A global compilation of in situ aquatic high spectral resolution inherent and apparent optical property data for remote sensing applications

: Light emerging from natural water bodies and measured by remote sensing radiometers contains information about the local type and concentrations of phytoplankton, non-algal particles and colored dissolved organic matter in the underlying waters. An increase in spectral resolution in forthcoming satellite and airborne remote sensing missions is expected to lead to new or improved capabilities to characterize aquatic ecosystems. Such upcoming missions include NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Mission; the NASA Surface Biology and Geology observable mission; and NASA Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) airborne missions. In anticipation of these missions, we present an organized dataset of geographically diverse, quality-controlled, high spectral resolution inherent and apparent optical property (IOP/AOP) aquatic data. The data are intended to be of use to increase our understanding of aquatic optical properties, to develop aquatic remote sensing data product algorithms, and to perform calibration and validation activities for forthcoming aquatic-focused imaging spectrometry missions. The dataset is comprised of contributions from several investigators and investigating teams collected over a range of geographic areas and water backscattering, as well as remote-sensing reflectance, and irradiance reflectance. The dataset can be radiance distribution the of reflectance ( and radiance- remote-sensing reflectance ( IOPs absorption backscattering m ( a ph ( λ ), m -1 non-algal ( a ( ( cdom ( λ m backscattering bw ( m -1 ) ( λ m -1 ). well-documented, quality-controlled data sets consisting of near-synchronous depth profiles of IOPs and AOPs within the water column and near-surface reflectance and optical properties as part of an international effort to build a dataset for algorithm development and testing. All contributors to the database have actively taken part in the quality assessment of the data. Variable assignments, accuracy estimates, and measurement details were given and confirmed by the data providers. Data that either had IOP or AOP at high spectral resolution 140 were included in the dataset. To arrange data in an organized, uniform structure, data were edited as follows. Data were filtered by considering depths from the surface to no greater than 50 m depth. We rounded data provided at fractional wavelengths to the nearest integer. Missing data is represented in the data files by placeholder values of − 999. Metadata is provided at the top of each data file, detailing the contact information for the data provider, the file source, data publication reference(s), native data collection range and resolution. The spectral range of the Schaeffer collected in situ measurements and water samples during boat-based surveys in Florida estuaries 310 between September 2009 and November 2011. Hydrographic profiling measurements were collected using a Seabird CTD package. A free-falling hyperspectral profiling system (HyperPRO, Satlantic, Halifax, NS, Canada) provided in-water hyperspectral (400–735 nm, interpolated every 1 nm) measures of downwelling irradiance ( E d ( z , λ )), upwelling radiance ( L u ( z , λ )), and depth ( z ). Water samples were collected 0.5 m below the air-water surface for absorption (phytoplankton pigment, non-algal particles, CDOM) and extracted chlorophyll analyses. 315 CDOM absorption was measured in a 10 cm cuvette using a Shimadzu UV1700 dual-beam spectrophotometer at 1 nm intervals between 200–700 nm with Milli-Q deionized water as a reference. Total particulates were collected on Whatman 25 mm GF/F filters and analyzed with a Shimadzu UV1700 dual-beam spectrophotometer at 1 nm intervals between 400– 800 nm with 0.2 μm filtered seawater as the reference standard (Pegau et al., 2003). Pigments were extracted from filters with warm methanol and rescanned to measure the detrital absorption (Kishino 320 et al., 1985). aquatic data from a variety of inland, coastal, estuary, and open ocean equatorial, mid- and high-latitude locations. This compilation of aquatic data is a first step in achieving a global distribution of high resolution IOP and AOP data, which we encourage the community to use for aquatic remote sensing development and related activities. We recommend further in situ campaigns be commissioned to collect coincident spectral resolution IOP and AOP data over regions with limited current coverage, for example, high latitude, inland and southerly waters. Such data could also be collected via and in conjunction with upcoming airborne high spectral resolution remote sensing campaigns. Additional in situ data collection over gap areas would be helpful in development, calibration and validation of global algorithms.

3 Torrecilla and others (2011) demonstrated that hyperspectral data of phytoplankton absorption and remote-sensing reflectance provide improved discrimination of dominant phytoplankton groups in open-ocean environments 75 compared with multi-spectral data. High spectral resolution aquatic remote sensing significantly improves retrievals of optical constituents in inland, coastal and polar aquatic environments, where these environments exhibit significant smaller-scale temporal and spatial variability, increased decoupling between in-water constituents, and a greater dynamic range in parameter values compared to the open ocean (Mouw et al., 2015;Bell et al., 2015;Dierssen et al., 2015;Hu et al., 2015;Vandermeulen et al., 2017). In inland, coastal and polar aquatic areas, 80 dissolved organic matter (DOM) and non-algal particles (NAP) play a more important role in affecting the color of water as well as its biogeochemistry, sediment transport, and primary productivity (Devred et al., 2013;Mouw et al., 2017). Thus, greater measurement precision is desirable. Carbon pools are also varied in inland and coastal environments due to riverine inputs, terrestrial influence, resuspension and mixing requiring greater spectral resolution and broader spectral range to differentiate the spectral slope of CDOM sources. Further, there are 85 increased instances of harmful algal bloom formation in many aquatic environments. Some harmful algal blooms can be discriminated based on their unique optical signatures and therefore additional spectral bands beyond the current multi-spectral capabilities would be highly beneficial (Wang et al. 2016, Pahlevan et al., 2019. Moving geographically to polar latitudes, Neukermans and others (2016) demonstrated improved discrimination of planktonic communities in the Arctic by using hyperspectral instead of multispectral satellite data. In short, remote 90 sensing capabilities in all aquatic environments are expected to improve considerably in precision and accuracy with high radiometric quality high spectral resolution measurements.
We summarize many of the historic, current and forthcoming high spectral resolution satellite missions potentially applicable to aquatic remote sensing goals in Figs. 1 and 2. High spectral resolution technological demonstration 95 satellite missions that have flown or are currently in operation or late planning stages are detailed as follows. One of the longest spaceborne hyperspectral data records is provided by NASA's EO-1 Hyperion sensor, which was NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission is intended to be a hyperspectral atmospheric and ocean color mission to be launched in 2022-2023 and to provide data to further the understanding of a myriad of Earth system processes including those involving ocean ecology, biogeochemistry, as well as 115 atmospheric composition and dynamics (see more details in Werdell et al., 2019). One of the central objectives of the PACE mission is to improve our understanding and quantification of the aquatic biogeochemical cycling and ecosystem function in response to anthropogenic and natural environment variability and change. High spectral resolution coincident IOP/AOP data are required to aid in development and refinement of algorithms to characterize and quantify aquatic conditions and for the calibration and validation of satellite measurements. A Surface Biology 120 and Geology mission is an additional likely upcoming U.S. space agency hyperspectral mission. It has been recommended as the first Earth Observation mission to come following the currently scheduled remote sensing missions. This Surface Biology and Geology mission is targeted to collect hyperspectral visible-shortwave infrared imagery and multi-or hyperspectral thermal imagery, at 30-60 m spatial resolution and will include measurements of inland and coastal environments (National Academies of Sciences, Engineering, and Medicine, 2018). 125 At present, there is a paucity of coincident in situ optical aquatic measurements of high spectral resolution. There are databases providing multispectral resolution IOPs and AOPs, with varying degrees of updates in recent years (e.g. Werdell and Bailey, 2002;Werdell and Bailey, 2005;Valente et al., 2019). We present the first organization of existing quality-controlled hyperspectral IOP and AOP data from polar, open ocean, estuary, coastal, and inland 130 water. The dataset is intended for remote sensing algorithm development activities associated with upcoming high spectral resolution satellite and airborne missions.

Materials and Methods
In 2015, in the early development of the PACE Mission, there was an open call to the aquatic remote sensing 135 community to contribute well-documented, quality-controlled data sets consisting of near-synchronous depth profiles of IOPs and AOPs within the water column and near-surface reflectance and optical properties as part of an international effort to build a dataset for algorithm development and testing. All contributors to the database have actively taken part in the quality assessment of the data. Variable assignments, accuracy estimates, and measurement details were given and confirmed by the data providers. Data that either had IOP or AOP at high spectral resolution 140 were included in the dataset. To arrange data in an organized, uniform structure, data were edited as follows. Data were filtered by considering depths from the surface to no greater than 50 m depth. We rounded data provided at fractional wavelengths to the nearest integer. Missing data is represented in the data files by placeholder values of −999. Metadata is provided at the top of each data file, detailing the contact information for the data provider, the file source, data publication reference(s), native data collection range and resolution. The spectral range of the 145 https://doi.org/10.5194/essd-2019-105 database is 300-900 nm, provided at 1 nm resolution. Variables included in the database are listed in Table 1. Data collection characteristics are presented in Table 2. Figure 3 and Table 3 detail the global distribution of coincident IOP/AOP data. In general terms, AOPs were measured using commercially available radiometer systems that either float at the surface or vertically profile the water column. IOPs were measured using in-water instrumentation and spectrophotometric analysis of discrete water samples (i.e. water sample removed from the aquatic environment). 150 Brief descriptions of provider and cruise-specific protocols and methodology are given in the following paragraphs.

Methods by Data Contributor and Expedition
In this section, the data providers describe their specific data collection methods used in acquiring and processing the provided data. Methods not previously published in peer reviewed literature are detailed fully here. 155

Ackleson -RIO-SFE-1 and RIO-SFE-3
Ackleson provides in situ data from the Remote and In Situ Observations -San Francisco Bay and Delta Ecosystem (RIO-SFE) data collection efforts over nine stations in the bay area of San Francisco, California, USA. In-water spectral absorption and attenuation were measured using a WETLabs AC-S and AC-9. The AC-9 intake was passed 160 through a 0.7 μm cartridge filter to remove particulates, thus, those measurements represent only very small particles and dissolved impurities (acdom and ccdom). The particulate absorption coefficient, ap(λ), was calculated from the difference between AC-S measurements of whole water, a(λ) and ac-9 acdom(λ). Backscattering, bb(λ), was measured by a WETLabs ECO-VSF 3.

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Above-water Rrs(λ) was measured between 400 nm and 900 nm using an Analytical Spectral Devices (ASD; Boulder, CO) handheld Spectrometer. The procedure for measuring reflectance is a modified version of Carder and Steward (1985). At each station, 10 sets of measurements were made consisting of 1) reflected radiance from a Spectralon 10% reflectance plaque (Labsphere, Inc., North Sutton, NH), 2) radiance reflected from the sea surface, and 3) radiance from the section of the sky that would be reflected off the sea surface at the measurement angle. 170 These repetitions were completed as rapidly as possible in order to minimize the impact of changing light or water conditions. Measurements were made between 90° and 135° azimuthal angle relative to the position of the sun and at a 30° angle relative to the vertical to minimize sun glint (Mobley and Stramski, 1997;Mobley 1999).

Boss, Chase -Tara Expeditions and SABOR 175
The Tara Oceans expedition was a two Atlantic and Mid-Atlantic coast from July thru August 2014. A full description of these Tara and SABOR expeditions and the Boss/Chase provided IOP and AOP datasets and data processing can be found in Boss et al., 2013, Chase et al., 2017, and Matsuoka et al., 2017. Briefly, IOPs were measured by an inline system that included a WET-Labs AC-S, a CDOM fluorometer and a thermosalinograph. Particulate properties were computed from the difference between measurements of the total and dissolved fraction (Dall'Olmo et al., 2009;Slade et al., 2010). 185 Absorption by the dissolved fraction was computed by interpolating between daily discrete samples collected with a 2 m long Ultra Path capillary wave guide using the filtered AC-S measurements (Matsuoka et al., 2017). During the Tara Oceans/Mediterranean and the SABOR campaigns, reflectance was measured using a Satlantic hyper-spectral radiometer buoy (a.k.a. HyperPro in buoy mode), with radiance measured by the upwelling radiometer and propagated to the surface using a bio-optical model, and then used together with downwelling irradiance to calculate 190 remote-sensing reflectance (Rrs(λ)) (see Chase et al., 2017 for details on data processing). During the Tara Arctic campaign, a C-OPS profiling radiometer system was used to measure upwelling radiance and downwelling irradiance and subsequently calculate Rrs(λ) at 19 wavelengths between 320 nm and 880 nm.

Bricaud -BIOSOPE 195
The BIogeochemistry & Optics SOuth Pacific Experiment (BIOSOPE) cruise on R/V l'Atalante, from October through December 2004 followed an 8000 km transect from the mesotrophic waters around the Marquesas Islands to the hyperoligotrophic waters of the South Pacific Gyre, and then to the eutrophic waters of the upwelling area off Chile. BIOSOPE was a collaborative cruise where participating investigators were responsible for making subsets of optical measurements. With the combined data of the contributing BIOSOPE investigators, nearly all BIOSOPE 200 campaign stations contain complete sets of AOP and IOP data. This section summarizes Bricaud's methodologies in BIOSOPE campaign data collection. A detailed description of the dataset and methods can be found in Bricaud et al. (2010).
Particulate and CDOM absorption measurements were made on board. For particulate absorption measurements, 205 seawater samples were collected on Whatman GF/F filters, and absorption spectra, ap(λ), were measured using the filter pad technique (with a soaked blank filter as a reference), using a Perkin-Elmer Lambda-19 spectrophotometer equipped with an integrating sphere. Non-algal absorption spectra, anap(λ), were measured on the same filters after pigment extraction in methanol (Kishino et al. 1985). When necessary, the residual absorption due to incompletely extracted pigments was corrected by applying an exponential fit (over the wavelength ranges where pigment 210 absorption is negligible) to actual spectra.
All spectra were shifted to zero in the near infrared (750-800 nm average) to minimize possible differences between sample and reference filters. Measured optical densities were corrected for the pathlength amplification effect (according to Allali et al. 1997 for clear waters, and to Bricaud and Stramski, 1990 for eutrophic waters) and then 215 7 converted into absorption coefficients (in m -1 ). Finally, phytoplankton absorption spectra, aph(λ), were obtained by subtracting anap(λ) from ap(λ).
CDOM absorption measurements were performed using a WPI Ultrapath capillary waveguide with a 2 m pathlength. Samples were filtered under dim light into glass bottles, using pre-rinsed 0.2 µm Sartorius filters, and 220 then analysed immediately. High-performance liquid chromatography quality water, artificially salted (35 g L -1 ) with precombusted NaCl, was used as reference water. Between each measurement, the sample cell was cleaned according to the WPI, Inc. recommendations. Replicate measurements (including all handling steps) showed that the reproducibility was approximately ± 0.005 m -1 at 375 nm.

Craig -BBOMB
All measurements from provider Craig are derived from collection of data at the Bedford Basin Ocean Monitoring Buoy (BBOMB), a coastal ocean monitoring buoy located in the Bedford Basin near Halifax, Nova Scotia, Canada.
A full description of the Craig dataset and acquisition protocols can be found in Craig et al. (2012). Water samples were collected by Niskin bottle at a depth of 1 m for the determination of various water column parameters, that 230 included spectral particulate absorption coefficient, ap(λ) and acdom(λ). Wherever possible, NASA Ocean Optics Protocols (Pegau et al., 2003) were followed for all sample acquisition, handling, storage and analysis. Briefly, ap(λ) and aph(λ) spectra were determined from water samples that were filtered under low pressure through a 25 mm GF/F (Whatman) filter. The particulate absorption coefficient, ap(λ), in the range 350-800 nm was determined in a Cary UV-VIS spectrophotometer with the filter pad mounted on a quartz glass slide and placed at the entrance to an 235 integrating sphere in a modification (Craig, 1999) of the Shibata (1959) opal glass technique. Samples were depigmented by soaking the filters in a 0.1% active chlorine solution of NaClO (Kishino et al., 1985;Tassan and Ferrari, 1995). The absorption spectra of the de-pigmented particles, anap(λ), were then measured as described above and aph(λ) calculated from ap(λ) − anap(λ).

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Depth profiles of hyperspectral downwelling irradiance, Ed(λ, z) (μW cm -2 nm -1 ) and upwelling radiance, Lu(λ, z) (μW cm -2 nm -1 sr -1 ) (where z is depth in the water column) were made with a HyperPro (Satlantic Inc.) profiling radiometer. Multiple casts (usually three) were made in quick succession and ~100 m away from the boat to avoid the influence of ship shadow (Mueller et al., 2003). A deck unit mounted to the superstructure of the boat also provided contemporaneous measurements of above-water surface incident irradiance, Es(λ), during profile 245 acquisition.

Lewis -BIOSOPE
Another participating science investigator on the BIOSOPE campaign was M. Lewis. This section details his collection of BIOSOPE cruise data. Remote sensing spectral reflectance (Rrs(λ), sr -1 , specifically, the ratio of water- 8 leaving radiance to downwelling irradiance above sea surface) in the South Pacific gyre was computed from direct measurements of downwelling irradiance above the sea surface (Es(λ), W m -2 nm -1 ) taken aboard ship, and measurements of upwelling radiance (Lu(λ), W m -2 nm -1 sr -1 ) made at a depth of 20 cm below the ocean surface, using a modified hyperspectral profiling radiometer adapted to float at the sea-surface and tethered such that the instrument operated at a distance of ~100 m from the vessel (HyperPro, Satlantic; Claustre et al., 2008;Stramski et 255 al., 2008;Lee et al., 2010). Instrument tilt was measured directly; measurements were rejected if tilts exceeded 5 degrees. Measurements were made over the spectral region 380-800 nm with a resolution of 3.3 nm and with each band having a half-maximum bandpass of 10 nm. Dark values were taken every five samples by use of an internal shutter. These were linearly interpolated for each light value, and then subtracted from the observations. Calibration coefficients and corrections for immersion effects were obtained following standard protocols (Mueller 260 et al., 2003) and applied to the measurements; demonstrated absolute accuracies are < 2.8% for radiance and < 2.1% for irradiance (see Gordon et al., 2009). Irradiance and radiance data were taken for 3 minutes at each deployment, with each observation within the deployment time-series representing integration times of 0.03 to 0.5 seconds, depending on the intensity of the incident radiance. These measurements were then interpolated to a common time frame at a frequency of every 2 seconds and to a common spectral resolution every 2 nm. 265 Upwelling radiance measurements were then propagated to the sea-surface using an iterative approach that estimates the spectral diffuse attenuation coefficient from spectral ratios of measured radiance, and the water-leaving radiance above the sea surface, LW(λ), is then computed based on Fresnel reflectance at the water-air boundary and the real relative index of refraction of water (Mueller et al., 2003). A 3 minute time series of Rrs was made by dividing the 270 computed water-leaving radiance by the downward irradiance for each time interval, and an average value and standard deviation computed for each deployment.

Mouw -Lake Superior Studies
Provider Mouw contributed data from measurements made by researchers at the University of Rhode Island in the 275 inland water body, Lake Superior, the largest of the Great Lakes of North America. A detailed description of the methods used for inland IOP and AOP observations can be found in Mouw et al. (2017). Optical and biogeochemical data were collected in Lake Superior during the ice-free months (May-October) of 2013 through 2016. The dataset consists of a full suite of coincident IOPs and AOPs, including a, acdom, acdom_dis, anap_dis, anw, ap, ap_dis, bb, bbp, c, cnw, and Rrs(λ). The variables used to retrieve Rrs are available by request from the data contributor. 280 The contributor also notes that aph can be calculated from the provided variables.
AOP radiometric measurements were made with three HyperOCR spectral radiometers (Satlantic Inc.) that measure between 350 nm and 800 nm with approximately 3 nm resolution (137 total wavelengths). In-water Ed(λ) and Lu(λ) HyperOCR sensors were attached to a free-falling Profiler II frame (Satlantic Inc.), while the Es(λ) sensor was 285 mounted on top of the ship to allow for correction of the other measurements due to changing sky conditions. At each station, the system was deployed for three cast types: surface, multi-and full profile. To characterize the airwater interface, a floatation collar on the profiler frame enabled continuous measurement of Lu(λ) approximately 20 cm below the water surface for 5 minutes (surface profile). The flotation collar was removed, and the profiler then deployed in free-fall mode, measuring five consecutive profiles from the surface to 10 m to characterize the near-290 surface light field (multi-profile). Finally, the profiler was allowed to free-fall to the 1% light level or to within 10 m of the bottom, whichever was shallower (full profile). All methods and analysis follow the NASA ocean optics protocols for satellite ocean color sensor validation (Mueller et al., 2003).
IOPs were collected via a vertically profiled bio-optical package that measures absorption, attenuation (WET Labs 295 AC-S) and backscattering (WET Labs ECO-BB9) along with concurrent temperature, salinity (SeaBird CTD 37SI) and fluorometeric chlorophyll a (WET Labs ECO-FL3). All methods and analysis followed the NASA ocean optics protocols for satellite ocean color sensor validation (Mueller et al., 2003). Total absorption and attenuation (a(λ) and c(λ), m -1 , respectively) were resolved at 81 wavelengths between 400-750 nm.

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For laboratory analysis of discrete water samples, spectral CDOM, particulate, non-algal and phytoplankton absorption were measured spectrophotometrically (Perkin-Elmer Lambda 35 UV/VIS dual-beam) for wavelengths between 300 nm and 800 nm. Absorption of CDOM filtrate was measured in a 10 cm cuvette following NASA's Ocean Optics Protocols (Mueller et al., 2003) using a slit-width of 2 nm and a scan rate of 240 nm min -1 . For particulate and non-algal absorption, we followed the transmission-reflectance (T−R) method (Tassan and Ferrari, 305 2002;Lohrenz, 2000;Lohrenz et al., 2003) that utilizes an integrating sphere to correct measurements for the contribution of scattering.

Schaeffer -Florida Estuary Optics
Provider Schaeffer collected in situ measurements and water samples during boat-based surveys in Florida estuaries 310 between September 2009 and November 2011. Hydrographic profiling measurements were collected using a Seabird CTD package. A free-falling hyperspectral profiling system (HyperPRO, Satlantic, Halifax, NS, Canada) provided in-water hyperspectral (400-735 nm, interpolated every 1 nm) measures of downwelling irradiance (Ed(z,λ)), upwelling radiance (Lu(z,λ)), and depth (z). Water samples were collected 0.5 m below the air-water surface for absorption (phytoplankton pigment, non-algal particles, CDOM) and extracted chlorophyll analyses. 315 CDOM absorption was measured in a 10 cm cuvette using a Shimadzu UV1700 dual-beam spectrophotometer at 1 nm intervals between 200-700 nm with Milli-Q deionized water as a reference. Total particulates were collected on Whatman 25 mm GF/F filters and analyzed with a Shimadzu UV1700 dual-beam spectrophotometer at 1 nm intervals between 400-800 nm with 0.2 μm filtered seawater as the reference standard (Pegau et al., 2003).
For the ANT26 and KM12 cruises, discrete water samples within the upper 5 m were collected from a CTD-Rosette equipped with Niskin bottles. The spectral absorption coefficient of particulate material, ap(λ), was determined 345 spectrophotometrically with a filter pad technique for particles retained on a 25 mm glass fiber filter (GF/F, Whatman). Measurements were made at 1 nm resolution over the spectral region 300-850 nm using a Perkin-Elmer Lamba 18 spectrophotometer equipped with a 15 cm diameter integrating sphere. The filters were placed inside the sphere to minimize potential scattering error, and the correction for pathlength amplification factor determined for this configuration of measurement was used . The partitioning of ap(λ) into phytoplankton, 350 aph(λ), and non-algal particle, anap(λ), contributions was accomplished through the chemical extraction of pigments using methanol (Kishino et al., 1985). The absorption coefficient of CDOM, acdom(λ), on ANT26 was determined on discrete water samples using a PSICAM instrument (Röttgers and Doerffer, 2007). For KM12, acdom was measured in situ using a WET Labs AC-S.

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The spectral remote-sensing reflectance, Rrs(λ), for the ANT26 and KM12 cruises was determined by averaging a time-series of radiometric measurements from a Satlantic HyperPro II radiometer attached to a surface float and ~3 nm resolution and subsequently interpolated to 1 nm intervals. Subsurface measurements of the upwelling zenith radiance (i.e., light propagating towards zenith) made at 0.2 m depth were propagated to and across the sea-surface 360 and combined with above-surface measurements of downwelling planar irradiance to estimate Rrs(λ) .

Data Availability
The diverse set of in situ apparent and inherent optical property data are stored and provided free of charge at the 365

Results and Discussion
Overall, the collection of datasets provides mostly coincident IOP/AOP data from a wide range of latitudes and water types, including polar, open ocean, estuary, coastal and inland water environments. We detailed the specific cruise, instrument and methodology approaches taken by each data provider. The majority of the data has been 375 published as referenced. The few contributed data sets which are not yet published in peer reviewed literature are fully described in this manuscript. Thus, the data provide a robust means to evaluate aquatic remote sensing observations toward further remote sensing science research and development goals. The in situ dataset has been stored and is provided free of charge at the PANGAEA data archive and publisher for Earth and Environmental Science (https://doi.pangaea.de/10.1594/PANGAEA.902230) as detailed in Section 3. 380 Hereafter we describe the spatial and temporal resolution covered by the dataset for coincident IOP and AOP, where when referring to coincident data, we describe data that have Rrs and at least one IOP variable available. IOP and AOP data are provided from 12 cruises, from 2004 through 2016, covering Arctic, mid-and equatorial open ocean, estuary, coastal and inland aquatic sites (see Table 2, Fig. 3). A summary of the number of data points available for 385 every cruise for each of the variables is provided in Table 3. Table 3 shows that IOPs are generally collected at more stations than AOPs. The number of data available for IOPs is also much larger than AOPs because we count every single depth as a single data point. The three datasets with the largest amount of data (where each station, depth and and the Ackleson dataset provides between nine and 33 different geographic stations. Of note, from the BIOSOPE collaborative cruise, coincident BIOSOPE AOP and IOP data is provided by a suite of contributors. In this 395 manuscript, BIOSOPE data contributors and variables include Bricaud (acdom, anap, ap), Lewis (Rrs) and Stramski/Reynolds (bb).
Similar to the synergies of the BIOSOPE campaign with multiple investigators, dataset users are also encouraged to consider harnessing provided data to derive additional desired variables. For example, many stations contain a 400 complete set of both an AOP measurement (R or Rrs) and the two main IOPs (a and bb). Note that total absorption can be calculated if all constituent absorption coefficients are measured in conjunction with published IOPs of pure water; this applies to most of our stations. Derivation and combinations of provided data ultimately depend on the intent and goals of the user.

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We show the range in reflectance values (Rrs) provided from diverse geographic locations of inland, estuary, coastal, open ocean and polar waters in Fig. 4. The diversity in the signal from inland water (Fig. 4, f) to coastal (Fig. 4, a, d, g), Arctic (Fig. 4, b) and open ocean waters (Fig. 4, c, e, h) show a range of the various particulate, biogeochemical, and other water conditions characteristic of different aquatic environments. The graphs also show the level of detail that can be extracted by varying spectral resolutions. Lower spectral resolution is shown in the 410 Boss/Chase Arctic data (from 5 nm to tens of nm separation), and higher resolution is found in Boss/Chase Tara Oceans, Lewis and Mouw (2-3 nm spectral resolution) and Ackleson, Craig, Schaeffer, and Stramski/Reynolds (1 nm spectral resolution).
When assessing the geographic distribution of the coincident IOP and AOP data, we found data were more frequent 415 for latitudes between 30°N and 40°N and longitudes between 50°W and 100°W (Fig. 5). The Ackleson (San Francisco Bay), Schaeffer (northern Gulf of Mexico) and Mouw (Lake Superior) data were acquired at those latitudes and longitudes. These results also highlight the lack of data for the area between 100°E and 180°E and at latitudes south of 50°.

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We caution users of the datasets to consider inherent limitations to certain data collections. For example, some data collected in turbid waters were found to contain less signal compared to noise. Specifically, the AC-S dataset of Boss/Chase has significant uncertainties in ap in the blue part of the spectrum due to uncertainty in the scattering correction of this measurement, particularly in turbid waters (e.g. Stockley et al., 2017). Additionally, as previously detailed, not all data collected is coincident. We have indicated in Fig. 3 and Table 3 and several details including 425 the geographic and variable distribution concerning coincident data. Overall, because most data have already been published in peer review literature with study collection, processing and analysis details and where needed fully detailed here; readers are able to determine the utility and applicability of the datasets provided toward further use of the data. We have compiled aquatic data from a variety of inland, coastal, estuary, and open ocean equatorial, mid-and highlatitude locations. This compilation of aquatic data is a first step in achieving a global distribution of high spectral resolution IOP and AOP data, which we encourage the community to use for aquatic remote sensing algorithm development and related activities. We recommend further in situ campaigns be commissioned to collect coincident 435 high spectral resolution IOP and AOP data over regions with limited current coverage, for example, high latitude, inland and southerly waters. Such data could also be collected via and in conjunction with upcoming airborne high spectral resolution remote sensing campaigns. Additional in situ data collection over gap areas would be helpful in development, calibration and validation of global algorithms.

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As additional high spectral resolution IOP/AOP data become available, this dataset can be expanded accordingly. A comprehensive collection of hyperspectral IOP/AOP datasets would be extremely useful for both development of aquatic remote sensing algorithms, and for the planning of future field sampling missions to address identified gaps.
Future expansion of this collection of datasets, beyond addition of optical data, could be inclusion of biogeochemical information (e.g. phytoplankton pigments, carbon stocks, turbidity, particulate size distribution, and 445 phytoplankton composition) to further assist in development of algorithms relating to biogeochemical parameters. It is crucial to collect coincident high spectral resolution IOP and AOP remote sensing data for the development of robust algorithms. These data, algorithms and scientific investigations can improve our understanding of Earth system biogeochemical, ecological and physical processes on local to global scales.

Author Contribution
The initial concept for this effort came from the NASA PACE Mission early science project discussions on a goal to provide the community with high spectral resolution datasets. CR and EB sent initial community requests for in situ aquatic data contributions. KC gathered and stewarded the data organization effort. KC led preparation, writing of the manuscript and generation of figures and tables. All data providers assisted in writing the methods of their data 455 collection. All co-authors contributed to the scientific discussion, review and editing of the manuscript.

c(λ)
Total attenuation equal to sum of particulate attenuation, CDOM attenuation and water attenuation (m -1 )