--- - attributes: ~ caption: 'This map shows climate-related impacts that have occurred in each region since the Third National Climate Assessment in 2014 and response actions that are helping the region address related risks and costs. These examples are illustrative; they are not indicative of which impact is most significant in each region or which response action might be most effective. Source: NCA4 Regional Chapters.' chapter_identifier: overview-executive-summary create_dt: 2018-04-09T18:52:15 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/overview_regional-impacts-and-actions_v1.yaml identifier: overview_regional-impacts-and-actions_v1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:24 time_end: ~ time_start: ~ title: Impacts & Responses uri: /report/nca4/chapter/overview-executive-summary/figure/overview_regional-impacts-and-actions_v1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Increasing heavy rains are leading to more soil erosion and nutrient loss on midwestern cropland. Integrating strips of native prairie vegetation into row crops has been shown to reduce soil and nutrient loss while improving biodiversity. The inset shows a close-up example of a prairie vegetation strip. From Figure 21.2, Ch. 21: Midwest (Photo credits: [main photo] Lynn Betts; [inset] Farnaz Kordbacheh).' chapter_identifier: overview-executive-summary create_dt: 2018-05-01T12:33:24 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/prairie-strips.yaml identifier: prairie-strips lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 10 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:26 time_end: ~ time_start: ~ title: Prairie Strips uri: /report/nca4/chapter/overview-executive-summary/figure/prairie-strips url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Soybeans in Texas experience the effects of drought in August 2013. During 2010–2015, a multiyear regional drought severely affected agriculture in the Southern Great Plains. One prominent impact was the reduction of irrigation water released for farmers on the Texas coastal plains. Photo credit: Bob Nichols, USDA.' chapter_identifier: overview-executive-summary create_dt: 2018-04-20T18:44:48 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/soybeans-impacted-by-drought-near-navasota--texas.yaml identifier: soybeans-impacted-by-drought-near-navasota--texas lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 11 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:26 time_end: ~ time_start: ~ title: Soybeans uri: /report/nca4/chapter/overview-executive-summary/figure/soybeans-impacted-by-drought-near-navasota--texas url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Desalination activities in Texas are an important contributor to the state’s efforts to meet current and projected water needs for communities, industry, and agriculture. The state’s 2017 Water Plan recommended an expansion of desalination to help reduce longer-term risks to water supplies from drought, higher temperatures, and other stressors. There are currently 44 public water supply desalination plants in Texas. From Figure 23.8, Ch. 23: S. Great Plains (Source: adapted from Texas Water Development Board 2017).' chapter_identifier: overview-executive-summary create_dt: 2018-05-01T18:59:26 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/texas-desalination-plants-ch1.yaml identifier: texas-desalination-plants-ch1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 12 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:28 time_end: ~ time_start: ~ title: Texas Desalination Plants uri: /report/nca4/chapter/overview-executive-summary/figure/texas-desalination-plants-ch1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Razor clamming draws crowds on the coast of Washington State. This popular recreation activity is expected to decline due to ocean acidification, harmful algal blooms, warmer temperatures, and habitat degradation. From Figure 24.7, Ch. 24: Northwest (Photo courtesy of Vera Trainer, NOAA).' chapter_identifier: overview-executive-summary create_dt: 2018-05-01T19:05:27 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/razor-clamming.yaml identifier: razor-clamming lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 13 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:29 time_end: ~ time_start: ~ title: Razor Clamming uri: /report/nca4/chapter/overview-executive-summary/figure/razor-clamming url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'The figure shows the years when severe coral bleaching is projected to occur annually in the Hawaiʻi and U.S.-Affiliated Pacific Islands region under a higher scenario (RCP8.5). Darker colors indicate earlier projected onset of coral bleaching. Under projected warming of approximately 0.5°F per decade, all nearshore coral reefs in the region will experience annual bleaching before 2050. From Figure 27.10, Ch. 27: Hawai‘i & Pacific Islands (Source: NOAA).' chapter_identifier: overview-executive-summary create_dt: 2018-04-20T16:19:08 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/overview_severe-coral-bleaching_v4.yaml identifier: overview_severe-coral-bleaching_v4 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 14 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:30 time_end: ~ time_start: ~ title: Overview_severe coral bleaching_v4 uri: /report/nca4/chapter/overview-executive-summary/figure/overview_severe-coral-bleaching_v4 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Examples of coral farming in the U.S. Caribbean and Florida demonstrate different types of structures used for growing fragments from branching corals. Coral farming is a strategy meant to improve the reef community and ecosystem function, including for fish species. The U.S. Caribbean Islands, Florida, Hawai‘i, and the U.S.-Affiliated Pacific Islands face similar threats from coral bleaching and mortality due to warming ocean surface waters and ocean acidification. Degradation of coral reefs is expected to negatively affect fisheries and the economies that depend on them as habitat is lost in both regions. While coral farming may provide some targeted recovery, current knowledge and efforts are not nearly advanced enough to compensate for projected losses from bleaching and acidification. From Figure 20.11, Ch. 20: U.S. Caribbean (Photo credits: [top left] Carlos Pacheco, U.S. Fish and Wildlife Service; [bottom left] NOAA; [right] Florida Fish and Wildlife).' chapter_identifier: overview-executive-summary create_dt: 2018-05-01T19:10:41 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/promoting-reef-recovery.yaml identifier: promoting-reef-recovery lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 15 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:31 time_end: ~ time_start: ~ title: Promoting Reef Recovery uri: /report/nca4/chapter/overview-executive-summary/figure/promoting-reef-recovery url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: '(left) The chart shows the average annual number of days above 100°F in Phoenix, Arizona, for 1976–2005, and projections of the average number of days per year above 100°F through the end of the 21st century (2070–2099) under the lower (RCP4.5) and higher (RCP8.5) scenarios. Dashed lines represent the 5th–95th percentile range of annual observed values. Solid lines represent the 5th–95th percentile range of projected model values. (right) The map shows hydration stations and cooling refuges (cooled indoor locations that provide water and refuge from the heat during the day) in Phoenix in August 2017. Such response measures for high heat events are expected to be needed at greater scales in the coming years if the adverse health effects of more frequent and severe heat waves are to be minimized. Sources: (left) NOAA NCEI, CICS-NC, and LMI; (right) adapted from Southwest Cities Heat Refuges (a project by Arizona State University’s Resilient Infrastructure Lab), available [here](http://www.coolme.today/#phoenix). Data provided by Andrew Fraser and Mikhail Chester, Arizona State University.' chapter_identifier: overview-executive-summary create_dt: 2018-04-20T18:58:12 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/impacts-and-actions-due-to-heat-in-phoenix--arizona.yaml identifier: impacts-and-actions-due-to-heat-in-phoenix--arizona lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 16 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T19:06:38 time_end: ~ time_start: ~ title: 'Projected Change in Very Hot Days by 2100 in Phoenix, Arizona' uri: /report/nca4/chapter/overview-executive-summary/figure/impacts-and-actions-due-to-heat-in-phoenix--arizona url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: '(left) A federal grant is being used to relocate the tribal community of Isle de Jean Charles, Louisiana, in response to severe land loss, sea level rise, and coastal flooding. From Figure 15.3, Ch. 15: Tribes (Photo credit: Ronald Stine). (right) As part of the resettlement of the tribal community of Isle de Jean Charles, residents are working with the Lowlander Center and the State of Louisiana to finalize a plan that reflects the desires of the community. From Figure 15.4, Ch. 15: Tribes (Photo provided by Louisiana Office of Community Development).' chapter_identifier: overview-executive-summary create_dt: 2018-04-23T19:45:54 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/isle-de-jean-charles-community-relocation.yaml identifier: isle-de-jean-charles-community-relocation lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 17 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:33 time_end: ~ time_start: ~ title: Isle de Jean Charles Community Relocation uri: /report/nca4/chapter/overview-executive-summary/figure/isle-de-jean-charles-community-relocation url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "A rock revetment was installed in the Alaska Native Village of Kivalina in 2010 to reduce increasing risks from erosion. A new rock revetment wall has a projected lifespan of 15 to 20 years. From Figure 15.3, Ch. 15: Tribes (Photo credit: ShoreZone. Creative Commons License CC BY 3.0). The inset shows a close-up of the rock wall in 2011. Photo credit: U.S. Army Corps of Engineers–Alaska District." chapter_identifier: overview-executive-summary create_dt: 2018-05-01T12:48:24 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/adaptation-measures-in-kivalina--ak.yaml identifier: adaptation-measures-in-kivalina--ak lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 18 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:35 time_end: ~ time_start: ~ title: 'Adaptation Measures in Kivalina, AK' uri: /report/nca4/chapter/overview-executive-summary/figure/adaptation-measures-in-kivalina--ak url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: '(a) The map shows the number of mitigation-related activities at the state level (out of 30 illustrative activities) as well as cities supporting emissions reductions; (b) the chart depicts the type and number of activities by state. Several territories also have a variety of mitigation-related activities, including American Sāmoa, the Federated States of Micronesia, Guam, Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. From Figure 29.1, Ch. 29: Mitigation (Sources: [a] EPA and ERT, Inc. [b] adapted from America’s Pledge 2017).' chapter_identifier: overview-executive-summary create_dt: 2017-10-27T19:56:48 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/state_and_local_mitigation_and_clean_energy_policies.yaml identifier: state_and_local_mitigation_and_clean_energy_policies lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 19 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T16:12:51 time_end: ~ time_start: ~ title: Mitigation-Related Activities at State and Local Levels uri: /report/nca4/chapter/overview-executive-summary/figure/state_and_local_mitigation_and_clean_energy_policies url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Long-term observations demonstrate the warming trend in the climate system and the effects of increasing atmospheric greenhouse gas concentrations (Ch. 2: Climate, Box 2.2). This figure shows climate-relevant indicators of change based on data collected across the United States. Upward-pointing arrows indicate an increasing trend; downward-pointing arrows indicate a decreasing trend. Bidirectional arrows (e.g., for drought conditions) indicate a lack of a definitive national trend.

Atmosphere (a–c): (a) Annual average temperatures have increased by 1.8°F across the contiguous United States since the beginning of the 20th century; this figure shows observed change for 1986–2016 (relative to 1901–1960 for the contiguous United States and 1925–1960 for Alaska, Hawai‘i, Puerto Rico, and the U.S. Virgin Islands). Alaska is warming faster than any other state and has warmed twice as fast as the global average since the mid-20th century (Ch. 2: Climate, KM 5; Ch. 26: Alaska, Background). (b) The season length of heat waves in many U.S. cities has increased by over 40 days since the 1960s. Hatched bars indicate partially complete decadal data. \\(c) The relative amount of annual rainfall that comes from large, single-day precipitation events has changed over the past century; since 1910, a larger percentage of land area in the contiguous United States receives precipitation in the form of these intense single-day events.

Ice, snow, and water (d–f): (d) Large declines in snowpack in the western United States occurred from 1955 to 2016. (e) While there are a number of ways to measure drought, there is currently no detectable change in long-term U.S. drought statistics using the Palmer Drought Severity Index. (f) Since the early 1980s, the annual minimum sea ice extent (observed in September each year) in the Arctic Ocean has decreased at a rate of 11%–16% per decade (Ch. 2: Climate, KM 7).

Oceans and coasts (g–i): (g) Annual median sea level along the U.S. coast (with land motion removed) has increased by about 9 inches since the early 20th century as oceans have warmed and land ice has melted (Ch. 2: Climate, KM 4). (h) Fish, shellfish, and other marine species along the Northeast coast and in the eastern Bering Sea have, on average, moved northward and to greater depths toward cooler waters since the early 1980s (records start in 1982). (i) Oceans are also currently absorbing more than a quarter of the carbon dioxide emitted to the atmosphere annually by human activities, increasing their acidity (measured by lower pH values; Ch. 2: Climate, KM 3).

Land and ecosystems (j–l): (j) The average length of the growing season has increased across the contiguous United States since the early 20th century, meaning that, on average, the last spring frost occurs earlier and the first fall frost arrives later; this map shows changes in growing season length at the state level from 1895 to 2016. (k) Warmer and drier conditions have contributed to an increase in large forest fires in the western United States and Interior Alaska over the past several decades (CSSR, Ch. 8.3). (l) Degree days are defined as the number of degrees by which the average daily temperature is higher than 65°F (cooling degree days) or lower than 65°F (heating degree days) and are used as a proxy for energy demands for cooling or heating buildings. Changes in temperatures indicate that heating needs have decreased and cooling needs have increased in the contiguous United States over the past century.

Sources: (a) adapted from Vose et al. 2017, (b) EPA, (c–f and h–l) adapted from EPA 2016, (g and center infographic) EPA and NOAA.
The interactive version of this figure was revised in June 2019. See Errata for details: https://nca2018.globalchange.gov/downloads

" chapter_identifier: overview-executive-summary create_dt: 2017-07-20T19:02:07 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/indicators-nca3-image.yaml identifier: indicators-nca3-image lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2019-06-10T18:50:54 time_end: ~ time_start: ~ title: Indicators of Change uri: /report/nca4/chapter/overview-executive-summary/figure/indicators-nca3-image url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Adaptation entails a continuing risk management process. With this approach, individuals and organizations become aware of and assess risks and vulnerabilities from climate and other drivers of change, take actions to reduce those risks, and learn over time. The gray arced lines compare the current status of implementing this process with the status reported by the Third National Climate Assessment in 2014; darker color indicates more activity. From Figure 28.1, Ch. 28: Adaptation (Source: adapted from National Research Council, 2010. Used with permission from the National Academies Press, © 2010, National Academy of Sciences. Image credits, clockwise from top: National Weather Service; USGS; Armando Rodriguez, Miami-Dade County; Dr. Neil Berg, MARISA; Bill Ingalls, NASA).' chapter_identifier: overview-executive-summary create_dt: 2018-04-22T18:26:27 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/overview_adaptation-stages---progress-since-nca3_v1.yaml identifier: overview_adaptation-stages---progress-since-nca3_v1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 20 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:38 time_end: ~ time_start: ~ title: Five Adaptation Stages and Progress uri: /report/nca4/chapter/overview-executive-summary/figure/overview_adaptation-stages---progress-since-nca3_v1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Annual economic impact estimates are shown for labor and air quality. The bar graph on the left shows national annual damages in 2090 (in billions of 2015 dollars) for a higher scenario (RCP8.5) and lower scenario (RCP4.5); the difference between the height of the RCP8.5 and RCP4.5 bars for a given category represents an estimate of the economic benefit to the United States from global mitigation action. For these two categories, damage estimates do not consider costs or benefits of new adaptation actions to reduce impacts, and they do not include Alaska, Hawaiʻi and U.S.-Affiliated Pacific Islands, or the U.S. Caribbean. The maps on the right show regional variation in annual impacts projected under the higher scenario (RCP8.5) in 2090. The map on the top shows the percent change in hours worked in high-risk industries as compared to the period 2003–2007. The hours lost result in economic damages: for example, $28 billion per year in the Southern Great Plains. The map on the bottom is the change in summer-average maximum daily 8-hour ozone concentrations (ppb) at ground-level as compared to the period 1995–2005. These changes in ozone concentrations result in premature deaths: for example, an additional 910 premature deaths each year in the Midwest. Source: EPA, 2017. Multi-Model Framework for Quantitative Sectoral Impacts Analysis: A Technical Report for the Fourth National Climate Assessment. U.S. Environmental Protection Agency, EPA 430-R-17-001.' chapter_identifier: overview-executive-summary create_dt: 2018-04-22T17:18:53 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/overview_sectoral-cost-savings-from-mitigation_v1.yaml identifier: overview_sectoral-cost-savings-from-mitigation_v1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 21 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:39 time_end: ~ time_start: ~ title: New Economic Impact Studies uri: /report/nca4/chapter/overview-executive-summary/figure/overview_sectoral-cost-savings-from-mitigation_v1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Annual average temperatures across the United States are projected to increase over this century, with greater changes at higher latitudes as compared to lower latitudes, and under a higher scenario (RCP8.5; right) than under a lower one (RCP4.5; left). This figure shows projected differences in annual average temperatures for mid-century (2036–2065; top) and end of century (2071–2100; bottom) relative to the near present (1986–2015). From Figure 2.4, Ch. 2: Climate (Source: adapted from Vose et al. 2017)." chapter_identifier: overview-executive-summary create_dt: 2017-10-27T16:17:18 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/projected-global-temperatures.yaml identifier: projected-global-temperatures lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T19:05:38 time_end: ~ time_start: ~ title: Projected Changes in U.S. Annual Average Temperatures uri: /report/nca4/chapter/overview-executive-summary/figure/projected-global-temperatures url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The maps show projections of change in relative sea level along the U.S. coast by 2100 (as compared to 2000) under the lower (RCP4.5) and higher (RCP8.5) scenarios (see CSSR, Ch. 12.5). Globally, sea levels will continue to rise from thermal expansion of the ocean and melting of land-based ice masses (such as Greenland, Antarctica, and mountain glaciers). Regionally, however, the amount of sea level rise will not be the same everywhere. Where land is sinking (as along the Gulf of Mexico coastline), relative sea level rise will be higher, and where land is rising (as in parts of Alaska), relative sea level rise will be lower. Changes in ocean circulation (such as the Gulf Stream) and gravity effects due to ice melt will also alter the heights of the ocean regionally. Sea levels are expected to continue to rise along almost all U.S. coastlines, and by 2100, under the higher scenario, coastal flood heights that today cause major damages to infrastructure would become common during high tides nationwide (Ch. 8: Coastal; Scenario Products section in Appendix 3). Source: adapted from CSSR, Figure 12.4." chapter_identifier: overview-executive-summary create_dt: 2017-10-27T19:08:56 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/historical_and_projected_global_mean_sea_level_rise.yaml identifier: historical_and_projected_global_mean_sea_level_rise lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T16:09:39 time_end: ~ time_start: ~ title: U.S. Sea Level Rise uri: /report/nca4/chapter/overview-executive-summary/figure/historical_and_projected_global_mean_sea_level_rise url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Wildfires are increasingly encroaching on American communities, posing threats to lives, critical infrastructure, and property. In October 2017, more than a dozen fires burned through northern California, killing dozens of people and leaving thousands more homeless. Communities distant from the fires were affected by poor air quality as smoke plumes darkened skies and caused the cancellation of school and other activities across the region. (left) A NASA satellite image shows active fires on October 9, 2017. (right) The Tubbs Fire, which burned parts of Napa, Sonoma, and Lake counties, was the most destructive in California’s history. It caused an estimated $1.2 billion in damages and destroyed over 5,000 structures, including 5% of the housing stock in the city of Santa Rosa. Image credits: (left) NASA; (right) Master Sgt. David Loeffler, U.S. Air National Guard.' chapter_identifier: overview-executive-summary create_dt: 2018-04-23T14:10:49 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/wildfire-at-the-wildland-urban-interface.yaml identifier: wildfire-at-the-wildland-urban-interface lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 5 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:45 time_end: ~ time_start: ~ title: Wildland-Urban Fire uri: /report/nca4/chapter/overview-executive-summary/figure/wildfire-at-the-wildland-urban-interface url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Hurricane Harvey led to widespread flooding and knocked out power to 300,000 customers in Texas in 2017, with cascading effects on critical infrastructure facilities such as hospitals, water and wastewater treatment plants, and refineries. The photo shows Port Arthur, Texas, on August 31, 2017—six days after Hurricane Harvey made landfall along the Gulf Coast. From Figure 17.2, Ch. 17: Complex Systems (Photo credit: Staff Sgt. Daniel J. Martinez, U.S. Air National Guard).' chapter_identifier: overview-executive-summary create_dt: 2018-04-16T19:09:23 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/hurricane-harvey-flooding-ch1.yaml identifier: hurricane-harvey-flooding-ch1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:46 time_end: ~ time_start: ~ title: Hurricane Harvey Flooding uri: /report/nca4/chapter/overview-executive-summary/figure/hurricane-harvey-flooding-ch1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Floodwaters from the Missouri River surround the Omaha Public Power District’s Fort Calhoun Station, a nuclear power plant just north of Omaha, Nebraska, on June 20, 2011. The flooding was the result of runoff from near-record snowfall totals and record-setting rains in late May and early June. A protective berm holding back the floodwaters from the plant failed, which prompted plant operators to transfer offsite power to onsite emergency diesel generators. Cooling for the reactor temporarily shut down, but spent fuel pools were unaffected. From Figure 22.5, Ch. 22: N. Great Plains (Photo credit: Harry Weddington, U.S. Army Corps of Engineers).' chapter_identifier: overview-executive-summary create_dt: 2018-05-01T12:28:29 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/fort-calhoun-flooding.yaml identifier: fort-calhoun-flooding lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:47 time_end: ~ time_start: ~ title: Fort Calhoun Nuclear Station Flood uri: /report/nca4/chapter/overview-executive-summary/figure/fort-calhoun-flooding url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Low-lying Norfolk, Virginia, houses the world’s largest naval base, which supports multiple aircraft carrier groups and is the duty station for thousands of employees. Most of the area around the base lies less than 10 feet above sea level, and local relative sea level is projected to rise between about 2.5 and 11.5 feet by the year 2100 under the Lower and Upper Bound USGCRP sea level rise scenarios, respectively (see Scenario Products section of Appendix 3 for more details on these sea level rise scenarios; see also Ch. 8: Coastal, Case Study “Key Messages in Action—Norfolk, Virginia”). Photo credit: Mass Communication Specialist 1st Class Christopher B. Stoltz, U.S. Navy.' chapter_identifier: overview-executive-summary create_dt: 2018-04-19T15:27:19 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/norfolk-naval-base.yaml identifier: norfolk-naval-base lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 8 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:49 time_end: ~ time_start: ~ title: Norfolk Naval Base uri: /report/nca4/chapter/overview-executive-summary/figure/norfolk-naval-base url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The Department of Defense (DoD) has significant experience in planning for and managing risk and uncertainty. The effects of climate and extreme weather represent additional risks to incorporate into the Department’s various planning and risk management processes. To identify DoD installations with vulnerabilities to climate-related impacts, a preliminary Screening Level Vulnerability Assessment Survey (SLVAS) of DoD sites worldwide was conducted in 2015. The SLVAS responses (shown for the United States; orange dots) yielded a wide range of qualitative information. The highest number of reported effects resulted from drought (782), followed closely by wind (763) and non-storm surge related flooding (706). About 10% of sites indicated being affected by extreme temperatures (351), while flooding due to storm surge (225) and wildfire (210) affected about 6% of the sites reporting. The survey responses provide a preliminary qualitative picture of DoD assets currently affected by severe weather events as well as an indication of assets that may be affected by sea level rise in the future. Source: adapted from Department of Defense 2018 (LINK)." chapter_identifier: overview-executive-summary create_dt: 2018-04-20T19:08:05 href: https://data.globalchange.gov/report/nca4/chapter/overview-executive-summary/figure/us-military-bases-vulnerable-to-more-than-one-potential-impact.yaml identifier: us-military-bases-vulnerable-to-more-than-one-potential-impact lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 9 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-27T16:10:50 time_end: ~ time_start: ~ title: US Military Bases Vulnerable to More than One Potential Impact uri: /report/nca4/chapter/overview-executive-summary/figure/us-military-bases-vulnerable-to-more-than-one-potential-impact url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows (a) the contribution of agriculture and related sectors to the U.S. economy and (b) employment figures in agriculture and related sectors (as of 2015). Agriculture and other food-related value-added sectors account for 21 million full- and part-time jobs and contribute about $1 trillion annually to the United States economy. Source: adapted from Kassel et al. 2017.{{< tbib '1' 'a72ad8b0-77de-44f6-94f6-430dacc1bd69' >}}" chapter_identifier: agriculture-and-rural-communities create_dt: 2017-06-01T20:32:27 href: https://data.globalchange.gov/report/nca4/chapter/agriculture-and-rural-communities/figure/farm-and-poverty-county-map.yaml identifier: farm-and-poverty-county-map lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:43:00 time_end: ~ time_start: ~ title: Agricultural Jobs and Revenue uri: /report/nca4/chapter/agriculture-and-rural-communities/figure/farm-and-poverty-county-map url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows county-level (a) population changes for 2010–2017 and (b) poverty rates for 2011–2015 in rural U.S. communities. Rural populations are migrating to urban regions due to relatively slow employment growth and high rates of poverty. Data for the U.S. Caribbean region were not available at the time of publication. Sources: (a) adapted from ERS 2018{{< tbib '2' '861917c1-26d0-4d54-98eb-da50a55ba587' >}}; (b) redrawn from ERS 2017.{{< tbib '3' '1f9c41a2-775b-41e7-b93f-fd10e077ee66' >}}" chapter_identifier: agriculture-and-rural-communities create_dt: 2017-09-14T16:49:35 href: https://data.globalchange.gov/report/nca4/chapter/agriculture-and-rural-communities/figure/fig10-2.yaml identifier: fig10-2 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:43:07 time_end: ~ time_start: ~ title: Population Changes and Poverty Rates in Rural Counties uri: /report/nca4/chapter/agriculture-and-rural-communities/figure/fig10-2 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows changes in groundwater levels in the Ogallala Aquifer from predevelopment to 2015. Source: adapted from McGuire 2017.{{< tbib '163' '6d4637d5-5eb3-43c9-bb36-050b0ef08df5' >}}" chapter_identifier: agriculture-and-rural-communities create_dt: 2017-09-14T16:58:04 href: https://data.globalchange.gov/report/nca4/chapter/agriculture-and-rural-communities/figure/historical-cycle-of-agriculture-and-groundwater-use.yaml identifier: historical-cycle-of-agriculture-and-groundwater-use lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:43:13 time_end: ~ time_start: ~ title: Changes in the Ogallala Aquifer uri: /report/nca4/chapter/agriculture-and-rural-communities/figure/historical-cycle-of-agriculture-and-groundwater-use url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows the percent of land area in the contiguous 48 states experiencing extreme one-day precipitation events between 1910 and 2017. These extreme events pose erosion and water quality risks that have increased in recent decades. The bars represent individual years, and the orange line is a nine-year weighted average. Source: adapted from EPA 2016.{{< tbib '171' '909a0b17-06fc-4995-a5b2-d837cabc4b6d' >}}" chapter_identifier: agriculture-and-rural-communities create_dt: 2017-09-14T17:11:26 href: https://data.globalchange.gov/report/nca4/chapter/agriculture-and-rural-communities/figure/ag-extreme-one-day-precipitation-events.yaml identifier: ag-extreme-one-day-precipitation-events lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:43:19 time_end: ~ time_start: ~ title: Land Area and Extreme Precipitation uri: /report/nca4/chapter/agriculture-and-rural-communities/figure/ag-extreme-one-day-precipitation-events url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows the predicted reduction in annual milk production in 2030 compared to 2010 in climate change induced heat stress. The regions are grouped according to USDA regional Climate Hubs (https://www.climatehubs.oce.usda.gov), and the colored bars show the four global climate models used. Source: redrawn from Key et al. 2014.{{< tbib '83' 'aa7e61cd-e4b5-47d8-96eb-6ef0dfc4e2ae' >}}" chapter_identifier: agriculture-and-rural-communities create_dt: 2018-04-04T14:35:33 href: https://data.globalchange.gov/report/nca4/chapter/agriculture-and-rural-communities/figure/predicted-reduction-milk-production.yaml identifier: predicted-reduction-milk-production lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 5 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:43:27 time_end: ~ time_start: ~ title: Projected Reduction in Milk Production uri: /report/nca4/chapter/agriculture-and-rural-communities/figure/predicted-reduction-milk-production url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "These maps show current population along with population projections by county for the year 2100. Projected populations are based on Shared Socioeconomic Pathways (SSPs)—a collection of plausible future pathways of socioeconomic development.{{< tbib '8' '9c909a77-a1d9-477d-82fc-468a6b1af771' >}} The middle map is based on demography consistent with the SSP2, which follows a middle-of-the-road path where trends do not shift markedly from historical patterns. The bottom map uses demography consistent with SSP5, which follows a more rapid technical progress and resource-intensive development path. Increasing urban populations pose challenges to planners and city managers as they seek to maintain and improve urban environments. Data are unavailable for the U.S. Caribbean, Alaska, and Hawai‘i & U.S.-Affiliated Pacific Islands regions. Source: EPA" chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2017-08-02T12:13:45 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/iclus-2100-population-projections---ssp2-and-ssp5.yaml identifier: iclus-2100-population-projections---ssp2-and-ssp5 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T17:09:56 time_end: ~ time_start: ~ title: Current and Projected U.S. Population uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/iclus-2100-population-projections---ssp2-and-ssp5 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Projected increases in the number of very hot days (compared to the 1976–2005 average) are shown for each of five U.S. cities under lower (RCP4.5) and higher (RCP8.5) scenarios. Here, very hot days are defined as those on which the daily high temperature exceeds a threshold value specific to each of the five U.S. cities shown. Dots represent the modeled median (50th percentile) values, and the vertical bars show the range of values (5th to 95th percentile) from the models used in the analysis. Modeled historical values are shown for the same temperature thresholds, for the period 1976–2005, in the lower left corner of the figure. These and other U.S. cities are projected to see an increase in the number of very hot days over the rest of this century under both scenarios, affecting people, infrastructure, green spaces, and the economy. Increased air conditioning and energy demands raise utility bills and can lead to power outages and blackouts. Hot days can degrade air and water quality, which in turn can harm human health and decrease quality of life. Sources: NOAA NCEI, CICS-NC, and LMI.' chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2017-05-31T20:28:19 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/heat-projections-for-msas.yaml identifier: heat-projections-for-msas lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T19:09:17 time_end: ~ time_start: ~ title: Projected Change in the Number of Very Hot Days uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/heat-projections-for-msas url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Many U.S. cities are projected to see more days with heavy precipitation, increasing the risk of urban flooding, especially in areas with a lot of paved surfaces. Projections of percent changes in the number of days with heavy precipitation (compared to the 1976–2005 average) are shown for each of five U.S. cities under lower (RCP4.5) and higher (RCP8.5) scenarios. Here, days with heavy precipitation are defined as those on which the amount of total precipitation exceeds a threshold value specific to each city. Dots represent the modeled median (50th percentile) values, and the vertical bars show the range of values (5th to 95th percentile) from the models used in the analysis. Modeled historical values are shown for the same thresholds, for the period 1976–2005, in the lower left corner of the figure. Historical values are given in terms of frequency (days per year) and return period (average number of years between events). Sources: NOAA NCEI, CICS-NC, and LMI.' chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2018-04-03T15:48:15 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/projected-change-in-precipitation.yaml identifier: projected-change-in-precipitation lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T19:09:29 time_end: ~ time_start: ~ title: Projected Change in Number of Days with Heavy Precipitation uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/projected-change-in-precipitation url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "These images show surface temperatures of playground equipment in metropolitan Phoenix, Arizona. Children are particularly susceptible to high heat{{< tbib '12' 'f1e633d5-070a-4a7d-935b-a2281a0c9cb6' >}} and can be exposed through daily activities. (A) A slide and dark rubber surface in the sun (orange/red colors are shown reaching temperatures of 71°C [160°F] and 82°C [180°F], respectively. The blue/green colors are under a shade sail. (B) Playground steps made of black powder-coated metal are shown reaching a temperature of 58°C (136°F) in the direct sunlight. Images use infrared thermography and were taken mid-day on September 15, 2014. Credit: Vanos et al. 2016.{{< tbib '49' '25f43b4b-e8eb-4daa-8c9b-cf0991f72c6d' >}}" chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2018-04-03T20:08:58 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/extreme-heat-photo.yaml identifier: extreme-heat-photo lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-30T15:27:56 time_end: ~ time_start: ~ title: Threats from Extreme Heat uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/extreme-heat-photo url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Flash flooding overwhelmed drainage systems and swamped roadways in Pittsburgh, Pennsylvania, in 2011. The flooding disrupted businesses and commutes, damaged homes, and caused four deaths. Photo credit: Pittsburgh Post-Gazette.' chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2018-04-03T20:09:44 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/flash-flooding-photo.yaml identifier: flash-flooding-photo lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 5 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-30T15:27:58 time_end: ~ time_start: ~ title: Flash Flooding Impacts Urban Infrastructure and Well-Being uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/flash-flooding-photo url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'With heavy downpours increasing nationally, urban areas experience costly impacts. (top) In cities with combined sewer systems, storm water runoff flows into pipes containing sewage from homes and industrial wastewater. Intense rainfall can overwhelm the system so untreated wastewater overflows into rivers. Overflows are a water pollution concern and increase risk of exposure to waterborne diseases. (bottom) Intense rainfall can also result in localized flooding. Closed roads and disrupted mass transit prevent residents from going to work or school and first responders from reaching those in need. Home and commercial property owners may need to make costly repairs, and businesses may lose revenue. Source: EPA.' chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2017-08-02T15:02:54 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/cascading-consequences-of-heavy-rainfall-for-urban-systems.yaml identifier: cascading-consequences-of-heavy-rainfall-for-urban-systems lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 6 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-30T15:28:00 time_end: ~ time_start: ~ title: Cascading Consequences of Heavy Rainfall for Urban Systems uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/cascading-consequences-of-heavy-rainfall-for-urban-systems url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Protecting vulnerable people and places from the impacts of climate change involves infrastructure design (for example, green space and highly reflective roofing), along with social and institutional change (such as designating cooling centers). Social equity is supported by widespread participation in adaptation decision-making by non-profit organizations, local businesses, vulnerable populations, school districts, city governments, utility providers, and others. Source: EPA.' chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2017-08-02T14:13:10 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/the-bee-branch-greenway.yaml identifier: the-bee-branch-greenway lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 7 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-30T15:28:03 time_end: ~ time_start: ~ title: Urban Adaptation Strategies and Stakeholders uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/the-bee-branch-greenway url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "In response to a history of flooding, Dubuque, Iowa, installed the Bee Branch Creek Greenway to control flooding and provide recreational space.{{< tbib '138' '99f11503-c2c3-4ec5-825c-c6ed59d28613' >}} Photo credit: City of Dubuque, Iowa." chapter_identifier: built-environment-urban-systems-and-cities create_dt: 2018-04-03T20:10:20 href: https://data.globalchange.gov/report/nca4/chapter/built-environment-urban-systems-and-cities/figure/green-infrastructure-photo.yaml identifier: green-infrastructure-photo lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 8 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-30T15:28:05 time_end: ~ time_start: ~ title: 'Greenway in Dubuque, Iowa' uri: /report/nca4/chapter/built-environment-urban-systems-and-cities/figure/green-infrastructure-photo url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Heavy precipitation, coastal flooding, heat, and changes in average precipitation and temperature affect assets (such as roads and bridges) across all modes of transportation. The figure shows major climate-related hazards and the transportation assets impacted. Photos illustrate national performance goals (listed in 23 U.S.C. § 150{{< tbib '8' 'c12d5f3d-a18a-4177-b975-657e968f1b47' >}}) that are at risk due to climate-related hazards. Source: USGCRP. Photo credits from left to right: JAXPORT, Meredith Fordham Hughes [CC BY-NC 2.0]; Oregon Department of Transportation [CC BY 2.0]; NPS – Mississippi National River and Recreation Area; Flickr user Tom Driggers [CC BY 2.0]; Flickr user Mike Mozart [CC BY 2.0]; Flickr user Jeff Turner [CC BY 2.0]; Flickr user William Garrett [CC BY 2.0]." chapter_identifier: transportation create_dt: 2018-03-27T02:47:05 href: https://data.globalchange.gov/report/nca4/chapter/transportation/figure/transportation-goals-at-risk.yaml identifier: transportation-goals-at-risk lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:44:57 time_end: ~ time_start: ~ title: U.S. Transportation Assets and Goals at Risk uri: /report/nca4/chapter/transportation/figure/transportation-goals-at-risk url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The figure shows annual vehicle-hours of delay for major roads (principal arterials, minor arterials, and major collectors) due to high tide flooding by state, year, and sea level rise scenario (from Sweet et al. 2017).{{< tbib '59' '3bae2310-7572-47e2-99a4-9e4276764934' >}} Years are shown using decadal average (10-year) values (that is, 2020 is 2016–2025), except 2100, which is a 5-year average (2096–2100). One vehicle-hour of delay is equivalent to one vehicle delayed for one hour. Source: Jacobs et al. 2018,{{< tbib '61' 'b4808700-a94a-44da-b2bb-d360a83146f1' >}} Figure 3, reproduced with permission of the Transportation Research Board." chapter_identifier: transportation create_dt: 2017-09-19T01:43:14 href: https://data.globalchange.gov/report/nca4/chapter/transportation/figure/delay-hours-from-sea-level-rise.yaml identifier: delay-hours-from-sea-level-rise lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:44:53 time_end: ~ time_start: ~ title: Annual Vehicle-Hours of Delay Due to High Tide Flooding uri: /report/nca4/chapter/transportation/figure/delay-hours-from-sea-level-rise url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'This figure shows transportation vulnerability and/or risk assessments from 2012 to 2016 by location. Cumulatively, these vulnerability assessments elucidate national-scale vulnerabilities and progress. Data for the U.S. Caribbean region were not available. Source: ICF and U.S. Department of Transportation.' chapter_identifier: transportation create_dt: 2017-03-29T17:43:53 href: https://data.globalchange.gov/report/nca4/chapter/transportation/figure/transportation_vulnerability_assessment.yaml identifier: transportation_vulnerability_assessment lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T20:36:43 time_end: ~ time_start: ~ title: Transportation Vulnerability and Risk Assessments uri: /report/nca4/chapter/transportation/figure/transportation_vulnerability_assessment url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Flooding events can result in serious damage to road infrastructure. Here, debris flow covers US Highway 14 (Poudre Canyon) after the High Park Fire in 2012. Photo credit: Justin Pipe, Colorado Department of Transportation.' chapter_identifier: transportation create_dt: 2018-04-16T19:41:27 href: https://data.globalchange.gov/report/nca4/chapter/transportation/figure/12-4-colorado-debris-flows-.yaml identifier: 12-4-colorado-debris-flows- lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:45:05 time_end: ~ time_start: ~ title: Flood Impacts on Colorado Highway uri: /report/nca4/chapter/transportation/figure/12-4-colorado-debris-flows- url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Climate change will alter (black bold text) chemical and physical interactions that create, remove, and transport air pollution (red text and gray arrows). Human activities and natural processes release precursors for ground-level ozone (O3) and particulate matter with a diameter less than 2.5 micrometers (PM2.5), including methane (CH4), carbon monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), sulfur dioxide (SO2), ammonia (NH3), organic carbon (OC), black carbon (BC), and dimethyl sulfide (DMS); and direct atmospheric pollutants, including mineral dust, sea salt, pollen, spores, and food particles. Source: adapted from Fiore et al. 2015.{{< tbib '4' 'b4038a28-b14b-4ae8-b783-0de19e3cffdd' >}} Reprinted by permission of the publisher (Taylor & Francis Ltd., http://www.tandfonline.com)." chapter_identifier: air-quality create_dt: 2017-05-31T19:01:50 href: https://data.globalchange.gov/report/nca4/chapter/air-quality/figure/airquality_climate_v05302017.yaml identifier: airquality_climate_v05302017 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:45:16 time_end: ~ time_start: ~ title: Pathways by Which Climate Change Will Influence Air Pollution uri: /report/nca4/chapter/air-quality/figure/airquality_climate_v05302017 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The maps show the change in summer averages of the maximum daily 8-hour ozone concentration. Summertime ozone is projected to change non-uniformly across the United States based on multiyear simulations from the Community Multiscale Air Quality (CMAQ) modeling system. Those changes are amplified under the higher scenario (RCP8.5) compared with the lower scenario (RCP4.5), as well as at 2090 compared with 2050. Source: adapted from EPA 2017.{{< tbib '1' '0b30f1ab-e4c4-4837-aa8b-0e19faccdb94' >}}" chapter_identifier: air-quality create_dt: 2017-05-31T19:10:21 href: https://data.globalchange.gov/report/nca4/chapter/air-quality/figure/ozone.yaml identifier: ozone lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:45:25 time_end: ~ time_start: ~ title: Projected Changes in Summer Season Ozone uri: /report/nca4/chapter/air-quality/figure/ozone url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "This conceptual diagram illustrates the exposure pathways by which climate change could affect human health. Exposure pathways exist within the context of other factors that positively or negatively influence health outcomes (gray side boxes). Key factors that influence vulnerability for individuals are shown in the right box and include social determinants of health and behavioral choices. Key factors that influence vulnerability at larger scales, such as natural and built environments, governance and management, and institutions, are shown in the left box. The extent to which climate change could alter the burden of disease in any location at any point in time will depend not just on the magnitude of local climate change but also on individual and population vulnerability, exposure to changing weather patterns, and capacity to manage risks, which may also be affected by climate change. Source: Balbus et al. 2016.{{< tbib '2' '6b118a80-8335-4c02-91cf-762c8bb14301' >}}" chapter_identifier: human-health create_dt: 2018-04-06T19:09:27 href: https://data.globalchange.gov/report/nca4/chapter/human-health/figure/climate-change-and-health.yaml identifier: climate-change-and-health lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:45:50 time_end: ~ time_start: ~ title: Climate Change and Health uri: /report/nca4/chapter/human-health/figure/climate-change-and-health url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Examples of populations at higher risk of exposure to adverse climate-related health threats are shown along with adaptation measures that can help address disproportionate impacts. When considering the full range of threats from climate change as well as other environmental exposures, these groups are among the most exposed, most sensitive, and have the least individual and community resources to prepare for and respond to health threats. White text indicates the risks faced by those communities, while dark text indicates actions that can be taken to reduce those risks. Source: EPA.' chapter_identifier: human-health create_dt: 2018-03-30T23:52:32 href: https://data.globalchange.gov/report/nca4/chapter/human-health/figure/fig--14-x-vulnerable-populations-km2.yaml identifier: fig--14-x-vulnerable-populations-km2 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:45:44 time_end: ~ time_start: ~ title: Vulnerable Populations uri: /report/nca4/chapter/human-health/figure/fig--14-x-vulnerable-populations-km2 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "These maps shows the locations of hospitals in Charleston County, South Carolina, and Miami-Dade County, Florida, with respect to storm surge inundation for different categories of hurricanes making landfall at high tide. Colors indicate the lowest category hurricane affecting a given location, with darker blue shading indicating areas with the greatest susceptibility to flooding and darker red dots indicating the most vulnerable hospitals. Four of the 38 (11%) hospitals in Miami-Dade County face possible storm surge inundation following a Category 2 hurricane; this could increase to 26 (68%) following a Category 5 hurricane. Charleston hospitals are more exposed to inundation risks. Seven of the 11 (64%) hospitals in Charleston County face possible storm surge inundation following a Category 2; this could increase to 9 (82%) following a Category 4. The impacts of a storm surge will depend on the effectiveness of resilience measures, such as flood walls, deployed by the facilities. Data from National Hurricane Center 2018{{< tbib '152' '6507ef2b-a68a-420c-9aac-cd1d5c0fc210' >}} and the Department of Homeland Security 2018.{{< tbib '153' 'f40f0493-f23a-476c-9900-2dd34eb7fd6a' >}}" chapter_identifier: human-health create_dt: 2017-06-23T15:27:43 href: https://data.globalchange.gov/report/nca4/chapter/human-health/figure/hospitals_floodplain_sandy.yaml identifier: hospitals_floodplain_sandy lat_max: 32 lat_min: 25 lon_max: -80 lon_min: -79 ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T20:35:18 time_end: ~ time_start: ~ title: Hospitals at Risk from Storm Surge by Tropical Cyclones uri: /report/nca4/chapter/human-health/figure/hospitals_floodplain_sandy url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The maps show estimated changes in annual net mortality due to extremely hot and cold days in 49 U.S. cities for 2080–2099 as compared to 1989–2000. Across these cities, the change in mortality is projected to be an additional 9,300 deaths each year under a higher scenario (RCP8.5) and 3,900 deaths each year under a lower scenario (RCP4.5). Assuming a future in which the human health response to extreme temperatures in all 49 cities was equal to that of Dallas today (for example, as a result of availability of air conditioning or physiological adaptation) results in an approximate 50% reduction in these mortality estimates. For example, in Atlanta, an additional 349 people are projected to die from extreme temperatures each year by the end of century under RCP8.5. Assuming residents of Atlanta in 2090 have the adaptive capacity of Dallas residents today, this number is reduced to 128 additional deaths per year. Cities without circles should not be interpreted as having no extreme temperature impact. Data not available for the U.S. Caribbean, Alaska, or Hawai‘i & U.S.-Affiliated Pacific Islands regions. Source: adapted from EPA 2017.{{< tbib '157' '0b30f1ab-e4c4-4837-aa8b-0e19faccdb94' >}}" chapter_identifier: human-health create_dt: 2018-04-06T19:11:01 href: https://data.globalchange.gov/report/nca4/chapter/human-health/figure/projected-extreme-temperature-mortality.yaml identifier: projected-extreme-temperature-mortality lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:46:00 time_end: ~ time_start: ~ title: Projected Change in Annual Extreme Temperature Mortality uri: /report/nca4/chapter/human-health/figure/projected-extreme-temperature-mortality url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Many Indigenous peoples are taking steps to adapt to climate change impacts. You can use the interactive version of this map available at https://biamaps.doi.gov/nca/ to search by activity type, region, and sector and to find more information and links to each project. To provide feedback and add new projects for inclusion in the database, see: https://www.bia.gov/bia/ots/tribal-resilience-program/nca/. Thus far, tribal entities in the Northwest have the highest concentration of climate activities (Ch. 24: Northwest). For other case studies of tribal adaptation activities, see both the Institute for Tribal Environmental Professionals’ Tribal Profiles,{{< tbib '1' 'd3ebe118-8e13-4c66-af22-b50a8a707360' >}} and Tribal Case Studies within the U.S. Climate Resilience Toolkit. {{< tbib '2' 'aef9a0ac-5050-4f22-8006-45bc1981fba1' >}},{{< tbib '3' '102c643a-31f7-4881-b0cb-74335c20bf6f' >}} Source: Bureau of Indian Affairs." chapter_identifier: tribal-and-indigenous-communities create_dt: 2017-04-05T20:12:03 href: https://data.globalchange.gov/report/nca4/chapter/tribal-and-indigenous-communities/figure/chafigure-0-1.yaml identifier: chafigure-0-1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-12-03T20:00:12 time_end: ~ time_start: ~ title: Indigenous Peoples Climate Initiatives and Plans uri: /report/nca4/chapter/tribal-and-indigenous-communities/figure/chafigure-0-1 url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "Communities’ economic potential and livelihoods rely on infrastructure and the essential services it delivers, and many tribes and Indigenous communities already face acute infrastructure challenges that make them highly vulnerable to climate impacts.{{< tbib '22' '5b754441-464c-49fd-90e8-c184fc2ba1f5' >}} Indigenous peoples along the coasts and in the islands, the Southwest, and Alaska have experienced the most extensive infrastructure-related impacts thus far (Ch. 8: Coastal; Ch. 20: U.S. Caribbean; Ch. 25: Southwest; Ch. 26: Alaska; Ch. 27: Hawaiʻi & Pacific Islands). Source: USGCRP." chapter_identifier: tribal-and-indigenous-communities create_dt: 2017-05-15T20:31:03 href: https://data.globalchange.gov/report/nca4/chapter/tribal-and-indigenous-communities/figure/infrastructure-vulnerabilities.yaml identifier: infrastructure-vulnerabilities lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T17:04:19 time_end: ~ time_start: ~ title: Infrastructure and Economic Vulnerabilities uri: /report/nca4/chapter/tribal-and-indigenous-communities/figure/infrastructure-vulnerabilities url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'These photos show aerial views of (left) Isle de Jean Charles, Louisiana, and (right) Kivalina, Alaska. As projections of sea level rise and coastal inundation are realized, many impacted communities are confronting political, ecological, and existential questions about how to adapt. Photo credits: (left) Ronald Stine; (right) ShoreZone ([CC BY 3.0](https://creativecommons.org/licenses/by/3.0/legalcode)).' chapter_identifier: tribal-and-indigenous-communities create_dt: 2018-04-04T00:57:48 href: https://data.globalchange.gov/report/nca4/chapter/tribal-and-indigenous-communities/figure/isle-de-jean-charles--la.yaml identifier: isle-de-jean-charles--la lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 3 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T17:04:33 time_end: ~ time_start: ~ title: 'Isle de Jean Charles, LA, and Kivalina, AK' uri: /report/nca4/chapter/tribal-and-indigenous-communities/figure/isle-de-jean-charles--la url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Some tribal communities at risk of displacement from climate change are actively planning whole-community relocation strategies. As part of the resettlement of the tribal community of Isle de Jean Charles, residents are working with the Lowlander Center (a local, nongovernmental organization), the State of Louisiana, and others to finalize a plan that reflects the physical, sociocultural, and economic needs of the community. Photo credit: Louisiana Office of Community Development.' chapter_identifier: tribal-and-indigenous-communities create_dt: 2018-04-04T01:02:44 href: https://data.globalchange.gov/report/nca4/chapter/tribal-and-indigenous-communities/figure/community-planning.yaml identifier: community-planning lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 4 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T17:04:04 time_end: ~ time_start: ~ title: Community Planning uri: /report/nca4/chapter/tribal-and-indigenous-communities/figure/community-planning url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: 'Severe flooding in Thailand in 2011 created significant disruptions of local business operations and global supply chains, resulting in a range of impacts to U.S. business interests. Source: ICF.' chapter_identifier: north-american-and-other-international-effects create_dt: 2018-03-28T18:45:31 href: https://data.globalchange.gov/report/nca4/chapter/north-american-and-other-international-effects/figure/global-wheat-price.yaml identifier: global-wheat-price lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 1 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-29T18:11:29 time_end: ~ time_start: ~ title: Impact of 2011 Thailand Flooding on U.S. Business Interests uri: /report/nca4/chapter/north-american-and-other-international-effects/figure/global-wheat-price url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information - attributes: ~ caption: "The Famine Early Warning Systems Network involves a collaboration between U.S. government agencies, other national government ministries, and international partners to collect data and produce analyses of conditions in food-insecure regions and countries. The analyses integrate information on climate, agricultural production, prices, trade, nutrition, and other societal factors to develop scenarios of food security around the world 6 to 12 months in advance. This map shows projections of peak populations in need of emergency food assistance in 2018. Source: adapted from USAID 2018.{{< tbib '58' '00193d52-610b-44b0-8e81-7eeb2fe96d19' >}}" chapter_identifier: north-american-and-other-international-effects create_dt: 2018-03-28T18:03:58 href: https://data.globalchange.gov/report/nca4/chapter/north-american-and-other-international-effects/figure/famine-early-warning-system.yaml identifier: famine-early-warning-system lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ ordinal: 2 report_identifier: nca4 source_citation: ~ submission_dt: 2018-11-23T14:59:18 time_end: ~ time_start: ~ title: Famine Early Warning Systems Network uri: /report/nca4/chapter/north-american-and-other-international-effects/figure/famine-early-warning-system url: ~ usage_limits: Figure may be copyright protected and permission may be required. Contact original figure source for information