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Abstract (From http://www.ecologyandsociety.org/vol20/iss4/art14/): National Wildlife Refuges (NWRs) in the United States play an important role in the adaptation of social-ecological systems to climate change, land-use change, and other global-change processes. Coastal refuges are already experiencing threats from sea-level rise and other change processes that are largely beyond their ability to influence, while at the same time facing tighter budgets and reduced staff. We engaged in workshops with NWR managers along the U.S. Atlantic coast to understand the problems they face from global-change processes and began a multidisciplinary collaboration to use decision science to help address them. We are applying a...
The understanding of sea-level rise (SLR) processes has improved significantly over the past 15-20 years. Contributions from ice sheets and ocean dynamics are increasingly well-understood, and global budgets better constrained. In addition to physically-based models, semi-empirical methods, and more recently expert elicitations, are also available to describe potential SLR. In spite of these advances, there is still large uncertainty in the magnitude and timing of SLR over the next century and beyond. How much and how fast sea-level may rise can be a significant determinant of management actions in both natural and built environments. Assessing the potential vulnerability of the coastal zone to SLR requires integrating...
Global sea level is rising and may accelerate with continued fossil fuel consumption from industrial and population growth. In 2012, the U.S. Geological Survey conducted more than 30 training and feedback sessions with Federal, State, and nongovernmental organization (NGO) coastal managers and planners across the northern Gulf of Mexico coast to evaluate user needs, potential benefits, current scientific understanding, and utilization of resource aids and modeling tools focused on sea-level rise. In response to the findings from the sessions, this sea-level rise modeling handbook has been designed as a guide to the science and simulation models for understanding the dynamics and impacts of sea-level rise on coastal...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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Gulf Coast Prairie Landscape Conservation Cooperative partners are undertaking numerous efforts to conserve and restore coastal resources, many of which are sensitive to the effects of climate change. Natural resource managers need improved computer modeling tools to effectively evaluate possible sea level rise scenarios along the Gulf of Mexico Coast to better predict the effects on valuable habitats and wildlife.
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2014, 2015, AL-01, AL-02, ATMOSPHERIC/OCEAN INDICATORS, All tags...
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If current climate change trends continue, rising sea levels could inundate low-lying islands across the globe. The Northwestern Hawaiian Islands (NWHI) is a group of islands of great conservation importance that is threatened by sea-level rise. Stretching 2,000 km beyond the main Hawaiian Islands, the NWHI are a World Heritage Site and part of the Papahānaumokuākea Marine National Monument. The islands support the largest tropical seabird rookery in the world, providing breeding habitat for 21 species of seabirds, 4 land bird species, and essential habitat for other resident and migratory wildlife. Because these are low-lying islands, even small increases in sea-level could result in the loss of critical habitat,...
Categories: Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2009, Baby Brooks Bank, Bank 66, Birds, Birds, All tags...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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The U.S. Geological Survey Pacific Coastal and Marine Science Center collected data to investigate sediment dynamics in the shallows of San Pablo Bay and sediment exchange between bay shallows and the tidal salt marsh in China Camp State Park in a series of deployments between December 2013 and June 2016. This data release includes two related groups of data sets. The first group, denoted by names starting with CHC, is from deployments with stations in the San Pablo Bay channel, shallows, and mudflats, and within China Camp marsh. The second, denoted by names starting with SP, is from deployments at a subset of the stations in the San Pablo Bay shallows, collected during intervals between the CHC deployments. Stations...
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It contains supporting data from the wetland morphology modeling to support the analysis on the landscape effects of Mississippi River diversions in the context of sea-level rise on soil organic carbon (SOC) sequestration along coastal Louisiana wetlands.
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Coastal wetlands store more carbon than most ecosystems globally. However, little is known about the mechanisms that control the loss of organic matter in coastal wetlands at the landscape scale, and how sea-level rise will impact this important ecological function.
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This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...


map background search result map search result map Predicting the Risk of Species Extinctions Due to Sea-Level Rise in the Northwestern Hawaiian Islands Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (A1B maximum scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (A1B mean scenario) Evaluation of Regional Sea Level Affecting Marshes Model (SLAMM) Organic matter decomposition across a coastal wetland landscape in Louisiana, U.S.A. (2014-2015) Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration CoSMoS v3.1 flood depth and duration projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 flood depth and duration projections: average conditions in San Mateo County CoSMoS v3.1 water level projections: 1-year storm in San Francisco County CoSMoS v3.1 ocean-currents hazards: 1-year storm in San Francisco County CoSMoS v3.1 flood hazard projections: average conditions in San Francisco County CoSMoS v3.1 flood depth and duration projections: 1-year storm in Santa Cruz County CoSMoS v3.1 wave-hazard projections: 1-year storm in Santa Cruz County CoSMoS v3.1 flood depth and duration projections: 20-year storm in Santa Cruz County CoSMoS v3.1 ocean-currents hazards: 100-year storm in Santa Cruz County CoSMoS v3.1 water level projections: 1-year storm in San Francisco County CoSMoS v3.1 ocean-currents hazards: 1-year storm in San Francisco County CoSMoS v3.1 flood hazard projections: average conditions in San Francisco County CoSMoS v3.1 flood depth and duration projections: average conditions in San Mateo County CoSMoS v3.1 flood depth and duration projections: 1-year storm in Santa Cruz County CoSMoS v3.1 wave-hazard projections: 1-year storm in Santa Cruz County CoSMoS v3.1 flood depth and duration projections: 20-year storm in Santa Cruz County CoSMoS v3.1 ocean-currents hazards: 100-year storm in Santa Cruz County CoSMoS v3.1 flood depth and duration projections: 100-year storm in San Luis Obispo County Organic matter decomposition across a coastal wetland landscape in Louisiana, U.S.A. (2014-2015) Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (A1B maximum scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (A1B mean scenario) Predicting the Risk of Species Extinctions Due to Sea-Level Rise in the Northwestern Hawaiian Islands Evaluation of Regional Sea Level Affecting Marshes Model (SLAMM)