An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI).

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.

Assessment of MERIS reflectance data as processed with SeaDAS over the European seas.

The uncertainties associated with MERIS remote sensing reflectance (RRS) data derived from the SeaWiFS Data Analysis System (SeaDAS) are assessed with field observations. In agreement with the strategy applied for other sensors, a vicarious calibration is conducted using in situ data from the Marine Optical BuoY offshore Hawaii, and leads to vicarious adjustment factors departing from 1 by 0.2% to 1.6%. The three field data sets used for validation have been collected at fixed stations in the northern Adriatic Sea and the Baltic Sea, and in a variety of European waters in the Baltic, Black, Mediterranean and North Seas. Excluding Baltic waters, the mean absolute relative difference |ψ| between satellite and field data is 10-14% for the spectral interval 490-560 nm, 16-18% at 443 nm, and 24-26% at 413 nm. In the Baltic Sea, the |ψ| values are much higher for the blue bands characterized by low RRS amplitudes, but similar or lower at 560 and 665 nm. For the three validation sets, the root-mean-square differences decrease from approximately 0.0013 sr-1 at 413 nm to 0.0002 sr-1 at 665 nm, and are found similar or lower than those obtained for SeaWiFS or MODIS-Aqua. As derived from SeaDAS, the RRS records associated with these three missions thus provide a multi-mission data stream of consistent accuracy.

Upper Limb Phlegmasia Cerulea Dolens Secondary to Heparin-induced Thrombocytopenia: A Case Study.

INTRODUCTION: Phlegmasia cerulea dolens (PCD) is a rare pathology with a very high morbidity and mortality rate, which usually occurs in the lower limb. There is very little literature available to aid management. CASE REPORT: We present a case of upper limb PCD in a 67-year-old female secondary to heparin-induced thrombocytopenia caused by warfarin bridging. She presented to the orthopedic team with upper limb compartment syndrome from a bleed around a peripherally inserted central catheter, for which she was urgently taken to the theater for fasciotomies. Postoperatively, the patient's platelets dropped and the upper limb pain and swelling continued; after conservative management and anticoagulation failed the patient had an upper limb amputation of her right arm. CONCLUSION: With limited guidelines and management options restricted by the large fasciotomy wounds, we believe amputation was the patients' best option.