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.

From silk to satellite: half a century of ocean colour anomalies in the Northeast Atlantic.

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.

Exploring preparation practices of nursing and midwifery educators for in situ simulation-based education: A qualitative study in a large healthcare service.

AIM: This study aimed to explore nursing and midwifery clinical educators' preparation practices related to in situ simulation-based education, at a tertiary health service in Australia. BACKGROUND: Simulation-based education is routinely used in healthcare education and training. A key mechanism to optimise simulation-based education is learner preparation. While diverse pre-simulation preparation approaches are described in the literature, these are predominantly focused on activities that are undertaken in either university and/or skills centre contexts. In contrast, the learner preparation practices for simulation-based education that is delivered insitu in healthcare facilities by clinical nurse and midwifery educators are underexplored. DESIGN: This study used an exploratory qualitative design. METHODS: Participants were recruited using purposive sampling from a potential study group of thirty. Twelve individuals from the nursing and midwifery education group met selection criteria and agreed to participate in the study. Each individual participated in a semi-structured interview. Interview data were then transcribed and analysed using qualitative descriptive methods. RESULTS: Data analysis resulted in the development of four themes related to the preparation of participants for insitu simulation-based education sessions. Each theme informs the choices of clinical nurse/midwifery educators' preparation practices: 1) responsivity to workplace and clinical priorities; 2) clinical educator objectives; 3) preparedness for learning and clinical practice; and 4) evolving educational expertise. CONCLUSION: This study explored the preparation practices of nurse and midwifery clinical educators engaged in the delivery of insitu simulation-based education. Findings indicate a depth of experiences and a willingness to share practice insights, suggesting that insitu simulation-based education is an integral part of the in service repertoire and a key component of departmental education strategies, designed to support practice and hone skills required to deliver quality patient care.

Sun glint estimation in marine satellite images: a comparison of results from calculation and radiative transfer modeling.

The intensity and location of Sun glint in two Medium Resolution Imaging Spectrometer (MERIS) images was modeled using a radiative transfer model that includes elevation features as well as the slope of the sea surface. The results are compared to estimates made using glint flagging and correction approaches used within standard atmospheric correction processing code. The model estimate gives a glint pattern with a similar width but lower peak level than any current method, or than that estimated by a radiative transfer model with surfaces that include slope but not height. The MERIS third reprocessing recently adopted a new slope statistics model for Sun glint correction; the results show that this model is an outlier with respect to both the elevation model and other slope statistics models and we recommend that its adoption should be reviewed.

Generalized ocean color inversion model for retrieving marine inherent optical properties.

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Light transfer at the ocean surface modeled using high resolution sea surface realizations.

The behavior of light at the air-sea interface has been investigated using ray tracing methods with numerically realized surfaces that incorporate features on scales from 3 millimeters to 200 meters. The directional reflection of light at the surface realizations was tested using Monte Carlo code. Estimated directionally reflected radiances were generally in good agreement with those from existing methods that model the slope statistics but not the shape of the sea surface. However, significant differences were found for some incident and exitant directions. The model was used to quantitatively estimate the pixel-to-pixel variation in ocean color images caused by spatial variation in the sea surface shape.

Model of phytoplankton absorption based on three size classes.

Using the phytoplankton size-class model of Brewin et al. [Ecol. Model.221, 1472 (2010)], the two-population absorption model of Sathyendranath et al. [Int. J. Remote. Sens.22, 249 (2001)] and Devred et al. [J. Geophys. Res.111, C03011 (2006)] is extended to three populations of phytoplankton, namely, picophytoplankton, nanophytoplankton, and microphytoplankton. The new model infers total and size-dependent phytoplankton absorption as a function of the total chlorophyll-a concentration. A main characteristic of the model is that all the parameters that describe it have biological or optical interpretation. The three-population model performs better than the two-population model at retrieving total phytoplankton absorption. Accounting for the contributions of picophytoplankton and nanophytoplankton, rather than the combination of both as in the two-population model, improved significantly the retrieval of phytoplankton absorption at low chlorophyll-a concentrations. Class-dependent specific absorption of phytoplankton derived using the model compares well with previously published models. However, the model presented in this paper provides the specific absorption of three size classes and is applicable to a continuum of chlorophyll-a concentrations. Absorption obtained from remotely sensed chlorophyll-a using our model compares well with in situ absorption measurements.

Citizens and scientists collect comparable oceanographic data: measurements of ocean transparency from the Secchi Disk study and science programmes.

Marine phytoplankton accounts for approximately 50% of all photosynthesis on Earth, underpins the marine food chain and plays a central role in the Earth's biogeochemical cycles and climate. In situ measurements of ocean transparency can be used to estimate phytoplankton biomass. The scale and challenging conditions of the ocean make it a difficult environment for in situ studies, however. Here, we show that citizen scientists (seafarers) using a simple white Secchi Disk can collect ocean transparency data to complement formal scientific efforts using similar equipment. Citizen scientist data can therefore help understand current climate-driven changes in phytoplankton biomass at a global scale.

A case study - Implementing a registered nurse professional recognition program across a Queensland hospital and health service.

Ongoing advancement and documentation of professional development is required to maintain nursing registration and competency to practise in Australia and many other countries. All Australian registered nurses are required to undertake a minimum of 20 h of continuing professional development annually and demonstrate competence to practice; this is a criterion for nursing registration. Many health care organisations nationally and internationally develop programs to support such processes, assisting nurses to formally document their ongoing education and commitment to best practice, and clearly demonstrate their ongoing continuing professional development. Such programs align with the MAGNET ® principles of providing structural empowerment, exemplary professional practice and new knowledge, innovations and improvements. This study describes the implementation, evaluation and impact of the registered nurse professional recognition program undertaken by one Hospital and Health Service in South East Queensland using Donabedian's structure, process outcome framework. The registered nurse professional recognition program was implemented to invest in and develop the nursing workforce by providing an opportunity for registered nurses to assess and document their professional skills, knowledge and expertise that are critical to the provision of safe and cost-effective patient and family-centred care.

Satellite Ocean Colour: Current Status and Future Perspective.

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and interannual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

MERIS observations of phytoplankton phenology in the Baltic Sea.

The historical data from the MEdium Resolution Imaging Spectrometer (MERIS) is an invaluable archive for studying global waters from inland lakes to open oceans. Although the MERIS sensor ceased to operate in April 2012, the data capacities are now re-established through the recently launched Sentinel-3 Ocean and Land Colour Instrument (OLCI). The development of a consistent time series for investigating phytoplankton phenology features is crucial if the potential of MERIS and OLCI data is to be fully exploited for inland water monitoring. This study presents a time series of phytoplankton abundance and bloom spatial extent for the highly eutrophic inland water of the Baltic Sea using the 10-year MERIS archive (2002-2011) and a chlorophyll-a based Summed Positive Peaks (SPP) algorithm. A gradient approach in conjunction with the histogram analysis was used to determine a global threshold from the entire collection of SPP images for identifying phytoplankton blooms. This allows spatio-temporal dynamics of daily bloom coverage, timing, phytoplankton abundance and spatial extent to be investigated for each Baltic basin. Furthermore, a number of meteorological and hydrological variables, including spring excess phosphate, summer sea surface temperature and photosynthetically active radiation, were explored using boosted regression trees and generalised additive models to understand the ecological response of phytoplankton assemblages to environmental perturbations and potential predictor variables of summer blooms. The results indicate that the surface layer excess phosphate available in February and March had paramount importance over all other variables considered in governing summer bloom abundance in the major Baltic basins. This finding allows new insights into the development of early warning systems for summer phytoplankton blooms in the Baltic Sea and elsewhere.

Seafarer citizen scientist ocean transparency data as a resource for phytoplankton and climate research.

The oceans' phytoplankton that underpin the marine food chain appear to be changing in abundance due to global climate change. Here, we compare the first four years of data from a citizen science ocean transparency study, conducted by seafarers using home-made Secchi Disks and a free Smartphone application called Secchi, with contemporaneous satellite ocean colour measurements. Our results show seafarers collect useful Secchi Disk measurements of ocean transparency that could help future assessments of climate-induced changes in the phytoplankton when used to extend historical Secchi Disk data.

Determination of phytoplankton abundances (Chlorophyll-a) in the optically complex inland water - The Baltic Sea.

A novel approach, termed Summed Positive Peaks (SPP), is proposed for determining phytoplankton abundances (Chlorophyll-a or Chl-a) and surface phytoplankton bloom extent in the optically complex Baltic Sea. The SPP approach is established on the basis of a baseline subtraction method using Rayleigh corrected top-of-atmosphere data from the Medium Resolution Imaging Spectrometer (MERIS) measurements. It calculates the reflectance differences between phytoplankton related signals observed in the MERIS red and near infrared (NIR) bands, such as sun-induced chlorophyll fluorescence (SICF) and the backscattering at 709nm, and considers the summation of the positive line heights for estimating Chl-a concentrations. The SPP algorithm is calibrated against near coincident in situ data collected from three types of phytoplankton dominant waters encountered in the Baltic Sea during 2010 (N=379). The validation results show that the algorithm is capable of retrieving Chl-a concentrations ranging from 0.5 to 3mgm-3, with an RMSE of 0.24mgm-3 (R2=0.69, N=264). Additionally, the comparison results with several Chl-a algorithms demonstrates the robustness of the SPP approach and its sensitivity to low to medium biomass waters. Based on the red and NIR reflectance features, a flagging method is also proposed to distinguish intensive surface phytoplankton blooms from the background water.

Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling.

Spectral measurements of remote-sensing reflectance (Rrs) and absorption coefficients carried out in three European estuaries (Gironde and Loire in France, Tamar in the UK) are presented and analyzed. Typical Rrs and absorption spectra are compared with typical values measured in coastal waters. The respective contributions of the water constituents, i.e., suspended sediments, colored dissolved organic matter, and phytoplankton (characterized by chlorophyll-a), are determined. The Rrs spectra are then reproduced with an optical model from the measured absorption coefficients and fitted backscattering coefficients. From Rrs ratios, empirical quantification relationships are established, reproduced, and explained from theoretical calculations. These quantification relationships were established from numerous field measurements and a reflectance model integrating the mean values of the water constituents' inherent optical properties. The model's sensitivity to the biogeochemical constituents and to their nature and composition is assessed.

Use of a Spectralon panel to measure the downwelling irradiance signal: case studies and recommendations.

Field determinations of the remote sensing reflectance signal are necessary to validate ocean color satellite sensors. The measurement of the above-water downwelling irradiance signal Ed(0+) is commonly made with a reference plaque of a known reflectance. The radiance reflected by the plaque (L(dspec)) can be used to determine Ed(0+) if the plaque is assumed to be near Lambertian. To test this assumption, basic experiments were conducted on a boat under changing sky conditions (clear, cloudy, covered) and with different configurations for simultaneous measurements of L(dspec) and Ed(0+). For all measurement configurations, results were satisfactory under a clear sky. Under cloudy or covered skies, shadow effects on the plaque induced errors up to 100% in the determination of Ed(0+). An appropriate measurement configuration was defined, which enabled Ed(0+) to be determined with an accuracy of better than +/- 15% regardless of the sky conditions.