Methods in Oceanography最新文献

Autosamplers are ubiquitous tools in laboratories, and an integral part of many analytical instruments. However, most autosamplers are expensive, and as such they are not used in all laboratories. One option is to purchase an analytical instrument without its autosampler, and integrate an autosampler from another supplier. Using scripting, it is possible to couple any autosampler with any analytical instrument, as long as both have a graphical user interface (GUI). Here we show that it is possible to integrate an inexpensive robotic arm kit, which has a GUI, to any analytical device that also has a GUI. The coupling is simple and does not require any electronic knowledge. We demonstrated that the robotic arm worked as an autosampler with 3 different analytical instruments for 8 different chemical measurements: total alkalinity, pH, total carbon, total organic carbon (including isotopic composition), total inorganic carbon (including isotopic composition) and total nitrogen in water samples. The setup is an economical alternative to the common liquid autosamplers.

In order to correctly understand the rates and mechanisms of biogeochemical cycling along the water column, special attention must be paid to data analysis techniques.

We propose a revised procedure combining precision and practicality to minimize sample handling errors that would affect the determination of both mass fluxes and the composition of material collected by sediment traps in the Antarctic region. The key points to take in account are: (i) the mesh size used for removing “large” particles or aggregates (from 150 micron to 1 mm); (ii) the absence of filters; and (iii) the use of a microscope to pick out “swimmers”.

We also recommend: removal of all swimmers using a 650-micron mesh; analysis using a stereomicroscope; and quantitative subdividing using a peristaltic pump.

Whitecaps on the ocean surface mark localized areas where interactions between the atmosphere and ocean are enhanced. Contemporary methods of quantifying total whitecap coverage rely on converting color sea surface images into their binary equivalent using specific threshold-based automated algorithms. However, there are very few studies that have separated and quantified whitecap coverage into its active (stage-A) and maturing (stage-B) evolutionary stages, which can potentially provide more suitable parameters for use in breaking wave models, air–sea gas transfer, aerosol production, and oceanic albedo studies. Previous active and maturing whitecap studies have used a pixel intensity separation technique, which involves first separating the whitecap and background pixels, and subsequently establishing a second threshold to distinguish between active and maturing whitecaps. In this study, a dataset of more than 64,000 images from the North Atlantic were initially processed to determine the total whitecap coverage using the Automated Whitecap Extraction method. The whitecap pixels of each image were then distinguished as either stage-A or stage-B whitecaps by applying a spatial separation technique which does not rely solely on pixel intensity information but also on the location (relative to the wave crest), visual intensity, texture and shape of each whitecap. The comparison between the spatial separation and pixel intensity separation techniques yielded average relative errors of 34.8% and $-44.0\%$ for stage-A and -B coverage, respectively. The pixel intensity method was found to be less suitable when compared to the spatial separation method as it relies on the assumption that the pixel intensity for stage-A is always greater than that for stage-B.

In the present study, an attempt has been made to estimate sea surface salinity (SSS) by blending in situ observations from the National Oceanic and Atmospheric Administration/Pacific Marine Environmental Laboratory—Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction buoy with satellite data from the Soil Moisture and Salinity Mission using objective analysis approach. A preliminary analysis is done in the tropical Indian Ocean at monthly time scale for the year 2010 at 0.25°latitude ×0.25°longitude resolution. Comparison with other independent in situ SSS observations suggests that the analyzed SSS takes the advantage of high spatial coverage by the satellite and accurate measurements from the buoy data and has potential for better SSS estimation.

The pigment absorption peak in the red waveband observed in phytoplankton and particulate absorption spectra is primarily associated with chlorophyll-$a$ and exhibits much lower pigment packaging compared to the blue peak. The minor contributions to the signature by accessory pigments can be largely removed by computing the line height absorption at 676 nm above a linear background between approximately 650 nm and 715 nm. The line height determination is also effective in removing the contributions to total or particulate absorption by colored dissolved organic matter and non-algal particles, and is relatively independent of the effects of biofouling. The line height absorption is shown to be significantly related to the extracted chlorophyll concentration over a large range of natural optical regimes and diverse phytoplankton cultures. Unlike the in situ fluorometric method for estimating chlorophyll, the absorption line height is not sensitive to incident irradiance, in particular non-photochemical quenching. The combination of the two methods provides a combination of robust phytoplankton biomass estimates, pigment based taxonomic information and a means to estimate the photosynthetic parameter, $E_K$, the irradiance at which photosynthesis transitions from light limitation to light saturation.

This paper describes my career in Ocean Optics over nearly half a century. It was centered around the Inherent Optical Properties (IOP, the scattering and absorption properties of sea water and its dissolved and suspended materials). The paper describes the development of instrumentation for the measurement of the IOP, the applicable theories, and the inversions to obtain biogeochemical parameters. This is not intended to be a thorough review, but rather describes a personal journey.

A dataset consisting of AC-S measurements of (hyper-) spectral particulate absorption, scattering and attenuation coefficients were obtained from measurements performed on the flow-through system of the R/V Tara during its 2.5-year long expedition.

The AC-S instruments were robust, working continuously with weekly maintenance for about 3 months at a time, and provided absorption (attenuation) data for 454 (375) days, or 90% (75%) of total possible days during the expedition.

This dataset has been mapped to 1 km×1 km bins to avoid over emphasizing redundant data, and to match the spatial scale of typical ocean color satellite sensors. It consists of nearly 70,000 particulate absorption spectra and about 60,000 particulate scattering and attenuation spectra. These data are found to be consistent with chlorophyll extraction and with the published average shapes of particulate absorption and scattering spectra and bio-optical relationships. This dataset is richer than previous ones in the data from open-ocean (oligotrophic) environments making it more representative of global distributions and of utility for global algorithm development.

Forecasting Optics REaltime in Shallow Energetic Environments (FORESEE) was developed for predictions of underwater visibility in dynamic surf zone environments. FORESEE employs key measurements of physical forcing and beam attenuation coefficient (beam c) and numerical wave and hydrodynamic models to: (1) generate predictions of energy variation, (2) relate energy characteristics to the optical property of interest, beam c, and (3) produce 24-hr forecast maps of spatially resolved visibility conditions at a site of interest. FORESEE beam c prediction performance was very good using site-specific data collected in Waimanalo, Hawaii (average root mean squared error of 0.38 m⁻¹). Predictions of probability of object detection (P_d) were on average within 75% accuracy for 2-m diver visibility. Differences between modeled and measured P_d may have been affected by a phytoplankton bloom that was observed during field data collection. The addition of a growth term and a bottom-type term to the model could account for biological processes and differing bottom types in nearshore regions. Further improvements could also be made with more accurate model boundary conditions.

Determinations of inherent optical properties of natural waters are fundamental in marine optical research. In situ measurements of light absorption are mostly obtained with an instrument that uses a reflective tube design to reduce concomitant errors induced by light scattering (ac-9, WETLabs Inc.). The remaining, generally still substantial, error is commonly corrected using one of a number of different approaches, each of which is based on a set of assumptions. Until now, the errors in these measurements have only been theoretically examined using Monte Carlo modeling Leymarie et al. (2010). The study presented here used a lab-based point source integrating cavity absorption meter (PSICAM) which avoids scattering errors. The PSICAM data were used to evaluate the absorption determination with an ac-9 in coastal waters for each of the scattering correction approaches. The results showed that the assumption of negligible absorption at wavelengths >700 nm is not valid in coastal waters and that, as a result, ac-9 measurements strongly underestimate absorption at longer wavelengths (>600 nm). An empirical relationship between uncorrected (for scattering) ac-9 measurements and the true absorption at 715 nm was included in the correction scheme; this improved the quality of ac-9 data at longer wavelengths but showed overestimation at shorter wavelengths. However, additional inclusion of a scatter correction for the ac-9 attenuation measurement resulted in a significant improvement of the proportional scatter error correction across the spectrum. Despite these innovations, variations in scattering properties can, combined with low absorption at specific wavelengths, result in relatively large percentage errors for individual measurements.