A compilation of global bio-optical in situ data for ocean colour satellite applications – version three

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.org/10.1594/PANGAEA.941318 (Valente et al., 2022)

The Challenges of Interpreting Oil–Water Spatial and Spectral Contrasts for the Estimation of Oil Thickness: Examples From Satellite and Airborne Measurements of the Deepwater Horizon Oil Spill

Optical remote sensing is one of the most commonly used techniques to detect oil in the surface ocean. This is because oil has optical properties that are different from water to modulate oil-water spatial and spectral contrasts. However, understanding these contrasts is challenging because of variable results from laboratory and field experiments as well as from different observing conditions and spatial/spectral resolutions of remote sensing imagery. Here, through reviewing published oil-water spectral contrasts and analyzing remotely sensed spectra collected by several satellite and airborne sensors (MERIS, MODIS, MISR, Landsat, and AVIRIS) from the Deepwater Horizon oil spill, we provide the interpretation of the spatial/spectral contrasts of various oil slicks and discuss the challenges in such interpretations. In addition to oil thickness, several other factors also affect oil-water spatial/spectral contrasts, including sun glint strength, oil emulsification state, optical properties of oil covered water, and spatial/spectral resolutions of remote sensing imagery. In the absence of high spatial- and spectral-resolution imagery, a multistep scheme may be used to classify oil type (emulsion and non-emulsion) and to estimate relative oil thickness for each type based on the known optical properties of oil, yet such a scheme requires further research to improve and validate

The Antares Observation Network

The ANTARES network seeks to understand the variability of the coastal environment on a continental scale and the local, regional, and global factors and processes that modulate this variability. The target are coastal zones of South America and the Caribbean Sea. The initial approach includes developing time series of in situ and satellite-based environmental observations in coastal and oceanic regions. The network is constituted by experts that seek to exchange ideas, develop an infrastructure for mutual logistical and knowledge support, and link in situ time series of observations located around the Americas with real-time and historical satellite-derived time series of relevant products. A major objective is to generate information that will be distributed publicly and openly in the service of coastal ocean research, resource management, science-based policy making and education in the Americas. As a first stage, the network has linked oceanographic time series located in Argentina, Brazil, Chile and Venezuela. The group has also developed an online tool to examine satellite data collected with sensors such as NASA\u27s MODIS. Specifically, continental-scale high-resolution (1 km) maps of chlorophyll and sea surface temperature are generated and served daily over the web according to specifications of users within the ANTARES network. Other satellite-derived variables will be added as support for the network is solidified. ANTARES makes data available and offers simple analysis tools that anyone can use with the ultimate goal of improving coastal assessments, management and policies

Atmospheric Correction of Aisa Measurements Over the Florida Keys Optically Shallow Waters: Challenges in Radiometric Calibration and Aerosol Selection

An Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imager was deployed on a manned aircraft flown at 1305-m altitude to collect data over optically shallow waters in the Florida Keys with the ultimate goal of mapping water quality and benthic habitats. As a first step, we developed a practical atmospheric correction (AC) approach to derive surface remote-sensing reflectance ((Rrs) from AISA measurements using radiative transfer simulations and constraints obtained from field spectral Rrs measurements. Unlike previously published method, the AC approach removes the surface Fresnel reflection and accounts for aircraft altitude and nonzero near-infrared (NIR) reflectance through iteration over the pre-established look-up tables (LUTs) based on MODTRAN calculations. Simulations and comparison with concurrent in situRrs measurements show the feasibility of the approach in deriving surface Rrs with acceptable uncertainties. The possibility of errors in the radiometric calibration of AISA is demonstrated, although a definitive assessment cannot be made due to lack of enough concurrent in situ measurements. The need for noise reduction and the difficulty in carrying out a vicarious calibration are also discussed to help advance the design of future AISA missions

Binational Collaboration to Study Gulf of Mexico\u27S Harmful Algae

Blooms of the toxic marine dinoflagellate Karenia brevis cause massive fish kills and other public health and economic problems in coastal waters throughout the Gulf of Mexico [Steidinger, 2009]. These harmful algal blooms (HABs) are a gulf-wide problem that require a synoptic observing system for better serving decision-making needs. The major nutrient sources that initiate and maintain these HABs and the possible connectivity of blooms in different locations are important questions being addressed through new collaborations between Mexican and U.S. researchers and government institutions. These efforts were originally organized under the U.S./Mexico binational partnership for the HABs Observing System (HABSOS), led by the U.S. Environmental Protection Agency\u27s Gulf of Mexico Program (EPAGMP) and several agencies in Veracruz, Mexico, since 2006. In 2010 these efforts were expanded to include other Mexican states and institutions with the integrated assessment and management of the Gulf of Mexico Large Marine Ecosystem (GoMLME) program sponsored by the Global Environment Facility (GEF), the United Nations Industrial Development Organization (UNIDO), the Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT), and the National Oceanic and Atmospheric Administration (NOAA)