The number of stations where metadata and biogeochemical, IOP, and AOP data were collected over the CoastColour sites are reported in Table 3a and b. The availability of measurements throughout the sites varies from one parameter to another; for example, chlorophyll a concentration measurements are available from 16 sites, while the scattering coefficient spectra are provided at 2 sites.

Metadata, including depth, temperature, and salinity, exceed 20 000 for each parameter, whereas the numbers of bio-geochemical data, IOPs, and AOPs are much lower: 11 208 chlorophyll a concentration measurements, 538 TSM measurements, 957 reflectance spectra (the other AOP data do not reach 200 data each), and fewer than 700 IOP data (for each parameter) except for turbidity (N=2187).

The number of CHL and turbidity measurements collected at the North Sea site constitute 77.0 and 99.8 % of the measurements respectively, while smaller numbers of TSM and RLw data are provided from the North Sea site: 39.4 and 5.6 % of the total CCRR match-up field TSM and reflectance data respectively. When excluding the turbidity data, 91.6 % of the IOP measurements are contributed from the southern California (38.7 %), North Sea (22.9 %), Florida (7.6 %), and Great Barrier Reef region (7.0 %) sites.

The methods of chlorophyll a, TSM, IOPs, and Rrs measurements performed by each data contributor are briefly described below. Chlorophyll a measurement methods by the different laboratories are summarized in Table 4.

Chlorophyll a concentrations were measured by either high-performance liquid chromatography (HPLC), fluorometry, or spectrophotometry. In the following, TChl a refers to chlorophyll a measurements determined by HPLC and Chl a denotes chlorophyll a obtained by fluorometry or spectrophotometry. TSM concentrations were collected at nine sites: the eastern Mediterranean Sea (hereafter E. Md. Sea), the Baltic Sea and E. Md. Sea, the Great Barrier Reef region (referred to hereafter as the GBR region), the Indonesian waters, Morocco and the western Mediterranean Sea (hereafter Morocco-W. Md. Sea), the North Sea, the Red Sea, and Tasmania coastal waters.

In the CEOAS data set, 422 TChl a data were measured from 2006 to 2009 at the Oregon–Washington site and 2 at the central California site. Samples were stored at -80 ∘C until HPLC analysis. The distribution of TChl a measurements from Oregon–Washington is seasonally unbalanced with 8 % of the measurements collected during the period of December–February, 38 % in March–May, 50 % in June–August, and 50 % in September–November.

The CSIC data set contains 736 Chl a and 667 POM measurements collected in the Gulf of Cádiz (southwest Iberian Peninsula) within the Morocco-W. Md. Sea site. The measurements were taken in the nearshore area (< 30 km) of the Guadalquivir estuary from 2005 to 2007, and offshore during 2008 with slightly fewer measurements during the periods June–August (19 % of the data). Chlorophyll analysis was conducted by filtering samples of 500 mL through Whatman GF/F glass fibre filters (0.7 µm pore size), extracting in 90 % acetone, and measuring chlorophyll a by standard fluorometric methods using a Turner Designs model 10 fluorometer following JGOFS protocols (IOC/UNESCO, 1994). TSM concentrations were measured gravimetrically on pre-weighted Whatman GF/F (0.7 µm pore size) after rinsing with distilled water, following JGOFS protocols (IOC/UNESCO, 1994). Organic matter lost on ignition was determined by reweighting the filters after 3 h in the oven at 500 ∘C, giving the concentrations of PIM and POM (by subtraction). TSM and PIM measurements, contaminated by salt (filters not correctly rinsed), show low variability in TSM and PIM, with 90 % of TSM measurements comprised between 31.1 and 48.3 g m-3. Therefore, only Chl a and POM measurements are retained from the initial CSIC data set.

The CSIR chlorophyll data were collected from the Benguela coastal surface waters and measured using the standard fluorometric method of Parsons et al. (1984) with a Turner Designs 10AU fluorometer. A total of 131 Chl a measurements are available from March to April for years 2005–2009.

The CSIRO data set consists of data collected at 63 stations in the GBR region from 2005 to 2008 (where 25, 19, and 55 % are available from March to May, June to August, and September to November respectively) and at 21 stations in the Tasmanian waters in May 2007. Water samples were filtered through Whatman GF/F glass fibre filters with 0.7 µm nominal pore size and stored in liquid nitrogen until analysis by HPLC. The analyses conducted on the data set collected before July 2004 followed the method of Wright et al. (1991), while the method of Van Heukelem and Thomas (2001) was used for the subsequent campaigns (Oubelkheir et al., 2006; Blondeau-Patissier et al., 2009). For TSM analysis, the filters were pre-ashed at 450 ∘C, pre-washed in 100 mL of Milli-Q water, dried and pre-weighted. The samples were rinsed with 50 mL of distilled water and stored in Petri slides at 4 ∘C. The filters were dried at 60 ∘C (van der Linde, 1998).

The EMECO data set is provided by the International Council for the Exploration of the seas (ICES) and Smartbuoys data by the Centre for Environment, Fisheries and Aquaculture Science (Cefas), totaling 6274 stations with Chl a measurements, calibrated by HPLC. The distribution of these measurements is slightly unbalanced between the seasons (29 % of data available during March–May and 19 % in September–November).

The GKSS TSM and TChl a measurements were collected at 48 stations in the North Sea. TChl a and TSM measurements follow the protocol described in Doerffer and Schönfeld (2009). The sampling is equally distributed between the periods April–May, June–July, and September–October of years 2005–2006, with no measurements during December–February.

The HCMR data were collected at transect stations, where samples were taken in Niskin bottles from HCMR RV Aegaeo, in the E. Md. Sea site. For Chl a measurements, the filtrations were performed using 47 mm diameter nucleopore filters consisting of Millipore® polycarbonate membrane filters, with 0.2 µm nominal pore size; Chl a was measured using Turner 00-AU-10 and Turner TD700 fluorometers using EPA Method 445 (Holm-Hansen et al., 1965) adapted by Arar and Collins (1992). For TSM measurements, the samples were filtered through 47 mm diameter, IsoporeTM 0.45 µm polycarbonate membrane filters (Millipore®). After filtration of water samples, the filters were rinsed with Milli-Q water to remove salt. The filters were dried in the oven at 60 ∘C. In total, 294 Chl a measurements were collected from 2005 to 2009. Unbalanced percentages of Chl a data of 18 and 32 % are available from the periods June–August and September–November respectively. TSM measurements are available at 45 stations, sampled during years 2005 and 2008, with 47, 13, and 40 % of the data taken during the periods March–May, June–August, and September–November respectively.

The Ifremer data set consists of 975 Chl a measurements collected at 30 different locations within the Armorican Shelf (northwest of France), from 2005 to 2009. Data are available from the French phytoplankton surveillance network (REseau PHYtoplankon, REPHY; Gohin, 2011). Fluorometric measurements of Chl a were performed mostly in laboratory using a Turner C7 and C3. Over the four periods (seasons) from December–February to September–November, there are 18, 27, 32, and 23 % of the total number of Chl a measurements respectively.

The ITC measurements of Chl a and TSM were carried out in the Mahakam Delta waters from the upstream turbid Mahakam River down to the clear water situated in the seaward area influenced by the Makassar Strait. From each station, two 1 L bottles of surface water samples were taken and then stored onboard in cool and dark conditions until their processing in the laboratory. TSM concentrations were determined using the gravimetric method. Water samples were filtered through previously weighted 47 mm diameter filters (Whatman GF/F filters, pore size of 0.45 µm). The filters were dried and reweighed (Clesceri et al., 1998). Chl a concentrations were measured using a spectrophotometer after the water samples had been filtered through 47 mm diameter filters (membrane filter, pore size of 0.45 µm) (Clesceri et al., 1998). The Chl a and TSM measurements cover the wet (May) and dry (August) seasons in 2008 and the dry season in August 2009, with a total of 119 stations.

The KORDI data set includes 47 Chl a and 78 TSM measurements collected at the East China Sea site. Samples were filtered through a 25 mm diameter GF/F glass fibre filter. Chl a measurements were performed through the methanol-extraction method using a PerkinElmer Lambda 19 dual-beam spectrophotometer. TSM and Chl a data are available from cruises carried out during April and June 2007 and April 2009, and 31 % of TSM data are available from measurements made in July 2006. During the periods of April–May and June–July, respectively 41 and 59 % of TSM measurements are available, while 68 and 32 % of the Chl a data are provided for these periods.

The NOAA Chl a measurements were performed based on in vitro fluorescence measurements following 24 h dark period extractions in acetone. A total of 136 measurements are available from the Oregon–Washington site sampled from July to September 2008; 122 Chl a data from southern California acquired during the period September–November in 2008; and 606 Chl a data from the central California site, measured from 2005 to 2010. From the periods of September–November and June–August, respectively 52 and 30 % of the NOAA Chl a collection are available.

The NASA bio-Optical Marine Algorithm Dataset (NOMAD) presents a large collection of bio-optical data in ocean and coastal waters (Werdell and Bailey, 2005). The NASA SeaWiFS Bio-optical Archive and Storage System (SeaBass; Werdell et al., 2003), the source of the NOMAD data set, includes both the HPLC and fluorometric methods. HPLC methods may have differed between laboratories in order to separate different types of pigments, which may depend on the predominant component of chlorophyll (Hooker et al., 2005). HPLC-derived TChl a measurements in the NOMAD data set are the sum of monovinyl and divinyl chlorophyll a, plus chlorophyllide a, allomers, and epimers (Werdell and Bailey, 2005). The NOMAD TChl a data set constitutes 24 % of the total TChl a measurements gathered within the CoastColour match-up data set. From 2005 to 2007, 175 TChl a data were collected from the six CoastColour sites – Acadia (40), Chesapeake Bay (69), Gulf of Mexico (41), Indonesian waters (4), southern California (16), and Trinidad and Tobago (5) – and 142 Chl a measurements from Acadia (25 data), Chesapeake Bay (12), Florida (84), Gulf of Mexico (6), Indonesian waters (4), and Trinidad and Tobago (11).

The PML data set was collected during RV Aegaeo and RV James Clark Ross cruises in the MOS-2 and L4 areas respectively. The extraction of chlorophyll was performed in acetone including apo-carotenoate, and the separation used reversed-phase HPLC with 30 s of sonification and 5 min of centrifugation (4000 rpm) (Barlow et al., 1997). In the PML data set, divinyl-chlorophyll a, chlorophyllide-a and chlorophyll a isomers and epimers are added to chlorophyll a (Barlow et al., 1997). For TSM measurements, 2 to 4 L seawater samples were filtered in triplicates and washed with Milli-Q water. Filters were pre-ashed at 450 ∘C for 4 h, pre-washed in 500 mL of Milli-Q water, oven-dried at 75 ∘C for 24 h, and pre-weighted (van der Linde, 1998). A total of 191 pairs of Chl a and TChl a and 136 TSM measurements were collected by PML between 2005 and 2009. The distributions of Chl a, TChl a, and TSM measurements are overall well balanced across seasons.

The UNICAN data set includes 28 TSM and Chl a measurements collected in the North Sea region (the Bay of Biscay) in July 2010. Chl a was measured through a Hach Lange DR-5000 with Whatman GF/F filter following the spectrophotometric method described by Clesceri et al. (1998) (trichrometric method), using a white reference to control the quality of the measurements. TSM was estimated using a gravimetric method after filtration through GF/C glass fibre filters.

IOP measurements were collected at 11 sites (blue symbols in Fig. 2). The measurement methods for the total absorption coefficient, a; absorption by CDOM, ag; absorption by particles, ap; absorption by detritus, ad; absorption by phytoplankton pigments, aphy; scattering b and backscattering coefficients bb; total beam attenuation coefficient, c; and particle beam attenuation, cp, are briefly described below.

For the CSIRO measurements of a, ap, and aphy, carried in the GBR region and Tasmania coastal waters, samples were filtered using a 25 mm Whatman GF/F filter with 0.7 µm nominal pore size and then stored in liquid nitrogen (Oubelkheir et al., 2006; Blondeau-Patissier et al., 2009). CDOM absorption was determined after filtration through polycarbonate filters (Millipore) of 0.22 µm nominal pore size, and water samples were filtered immediately after collection and stored in cool and dark conditions until analysis (Tilstone et al., 2003). The backscattering coefficients were measured using HOBI Labs HydroScat-6. The spectral dependency of the scattering coefficient was modelled as a hyperbolic function of wavelengths, using bands 412, 488, 510, 532, 555, and 650 nm (Oubelkheir et al., 2006; Blondeau-Patissier et al., 2009).

In the HCMR data set collected in the E. Md. Sea, 139 measurements of cp are provided at 470, 660, and 670 nm (available at least at one of these wavelengths), and 34 measurements of cp are given at 670 nm. The beam attenuation coefficients were measured using a 0.25 m path length transmissometer Chelsea Technologies Group Ltd Alpha Tracka II, emitting at 470 nm. The instrument was mounted on RV Aegaeo's permanent CTD rosette frame for casts through the water column. The data were quality-controlled, filtered, and binned at 1 m intervals (Karageorgis et al., 2012).

MSU IOP data consist of six measurements of a, b and c coefficients collected at the Gulf of Mexico site.

The NOMAD absorption coefficients ap, and ag, and absorption by detritus ad, were derived by spectroscopy at six CoastColour sites (Acadia, Cape Verde, Florida, Indonesian waters, Morocco-W. Md. Sea, and southern California). Note that for the Indonesian waters, only ag is provided. These data have been quality-controlled, removing unreasonable data and instrument artifacts (Werdell, 2005). The spectral backscattering coefficient provided in NOMAD data set was obtained using HOBI Labs HydroScat-2 and HydroScat-6 sensors, WET Labs ECObb and ECOVSF sensors, and Wyatt Technology Corporation DAWN photometers. The details on bb data processing are given in Werdell (2005).

Absorption coefficient spectra were measured by PML at 5 m depth in the North Sea, using the WET Labs ac9+. As reported in Martinez-Vicente et al. (2010), the measurements were corrected to account for temperature, salinity, and scattering effects. The samples were filtered through 47 mm diameter Whatman Anopore membranes (0.2 µm pore size), using pre-ashed glassware. Absorption coefficients were determined on the spectrophotometer and a 10 cm quartz cuvette from 350 to 750 nm, relative to a bi-distilled Milli-Q reference blank. ag was calculated from the optical density and the cuvette pathlength, then the baseline offset was subtracted from ag (Groom et al., 2009). The measurement of aphy followed the method of Tassan and Ferrari (1995). The coefficients ap and aphy were measured using a PerkinElmer Lambda 2 spectrophotometer, and 25 mm GF/F filters (Tilstone et al., 2012). ap were determined before and after pigment extraction using NaClO 1 % active chloride from 350 to 750 nm. The scattering measurements were performed using an ECO VSF-3 sensor (Martinez-Vicente et al., 2010).

Backscattering coefficients provided by UCSB were estimated from profiled measurements of the total volume scattering function β at 140 ∘, using a HobiLabs HydroScat-6, collected at the southern California site. These measurements were corrected for light attenuation along the photon path to the instrument detector (σ correction of Maffione and Dana, 1997) using concurrent absorption spectra (Kostadinov et al., 2007) for measurements up to 2005, and concurrent beam attenuation and absorption modelled from the diffuse attenuation coefficient for downwelling irradiance and the irradiance reflectance (see Antoine et al., 2011, for details). A total of 269 backscattering spectra initially measured at 442, 470, 510, 589, and 671 nm were interpolated at 412, 470, 510, and 589 nm assuming a λ-1 spectral dependency of the backscattering coefficient. UCSB absorption spectra up to 2005 were obtained using vertical profiles of WET Labs ac-9 measurements, after application of pure water calibration, as well as standard temperature, salinity, and scattering corrections (WET Labs ac-9 Protocol, 2003). Surface absorption values were derived from the upper 15 m absorption spectra, after filtering incomplete, negative, or extreme values; spectra were linearly interpolated at 412, 443, 490, 510, 530, 555, 620, and 665 nm (Kostadinov et al., 2007). Measurements of aphy, ag, and ad spectra were obtained using a Shimadzu UV2401-PC spectrophotometer. CDOM samples were filtered on 0–2 µm Poretics membranes, while GF/F filters were used to retain total particulate matter for ap measurement, corrected for pathlength effects following Guillocheau (2003). Pigment extraction was performed in 100 % methanol.

A total of 957 match-up field RLw spectra were collected at 13 CoastColour sites and provided from eight data providers, covering a variety of time periods as listed in Table 5. About 33 % of these data are provided for the southern California region, 13 % for the Indonesian coastal waters site, 9 % for the Benguela and Florida sites, and 8 % from the Acadia and Chesapeake Bay sites. Less than 19 % of the data set is provided from the rest of the CoastColour sites. Hyperspectral RLw measurements are available from the GBR region, the North Sea, and the Indonesian waters.

The instruments and methods of RLw measurements are summarized in Table 6 and briefly described below.

The CEOAS radiometric measurements in the Oregon–Washington site were performed using a Satlantic HyperPro II instrument, equipped with two hyperspectral sensors to vertically profile the upwelling radiance, Lu, and downwelling irradiance, Ed, in the water column, plus a separate surface sensor mounted high on the ship deck that measures the above-water downwelling irradiance, Es. Processing of the collected data was performed using Satlantic ProSoft software version 8.1.3_1 (see http://satlantic.com/sites/default/files/documents/ProSoft-7.7- Manual.pdf for equations). In summary, the above-water radiance, Lw, is calculated by extrapolating the profiled Lu measurements to the subsurface (Lu(0-)) and then accounting for the air–sea interface: Lw = Lu(0-)(1-ρ)/nw2, where ρ is the Fresnel reflectance of the air–sea interface (set to 0.021) and nw=1.345 is the refractive index of seawater. The surface irradiance reflectance is then obtained by RLw =π Lw / Es. Of the 137 wavelengths measured by the HyperPro II, this study presents data from 21 wavelengths covering 412 to 780 nm for RLw.

In the Benguela site, the CSIR used a Satlantic radiometer mounted on a floating buoy attached to the ship in order to measure the upwelling radiance Lu and the downwelling irradiance Ed at 0.66 m below the water surface. Lu was extrapolated to Lw by means of the upwelling diffuse attenuation coefficient, Ku, as described by Albert and Mobley (2003). RLw was estimated from Lw and Ed using a reflectance inversion algorithm optimized for local conditions.

The CSIRO RLw measurements in the GBR region were conducted under stable clear-sky conditions using one TriOS RAMSES instrument. Subsequent water-leaving radiance, Lw; sky radiance, Lsky; and Spectralon upwelling radiance, Lspec, were measured. Irradiance was calculated from Spectralon measurements according to Ed =π Lspec C, where C is the reflectance correction factor accounting for non-perfect Lambertian panel properties. Water-leaving reflectance was calculated according to the REVAMP protocol (Tilstone et al., 2003) by applying a sky correction factor.

The GKSS radiometric measurements were conducted onboard ferry cruises in the North Sea region, using three TriOS RAMSES radiometers that simultaneously measure Lu at 45∘ viewing angle, Es, and Lsky, with an azimuth angle between 130 and 140∘ relative to the sun. The water-leaving reflectance RLw was computed according to RLw =π(Lu-ρskyLsky)/Ed, where the specular reflectance ρsky is computed using the Fresnel law, as a function of the refractive index for the mean salinity along the transect.

The ITC measurements carried out in the Indonesian waters used two TriOS RAMSES spectroradiometers. The surface water upwelling and sky downwelling radiance measurements, Lu and Lsky, were measured sequentially at 40∘ zenith angle and at 40∘ nadir angle respectively. The irradiance sensor was mounted on an aluminium pole on top of the boat, pointing upward. The boat was positioned on a station to point the radiance sensor at a relative azimuth angle of 135∘ away from the sun. The sensors measured over the wavelength range 350–950 nm with a sampling interval of approximately 3.3 nm. The measurements were conducted under different cloud conditions. The sky radiance reflected by the water surface, ρsky, was estimated by assuming very small (but not zero) water-leaving reflectance in the near infrared and that ρsky values were less than 0.07, which is the highest value of scattered cumulus clouds by Mobley (1999). The result of ρsky values were relatively similar with ρsky values given by Mobley (1999) for each cloud type condition. The water-leaving reflectance was obtained following the equation RLw =π(Lu-ρskyLsky)/Ed.

The MSU radiometric measurements are provided for the Gulf of Mexico in the Mississippi Sound area (around Gulfport). The reflectance spectra were measured at 14 wavelengths in the spectral range 380–780 nm.

From the NOMAD database, Lw and Es measurements were extracted for the match-up locations between 2005 and 2010 and converted to RLw spectra. Various instruments were used for the measurements of the remote-sensing reflectance, Rrs, in the NOMAD data set (Werdell and Bailey, 2005), including in-water profiling or above-water measurements. All in- and above-water data from various instruments and data providers were consistently processed to Rrs, with the methods described in Werdell and Bailey (2005).

The UCSB RLw measurements in the southern California region were obtained using above-water radiometric measurements of one Dual FieldSpec spectrometer (ASD) instrument and underwater measurements of a Biospherical Instruments (San Diego, California) profiling reflectance radiometer (PRR-600), as described by Toole et al. (2000). Sea surface radiance, Ls, at viewing zenith angle of 45∘; sky radiance (which would be reflected into Ls), Lsky; and Spectralon upwelling radiance, Lspec, were measured by the FieldSpec spectrometer. The above water reflectance was estimated following Toole et al. (2000): the above-water irradiance was calculated from Spectralon measurements according to Ed =πLspec/ρspec, where ρspec is the reflectance of the plaque; the water-leaving reflectance was calculated as RLw =π(Ls-ρLsky)/Ed-residual(750), where residual(750) corrects for any residual reflected sky radiance, assuming zero water-leaving radiance at 750 nm. Underwater downwelling irradiance, Ed-, and upwelling radiance, Lu-, were measured along vertical profiles using the Biospherical PRR-600 and then interpolated to above-water radiance and irradiance respectively, leading to a new estimate of RLw spectra, which were merged with FieldSpec reflectances (see Toole et al., 2000, for details).

MERIS CoastColour processing (see flow chart in Fig. 4) is applied to MERIS Level 1 Full Resolution Full Swath (FRS) to produce MERIS level 2 match-up data sets, namely MERIS water-leaving reflectance (L2R) and MERIS water quality products (L2W), over the CoastColour sites. Here, a brief description of MERIS CoastColour processing is given.

MERIS FRS products, including auxiliary data such as surface pressure, ozone, geographical location (used to identify products having an overlap with one of the test sites), viewing and sun angles, and solar flux, are processed with the Accurate MERIS Ortho-Rectified Geolocation Operational Software (AMORGOS processor, developed by ACRI-ST within ESA GlobCover project), yielding geometrically corrected MERIS child products (FSG). The L1P processor subscenes the FSG data; applies the radiometric and smile corrections; and performs equalization following Bouvet and Ramoino (2010) and pixel classification, screening cloud pixels.

The L1P product, which contains the top of atmosphere radiance reflectance (TOA), is then atmospherically corrected to determine the water-leaving radiance reflectance, following the steps described in Doerffer (2011), which yields the L2R products. Furthermore, water pixels are classified according to their TOA reflectances and available geographical information, and L2W products are generated using various ocean colour algorithms. A complete list of the parameters contained in L2R and L2W products is given in Table 7.

Boxes of 5 × 5 pixels are extracted from L1P, L2R, and related L2W products at all match-up locations present for a given test site and are stored in three files associated with the site. Further processing is performed to average MERIS L2R spectra in each 5 × 5 box, discarding low-quality pixels (see the list of critical flags in Table 7) and yielding the mean reflectance, referred to hereafter as MERIS RLw, and its standard deviation. Other L2W and atmospheric products are also averaged over the 5 × 5 box (see the list in Table 8).

Finally, around each match-up location MERIS L1P, L2R, and L2W subscenes are provided in BEAM-DIMAP (“.dim”) format, and are associated with a KMZ file for quick visualization of area location via Google Earth.

With respect to the match-up field RLw data set, the MERIS RLw data set includes supplementary data from the following regions: the central California, E. Md. Sea and East China Sea, and Tasmania coastal waters, and extended data from Morocco-W. Md. Sea and the North Sea concurrent with extra match-up field WQ measurements (IOPs and/or biogeochemical data sets). The MERIS RLw data set is not available for all the locations of the match-up field RLw measurements (e.g. Benguela, Indonesian waters, GBR region), either because no MERIS image is available within 1 h of the match-up field measurement or because MERIS pixels are flagged as cloud, land, suspect, sunglint, or invalid. After rejection of the flagged pixels, 457 MERIS RLw spectra remain from the CoastColour sites. About 80 % of these spectra are available from the North Sea region and match in situ measurements of temperature, salinity, and/or turbidity.

An overview of the optical conditions and CHL ranges covered by the in situ measurements is given by Fig. 24.

Figure 24 presents a scatter plot of CHL vs. RLw band ratio 709 : 665 which shows that the highest CHL concentrations are exhibited during phytoplankton blooms in the Benguela waters, where the RLw band ratio 709 : 665 is the most sensitive to CHL variations. For CHL < 10 mg m-3, the measurements from the Oregon–Washington and Benguela sites contain globally lower values of RLw band ratio than in the other sites (left graph in Fig. 24).

The relationship between CHL and reflectance band ratio 490 : 560 is quite consistent throughout the CCRR data sets (Fig. 25), except for the in situ measurements from the Benguela site (blue filled circles in Fig. 25a). This is due to the very high CHL > 100 mg m-3 present in the Benguela site, as previously noted in Fig. 24c, as well as the match-up field data set in Fig. 7b associated with low RLw ratios outlying the rest of data, and spanning from 0.2 down to 0.02.

Figure 26 shows the distribution of RLw at 620 nm as a function of TSM concentrations, plotted using different colours for each of the CoastColour sites: Indonesian waters, Mediterranean Sea, and the North Sea (light- and dark-green colours are used for the North Sea region to distinguish the data provider). Linear regression is applied and the associated equations are reported in the same figure. The slopes of the regression lines range from 0.48 to 0.81. The associated goodness of fit coefficients are 39, 59, 89, and 67 % for the Indonesian, North Sea (GKSS), North Sea (RBINS), and Mediterranean Sea measurements respectively. In the GKSS data, most of the scatter occurs at low TSM ranges < 7 g m-3, whereas the measurements from the Indonesian site, taken mainly in highly turbid waters (average and median values being 41.6 and 26 g m-3 respectively), show a global scatter. This scatter can be due to a high variability in the specific inherent optical properties of particles, caused by varying particles size, and/or composition within the sites. The scatter may also be impacted by mismatches of RLw and/or TSM measurements in water with high spatiotemporal variability.

The regression line fitting all the data is given by log10(RLw(620)) =0.67log⁡10(TSM)-2.82 (shown by a dashed black line in Fig. 26) with R2= 69 %.

The distribution of the reflectance as a function of TSM concentrations in the three CCRR data sets is presented by the scatter plots of TSM vs. the reflectance at 665 nm (Fig. 27a, b) and of TSM vs. the reflectance band ratio 665 : 490 (Fig. 27c, d). The simulated TSM vs. RLw(665) scatter plots follow the trend of the match-ups and in situ data sets, with a scatter indicating either a variable particulate mass-specific backscattering coefficient different from that assumed in the simulations (Table 11) or measurement errors.

When using the reflectance band ratio, there is a significantly larger scatter of the simulated data due to the effects of CDOM and phytoplankton absorption affecting the reflectance at 490 nm, whereas this scatter is less noticeable in the in situ or match-up data of the five regions (Fig. 27c, d), which indicates less variability in CDOM absorption coefficient and phytoplankton concentrations in these measurements than in the modelled data set.

The general shift between the in situ reflectance data set and match-up data (Fig. 27a, b) is not noticeable in the reflectance ratios (Fig. 27c, d), suggesting similar 665 : 490 absorption coefficient ratios in the two data sets, at least in the North Sea regions; at lower TSM range (< 10 g m-3), the reduced scatter (in the reflectance band ratios vs. TSM, compared to RLw(665) vs. TSM) could also be due to a removal of spectrally white errors.

The distribution of the ranges of RLw(665) and RLw(665) / RLw(490) in terms of TSM and within the sites – Indonesian waters, the Mediterranean Sea, and the North Sea – is consistent with the distribution of CHL vs. TSM (Fig. 10) in these sites, especially at low TSM < 10 g m-3, where CHL is highly correlated with RLw(665).