Marine primary productivity is an important agent in the global cycling of carbon dioxide, a major ‘greenhouse gas’, and variations in the concentration of the ocean's phytoplankton biomass can therefore explain trends in the global carbon budget. Since the launch of satellite-mounted sensors globe-wide monitoring of chlorophyll, a phytoplankton biomass proxy, became feasible. Just as satellites, the Forel-Ule (FU) scale record (a hardly explored database of ocean colour) has covered all seas and oceans – but already since 1889. We provide evidence that changes of ocean surface chlorophyll can be reconstructed with confidence from this record. The EcoLight radiative transfer numerical model indicates that the FU index is closely related to chlorophyll concentrations in open ocean regions. The most complete FU record is that of the North Atlantic in terms of coverage over space and in time; this dataset has been used to test the validity of colour changes that can be translated to chlorophyll. The FU and FU-derived chlorophyll data were analysed for monotonously increasing or decreasing trends with the non-parametric Mann-Kendall test, a method to establish the presence of a consistent trend. Our analysis has not revealed a globe-wide trend of increase or decrease in chlorophyll concentration during the past century; ocean regions have apparently responded differentially to changes in meteorological, hydrological and biological conditions at the surface, including potential long-term trends related to global warming. Since 1889, chlorophyll concentrations have decreased in the Indian Ocean and in the Pacific; increased in the Atlantic Ocean, the Mediterranean, the Chinese Sea, and in the seas west and north-west of Japan. This suggests that explanations of chlorophyll changes over long periods should focus on hydrographical and biological characteristics typical of single ocean regions, not on those of ‘the’ ocean.

Abstract:In the European Citclops project, with a prime aim of developing new tools to involve citizens in the water quality monitoring of natural waters, colour was identified as a simple property that can be measured via a smartphone app and by dedicated low-cost instruments. In a recent paper, we demonstrated that colour, as expressed mainly by the hue angle (α), can also be derived accurately and consistently from the ocean colour satellite instruments that have observed the Earth since 1997. These instruments provide superior temporal coverage of natural waters, albeit at a reduced spatial resolution of 300 m at best. In this paper, the list of algorithms is extended to the very first ocean colour instrument, and the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m resolution product. In addition, we explore the potential of the hue angle derivation from multispectral imaging instruments with a higher spatial resolution but reduced spectral resolution: the European Space Agency (ESA) multispectral imager (MSI) on Sentinel-2 A,B, the Operational Land Imager (OLI) on the National Aeronautics and Space Administration (NASA) Landsat-8, and its precursor, the Enhanced Thematic Mapper Plus (ETM+) on Landsat-7. These medium-resolution imagers might play a role in an upscaling from point measurements to the typical 1-km pixel size from ocean colour instruments. As the parameter α (the colour hue angle) is fairly new to the community of water remote sensing scientists, we present examples of how colour can help in the image analysis in terms of water-quality products.

Coastal areas of the North Sea are commercially important for fishing and tourism, and are subject to the increasingly adverse effects of harmful algal blooms, eutrophication and climate change. Monitoring phytoplankton in these areas using Ocean Colour Remote Sensing is hampered by the high spatial and temporal variation in absorption and scattering properties. In this paper we demonstrate a clustering method based on specificabsorption properties that give accurate water quality products from the Medium Resolution Imaging Spectrometer (MERIS). A total of 468 measurements of Chlorophyll a (Chla), Total Suspended Material (TSM), specific-(sIOP) and inherent optical properties (IOP) were measured in the North Sea between April 1999 and September 2004. Chla varied from 0.2 to 35 mg m-3 , TSM from 0.2 to 75 g m-3 and absorption properties of coloured dissolved organic material at 442 nm (a CDOM (442)) was 0.02 to 0.26 m-1. The variation in absorption properties of phytoplankton (a ph) and non-algal particles (a NAP) were an order of magnitude greater than that for a ph normalized to Chla (a ph *) and a NAP normalized to TSM (a NAP *). Hierarchical cluster analysis on a ph *, a NAP * and a CDOM reduced this large data set to three groups of high a NAP *-a CDOM , low a ph * situated close to the coast, medium values further offshore and low a NAP *-a CDOM , high a ph * in open ocean and Dutch coastal waters. The median sIOP of each cluster were used to parameterize a semi-analytical algorithm to retrieve concentrations of Chla, TSM and a CDOM (442) from MERIS data. A further 60 measurements of normalized water leaving radiance (nL w), Chla, TSM, a CDOM (442) and a NAP (442) collected between 2003 and 2006 were used to assess the accuracy of the satellite products. The regionalized MERIS algorithm showed improved performance in Chla and a CDOM (442) estimates with relative percentage differences of 29 and 8% compared to 34 and 134% for standard MERIS Chla and a dg (442) products, and similar retrieval for TSM at concentrations >1 gm-3 .

The Forel-Ule colour comparator scale has been applied globally and intensively by oceanographers and limnologists since the 19th century, providing one of the oldest oceanographic data sets. Present and future Forel-Ule classifications of global oceanic, coastal and continental waters can facilitate the interpretation of these long-term ocean colour data series and provide a connection between the present and the past that will be valuable for climate-related studies.Within the EC-funded project CITLOPS (Citizens' Observatory for Coast and Ocean Optical Monitoring), with its main goal to empower endusers, willing to employ community-based environmental monitoring, our aim is to digitalize the colours of the Forel-Ule scale to establish the colour of natural waters through smartphone imaging. The objective of this study was to reproduce the Forel-Ule scale following the original recipes, measure the transmission of the solutions and calculate the chromaticity coordinates of the scale as Wernand and Van der Woerd did in 2010, for the future development of a smartphone application. Some difficulties were encountered when producing the scale, so a protocol for its consistent reproduction was developed and is described in this study. Recalculated chromaticity coordinates are presented and compared to measurements conducted by former scientists. An error analysis of the spectral and colourimetric information shows negligible experimental errors.

The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

François Alphonse Forel (1890) and Willi Ule (1892) composed a colour comparator scale, with tints varying from indigo-blue to cola brown, to quantify the colour of natural waters, like seas, lakes and rivers. For each measurement, the observer compares the colour of the water above a submersed white disc (Secchi disc) with a hand-held scale of pre-defined colours. The scale can be well reproduced from a simple recipe for twenty-one coloured chemical solutions and because the ease of its use, the Forel-Ule (FU) scale has been applied globally and intensively by oceanographers and limnologists from the year 1890. Indeed, the archived FU data belong to the oldest oceanographic data sets and do contain information on the changes in geobiophysical properties of natural waters during the last century. In this article, we describe the optical properties of the FU scale and its ability to cover the colours of natural waters, as observed by the human eye. The recipe of the scale and its reproduction is described. The spectral transmission of the tubes and their respective chromaticity coordinates are presented. The FU scale, in all its simplicity, is found to be an adequate ocean colour comparator scale. The scale is well characterized, stable and observations are reproducible. Thus, the large historic data sets of FU measurements are coherent and well calibrated. Moreover, the scale can be coupled to contemporary multi-spectral observations with hand-held and satellite-based spectrometers. A reintroduction of the FU scale is recommended to expand the historical database and to facilitate a tie-in with present satellite ocean colour observations by tranforming MERIS normalized multi-band reflectance image into a FU indexed image.

Abstract. Multispectral information from satellite borne ocean colour sensors is at present used to characterize natural waters via the retrieval of concentrations of the three dominant optical constituents; pigments of phytoplankton, non-algal particles and coloured dissolved organic matter. A limitation of this approach is that accurate retrieval of these constituents requires detailed local knowledge of the specific absorption and scattering properties. In addition, the retrieval algorithms generally use only a limited part of the collected spectral information. In this paper we present an additional new algorithm that has the merit of using the full spectral information in the visible domain to characterize natural waters in a simple and globally valid way. This Forel-Ule MERIS (FUME) algorithm converts the normalized multiband reflectance information into a discrete set of numbers using uniform colourimetric functions. The Forel-Ule (FU) scale is a sea colour comparator scale that has been developed to cover all possible natural sea colours, ranging from indigo blue (the open ocean) to brownish-green (coastal water) and even brown (humic-acid dominated) waters. Data using this scale have been collected since the late nineteenth century, and therefore, this algorithm creates the possibility to compare historic ocean colour data with present-day satellite ocean colour observations. The FUME algorithm was tested by transforming a number of MERIS satellite images into Forel-Ule colour index images and comparing in situ observed FU numbers with FU numbers modelled from in situ radiometer measurements. Similar patterns and FU numbers were observed when comparing MERIS ocean colour distribution maps with ground truth Forel-Ule observations.The FU numbers modelled from in situ radiometer measurements showed a good correlation with observed FU numbers (R 2 = 0.81 when full spectra are used and R 2 = 0.71 when MERIS bands are used).

This document presents the WAter COlor from Digital Images (WACODI) algorithm, which extracts the color of natural waters from images collected by low-cost digital cameras, in the context of participatory science and water quality monitoring. SRGB images are converted to the CIE XYZ color space, undergoing a gamma expansion and illumination correction that includes the specular reflection at the air-water interface.The XYZ values obtained for each pixel of the image are converted to chromaticity coordinates and Hue color angle (a w ), which is a measure of color. Based on the distributions of a w in sub-sections of the image, an approximation of the intrinsic color of the water is obtained. This algorithm was applied to images acquired in 2013 during two field campaigns in Northern Europe. The Hue color angles were derived from hyperspectral measurements above and below the surface, carried out simultaneously with image acquisition. When for each station a specific illumination correction was applied, based on the corresponding hyperspectral data, a good fit (r 2 5 0.93) was obtained between the image and the spectra Hue color angles (slope 5 0.98, intercept 5 20.03). When a more generic illumination correction was applied to the same images, based on the sky conditions at the time of the image acquisition (either overcast or sunny), a slightly inferior, but still satisfactory fit resulted. Results on the application of the WACODI algorithm to the first images collected by the public via the smartphone application or "APP," developed within the European FP7 Citclops, are presented at the end of this study.