A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GePandCO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll α, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015)

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications

Physical environments of the Caribbean Sea

The Caribbean Sea encompasses a vast range of physical environmental conditions that have a profound influence on the organisms that live there. Here we utilize a range of satellite and in situ products to undertake a region-wide categorization of the physical environments of the Caribbean Sea (PECS). The classification approach is hierarchical and focuses on physical constraints that drive many aspects of coastal ecology, including species distributions, ecosystem function, and disturbance. The first level represents physicochemical properties including metrics of satellite sea surface temperature, water clarity, and in situ salinity. The second level considers mechanical disturbance and includes both chronic disturbance from wind-driven wave exposure and acute disturbance from hurricanes. The maps have a spatial resolution of 1 km. An unsupervised neural network classification produced 16 physicochemical provinces that can be categorized into six broad groups: (1) low water clarity and low salinity and average temperatures; (2) low water clarity but average salinity and temperature, broadly distributed in the basin; (3) low salinity but average water clarity and temperature; (4) upwelling; (5) high latitude; and (6) offshore waters of the inner Caribbean. Additional mechanical disturbance layers impose additional pattern that operates over different spatial scales. Because physical environments underpin so much of coastal ecosystem structure and function, we anticipate that the PECS classification, which will be freely distributed as geographic information system layers, will facilitate comparative analyses and inform the stratification of studies across environmental provinces in the Caribbean basin

ENSO-Induced Co-Variability of Salinity, Plantkton Biomass and Coastal Currents in the Northern Gulf of Mexico

The northern Gulf of Mexico (GoM) is a region strongly influenced by river discharges of freshwater and nutrients, which promote a highly productive coastal ecosystem that host commercially valuable marine species. A variety of climate and weather processes could potentially influence the river discharges into the northern GoM. However, their impacts on the coastal ecosystem remain poorly described. By using a regional ocean-biogeochemical model, complemented with satellite and in situ observations, here we show that El Niño - Southern Oscillation (ENSO) is a main driver of the interannual variability in salinity and plankton biomass during winter and spring. Composite analysis of salinity and plankton biomass anomalies shows a strong asymmetry between El Niño and La Niña impacts, with much larger amplitude and broader areas affected during El Niño conditions. Further analysis of the model simulation reveals significant coastal circulation anomalies driven by changes in salinity and winds. The coastal circulation anomalies in turn largely determine the spatial extent and distribution of the ENSO-induced plankton biomass variability. These findings highlight that ENSO-induced changes in salinity, plankton biomass, and coastal circulation across the northern GoM are closely interlinked and may significantly impact the abundance and distribution of fish and invertebrates

A modern coastal ocean observing system using data from advanced satellite and in situ sensors – an example

Report of the Ocean Observation Research Coordination Network In-situ-Satellite Observation Working GroupThis report is intended to illustrate and provide recommendations for how ocean observing systems of the next decade could focus on coastal environments using combined satellite and in situ measurements. Until recently, space-based observations have had surface footprints typically spanning hundreds of meters to kilometers. These provide excellent synoptic views for a wide variety of ocean characteristics. In situ observations are instead generally point or linear measurements. The interrelation between space-based and in-situ observations can be challenging. Both are necessary and as sensors and platforms evolve during the next decade, the trend to facilitate interfacing space and in-situ observations must continue and be expanded. In this report, we use coastal observation and analyses to illustrate an observing system concept that combines in situ and satellite observing technologies with numerical models to quantify subseasonal time scale transport of freshwater and its constituents from terrestrial water storage bodies across and along continental shelves, as well as the impacts on some key biological/biogeochemical properties of coastal waters.Ocean Research Coordination Network and the National Science Foundatio

Natural variability of surface oceanographic conditions in the offshore Gulf of Mexico

AbstractThis work characterizes patterns of temporal variability in surface waters of the central Gulf of Mexico. We examine remote-sensing based observations of sea surface temperature (SST), wind speed, sea surface height anomaly (SSHA), chlorophyll-a concentration (Chl-a) and Net Primary Production (NPP), along with model predictions of mixed layer depth (MLD), to determine seasonal changes and long-term trends in the central Gulf of Mexico between the early 1980s and 2012. Specifically, we examine variability in four quadrants of the Gulf of Mexico (water depth >1000m). All variables show strong seasonality. Chl-a and NPP show positive anomalies in response to short-term increases in wind speed and to cold temperature events. The depth of the mixed layer (MLD) directly and significantly affects primary productivity throughout the region. This relationship is sufficiently robust to enable real-time estimates of MLD based on satellite-based estimates of NPP. Over the past 15–20years, SST, wind speed, and SSHA show a statistically significant, gradual increase. However, Chl-a and NPP show no significant trends over this period. There has also been no trend in the MLD in the Gulf of Mexico interior. The positive long-term trend in wind speed and SST anomalies is consistent with the warming phase of the Atlantic Multidecadal Oscillation (AMO) that started in the mid-90s. This also coincides with a negative trend in the El Niño/Southern Oscillation Multivariate ENSO Index (MEI) related to an increase in the frequency of cooler ENSO events since 1999–2000. The results suggest that over decadal scales, increasing temperature, wind speed, and mesoscale ocean activity have offsetting effects on the MLD. The lack of a trend in MLD anomalies over the past 20years explains the lack of long-term changes in chlorophyll concentration and productivity over this period in the Gulf. Understanding the background of seasonal and long-term variability in these ocean characteristics is important to interpret changes in ocean health due to episodic natural and anthropogenic events and long term climate changes or development activities. With this analysis we provide a baseline against which such changes can be measured

A Global Ecological Classification of Coastal Segment Units to Complement Marine Biodiversity Observation Network Assessments

A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 30 m Landsat-derived shoreline vector that was segmented into 4 million 1 km or shorter segments. Each segment was attributed with values from 10 variables that represent the ecological settings in which the coastline occurs, including properties of the adjacent water, adjacent land, and coastline itself. The 4 million segments were classified into 81,000 coastal segment units (CSUs) as unique combinations of variable classes. We summarize the process to develop the CSUs and derive summary descriptions for the seven MBON case study sites. We discuss the intended application of the new CSU data for research and management in coastal areas

Super sites for advancing understanding of the oceanic and atmospheric boundary layers

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Clayson, C. A., Centurioni, L., Cronin, M. F., Edson, J., Gille, S., Muller-Karger, F., Parfitt, R., Riihimaki, L. D., Smith, S. R., Swart, S., Vandemark, D., Boas, A. B. V., Zappa, C. J., & Zhang, D. Super sites for advancing understanding of the oceanic and atmospheric boundary layers. Marine Technology Society Journal, 55(3), (2021): 144–145, https://doi.org/10.4031/MTSJ.55.3.11.Air‐sea interactions are critical to large-scale weather and climate predictions because of the ocean's ability to absorb excess atmospheric heat and carbon and regulate exchanges of momentum, water vapor, and other greenhouse gases. These exchanges are controlled by molecular, turbulent, and wave-driven processes in the atmospheric and oceanic boundary layers. Improved understanding and representation of these processes in models are key for increasing Earth system prediction skill, particularly for subseasonal to decadal time scales. Our understanding and ability to model these processes within this coupled system is presently inadequate due in large part to a lack of data: contemporaneous long-term observations from the top of the marine atmospheric boundary layer (MABL) to the base of the oceanic mixing layer. We propose the concept of “Super Sites” to provide multi-year suites of measurements at specific locations to simultaneously characterize physical and biogeochemical processes within the coupled boundary layers at high spatial and temporal resolution. Measurements will be made from floating platforms, buoys, towers, and autonomous vehicles, utilizing both in-situ and remote sensors. The engineering challenges and level of coordination, integration, and interoperability required to develop these coupled ocean‐atmosphere Super Sites place them in an “Ocean Shot” class.NOAA CVP TPOS, Understanding Processes Controlling Near-Surface Salinity in the Tropical Ocean Using Multiscale Coupled Modeling and Analysis, NA18OAR4310402 to CAC and JE. NSF Award PLR-1425989 and OPP-1936222, Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) to SG. NOAA, BOEM, ONR, NSF, NOPP, NASA Applied Sciences Office, Biodiversity & Ecological Forecasting Program; National Science Foundation (Co-PI J. Pearlman); OceanObs Research Coordination Network (OCE-1728913) to FM-K. NASA, SWOT program, Award # 80NSSC20K1136 to ABVB. NSF, Investigating the Air-Sea Energy Exchange in the presence of Surface Gravity Waves by Measurements of Turbulence Dissipation, Production and Transport, OCE 17-56839; NSF, A Multi-Spectral Thermal Infrared Imaging System for Air-Sea Interaction Research, OCE 20-23678; NSF, Investigating the Relationship Between Ocean Surface Gravity–Capillary Waves, Surface-Layer Hydrodynamics, and Air–Sea Momentum Flux, OCE 20-49579 to CJZ. Partially funded by NOAA/Climate Program Office and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063 to DZ

Severe 2010 Cold-Water Event Caused Unprecedented Mortality to Corals of the Florida Reef Tract and Reversed Previous Survivorship Patterns

Background Coral reefs are facing increasing pressure from natural and anthropogenic stressors that have already caused significant worldwide declines. In January 2010, coral reefs of Florida, United States, were impacted by an extreme cold-water anomaly that exposed corals to temperatures well below their reported thresholds (16°C), causing rapid coral mortality unprecedented in spatial extent and severity. Methodology/Principal Findings Reef surveys were conducted from Martin County to the Lower Florida Keys within weeks of the anomaly. The impacts recorded were catastrophic and exceeded those of any previous disturbances in the region. Coral mortality patterns were directly correlated to in-situ and satellite-derived cold-temperature metrics. These impacts rival, in spatial extent and intensity, the impacts of the well-publicized warm-water bleaching events around the globe. The mean percent coral mortality recorded for all species and subregions was 11.5% in the 2010 winter, compared to 0.5% recorded in the previous five summers, including years like 2005 where warm-water bleaching was prevalent. Highest mean mortality (15%–39%) was documented for inshore habitats where temperatures were \u3c11°C for prolonged periods. Increases in mortality from previous years were significant for 21 of 25 coral species, and were 1–2 orders of magnitude higher for most species. Conclusions/Significance The cold-water anomaly of January 2010 caused the worst coral mortality on record for the Florida Reef Tract, highlighting the potential catastrophic impacts that unusual but extreme climatic events can have on the persistence of coral reefs. Moreover, habitats and species most severely affected were those found in high-coral cover, inshore, shallow reef habitats previously considered the “oases” of the region, having escaped declining patterns observed for more offshore habitats. Thus, the 2010 cold-water anomaly not only caused widespread coral mortality but also reversed prior resistance and resilience patterns that will take decades to recover

Reimagining the potential of Earth observations for ecosystem service assessments

The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide