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The aftermath of the 2010 Deepwater Horizon oil spill highlighted the lack of baseline spatial, behavioral, and abundance data for many species, including imperiled marine turtles, across the Gulf of Mexico. The ecology of marine turtles is closely tied to their vertical movements within the water column and is therefore critical knowledge for resource management in a changing ocean. A more comprehensive understanding of diving behavior, specifically surface intervals, can improve the accuracy of density and abundance estimates by mitigating availability bias. Here, we focus on the proportion of time marine turtles spend at the top 2 m of the water column to coincide with depths where turtles are assumed visible to observers during aerial surveys. To better understand what environmental and oceanographic conditions influence time at surface, we analyzed dive and spatial data from 136 satellite tags attached to three species of threatened or endangered marine turtles across 10 years. We fit generalized additive models with 11 remotely sensed covariates, including sea surface temperature (SST), bathymetry, and salinity, to examine dive patterns. Additionally, the developed model is the first to explicitly examine the potential connection between turtle dive patterns and ocean frontal zones in the Gulf of Mexico. Our results show species-specific associations of environmental covariates related to increased time at surface, particularly for depth, salinity, and frontal features. We define seasonal and spatial variation in time-at-surface patterns in an effort to contribute to marine turtle density and abundance estimates. These estimates could then be utilized to generate correction factors for turtle detection availability during aerial surveys.

Operational coarse-resolution satellite thermal sensors designed for global oceans are often insufficient for evaluating surface temperature of small water bodies. Here, the quality of the thermal data, collected by the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), over several South Florida estuaries, Chesapeake Bay, and Lake Okeechobee is evaluated using both in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) Sea Surface Temperature (SST) data. Overall, for SST between ~6 and ~32 °C, ECOSTRESS LST (Land Surface Temperature, used as a surrogate for SST in this study) appears to be slightly underestimated, with the underestimation being more severe at night (−1.13 °C) than during the day (−0.64 °C), in spring and summer (−1.25 ± 1.39 °C) than in autumn and winter (−0.57 ± 0.98 °C), and after May 2019 when two of the five bands failed. The root-mean-square uncertainties of ECOSTRESS SST are generally within 1–2 °C. Spatial analysis further suggests that ECOSTRESS SST covers waters closer to shore and reveals more spatial features than MODIS, with comparable image noise. From these observations, after proper georeferencing and empirical correction of the negative bias, ECOSTRESS SST may be used to evaluate the thermal environments of small water bodies, thus filling gaps in the coarse-resolution satellite data.

Since 2008, the world’s largest blooms of the green macroalgae, Ulva prolifera, have occurred every summer in the Yellow Sea, posing the question of whether these macroalgal blooms (MABs) have changed the phytoplankton biomass due to their perturbations of nutrient dynamics. We have attempted to address this question using long-term Moderate Resolution Imaging Spectroradiometer (MODIS) observations. A new MODIS monthly time-series of chlorophyll-a concentrations (Chl-a, an index of phytoplankton biomass) was generated after removing the macroalgae-contaminated pixels that were characterized by unexpectedly high values in the daily Chl-a products. Compared with Chl-a during July of 2002–2006 (the pre-MAB period), Chl-a during July of 2008–2012 (the MAB period) exhibited significant increases in the offshore Yellow Sea waters (rich in macroalgae), with mean Chl-a increased by 98% from 0.64 µg/L to 1.26 µg/L in the study region. In contrast, no significant Chl-a changes were observed during June between the two periods. After analyzing sea surface temperature, photosynthetically available radiation, and nutrient availability, we speculate that the observed Chl-a changes are due to nutrient competition between macroalgae and phytoplankton: during the MAB period, the fast-growing macroalgae would uptake the increased nutrients from the origin of Jiangsu Shoal; thus, the nutrients available to phytoplankton were reduced, leading to no apparent increases in biomass in the offshore Yellow Sea in June.

The most recent Visible Infrared Imager Radiometer Suite (VIIRS) is not equipped with a spectral band to detect solar-stimulated phytoplankton fluorescence. The lack of such a band may affect the ability of VIIRS to detect and quantify harmful algal blooms (HABs) in coastal waters rich in colored dissolved organic matter (CDOM) because of the overlap of CDOM and chlorophyll absorption within the blue-green spectrum. A recent HAB dominated by the toxin-producing dinoflagellate Karenia brevis in the northeastern Gulf of Mexico, offshore of Florida’s Big Bend region, allowed for comparison of the capacities of VIIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) to detect blooms in CDOM-rich waters. Both VIIRS and MODIS showed general consistency in mapping the CDOM-rich dark water, which measured a maximum area of 8900 km2 by mid-July 2014. However, within the dark water, only MODIS allowed detection of bloom patches—as indicated by high normalized fluorescence line height (nFLH). Field surveys between late July and mid-September confirmed Karenia brevis at bloom abundances up to 20 million cells·L−1 within these patches. The bloom patches were well captured by the MODIS nFLH images, but not by the default chlorophyll a concentration (Chla) images from either MODIS or VIIRS. Spectral analysis showed that VIIRS could not discriminate these high-phytoplankton water patches within the dark water due to its lack of fluorescence band. Such a deficiency may be overcome with new algorithms or future satellite missions such as the U.S. NASA’s Pre-Aerosol-Clouds-Ecology mission and the European Space Agency’s Sentinel-3 mission.

The temporal and spatial variation in submesoscale eddies in the coastal region of Lianyungang (China) is studied over a period of nearly two years with high-resolution (0.03°, about 3 km) observations of surface currents derived from high-frequency coastal radars (HFRs). The centers and boundaries of submesoscale eddies are identified based on a vector geometry (VG) method. A color index (CI) representing MODIS ocean color patterns with a resolution of 500 m is used to compute CI gradient parameters, from which submesoscale features are extracted using a modified eddy-extraction approach. The results show that surface currents derived from HFRs and the CI-derived gradient parameters have the ability to capture submesoscale processes (SPs). The typical radius of an eddy in this region is 2−4 km. Although no significant difference in eddy properties is observed between the HFR-derived current fields and CI-derived gradient parameters, the CI-derived gradient parameters show more detailed eddy structures due to a higher resolution. In general, the HFR-derived current fields capture the eddy form, evolution and dissipation. Meanwhile, the CI-derived gradient parameters show more SPs and fill a gap left by the HFR-derived currents. This study shows that the HFR and CI products have the ability to detect SPs in the ocean and contribute to SP analyses.

A new empirical Chl-a algorithm has been developed and validated for the largest freshwater lake of China (Poyang Lake) using a normalized green-red difference index (NGRDI), where the uncertainty was estimated to be ~25 mg·L−1 total suspended sediments or TSS) masked. The long-term Chl-a distribution showed significant spatial gradient and temporal variability, with Chl-a ranging between 2.4 ± 0.2 mg·m−3 in April and 4.4 ± 1.0 mg·m−3 in July and no significant increasing or decreasing trend during the 10-year period. In waters where Chl-a was retrievable (i.e., where TSS is 10 mg·m−3) in summer. The study not only provides, for the first time, synoptic baseline information on the lake’s Chl-a distributions and potential eutrophic regions, but also demonstrates a practical approach that might be extended to assess eutrophication conditions in other inland waters.

For near real-time water applications, the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua are currently the only satellite instruments that can provide well-calibrated top-of-atmosphere (TOA) radiance data over the global aquatic environments. However, TOA radiance data in the MODIS ocean bands over turbid atmosphere in east China often saturate, leaving only four land bands to use. In this study, an approach based on Empirical Orthogonal Function (EOF) analysis has been developed and validated to estimate chlorophyll a concentrations (Chla, μg/L) in surface waters of Taihu Lake, the third largest freshwater lake in China. The EOF approach analyzed the spectral variance of normalized Rayleigh-corrected reflectance (Rrc) data at 469, 555, 645, and 859 nm, and subsequently related that variance to Chla using 28 concurrent MODIS and field measurements. This empirical algorithm was then validated using another 30 independent concurrent MODIS and field measurements. Image analysis and radiative transfer simulations indicated that the algorithm appeared to be tolerant to aerosol perturbations, with unbiased RMS uncertainties of

A “black water” event, as observed from satellites, occurred off southwest Florida in 2012. Satellite observations suggested that the event started in early January and ended in mid-April 2012. The black water patch formed off central west Florida and advected southward towards Florida Bay and the Florida Keys with the shelf circulation, which was confirmed by satellite-tracked surface drifter trajectories. Compared with a previous black water event in 2002, the 2012 event was weaker in terms of spatial and temporal coverage. An in situ survey indicated that the 2012 black water patch contained toxic K. brevis and had relatively low CDOM (colored dissolved organic matter) and turbidity but high chlorophyll-a concentrations, while salinity was somewhat high compared with historical values. Further analysis revealed that the 2012 black water was formed by the K. brevis bloom initiated off central west Florida in late September 2011, while river runoff, Trichodesmium and possibly submarine groundwater discharge also played important roles in its formation. Black water patches can affect benthic coral reef communities by decreasing light availability at the bottom, and enhanced nutrient concentrations from black water patches support massive macroalgae growth that can overgrow coral reefs. It is thus important to continue the integrated observations where satellites provide synoptic and repeated observations of such adverse water quality events.

A comparison between efforts to detect methane anomalies by a simple band ratio approach from the Airborne Visual Infrared Imaging Spectrometer-Classic (AVIRIS-C) data for the Kern Front oil field, Central California, and the Coal Oil Point marine hydrocarbon seep field, offshore southern California, was conducted. The detection succeeded for the marine source and failed for the terrestrial source, despite these sources being of comparable strength. Scene differences were investigated in higher spectral and spatial resolution collected by the AVIRIS-C successor instrument, AVIRIS Next Generation (AVIRIS-NG), by a sensitivity study. Sensitivity to factors including water vapor, aerosol, planetary boundary layer (PBL) structure, illumination and viewing angle, and surface albedo clutter were explored. The study used the residual radiance method, with sensitivity derived from MODTRAN (MODerate resolution atmospheric correction TRANsmission) simulations of column methane (XCH4). Simulations used the spectral specifications and geometries of AVIRIS-NG and were based on a uniform or an in situ vertical CH4 profile, which was measured concurrent with the AVIRIS-NG data. Small but significant sensitivity was found for PBL structure and water vapor; however, highly non-linear, extremely strong sensitivity was found for surface albedo error. For example, a 10% decrease in the surface albedo corresponded to a 300% XCH4 increase over background XCH4 to compensate for the total signal, less so for stronger plumes. This strong non-linear sensitivity resulted from the high percentage of surface-reflected radiance in the airborne at-sensor total radiance. Coarse spectral resolution and feedback from interferents like water vapor underlay this sensitivity. Imaging spectrometry like AVIRIS and the Hyperspectral InfraRed Imager (HyspIRI) candidate satellite mission, have the advantages of contextual spatial information and greater at-sensor total radiance. However, they also face challenges due to their relatively broad spectral resolution compared to trace gas specific orbital sensors, e.g., the Greenhouse gases Observing SATellite (GOSAT), which is especially applicable to trace gas retrievals over scenes with high spectral albedo variability. Results of the sensitivity analysis are applicable for the residual radiance method and CH4 profiles used in the analysis, but they illustrate potential significant challenges in CH4 retrievals using other approaches.

Particle size distribution (PSD) is an important parameter that is relevant to many aspects of marine ecosystems, such as phytoplankton functional types, optical absorption and scattering from particulates, sediment fluxes, and carbon export. However, only a handful of studies have documented the PSD variability in different regions. Here, we investigate the PSD properties and variability in two shallow and semi-enclosed seas (the Bohai Sea (BS) and Yellow Sea (YS)), using in situ laser diffraction measurements (LISST-100X Type C) and other measurements at 79 stations in November 2013. The results show large variability in particle concentrations (in both volume and number concentrations), with volume concentrations varying by 57-fold. The median particle diameter (Dv50) from each of the water samples also covers a large range (22.4–307.0 μm) and has an irregular statistical distribution, indicating complexity in the PSD. The PSD slopes (2.7–4.5), estimated from a power-law model, cover nearly the entire range reported previously for natural waters. Small mineral particles (with large PSD slopes) are characteristic of near-shore waters prone to sediment resuspension by winds and tides, while large biological particles (with small PSD slopes) dominate the total suspended particulates for waters away from the coast. For the BS and YS, this study provides the first report on the properties and spatial variability of the PSD, which may influence the optical properties of the ocean surface and remote sensing algorithms that are based on estimations of particle concentrations and sizes.