased nitrate content of the upwelled water would lead to higher Chl-a in the upwelling region. The decreased Chl-a off southern Baja California resembles the effect of a decreased influence of strong El Nino events. (c) 2012 Elsevier Ltd. All rights reserved.

Kahru, M, Kudela RM, Anderson CR, Manzano-Sarabia M, Mitchell BG.  2014.  Evaluation of satellite retrievals of ocean chlorophyll-a in the California Current. Remote Sensing. 6:8524-8540.   10.3390/rs6098524   AbstractWebsite

Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R-2) between 0.79 and 0.88 and a median absolute percent error (MdAPE) between 21% and 27%. However, at in situ Chla > 1 mg m(-3), only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a) maintained reasonable accuracy (R-2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively), while the other sensors had R-2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.

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.

Kahru, M, Di Lorenzo E, Manzano-Sarabia M, Mitchell BG.  2012.  Spatial and temporal statistics of sea surface temperature and chlorophyll fronts in the California Current. Journal of Plankton Research. 34:749-760.   10.1093/plankt/fbs010   AbstractWebsite

The statistics of sea-surface fronts detected with the automated histogram method were studied in the California Current using sea-surface temperature (SST) and chlorophyll-a concentration (Chl) images from various satellite sensors. Daily maps of fronts were averaged into monthly composites of front frequency (FF) spanning 29 years (19812009) for SST and 14 years (19972010) for Chl. The large-scale distributions of frontal frequency of both SST (FFsst) and of Chl (FFchl) had a 500700 km wide band of elevated values (47) along the coast that roughly coincided with the area of increased mesoscale eddy activity. FFsst and FFchl were positively correlated at monthly and seasonal frequencies, but the year-to-year variations were not significantly correlated. The long-period (1 year and longer) variability in FFsst is influenced by the large-scale SST gradient, while at shorter timescales the influence of the Coastal Upwelling Index is evident. In contrast with FFsst, FFchl variability is less related to the coherent large-scale forcing and has stronger sensitivity to local forcings in individual areas. Decadal-scale increasing trends in the frequency of both SST and Chl fronts were detected in the Ensenada Front area (general area of the A-Front study) and corresponded to, respectively, trends towards colder SST and increasing chlorophyll-a concentration.

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.

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Mitchell, BG, Kahru M.  1998.  Algorithms for SeaWiFS standard products developed with the CalCOFI big-optical data set. California Cooperative Oceanic Fisheries Investigations Reports. 39:133-147. AbstractWebsite

Funding from NASA's Ocean Biogeochemistry Program and the Goddard Space Flight Center SeaWiFS Project was used to implement an ocean optics program as part of the routine cruises of the California Cooperative Oceanic Fisheries Investigations (CalCOFI). Since August 1993, data from more than 300 bio-optical stations have been acquired, merged with complementary data, and made available for developing remote sensing algorithms. The profiling instrument consisted of a Biospherical Instruments, Inc. MER-2040/2041 radiometer integrated with CTD probes, a transmissometer, and a fluorometer. A detailed calibration time series of the radiance and irradiance sensors has been maintained to ensure maximum accuracy. The data set has been used to develop empirical algorithms for Sea WiFS standard products including chlorophyll a (chl a), "CZCS pigments," and diffuse attenuation coefficient K-d(490). Algorithms using cubic regressions of remote sensing reflectance (R-rs) ratios provided the best estimation of chi a and pigments over the full range of chl a (0.05-22.3 mg m(-3)). Multiple linear regressions of multiple-band ratios proved to be less robust. Relationships between spectral K and chi a suggest that previous K algorithms may have errors due to estimates of pure-water absorption.

Murakami, H, Sasaoka K, Hosoda K, Fukushima H, Toratani M, Frouin R, Mitchell BG, Kahru M, Deschamps PY, Clark D, Flora S, Kishino M, Saitoh S, Asanuma I, Tanaka A, Sasaki H, Yokouchi K, Kiyomoto Y, Saito H, Dupouy C, Siripong A, Matsumura S, Ishizaka J.  2006.  Validation of ADEOS-II GLI ocean color products using in-situ observations. Journal of Oceanography. 62:373-393.   10.1007/s10872-006-0062-6   AbstractWebsite

The Global Imager (GLI) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) made global observations from 2 April 2003 to 24 October 2003. In cooperation with several institutes and scientists, we obtained quality controlled match-ups between GLI products and in-situ data, 116 for chlorophyll-a concentration (CHLA), 249 for normalized water-leaving radiance (nLw) at 443 nm, and 201 for aerosol optical thickness at 865 nm (Tau_865) and Angstrom exponent between 520 and 865 nm (Angstrom). We evaluated the GLI ocean color products and investigated the causes of errors using the match-ups. The median absolute percentage differences (MedPD) between GLI and in-situ data were 14.1-35.7% for nLws at 380-565 nm 52.5-74.8% nLws at 625-680 nm, 47.6% for Tau_865, 46.2% for Angstrom, and 46.6% for CHLA, values that are comparable to the ocean-color products of other sensors. We found that some errors in GLI products are correlated with observational conditions; nLw values were underestimated when nLw at 680 nm was high, CHLA was underestimated in absorptive aerosol conditions, and Tau_865 was overestimated in sunglint regions. The error correlations indicate that we need to improve the retrievals of the optical properties of absorptive aerosols and seawater and sea surface reflection for further applications, including coastal monitoring and the combined use of products from multiple sensors.