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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 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 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 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...
The goal of barrier island restoration in the northern Gulf of Mexico is to restore barrier island morphology using sediment to support the functions and habitats the islands provide. Barrier island restoration typically involves placement of sediment either directly on the island footprint or within the littoral zone for system transport and distribution. The re-engineering of barrier islands presents numerous challenges and uncertainties associated with climate change induced hurricanes/storms and other dynamic components of the system such as sediment availability and erosional trends. The goal of this study was to use a collaborative SDM approach to develop two Bayesian decision network models (DMs) for restoration...
Abstract (from SpringerLink): The resilience of socio-ecological systems to sea level rise, storms and flooding can be enhanced when coastal habitats are used as natural infrastructure. Grey infrastructure has long been used for coastal flood protection but can lead to unintended negative impacts. Natural infrastructure often provides similar services as well as added benefits that support short- and long-term biological, cultural, social, and economic goals. While natural infrastructure is becoming more widespread in practice, it often represents a relatively small fraction within portfolios of coastal risk-reducing strategies compared to more traditional grey infrastructure. This study provides a comprehensive...
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California - one of the nation's most populous states - hosts extensive public lands, crown-jewel national parks, and diverse natural resources. Resource managers in federal, state, tribal, and local agencies face challenges due to environmental changes and extreme events such as severe droughts, heat waves, flood events, massive wildfires, and forest dieback. However, state-of-the-art research that could aid in the management of natural resources facing these challenges is typically slow to be applied, owing to limited time and capacity on the part of both researchers and managers. This project aims to accelerate the application of science to resource management by facilitating the translation and synthesis of...
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To assess the current topography of the tidal marshes we conducted survey-grade elevation surveys at all sites between 2009 and 2013 using a Leica RX1200 Real Time Kinematic (RTK)Global Positioning System (GPS) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK network coverage (San Pablo, Petaluma, Pt. Mugu, and Newport), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Humboldt, Bolinas, Morro and Tijuana), rover positions were received in real time from a Leica GS10 antenna base station via radio link. When using the base station, we adjusted...
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To assess the current topography of the tidal marshes we conducted survey-grade elevation surveys at all sites between 2009 and 2013 using a Leica RX1200 Real Time Kinematic (RTK)Global Positioning System (GPS) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK network coverage (San Pablo, Petaluma, Pt. Mugu, and Newport), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Humboldt, Bolinas, Morro and Tijuana), rover positions were received in real time from a Leica GS10 antenna base station via radio link. When using the base station, we adjusted...
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We used WARMER, a 1-D cohort model of wetland accretion (Swanson et al., 2014), which is based on Callaway et al. (1996), to examine the effects of three SLR projections on future habitat composition at each study site. Each cohort in the model represents the total organic and inorganic matter added to the soil column each year. WARMER calculates annual elevation changes relative to MSL based on projected changes in relative sea level, subsidence, inorganic sediment accumulation, aboveground and belowground organic matter inputs, soil compaction, and organic matter decomposition for a representative marsh area. Cohort density, a function of soil mineral, organic, and water content, is calculated at each time step...
Abstract (from PLOS ONE): The responses of individuals and populations to climate change vary as functions of physiology, ecology, and plasticity. We investigated whether annual variation in seasonal temperature and precipitation was associated with relative abundances of breeding bird species at local and regional levels in southern California, USA, from 1968–2013. We tested our hypotheses that abundances were correlated positively with precipitation and negatively with temperature in this semiarid to arid region. We also examined whether responses to climate varied among groups of species with similar land-cover associations, nesting locations, and migratory patterns. We investigated relations between seasonal...
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We used WARMER, a 1-D cohort model of wetland accretion (Swanson et al., 2014), which is based on Callaway et al. (1996), to examine the effects of three SLR projections on future habitat composition at each study site. Each cohort in the model represents the total organic and inorganic matter added to the soil column each year. WARMER calculates annual elevation changes relative to MSL based on projected changes in relative sea level, subsidence, inorganic sediment accumulation, aboveground and belowground organic matter inputs, soil compaction, and organic matter decomposition for a representative marsh area. Cohort density, a function of soil mineral, organic, and water content, is calculated at each time step...
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Extreme weather events (such as floods, ice storms, tropical cyclones, and tornadoes) are increasing in frequency and causing severe consequences throughout the U.S. and particularly in Louisiana. These natural disasters are especially devastating for farmers, whose livelihoods depend on the environment. Most climate research and extension outreach focus on large-scale farmers and tend to reach White farmers who outnumber other farming communities, often failing to connect with smallholding and African American farmers. While these farmers make up less of the total agricultural population and economy, they are a critical part of the agricultural and ecological systems and a crucial component in building sustainable...
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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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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 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 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...


map background search result map search result map Morro Bay, California: Tidal Marsh Digital Elevation Model Pt. Mugu, California: Tidal Marsh Digital Elevation Model SLR Projections, Bolinas, Calif., 2010-2060 SLR Projections, Pt. Mugu, Calif., 2070-2110 Improving and Accelerating the Application of Science to Natural Resource Management in California CoSMoS v3.1 water level projections: 1-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: average conditions in Santa Barbara County CoSMoS v3.1 flood depth and duration projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Luis Obispo County CoSMoS v3.1 wave-hazard projections: 20-year storm in San Mateo County CoSMoS v3.1 wave-hazard projections: 100-year storm in San Mateo County CoSMoS v3.1 water level projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: average conditions in San Mateo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Mateo County CoSMoS v3.1 flood depth and duration projections: 1-year storm in Monterey County Assessing the Needs and Adaptation Practices of Smallholding and African American Farmers Facing Extreme Weather Events in Louisiana SLR Projections, Pt. Mugu, Calif., 2070-2110 Pt. Mugu, California: Tidal Marsh Digital Elevation Model SLR Projections, Bolinas, Calif., 2010-2060 Morro Bay, California: Tidal Marsh Digital Elevation Model CoSMoS v3.1 wave-hazard projections: 100-year storm in San Mateo County CoSMoS v3.1 water level projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: average conditions in San Mateo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Mateo County CoSMoS v3.1 wave-hazard projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: average conditions in Santa Barbara County CoSMoS v3.1 water level projections: 1-year storm in San Luis Obispo County CoSMoS v3.1 flood depth and duration projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 water level projections: 100-year storm in San Luis Obispo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Luis Obispo County CoSMoS v3.1 flood depth and duration projections: 1-year storm in Monterey County Assessing the Needs and Adaptation Practices of Smallholding and African American Farmers Facing Extreme Weather Events in Louisiana Improving and Accelerating the Application of Science to Natural Resource Management in California