31 research outputs found

    BIO EOV Report

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    Biogeochemical EOV assessment and impact of AtlantOS observation

    Evaluating Operational AVHRR Sea Surface Temperature Data at the Coastline Using Benthic Temperature Loggers

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    The nearshore coastal ocean is one of the most dynamic and biologically productive regions on our planet, supporting a wide range of ecosystem services. It is also one of the most vulnerable regions, increasingly exposed to anthropogenic pressure. In the context of climate change, monitoring changes in nearshore coastal waters requires systematic and sustained observations of key essential climate variables (ECV), one of which is sea surface temperature (SST). As temperature influences physical, chemical and biological processes within coastal systems, accurate monitoring is crucial for detecting change. SST is an ECV that can be measured systematically from satellites. Yet, owing to a lack of adequate in situ data, the accuracy and precision of satellite SST at the coastline are not well known. In a prior study, we attempted to address this by taking advantage of in situ SST measurements collected by a group of surfers. Here, we make use of a three year time-series (2014–2017) of in situ water temperature measurements collected using a temperature logger (recording every 30 min) deployed within a kelp forest (∌3 m below chart datum) at a subtidal rocky reef site near Plymouth, UK. We compared the temperature measurements with three other independent in situ SST datasets in the region, from two autonomous buoys located ∌7 km and ∌33 km from the coastline, and from a group of surfers at two beaches near the kelp site. The three datasets showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected from the kelp site and the two autonomous buoys were matched with operational Advanced Very High Resolution Radiometer (AVHRR) EO SST passes, all within 1 h of the in situ data. By extracting data from the closest satellite pixel to the three sites, we observed a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square differences at the kelp site over twice that observed at the two offshore buoys. Comparing the in situ water temperature data with pixels surrounding the kelp site revealed the performance of the satellite data improves when moving two to three pixels offshore and that this improvement was better when using an SST algorithm that treats each pixel independently in the retrieval process. At the three sites, we related differences between satellite and in situ SST data with a suite of atmospheric variables, collected from a nearby atmospheric observatory, and a high temporal resolution land surface temperature (LST) dataset. We found that differences between satellite and in situ SST at the coastline (kelp site) were well correlated with LST and solar zenith angle; implying contamination of the pixel by land is the principal cause of these larger differences at the coastline, as opposed to issues with atmospheric correction. This contamination could be either from land directly within the pixel, potentially impacted by errors in geo-location, or possibly through thermal adjacency effects. Our results demonstrate the value of using benthic temperature loggers for evaluating satellite SST data in coastal regions, and highlight issues with retrievals at the coastline that may inform future improvements in operational products

    Uncertainty in Ocean-Color Estimates of Chlorophyll for Phytoplankton Groups

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    Over the past decade, techniques have been presented to derive the community structure of phytoplankton at synoptic scales using satellite ocean-color data. There is a growing demand from the ecosystem modeling community to use these products for model evaluation and data assimilation. Yet, from the perspective of an ecosystem modeler these products are of limited use unless: (i) the phytoplankton products provided by the remote-sensing community match those required by the ecosystem modelers; and (ii) information on per-pixel uncertainty is provided to evaluate data quality. Using a large dataset collected in the North Atlantic, we re-tune a method to estimate the chlorophyll concentration of three phytoplankton groups, partitioned according to size [pico- (20 ÎŒm)]. The method is modified to account for the influence of sea surface temperature, also available from satellite data, on model parameters and on the partitioning of microphytoplankton into diatoms and dinoflagellates, such that the phytoplankton groups provided match those simulated in a state of the art marine ecosystem model (the European Regional Seas Ecosystem Model, ERSEM). The method is validated using another dataset, independent of the data used to parameterize the method, of more than 800 satellite and in situ match-ups. Using fuzzy-logic techniques for deriving per-pixel uncertainty, developed within the ESA Ocean Colour Climate Change Initiative (OC-CCI), the match-up dataset is used to derive the root mean square error and the bias between in situ and satellite estimates of the chlorophyll for each phytoplankton group, for 14 different optical water types (OWT). These values are then used with satellite estimates of OWTs to map uncertainty in chlorophyll on a per pixel basis for each phytoplankton group. It is envisaged these satellite products will be useful for those working on the validation of, and assimilation of data into, marine ecosystem models that simulate different phytoplankton groups.info:eu-repo/semantics/publishedVersio

    Satellite-detected fluorescence reveals global physiology of ocean phytoplankton

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    © 2009 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Biogeosciences 6 (2009): 779-794, doi: 10.5194/bg-6-779-2009Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.This work was supported by grants from the NASA Ocean Biology and Biogeochemistry Program and the NSF Biological Oceanography Program

    Optical types of inland and coastal waters

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    Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

    The influence of tides on the marine carbonate chemistry of a coastal polynya in the south-eastern Weddell Sea

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    Tides significantly affect polar coastlines by modulating ice shelf melt and modifying shelf water properties through transport and mixing. However, the effect of tides on the marine carbonate chemistry in such regions, especially around Antarctica, remains largely unexplored. We address this topic with two case studies in a coastal polynya in the south-eastern Weddell Sea, neighbouring the Ekström Ice Shelf. The case studies were conducted in January 2015 (PS89) and January 2019 (PS117), capturing semi-diurnal oscillations in the water column. These are pronounced in both physical and biogeochemical variables for PS89. During rising tide, advection of sea ice meltwater from the north-east created a fresher, warmer, and more deeply mixed water column with lower dissolved inorganic carbon (DIC) and total alkalinity (TA) content. During ebbing tide, water from underneath the ice shelf decreased the polynya's temperature, increased the DIC and TA content, and created a more stratified water column. The variability during the PS117 case study was much smaller, as it had less sea ice meltwater input during rising tide and was better mixed with sub-ice shelf water. The contrasts in the variability between the two case studies could be wind and sea ice driven, and they underline the complexity and highly dynamic nature of the system. The variability in the polynya induced by the tides results in an air–sea CO2 flux that can range between a strong sink (−24 mmol m−2 d−1) and a small source (3 mmol m−2 d−1) on a semi-diurnal timescale. If the variability induced by tides is not taken into account, there is a potential risk of overestimating the polynya's CO2 uptake by 67 % or underestimating it by 73 %, compared to the average flux determined over several days. Depending on the timing of limited sampling, the polynya may appear to be a source or a sink of CO2. Given the disproportionate influence of polynyas on heat and carbon exchange in polar oceans, we recommend future studies around the Antarctic and Arctic coastlines to consider the timing of tidal currents in their sampling strategies and analyses. This will help constrain variability in oceanographic measurements and avoid potential biases in our understanding of these highly complex systems
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