as_uhslc_all_slr_xflood_2070_high_20day_v3 eng UTF8 dataset service Carla Baizeau University of Hawaii at Manoa cbaizeau@hawaii.edu https://uhslc.soest.hawaii.edu http web browser information pointOfContact 2025-07-29 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 2 column row area Sea Level Rise: American Samoa: Extreme High-Tide Flooding: 2070 High Scenario: 20 Days Per Year 2023-09-26 creation 2023-09-26 issued 2025-07-29 revision 3.0 org.pacioos as_uhslc_all_slr_xflood_2070_high_20day_v3 Carla Baizeau University of Hawaii at Manoa cbaizeau@hawaii.edu https://uhslc.soest.hawaii.edu http web browser information originator Philip R. Thompson University of Hawaii Sea Level Rise Center (UHSLC) philiprt@hawaii.edu originator Pacific Islands Ocean Observing System (PacIOOS) info@pacioos.org http://pacioos.org http web browser information publisher Related publications: Han, S.-C., J. Sauber, F. Pollitz, and R. Ray. 2019. Sea level rise in the Samoan Islands escalated by viscoelastic relaxation after the 2009 Samoa-Tonga earthquake. Journal of Geophysical Research: Solid Earth, 124, 4142-4156. https://doi.org/10.1029/2018JB017110; Sweet, W.V., B.D. Hamlington, R.E. Kopp, C.P. Weaver, P.L. Barnard, D. Bekaert, W. Brooks, M. Craghan, G. Dusek, T. Frederikse, G. Garner, A.S. Genz, J.P. Krasting, E. Larour, D. Marcy, J.J. Marra, J. Obeysekera, M. Osler, M. Pendleton, D. Roman, L. Schmied, W. Veatch, K.D. White, and C. Zuzak. 2022. Global and regional sea level rise scenarios for the United States: Updated mean projections and extreme water level probabilities along U.S. coastlines. NOAA Technical Report NOS 01. National Oceanic and Atmospheric Administration, National Ocean Service, Silver Spring, MD, 111 pp. https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nos-techrpt01-global-regional-SLR-scenarios-US.pdf; Thompson, P.R., M.J. Widlansky, B.D. Hamlington, M.A. Merrifield, J.J. Marra, G.T. Mitchum, and W. Sweet. 2021. Rapid increases and extreme months in projections of United States high-tide flooding. Nature Climate Change, 11, 584-590. https://doi.org/10.1038/s41558-021-01077-8. This extreme 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 higher high water at 0 m (MHHW=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. When assessing the impacts of future sea level rise, it is important to consider how often flood conditions will occur in a given year. A low-lying location will begin to see impacts of being flooded a few times per year. Then, as sea level rise increases, it will flood tens of times per year. Eventually, that location may be flooded under a daily high tide. The present scenario models a frequency of 20 flooding days per year. Please note that this frequency represents an average number of times per year (Thompson et al., 2021). Any particular year may have substantially more or less flooding days depending on local climate variability (such as the El Nino, La Nina cycle) and year-to-year variability in the tides due to changes in the alignment of the Earth, Moon, and Sun. Secondly, flooding frequencies are based on data from the Pago Pago tide gauge on Tutuila, which means that estimates may not perfectly represent local conditions outside the harbor or on other islands. However, this is the best source of information available, and we do not expect this to lead to significant inaccuracies in the estimates of flooding frequency. In the 2070 high scenario represented here, the modeled water level for a 20-day frequency is 203 cm (168 cm for Rose and Swains). In this scenario, world-wide society continues to increase emissions. Tipping points (large and sudden changes) are triggered, and worst-case possibilities arise. It is recommended using this scenario for planning construction of infrastructure with highly critical use and longer lifespans, such as a new hospital. 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. PacIOOS provides timely, reliable, and accurate ocean information to support a safe, clean, productive ocean and resilient coastal zone in the U.S. Pacific Islands region. Using data produced by the University of Hawaii Sea Level Center (UHSLC), this product was developed in cooperation with the Pacific Islands Ocean Observing System (PacIOOS) at the University of Hawaii at Manoa (UH) School of Ocean and Earth Science and Technology (SOEST) and the Department of Oceanography at UH SOEST in partnership with the University of Hawaii Sea Grant College Program, also within UH SOEST. An associated online viewer was funded by the Pacific Islands Climate Adaptation Science Center (PI-CASC). Carla Baizeau University of Hawaii at Manoa cbaizeau@hawaii.edu https://uhslc.soest.hawaii.edu http web browser information pointOfContact http://pacioos.org/metadata/browse/as_uhslc_all_slr_xflood_2070_high_20day_v3.png Sample image. Earth Science > Climate Indicators > Atmospheric/Ocean Indicators > Sea Level Rise > Inundation Earth Science > Human Dimensions > Environmental Impacts Earth Science > Human Dimensions > Natural Hazards > Floods Earth Science > Oceans > Coastal Processes > Sea Level Rise theme GCMD Science Keywords Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Aunuu Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Manua Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Ofu Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Olosega Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Rose Atoll Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Swains Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Tau Ocean > Pacific Ocean > South Pacific Ocean > Polynesia > American Samoa > Tutuila place GCMD Location Keywords PacIOOS > Pacific Islands Ocean Observing System project GCMD Project Keywords PacIOOS > Pacific Islands Ocean Observing System dataCenter GCMD Data Center Keywords This data layer provides a scientific prediction of potential future conditions from flooding due to sea level rise. The methodology is based on published, peer-reviewed techniques. However, as with any forecast, accuracy cannot be guaranteed and actual impacts may vary from these predictions. While considerable effort has been made to implement all components in a thorough, correct, and accurate manner, errors are still possible. The results are provided without warranty of any kind. The risks associated with use or non-use of the results are assumed by the user. The data may be used and redistributed for free but is not intended for legal use, since it may contain inaccuracies. Neither the data Contributor, University of Hawaii, PacIOOS, NOAA, State of Hawaii nor the United States Government, nor any of their employees or contractors, makes any warranty, express or implied, including warranties of merchantability and fitness for a particular purpose, or assumes any legal liability for the accuracy, completeness, or usefulness, of this information. Pacific Islands Ocean Observing System (PacIOOS) largerWorkCitation project eng oceans 1 -171.089797256602 -168.141348975554 -14.5591355232811 -11.0480017523415 Sea Level Rise: American Samoa: Extreme High-Tide Flooding: 2070 High Scenario: 20 Days Per Year 2023-09-26 creation 2023-09-26 issued 2025-07-29 revision Carla Baizeau University of Hawaii at Manoa cbaizeau@hawaii.edu https://uhslc.soest.hawaii.edu http web browser information originator Pacific Islands Ocean Observing System (PacIOOS) info@pacioos.org http://pacioos.org http web browser information publisher This extreme 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 higher high water at 0 m (MHHW=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. When assessing the impacts of future sea level rise, it is important to consider how often flood conditions will occur in a given year. A low-lying location will begin to see impacts of being flooded a few times per year. Then, as sea level rise increases, it will flood tens of times per year. Eventually, that location may be flooded under a daily high tide. The present scenario models a frequency of 20 flooding days per year. Please note that this frequency represents an average number of times per year (Thompson et al., 2021). Any particular year may have substantially more or less flooding days depending on local climate variability (such as the El Nino, La Nina cycle) and year-to-year variability in the tides due to changes in the alignment of the Earth, Moon, and Sun. Secondly, flooding frequencies are based on data from the Pago Pago tide gauge on Tutuila, which means that estimates may not perfectly represent local conditions outside the harbor or on other islands. However, this is the best source of information available, and we do not expect this to lead to significant inaccuracies in the estimates of flooding frequency. In the 2070 high scenario represented here, the modeled water level for a 20-day frequency is 203 cm (168 cm for Rose and Swains). In this scenario, world-wide society continues to increase emissions. Tipping points (large and sudden changes) are triggered, and worst-case possibilities arise. It is recommended using this scenario for planning construction of infrastructure with highly critical use and longer lifespans, such as a new hospital. 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. Open Geospatial Consortium Web Feature Service (WFS) 1 -171.089797256602 -168.141348975554 -14.5591355232811 -11.0480017523415 tight GetCapabilities https://geo.pacioos.hawaii.edu/geoserver/PACIOOS/as_uhslc_all_slr_xflood_2070_high_20day_v3/ows?service=WFS&version=1.0.0&request=GetCapabilities OGC:WFS OGC-WFS Open Geospatial Consortium Web Feature Service (WFS). Supported WFS versions include 1.0.0, 1.1.0, and 2.0.0. Supported output formats include CSV, GeoJSON, GeoJSON-P, GML, KML, and Shapefile (Zipped). download Sea Level Rise: American Samoa: Extreme High-Tide Flooding: 2070 High Scenario: 20 Days Per Year 2023-09-26 creation 2023-09-26 issued 2025-07-29 revision Carla Baizeau University of Hawaii at Manoa cbaizeau@hawaii.edu https://uhslc.soest.hawaii.edu http web browser information originator Pacific Islands Ocean Observing System (PacIOOS) info@pacioos.org http://pacioos.org http web browser information publisher This extreme 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 higher high water at 0 m (MHHW=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. When assessing the impacts of future sea level rise, it is important to consider how often flood conditions will occur in a given year. A low-lying location will begin to see impacts of being flooded a few times per year. Then, as sea level rise increases, it will flood tens of times per year. Eventually, that location may be flooded under a daily high tide. The present scenario models a frequency of 20 flooding days per year. Please note that this frequency represents an average number of times per year (Thompson et al., 2021). Any particular year may have substantially more or less flooding days depending on local climate variability (such as the El Nino, La Nina cycle) and year-to-year variability in the tides due to changes in the alignment of the Earth, Moon, and Sun. Secondly, flooding frequencies are based on data from the Pago Pago tide gauge on Tutuila, which means that estimates may not perfectly represent local conditions outside the harbor or on other islands. However, this is the best source of information available, and we do not expect this to lead to significant inaccuracies in the estimates of flooding frequency. In the 2070 high scenario represented here, the modeled water level for a 20-day frequency is 203 cm (168 cm for Rose and Swains). In this scenario, world-wide society continues to increase emissions. Tipping points (large and sudden changes) are triggered, and worst-case possibilities arise. It is recommended using this scenario for planning construction of infrastructure with highly critical use and longer lifespans, such as a new hospital. 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. Open Geospatial Consortium Web Map Service (WMS) 1 -171.089797256602 -168.141348975554 -14.5591355232811 -11.0480017523415 tight GetCapabilities https://geo.pacioos.hawaii.edu/geoserver/PACIOOS/as_uhslc_all_slr_xflood_2070_high_20day_v3/ows?service=WMS&version=1.3.0&request=GetCapabilities OGC:WMS OGC-WMS Open Geospatial Consortium Web Map Service (WMS). Supported WMS versions include 1.1.1 and 1.3.0. Supported map formats include AtomPub, GeoRSS, GeoTIFF, GIF, JPEG, KML/KMZ, PDF, PNG, SVG, and TIFF. Supported info formats include GeoJSON, GeoJSON-P, GML, HTML, and plain text. download Sea Level Rise: American Samoa: Extreme High-Tide Flooding: 2070 High Scenario: 20 Days Per Year 2023-09-26 creation 2023-09-26 issued 2025-07-29 revision University of Hawaii Sea Level Center (UHSLC) https://uhslc.soest.hawaii.edu http web browser information originator Pacific Islands Ocean Observing System (PacIOOS) info@pacioos.org http://pacioos.org http web browser information distributor This extreme 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 higher high water at 0 m (MHHW=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. When assessing the impacts of future sea level rise, it is important to consider how often flood conditions will occur in a given year. A low-lying location will begin to see impacts of being flooded a few times per year. Then, as sea level rise increases, it will flood tens of times per year. Eventually, that location may be flooded under a daily high tide. The present scenario models a frequency of 20 flooding days per year. Please note that this frequency represents an average number of times per year (Thompson et al., 2021). Any particular year may have substantially more or less flooding days depending on local climate variability (such as the El Nino, La Nina cycle) and year-to-year variability in the tides due to changes in the alignment of the Earth, Moon, and Sun. Secondly, flooding frequencies are based on data from the Pago Pago tide gauge on Tutuila, which means that estimates may not perfectly represent local conditions outside the harbor or on other islands. However, this is the best source of information available, and we do not expect this to lead to significant inaccuracies in the estimates of flooding frequency. In the 2070 high scenario represented here, the modeled water level for a 20-day frequency is 203 cm (168 cm for Rose and Swains). In this scenario, world-wide society continues to increase emissions. Tipping points (large and sudden changes) are triggered, and worst-case possibilities arise. It is recommended using this scenario for planning construction of infrastructure with highly critical use and longer lifespans, such as a new hospital. 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. Open Geospatial Consortium Web Map Service - Cached (WMS-C) 1 -171.089797256602 -168.141348975554 -14.5591355232811 -11.0480017523415 tight GetCapabilities https://geo.pacioos.hawaii.edu/geoserver/PACIOOS/${id}/ows?service=WMS&version=1.1.1&request=GetCapabilities&tiled=true OGC:WMS-C OGC-WMS-C Open Geospatial Consortium Web Map Service - Cached (WMS-C). Use of WMS-C is similar to traditional WMS but with the addition of the "tiled=true" parameter, which triggers GeoServer to pull map tiles from GeoWebCache if they have been previously generated. This can dramatically improve performance, especially for larger datasets. Supported map formats include JPEG and PNG. Supported info formats include GeoJSON, GML, HTML, and plain text. download flood int Projected flood depth in centimeters (cm) above the 2005 mean higher high water (MHHW) tide level due to sea level rise inundation according to the modeled scenario. geom gml:MultiPolygonPropertyType Pacific Islands Ocean Observing System (PacIOOS) info@pacioos.org http://pacioos.org http web browser information publisher https://geo.pacioos.hawaii.edu/geoserver/ http GeoServer This URL provides access to this dataset via GeoServer, which offers multiple output formats and an OpenLayers viewer. download http://pacioos.org/shoreline/slr-amsam/ http PacIOOS: American Samoa Sea Level Rise Viewer This URL provides a viewer and/or data access for this dataset. download https://www.fisheries.noaa.gov/inport/item/72129 http Related URL NOAA National Geodetic Survey (NGS). 2022. NOAA NGS Topobathy Lidar DEM of Ofu and Olosega, American Samoa. NOAA National Centers for Environmental Information (NCEI). information https://www.fisheries.noaa.gov/inport/item/72133 http Related URL NOAA National Geodetic Survey (NGS). 2022. NOAA NGS Topobathy Lidar DEM of Rose Atoll, American Samoa. NOAA National Centers for Environmental Information (NCEI). information https://www.fisheries.noaa.gov/inport/item/72139 http Related URL NOAA National Geodetic Survey (NGS). 2022. NOAA NGS Topobathy Lidar DEM of Swains Island, American Samoa. NOAA National Centers for Environmental Information (NCEI). information https://www.fisheries.noaa.gov/inport/item/72142 http Related URL NOAA National Geodetic Survey (NGS). 2022. NOAA NGS Topobathy Lidar DEM of Ta'u, American Samoa. NOAA National Centers for Environmental Information (NCEI). information https://www.fisheries.noaa.gov/inport/item/72145 http Related URL NOAA National Geodetic Survey (NGS). 2022. NOAA NGS Topobathy Lidar DEM of Tutuila, American Samoa. NOAA National Centers for Environmental Information (NCEI). information dataset 2023-09-26T00:00:00Z Initial release (Version 1.0). 2024-07-31T00:00:00Z Data Update (Version 2.0): For improved accuracy, sea level rise inundation was recalculated using a newly released higher resolution digital elevation model (DEM) as its basis. Version 1.0 used a 2021 DEM with 1/9 arc-second resolution, except for Rose Atoll where a 2012 DEM with 1/3 arc-second resolution was used (NOAA/CIRES CUDEM). In contrast, Version 2.0 uses a NOAA National Geodetic Survey (NGS) 2022 lidar DEM with 1-meter resolution. Swains Island is now included in the Verison 2.0 results, but it and Rose Atoll do not include vertical land motion (VLM) in their estimates. All DEMs were leveled to mean sea level at 0 m (MSL=0) in 2005. 2025-07-29T22:00:00Z Data Update (Version 3.0): The flooded extent is now shown above mean higher high water (MHHW) in 2005, whereas previously it included the intertidal region from mean sea level (MSL) to MHHW. Additionally, the DEMs of the Manua islands (Ofu, Olosega, and Tau) are now adjusted to MHHW in 2005 using recently deployed tide gauges and benchmarks on Ofu and Tau. Previously, the Manua islands were adjusted using the nearest available tide gauge and benchmark in Pago Pago, Tutuila, leading to some inaccuracies and overestimation of flooding. This record was translated and enhanced from GeoServer OGC Web Services (OWS) using PacIOOS software.