Export 6 results:
Sort by: Author [ Title  (Asc)] Type Year
A B C D E F G H I J K L M N [O] P Q R S T U V W X Y Z   [Show ALL]
O'Reilly, JE, Maritorena S, Siegel D, O'Brien MO, Toole D, Mitchell BG, Kahru M, Chavez F, Strutton PG, Cota GF, Hooker SB, McClain C, Carder K, Muller-Karger F, Harding L, Magnuson A, Phinney D, Moore G, Aiken J, Arrigo KR, Letelier RM, Culver M.  2000.  Ocean color chlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. SeaWiFS Postlaunch Calibration and Validation Analyses. 11( McClain CR, Ed.).:9-23., Greenbelt, Md.: Goddard Space Flight Center Abstract
O'Reilly, JE, Maritorena S, Mitchell BG, Siegel DA, Carder KL, Garver SA, Kahru M, McClain C.  1998.  Ocean color chlorophyll algorithms for SeaWiFS. Journal of Geophysical Research-Oceans. 103:24937-24953.   10.1029/98jc02160   AbstractWebsite

A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color chlorophyll algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The radiance-chlorophyll data were assembled from various sources during the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is composed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 mu g L(-1). Most of the observations are from Case I nonpolar waters, and similar to 20 observations are from more turbid coastal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlorophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic polynomial formulations were generally superior to other kinds of equations. Empirical algorithms with increasing complexity (number of coefficients and wavebands), were calibrated to the SeaBAM data, and evaluated to illustrate the relative merits of different formulations. The ocean chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) function which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and has been chosen as the at-launch SeaWiFS operational chlorophyll a algorithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ratio formulation. This maximum band ratio (MBR) is a new approach in empirical ocean color algorithms and has the potential advantage of maintaining the highest possible satellite sensor signal:noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.

Kahru, M, Marinone SG, Lluch-Cota SE, Pares-Sierra A, Mitchell BG.  2004.  Ocean-color variability in the Gulf of California: scales from days to ENSO. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 51:139-146.   10.1016/j.dsr2.2003.04.001   AbstractWebsite

Time series of surface chlorophyll a concentration (C-sat) and phytoplankton net primary production (NPP) in the Gulf of California were derived using satellite data from OCTS, SeaWiFS, MODIS, AVHRR and the VGPM primary productivity model. The 6-year (1997-2003) time series showed variability at a multitude of scales. The annual cycle was the dominant mode in Gat variability in the entire gulf, except just south of the midriff islands where the semiannual cycle dominated. The semiannual cycle has C-sat maxima during the spring and fall transition periods when the general circulation is switching between cyclonic in the summer and anticyclonic in the winter and is less developed, therefore allowing a more efficient tidal mixing. The spring and fall maxima often consisted of multiple peaks of about 10 days. A significant peak at about 1 month was often present in the short-term C-sat variability, especially in areas near the midriff islands, suggesting the influence of tidal mixing. The interannual variability was dominated by the 1997-98 El Nino and the following La Nina. During the El Nino period NPP decreased by 30-40% in the southern part of the gulf (by approximately 1 Tg C month(-1)), but the changes in the central and northern parts were less evident. (C) 2004 Elsevier Ltd. All rights reserved.

Frants, M, Gille ST, Hewes CD, Holm-Hansen O, Kahru M, Lombrozo A, Measures CI, Mitchell BG, Wang HL, Zhou M.  2013.  Optimal multiparameter analysis of source water distributions in the Southern Drake Passage. Deep-Sea Research Part Ii-Topical Studies in Oceanography. 90:31-42.   10.1016/j.dsr2.2012.06.002   AbstractWebsite

In order to evaluate the effects of horizontal advection on iron supply in the vicinity of the Shackleton Transverse Ridge (SIR) in the southern Drake Passage, the water composition in the region is estimated along the isopycnal containing the subsurface iron peak. Optimal Multiparameter (OMP) analysis of temperature, salinity, oxygen and nutrient data is used to estimate the water composition at CID stations sampled in summer 2004 and winter 2006. The highest iron concentrations in the Ona Basin are found below the mixed layer, both in summer and in winter. The water composition derived from the OMP analysis is consistent with a scenario in which iron-rich shelf waters from the South Shetland Islands and the Antarctic Peninsula are advected northward on the eastern side of the SIR, where they interact with the low-iron waters of the Antarctic Circumpolar Current (ACC) in the Ona Basin. The shelf waters and the ACC waters appear to interact through a stirring process without fully mixing, resulting in a filamented distribution that has also been inferred from the satellite data. To the west of the STR, the shelf waters are primarily confined to the continental shelf, and do not extend northwards. This source of water distribution is consistent with the idea that iron enters the Ona Basin from the continental shelf through advection along an isopycnal, resulting in an iron concentration peak occurring below the winter mixed layer in the Ona Basin. (c) 2012 Elsevier Ltd. All rights reserved.

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, 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.