AndreaBozzo/ceres-open-data-index huggingface dataset:
Sea Surface Temperature (SST) Long-term Mean, 1985-2018 - American Samoa

Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the mean SST (degrees Celsius) of the weekly time series from 1985-2018.

These SST dataset are derived from CoralTemp 5-km gap-free analyzed blended sea surface temperature over the global ocean. CoralTemp is derived from three different but related 5-km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present. 1) Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002). 2) Geo-Polar Blended Night-Only Sea Surface Temperature Reanalysis (2002-2016). 3) Geo-Polar Blended Night-Only Sea Surface Temperature Near Real-Time (2017 to present). The 8-day composites are generated from daily Coral Reef Watch (CRW) files by OceanWatch Central Pacific.

The SST long-term mean was calculated by taking the average of all weekly data from 1985-2018 for each pixel.

Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/CRW_sst_v1_0_8day.graph

Tags: american samoa, aquatic ecosystems, biosphere, coastal areas, coastal processes, coral reef, coral reefs, earth science, ecosystems, human dimensions, human settlements, manua, marine ecosystems, ocean, ocean temperature, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, reef, reef habitat, rose atoll, sea surface temperature, south pacific ocean, swains, tau, tutuila
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Hui O Ka Wai Ola Water Quality Data

The goal of the Hui O Ka Wai Ola (Association Of The Living Waters) citizen-science based water quality program is to increase the capacity for monitoring water quality in Maui (2016-) and Lanai (2023-) coastal waters by generating reliable data to assess long-term water-quality conditions and detect temporal trends. These data augment the data produced by the Hawaii Department of Health (DOH) Clean Water Branch (CWB) beach monitoring program.
    
Data are collected and analyzed every two or three weeks for physical and chemical parameters, including ocean salinity, pH, temperature, organic nutrients (nitrogen and phosphorous compounds), dissolved oxygen (DO), and total suspended sediment (TSS). Some water samples are immediately tested at mobile labs while others are processed for testing at University of Hawaii and/or other labs.

Tags: ammonia, autoanalyzer, bottles/flasks/jars, central pacific ocean, chemical meters/analyzers, coastal stations, conductivity sensors, continent, earth science, fractional_saturation_of_oxygen_in_sea_water, hawaii, hawaiian islands, in situ land-based platforms, in situ/laboratory instruments, lanai, latitude, longitude, marine geochemistry, mass_concentration_of_ammonia_in_sea_water, mass_concentration_of_nitrate_and_nitrite_in_sea_water, mass_concentration_of_nitrogen_in_sea_water, mass_concentration_of_oxygen_in_sea_water, mass_concentration_of_phosphate_in_sea_water, mass_concentration_of_phosphorus_in_sea_water, mass_concentration_of_silicate_in_sea_water, maui, nitrate, nitrite, nitrogen, north america, ocean, ocean chemistry, ocean contaminants, ocean optics, ocean platform/ocean stations, ocean temperature, oceans, oxygen, pacific islands ocean observing system, pacific ocean, pacioos, ph, ph meters, phosphate, phosphorus, photon/optical detectors, salinity, salinity/density, samplers, sea_water_ph_reported_on_total_scale, sea_water_practical_salinity, sea_water_temperature, sea_water_turbidity, silicate, temperature sensors, temperature/humidity sensors, time, turbidity, turbidity meters, united states of america, water quality, water temperature
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Coral Favorability: Non-Managed Conditions: Intermediate Emissions - American Samoa

Many aspects of the environment are outside the control of local or regional resource managers. These conditions may require concerted global action to affect change (e.g., water temperatures) or cannot be controlled at all (e.g., wave power). This layer synthesized spatial information for several non-managed conditions to create a relative score for how favorable a given location is for coral growth and survival.

Environmental conditions contributing to this layer included: marine calcite concentration (a proxy for ocean acidification), irradiance (photosynthetically available radiation, or PAR), thermal stress (annual severe bleaching threshold), wave power (per meter of wave front), and proximity to soils eroded by sea level rise.

Projections exist for how some of these conditions may change over the next century based on the trajectory of global greenhouse gas emissions. This project explored how the relative favorability of non-managed conditions could change between the present climate scenario and the rest of the 21st century. This layer represents the future climate scenario for an intermediate emissions scenario (Representative Concentration Pathway 4.5), in which global greenhouse gas emissions peak mid-century and then begin to fall.

Covariation in these conditions was accounted for using principal component analysis (PCA) to form composite variables of conditions that have strong relationships with one another. The resulting principal components were averaged and scaled from 0 (worst) to 1 (best) to produce the coral favorability score for non-managed conditions. These data are provided as a raster with a resolution of 500 m for American Samoa, including Tutuila and the Manua Islands (Ofu, Olosega, and Tau).

Tags: american samoa, aquatic ecosystems, biosphere, coastal areas, coastal processes, conservation, coral reef, coral reef assessment, coral reefs, coupled climate models, earth science, earth science services, ecosystems, environmental impacts, environmental sustainability, human dimensions, human settlements, manua, marine ecosystems, models, ocean, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, reef, reef habitat, south pacific ocean, sustainability, tau, tutuila
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Sea Surface Temperature (SST) Average Annual Frequency of Anomalies, 1985-2018 - American Samoa

Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the annual average frequency of anomalies of SST from 1985-2018, with values presented as fraction of a year.

These SST dataset are derived from CoralTemp 5-km gap-free analyzed blended sea surface temperature over the global ocean. CoralTemp is derived from three different but related 5-km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present. 1) Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002). 2) Geo-Polar Blended Night-Only Sea Surface Temperature Reanalysis (2002-2016). 3) Geo-Polar Blended Night-Only Sea Surface Temperature Near Real-Time (2017 to present). The 8-day composites are generated from daily Coral Reef Watch (CRW) files by OceanWatch Central Pacific.

The SST average annual frequency of anomalies was calculated by taking the average number of weeks that exceeded the maximum monthly climatological SST value from 1985-2018 for each pixel.

Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/CRW_sst_v1_0_8day.graph

Tags: american samoa, aquatic ecosystems, biosphere, coastal areas, coastal processes, coral reef, coral reefs, earth science, ecosystems, human dimensions, human settlements, manua, marine ecosystems, ocean, ocean temperature, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, reef, reef habitat, rose atoll, sea surface temperature, south pacific ocean, swains, tau, tutuila
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Coral Favorability: Overall Environmental Conditions: Intermediate Emissions - Guam

The overall condition of the environment is a combination of managed and non-managed factors. While it is difficult for managers to prevent coral bleaching events, reefs experiencing fewer stressors may recover more quickly than reefs that were highly stressed at the time of bleaching. The scores for managed (see layer "gu_usgs_all_coralscore_mgt") and non-managed conditions (see layer "gu_usgs_all_coralscore_nonmgt_rcp45") were averaged to produce an overall environmental favorability score. This layer represents a relative score for how favorable overall conditions are for coral growth and survival from a scale of 0 (worst) to 1 (best) in the future climate scenario for an intermediate emissions scenario (Representative Concentration Pathway 4.5), in which global greenhouse gas emissions peak mid-century and then begin to fall. These data are provided for the island of Guam as a raster with a resolution of 1500 m.

Tags: aquatic ecosystems, biosphere, coastal areas, coastal processes, conservation, coral reef, coral reef assessment, coral reefs, coupled climate models, earth science, earth science services, ecosystems, environmental governance/management, environmental impacts, environmental sustainability, guam, human dimensions, human settlements, marine ecosystems, micronesia, models, ocean, oceans, pacific islands ocean observing system, pacific ocean, pacioos, reef, reef habitat, sustainability, western pacific ocean
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Turbidity (Kd490) Maximum Monthly Climatological Mean, 1998-2018 - American Samoa

Spectrally resolved water-leaving radiances (ocean color) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual 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 color data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean color 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 color data requires merging of the individual sensors without introducing artifacts.

The diffuse attenuation coefficient at 490 nm (Kd490) indicates the turbidity of the water column: i.e., how well visible light in the blue to green region of the spectrum penetrates the water column. The value of Kd490 represents the rate at which light at 490 nm is attenuated with depth. For example, a Kd490 of 0.1 per meter means that light intensity is reduced by one natural log within 10 meters of water. Thus, for a Kd490 of 0.1, one attenuation length is 10 meters. Higher Kd490 values mean shallower attenuation depths and thus higher turbidity, or lower clarity, of ocean water. This layer represents the maximum monthly climatological mean of Kd490 (m-1) from 1998-2018.

Data products generated by the Ocean Colour component of the European Space Agency (ESA) Climate Change Initiative (CCI) project. These files are 8-day 4-km composites of merged sensor products: Global Area Coverage (GAC), Local Area Coverage (LAC), MEdium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Ocean and Land Colour Instrument (OLCI), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and Visible Infrared Imaging Radiometer Suite (VIIRS).

A quality control mask was applied to remove spurious data associated with shallow water, following Gove et al., 2013. Monthly climatologies were calculated from monthly time series averaging for all same-months (e.g., January). Nearshore map pixels with no data were filled with values from the nearest neighboring valid offshore pixel by using a grid of points and the Near Analysis tool in ArcGIS then converting points to raster.

Data source: https://oceanwatch.pifsc.noaa.gov/erddap/griddap/esa-cci-kd-8d-v5-0.graph

Tags: american samoa, aquatic ecosystems, biosphere, coastal areas, coastal processes, coral reef, coral reefs, earth science, ecosystems, human dimensions, human settlements, kd490, manua, marine ecosystems, ocean, ocean optics, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, reef, reef habitat, rose atoll, south pacific ocean, swains, tau, turbidity, tutuila, water quality
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Commercial Net Fishing Estimated Average Annual Catch of Reef Fish, 2003-2013 - Hawaii

Nearshore fisheries in the Main Hawaiian Islands encompass a diverse group of fishers using a wide array of gears and targeting many different species. Communities in Hawaii often rely on these fisheries for economic, social, and cultural services. However, the stress from overfishing can cause ecosystem degradation and long-term economic loss. This layer represents the average annual commercial catch of reef fish by net fishing over the years 2003-2013 as reported in commercial catch data collected by the State of Hawaii Department of Aquatic Resources (DAR) Commercial Marine Landings Database (CML). "Net fishing" is a fairly broad category that can include everything from hand nets and throw nets to gill nets and seine nets; however, it was not possible to parse out more specific gears due to how DAR reports gear type. Commercial catch is reported to DAR in large irregular reporting blocks by gear and by species.

This layer's spatial footprint aligns with the inshore commercial reporting blocks from the shapefile served on the Hawaii Statewide GIS Program website (Fishchart2008.shp) (http://planning.hawaii.gov/gis/download-gis-data/). Data are filtered by DAR before release such that reporting blocks with less than three fishers reporting are excluded in order to protect fisher identities. It is not possible to explicitly distinguish between boat-based and shore-based fishing based on the gear types reported in CML data. The Ocean Tipping Points (OTP) project filtered the data for net fishing and reef fish species only and calculated average annual catch in kilograms by reporting block to match with data from the Marine Recreational Information Program (MRIP). In marine protected areas (MPAs) where boat-based fishing is not allowed, catch was set to zero; and inside de facto MPAs with restricted access, catch was reduced according to expert input and local knowledge. Average annual commercial catch data were converted from polygon to raster and then divided by the number of 100-m raster cells within each reporting block so that units are comparable to non-commercial fishing layers (kg/ha). The result assumes commercial catch is evenly distributed spatially across each reporting block.

Tags: agricultural aquatic sciences, agriculture, aquatic ecosystems, aquatic sciences, biosphere, central pacific ocean, coastal areas, coastal processes, continent, coral reef, coral reefs, earth science, ecosystems, environmental impacts, environmental sustainability, fisheries, hawaii, hawaiian islands, human dimensions, human settlements, marine ecosystems, north america, ocean, oceans, pacific islands ocean observing system, pacific ocean, pacioos, reef, reef habitat, sustainability, united states of america
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Sea Level Rise: American Samoa: High-Tide Flooding: 2090 Intermediate-High Scenario

This high-tide flooding layer provides a prediction of future sea level rise (SLR) inundation and was produced using a passive flooding model, often referred to as a "bathtub" model. It provides an assessment of flooded areas according to a specific water level. These water levels are determined using projections from the U.S. Interagency Task Force (ITF) (Sweet et al., 2022) in combination with land subsidence projections modeled by Han et al. (2019). The latter is included only for Tutuila, Aunuu, and Manua Islands (Ofu, Olosega, and Tau). In contrast, SLR projections for Swains Island and Rose Atoll only include the climate-related processes (ITF). The projections are modeled following both scenarios and time. The five scenarios range from low to high depending on the amount of greenhouse gases emissions, while time is divided by decade from 2030 to 2100.

We apply this model to the 2022 National Geodetic Survey (NGS) lidar DEM for American Samoa with 1-meter resolution. The DEM was leveled from NAD83 (PA11) to mean sea level at 0 m (MSL=0) in 2005. The adjustment of the DEM may lead to inaccuracies due to the lack of historic information. It is also important to acknowledge that any inaccuracies in the DEM will lead to inaccuracies in the flooding estimates.

In the 2090 intermediate-high scenario represented here, the modeled water level is 162 cm (126 cm for Rose and Swains). In this scenario, world-wide society continues to increase emissions rate. Tipping points, i.e. large and sudden changes, are triggered; ice loss increases rapidly but is not catastrophic. It is recommended using this scenario for planning construction of infrastructure with medium-to-high critical use and longer lifespans, such as a new government office.

Flood depth is provided in centimeters above the 2005 mean higher high water (MHHW) tide level.

It is essential to emphasize that the passive flooding model used to produce this data layer does not include the effects of waves on flooding. As a result, the extent and impacts of future flooding under high-wave conditions are not represented, which should be accounted for in planning efforts. In addition, the DEM is assumed to be unchanged as sea level rises, but in fact there will be erosion and changes in the shape of the land surface, and continued subsidence. This also must be considered, and it is best practice to consider any flooding extent or depth represented in this data layer as a best-case scenario, with the effects of dynamic shoreline processes leading to greater flood extent and depth than presented.

Tags: american samoa, atmospheric/ocean indicators, aunuu, climate indicators, coastal processes, earth science, environmental impacts, floods, human dimensions, inundation, manua, natural hazards, ocean, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, rose atoll, sea level rise, south pacific ocean, swains, tau, tutuila
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Sea Level Rise: American Samoa: High-Tide Flooding: 2030 Intermediate Scenario

This high-tide flooding layer provides a prediction of future sea level rise (SLR) inundation and was produced using a passive flooding model, often referred to as a "bathtub" model. It provides an assessment of flooded areas according to a specific water level. These water levels are determined using projections from the U.S. Interagency Task Force (ITF) (Sweet et al., 2022) in combination with land subsidence projections modeled by Han et al. (2019). The latter is included only for Tutuila, Aunuu, and Manua Islands (Ofu, Olosega, and Tau). In contrast, SLR projections for Swains Island and Rose Atoll only include the climate-related processes (ITF). The projections are modeled following both scenarios and time. The five scenarios range from low to high depending on the amount of greenhouse gases emissions, while time is divided by decade from 2030 to 2100.

We apply this model to the 2022 National Geodetic Survey (NGS) lidar DEM for American Samoa with 1-meter resolution. The DEM was leveled from NAD83 (PA11) to mean sea level at 0 m (MSL=0) in 2005. The adjustment of the DEM may lead to inaccuracies due to the lack of historic information. It is also important to acknowledge that any inaccuracies in the DEM will lead to inaccuracies in the flooding estimates.

In the 2030 intermediate scenario represented here, the modeled water level is 34 cm (7 cm for Rose and Swains). In this scenario, world-wide society continues current emissions rates, and sea level rises at increased rates compared to the intermediate-low scenario. Tipping points, i.e. large and sudden changes, are still not crossed. It is recommended using this scenario for planning construction of infrastructure with low-to-medium critical use and lifespans extending into the second half of the century, such as a new storefront.

Flood depth is provided in centimeters above the 2005 mean higher high water (MHHW) tide level.

It is essential to emphasize that the passive flooding model used to produce this data layer does not include the effects of waves on flooding. As a result, the extent and impacts of future flooding under high-wave conditions are not represented, which should be accounted for in planning efforts. In addition, the DEM is assumed to be unchanged as sea level rises, but in fact there will be erosion and changes in the shape of the land surface, and continued subsidence. This also must be considered, and it is best practice to consider any flooding extent or depth represented in this data layer as a best-case scenario, with the effects of dynamic shoreline processes leading to greater flood extent and depth than presented.

Tags: american samoa, atmospheric/ocean indicators, aunuu, climate indicators, coastal processes, earth science, environmental impacts, floods, human dimensions, inundation, manua, natural hazards, ocean, oceans, ofu, olosega, pacific islands ocean observing system, pacific ocean, pacioos, polynesia, rose atoll, sea level rise, south pacific ocean, swains, tau, tutuila
Organization: National Oceanic and Atmospheric Administration, Department of Commerce