---
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-annual-greenhouse-gas-index-2018.yaml
  identifier: indicator-annual-greenhouse-gas-index-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:\r\n\r\n1. The Annual Greenhouse Gas Index (AGGI) is a measure of the capacity of Earth’s atmosphere to trap heat as a result of the presence of long-lived greenhouse gases. The AGGI provides standardized information about how human activity has affected the climate system through greenhouse gas emissions.\r\n2. This indicator demonstrates that the warming influence of greenhouse gases in the atmosphere has increased substantially over the last several decades. In 2017, the AGGI was 1.42, an increase of more than 40% since 1990.\r\n3. The AGGI can inform decisions about mitigation strategies.\r\n\r\nFull Summary:\r\n\r\nRadiative forcing (shown on the left vertical axis) is the change in the amount of solar radiation, or energy from the sun, that is trapped by the atmosphere and remains near Earth. When radiative forcing is greater than zero, it has a warming effect; when it is less than zero, it has a cooling effect. In this indicator, radiative forcing from long-lived greenhouse gases is shown relative to the year 1750. The AGGI (shown on the right vertical axis) is an index of radiative forcing normalized to the year 1990; it shows how the warming influence of greenhouse gases in the atmosphere has increased since that year.\r\n\r\nThis indicator demonstrates the change in radiative forcing resulting from changing concentrations of the following greenhouse gases: carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), chlorofluorocarbons (CFC-11 and CFC-12), and a set of 15 minor, long-lived halogenated gases. The National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division provides high-precision measurements of the abundance and distribution of long-lived greenhouse gases that are used to calculate global average concentrations. Radiative forcing for each gas is computed from these concentrations, and total radiative forcing for all gases is used to calculate the AGGI.\r\n\r\nThe AGGI shows that the warming influence of long-lived greenhouse gases in the atmosphere increased by 42% between 1990 and 2017. Carbon dioxide is currently the largest contributor to radiative forcing. Radiative forcing from methane has steadily increased since 2007, after having been nearly constant from 1999 to 2006. Owing to the Montreal Protocol, an international agreement signed in 1987, CFCs have been decreasing since the mid- to late 1990s after a long period of increase. However, CFC replacements (many of the “other halogenated gases” in the graph) have been increasing since the phase-out of CFCs.\r\n\r\nFundamentally, the AGGI is a measure of what human activity has already done to affect the climate system through greenhouse gas emissions. It provides quantitative information in a simplified, standardized format that decision makers can use to inform mitigation strategies."
  title: 'Indicator: Annual Greenhouse Gas Index'
  topic: ~
  uri: /report/indicator-annual-greenhouse-gas-index-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-arctic-sea-ice-extent-2018.yaml
  identifier: indicator-arctic-sea-ice-extent-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points: \r\n\r\n1. Sea ice extent is a measure of the surface area of the ocean covered by sea ice. Increases in air and ocean temperatures decrease sea ice extent; in turn, the resulting darker ocean surface absorbs more solar radiation and increases Arctic warming. \r\n\r\n2. The minimum sea ice extent in the Arctic, measured in September of each year, has decreased by about 32% since 1979. \r\n\r\n3. This indicator can help decision makers understand the magnitude and rate of sea ice loss and anticipate the resultant impacts on coastal areas and marine commercial activities.  \r\n\r\nFull Summary: \r\n\r\nSea ice extent is estimated using daily satellite images to calculate the total ocean area that has an ice concentration of 15% or more. Trends in sea ice extent are calculated from average values measured during the month of September, which is typically when sea ice extent reaches its annual minimum. Minimum sea ice extent in the Arctic has decreased by about 32% since 1979 (the first full year of satellite data). At this rate, some projections suggest that the Arctic will be virtually ice-free during summers by the middle of this century.\r\nThe melting of sea ice reduces the area of white surface that reflects the sun’s radiation, simultaneously increasing the area of dark ocean surface that absorbs it. This albedo effect results in a cycle of further sea ice melt and more warming of the ocean. Before melting begins, snow-covered sea ice absorbs only about 20% of the solar radiation that reaches it, whereas the ice-free ocean surface absorbs over 90%. A warmer ocean may melt ice from below, or may release heat back into the atmosphere before the ocean refreezes in the winter—leading over time to less sea ice and a warmer climate. As sea ice cover declines and the Arctic atmosphere warms, wind patterns in the northern hemisphere may shift. In addition, the loss of ice increases the risk of erosion along coastlines and changes the presence of marine species in certain areas, affecting commercial fish stocks and the economies of some coastal towns. Decision makers can use this indicator to understand the magnitude and rate of sea ice loss and prepare for the associated impacts on coastlines and commercial industries."
  title: 'Indicator: Arctic Sea Ice Extent'
  topic: ~
  uri: /report/indicator-arctic-sea-ice-extent-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-atmospheric-carbon-dioxide-2018.yaml
  identifier: indicator-atmospheric-carbon-dioxide-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. This indicator tracks the global monthly average concentration of carbon dioxide in the atmosphere, capturing both seasonal and interannual trends. Carbon dioxide concentration is an important measure of how human activity has increased the heat-trapping capacity of the atmosphere.  \r\n\r\n2. Global monthly average concentrations of carbon dioxide have risen steadily from 339 parts per million in 1980 (averaged over the year) to 405 parts per million in 2017, an increase of more than 19% in less than 40 years.\r\n\r\n3. This indicator can inform carbon emissions policies at national and international levels.  \r\n\r\nFull Summary:  \r\n\r\nGreenhouse gases such as carbon dioxide trap heat in the atmosphere. Increasing concentrations of these gases have driven an increase in global temperatures. The Annual Greenhouse Gas Index (AGGI) shows that over the past decade, increases in carbon dioxide are responsible for about 84% of the increase in the heat-trapping capacity of the atmosphere. Although the atmospheric concentration of carbon dioxide fluctuates over seasonal cycles, as illustrated by the saw-tooth pattern in the graph, the overall trend has been a steady increase since data collection began. Global monthly average concentrations of carbon dioxide have risen from around 339 parts per million in 1980 (averaged over the year) to 405 parts per million in 2017, an increase of more than 19%\r\n\r\nThe National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division has measured carbon dioxide and other greenhouse gases for several decades through a globally distributed network of about 70 air sampling sites, including the Mauna Loa Observatory in Hawai’i. The data for this indicator come from a subset of about 40 of these sites located in isolated regions of the ocean. Information about global carbon dioxide concentrations can inform emissions policies at national and international levels."
  title: 'Indicator: Atmospheric Carbon Dioxide'
  topic: ~
  uri: /report/indicator-atmospheric-carbon-dioxide-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-billion-dollar-disasters-2018.yaml
  identifier: indicator-billion-dollar-disasters-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points: \r\n\r\n1. The number of weather and climate-related disasters exceeding 1 billion dollars has increased in the United States  since 1980. \r\n2. The increase in Billion Dollar Disasters over time represents a combination of factors, including an increase the magnitude and frequency of some kinds of hazards (flooding, extreme heat, a driving component of drought and wildfire hazards) and changes in the value and placement of assets and property. \r\n3. From 1980–2017, the U.S. experienced 227 weather and climate disasters with overall damage costs reaching or exceeding $1 billion, including Consumer Price Index (CPI) adjustments, for each individual event. The cumulative costs for these 227 events exceed $1.5 trillion.\r\n\r\nAbout the Indicator: \r\n\r\nThe Billion Dollar Disaster indicator provides insight into the frequency and the total estimated costs of major weather and climate events that occur in the United States. This indicator compiles the annual number of weather and climate-related disasters across seven event types. Events are included if they are estimated to cause more\r\nthan one billion U.S. dollars in direct losses. The cost estimates of these events are adjusted for inflation using the Consumer Price Index (CPI) and are based on costs documented in several Federal and private-sector databases.\r\n\r\nIn recent decades, the U.S. has experienced a rising number of weather and climate disasters that cause significant economic damages and societal losses. From 1980–2017, the annual average number of billion-dollar events was 6.0, including CPI adjustments. For the most recent 5 years (2013–2017), the annual average was 11.6 events.\r\n\r\nThe distribution of damage from U.S. Billion-dollar disaster events from 1980 to 2017 is dominated by tropical cyclone losses. Tropical cyclones have caused the most damage ($862 billion) and also have the highest average event cost ($21.6 billion per event). Hurricanes are responsible for slightly more than half (55.1%) of the total losses for all the U.S. billion-dollar disasters but represent less than one-fifth (17.6%) of all the billion-dollar events we have assessed since 1980.\r\n\r\nThe increase in population and material wealth over the last several decades are important factors for the increased damage potential. Climate change is also playing an increasing role in the increasing frequency of some types of extreme weather that lead to billion-dollar disasters. Most notably, the rise in vulnerability to drought, lengthening wildfire seasons and the potential for extremely heavy rainfall and inland flooding events are most acutely related to the influence of climate change (Melillo et al. 2014).\r\n\r\nWhy it's Important:\r\n\r\n- In addition to direct threats to life and safety, major weather and climate disasters claim property, disrupt business, and affect daily life.\r\n- All U.S. states, Puerto Rico, and the Virgin Islands have been impacted by at least one billion-dollar disaster since 1980.\r\n-  Climate change is playing a role in the increasing frequency of some types of extreme weather that lead to billion-dollar disasters."
  title: 'Indicator: Billion Dollar Disasters'
  topic: ~
  uri: /report/indicator-billion-dollar-disasters-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-frost-free-season-2018.yaml
  identifier: indicator-frost-free-season-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points: \r\n\r\n1. Observed changes in the length of the frost-free season, defined as the number of frost-free days in a year, reflect the overall warming trend in the climate system. The bars on the graph show the difference between the number of frost-free days in each year and the average number of frost-free days from 1979 to 2016. \r\n\r\n2. During the past 30 years, there has been an increase in the length of the frost-free season over the contiguous United States and Alaska, relative to the 1979–2016 average. \r\n\r\n3. This indicator can inform decisions about agricultural and natural resource management, including crop planning and wildfire risk management. \r\n\r\nFull Summary: \r\n\r\nDuring the past 30 years, there has been an increase in the length of the frost-free season (defined as the number of frost-free days in a year) over the contiguous United States and Alaska, relative to the 1979–2016 average. This change in the frost-free season reflects the overall warming trend in the climate system. The bars on the graph show the difference between the number of frost-free days in each year and the average number of frost-free days from 1979 to 2016. Global daily freeze-thaw data are provided by the National Aeronautics and Space Administration (NASA) Freeze-Thaw Earth Systems Data Record, which represents one of the longest continuous global records from satellite-based observations. Satellite microwave sensors are used to determine the frozen or thawed status of water on the land surface at a given time. Measurements are taken over the contiguous United States and Alaska and include all vegetated land areas where seasonal frozen temperatures are a major constraint to plant growth. Collecting these data over time provides information on the number of frost-free days in a given year. The frost-free season can be an important factor in determining the potential growing season for vegetation. This indicator can help decision makers understand and anticipate possible impacts on agricultural and natural resource sectors. For instance, some pests and pathogens affecting forests and crops are projected to benefit from warmer temperatures and longer frost-free seasons. A lengthening frost-free season may also impact habitat conditions and wildfire risk."
  title: 'Indicator: Frost Free Season'
  topic: ~
  uri: /report/indicator-frost-free-season-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-global-surface-temperature-2018.yaml
  identifier: indicator-global-surface-temperature-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. This long-term record of global temperature is a key indicator of warming in the climate system. The bars on the graph show the number of degrees by which the average global temperature for each year differs from the average global temperature during the last century.  \r\n\r\n2. Since 1880, the average global temperature has increased by more than 1.5°F. Since the 1980s, average temperatures have exceeded the last century’s average every year.  \r\n\r\n3. Changes in global temperatures over the past century provide one important line of evidence for the effects of increasing greenhouse gas emissions. Such evidence can inform national and international policy discussions.  \r\n\r\nFull Summary:  \r\n\r\nLong-term observations of global temperature demonstrate the warming trend in the climate system. Since 1880, the average annual global temperature has increased by more than 1.5°F. Since the 1980s, average annual temperatures have exceeded the last century’s average every year. \r\n\r\nThe bars on the graph show the number of degrees by which the average global temperature for each year differs from the average global temperature during the last century. Global average temperatures include air temperatures measured on land and sea surface temperatures measured from ships and buoys worldwide. The data shown in the graph were drawn from the National Oceanic and Atmospheric Administration (NOAA) Global Historical Climatology Network (GHCN) and International Comprehensive Ocean-Atmosphere Data Set (ICOADS). \r\n\r\nChanges in global temperatures over the past century provide one important line of evidence for the effects of increasing greenhouse gas emissions. Such evidence can inform national and international policy discussions."
  title: 'Indicator: Global Surface Temperatures'
  topic: ~
  uri: /report/indicator-global-surface-temperature-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-heating-and-cooling-degree-days-2018.yaml
  identifier: indicator-heating-and-cooling-degree-days-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. 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). The bars on the graph show the difference between the number of degree days in each year and the average number of degree days throughout the 20th century. Degree days reflect changes in climate and are used as a proxy for the energy demand for heating or cooling buildings.  \r\n\r\n2. During the past 20 years, the number of heating degree days has decreased and the number of cooling degree days has increased. The increase in cooling days is driven by more frequent days above 65°F and more frequent extreme high temperatures.  \r\n\r\n3. This indicator is used in utility planning and can support construction decisions. It provides information on the relationship between climate and energy use that can inform mitigation strategies.  \r\n\r\nFull Summary:  \r\n\r\nDegree 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). For example, one day with an average temperature of 90°F equals 25 cooling degree days—the same as 25 days with an average temperature of 66°F. This indicator is thus a proxy that captures both extremes in and duration of energy demand (generally, fossil fuel demand for heating and electricity demand for cooling). The bars on the graph show the difference between the number of degree days in each year and the average number of degree days throughout the 20th century (1901 to 2000).\r\n\r\nOver the past 20 years, there has been a decrease in the number of heating degree days and an increase in the number of cooling degree days relative to the 20th century average. The recent increase in cooling degree days is driven by more frequent days above 65°F and more frequent extreme high temperatures. \r\n\r\nHeating and cooling degree days are calculated by the National Oceanic and Atmospheric Administration (NOAA). Daily temperature values for each region of the United States are used to calculate deviations from the 65°F baseline. These values are population-weighted using United States Census Bureau data, such that, for example, the same temperature produces more degree days in New York City than in rural Nebraska. \r\n\r\nAs temperatures continue to rise, combined changes in heating and cooling degree days are projected to change patterns of energy use and increase net electricity demand nationwide. This indicator is used in utility planning and can support construction decisions that consider heating and cooling needs. It provides information on the relationship between climate and energy use that can inform mitigation strategies."
  title: 'Indicator: Heating and Cooling Degree Days'
  topic: ~
  uri: /report/indicator-heating-and-cooling-degree-days-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-us-heat-waves-2018.yaml
  identifier: indicator-us-heat-waves-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:   \r\n\r\n1. Heat waves are occurring more often than they used to in major cities across the United States. The frequency of heat waves has increased steadily over time, from an average of two heat waves per year during the 1960s to nearly six per year during the 2010s.  \r\n\r\n2. The average heat wave season across the 50 major cities in this indicator is 45 days longer now than it was in the 1960s. Heat waves that occur earlier in the spring or later in the fall can increase exposure to the health risks associated with heat waves.  \r\n\r\n3. Of the 50 metropolitan areas in this indicator, 43 experienced a statistically significant increase in heat wave frequency between the 1960s and 2010s. The length of the heat wave season has increased significantly in 45 of these locations.  \r\n\r\nFull Summary:  \r\n\r\nUnusually hot days and multi-day heat waves are a natural part of day-to-day variation in weather. As the Earth’s climate warms, however, hotter-than-usual days and nights are becoming more common and heat waves are expected to become more frequent and intense (Climate Science Special Report Executive Summary) <tbib>21f65069-74b3-4bf7-bc09-0f359b825aad</tbib>. Increases in these extreme heat events can lead to more heat-related illnesses and deaths, especially if people and communities are not prepared and do not take steps to adapt <tbib>f0640d95-a845-40e6-a442-88eeff3127dc</tbib>.  \r\n\r\nHeat waves are more than just uncomfortable, as they can lead to illness and death, particularly among older adults, the very young, economically disadvantaged groups, and other vulnerable populations such as those in outdoor occupations (Climate and Health Assessment, Chapter 2)<tbib>cc15eee3-9ebf-4350-9135-d9d72c4cacb7</tbib>. In addition, prolonged exposure to excessive heat can lead to other impacts—for example, damaging crops and injuring or killing livestock. Extreme heat events can also lead to power outages as heavy demands for air conditioning strain the power grid.  \r\n\r\nLarge urban areas already face challenges related to heat. Surface air temperatures are often higher in urban areas than in surrounding rural areas for a number of reasons, including the concentrated release of heat from buildings, vehicles, and industry. This urban heat island effect, is expected to strengthen in the future as the structure, spatial extent, and population density of urban areas change and grow (Climate Science Special Report, Chapter 10) <tbib>1b0ce605-0f6c-4e1f-8fea-71e87cb4304f</tbib>. \r\n\r\nAbout the Indicator:\r\n\r\nThis indicator examines trends over time in two characteristics of heat waves in the United States: Frequency: the number of heat waves that occur every year and Season length: the number of days between the first heat wave of the year and the last.  \r\n\r\nHeat waves can be defined in many ways. For consistency across the country, this indicator defines a heat wave as a period of two or more consecutive days where the daily minimum apparent temperature (actual temperature adjusted for humidity) in a particular city exceeds the 85th percentile of historical July and August temperatures (1981–2010) for that city. This approach is useful for several reasons:  \r\n\r\n- The most serious health impacts of a heat wave are often associated with high temperatures at night, which is when the daily minimum usually occurs. If the air temperature stays too warm at night, the body faces extra strain as the heart pumps harder to try to regulate body temperature. \r\n\r\n- Adjusting for humidity is important because when humidity is high, water does not evaporate as easily, so it is harder for the human body to cool off by sweating. That is why health warnings about extreme heat are often based on the “heat index,” which combines temperature and humidity. \r\n\r\n- By using the 85th percentile for each individual city, this indicator defines “unusual” in terms of local conditions. A specific temperature like 95°F might be considered unusually hot in one city but perfectly normal in another city. Plus, people in relatively warm regions (such as the Southwest) may be better acclimated and adapted to hot weather. \r\n\r\nData for this indicator are based on temperature and humidity measurements between 1961 and 2017 from long-term weather stations, which are generally located at airports. This indicator focuses on the 50 most populous U.S. metropolitan areas that have available weather data from a consistent location. The year 1961 was chosen as the starting point because most major cities have collected consistent data since at least that time."
  title: 'Indicator: Heat Waves'
  topic: ~
  uri: /report/indicator-us-heat-waves-2018
  url: ~
- _public: 1
  contact_email: christa.d.peters-lidard@nasa.gov
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-heavy-precipitation-2018.yaml
  identifier: indicator-heavy-precipitation-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. This indicator measures the change over time in the relative amount of annual rainfall delivered by large, single-day precipitation events. Extreme precipitation events are defined as days with precipitation in the top 1 percent of all days with precipitation.  \r\n\r\n2. Heavy precipitation is becoming more intense and more frequent across most of the United States, particularly in the Northeast and Midwest.  \r\n\r\n3. Increases in the intensity or frequency of heavy precipitation are key factors that affect the risk of floods and flash floods.   \r\n\r\nFull Summary:\r\n\r\nJust as water is fundamental to life, precipitation is integral to society and ecosystems. Ecosystems, human systems, and human practices have evolved to fit the expected patterns of precipitation intensity, amount, and timing. This indicator focuses on the observed changes in the intensity aspect of precipitation.  \r\n\r\nThis indicator represents the percent change in the precipitation amount occurring as very heavy precipitation. It does this by comparing two periods, a reference period of 1901–1960 and a more recent period of 1986–2016. A positive value indicates that more of the precipitation that falls each year is falling as part of a heavy precipitation event. The threshold used to define a heavy precipitation event is the top 1 percent of all days with precipitation during the reference period. The larger the percentage shown, the greater the relative change from the reference period to the more recent period.  \r\n\r\nExtreme precipitation is related to climate change in that, all else being equal, a warmer atmosphere can “hold” more water vapor, and therefore deliver more rainfall when conditions for heavy precipitation events occur.  On average, for the majority of the United States, the total amount of precipitation falling during heavy events is expected to increase. \r\n\r\nThe information presented here is relevant to decisions about retention of surface water for flood mitigation or human use. Runoff from heavy precipitation events literally shapes the landscape, as floods and flash floods carve out valleys and arroyos and deposit sediment on floodplains. Thus, ecosystems, even in relatively dry regions, often reflect the nature and historic patterns of flood events. Crop selection and planting dates are influenced by the timing and frequency of heavy rains. The built environment, particularly culverts, dams, and reservoirs are designed specifically to accommodate the frequency and intensity of heavy precipitation.   \r\n\r\nThis indicator is provides valuable evidence of the expectation that heavy precipitation will increase for most parts of the United States."
  title: 'Indicator: Heavy Precipitation '
  topic: ~
  uri: /report/indicator-heavy-precipitation-2018
  url: https://www.globalchange.gov/browse/indicators/heavy-precipitation
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-ocean-chlorophyll-concentrations-2018.yaml
  identifier: indicator-ocean-chlorophyll-concentrations-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. The concentration of chlorophyll is a proxy for the amount of photosynthetic plankton, or phytoplankton, present in the ocean. Phytoplankton populations are influenced by climatic factors such as sea surface temperatures and winds.  \r\n\r\n2. Some of the highest average chlorophyll concentrations are located near continental coasts of the Pacific and Atlantic Oceans.  \r\n\r\n3. Changes in phytoplankton populations may impact fish and other marine life, which can affect economic productivity and food availability. Decision makers can use this indicator to understand the health and productivity of marine ecosystems that depend on phytoplankton.  \r\n\r\nFull Summary:  \r\n\r\nPhytoplankton are microscopic, floating, plant-like organisms that live in oceans, lakes, and rivers. Phytoplankton form the base of the marine food web, converting solar energy into organic matter (primary production). This process ultimately feeds the world’s fish, sea birds, marine mammals, and humans. Because phytoplankton use photosynthetic pigments like chlorophyll to convert solar energy into organic matter, the amount of phytoplankton present in the ocean can be assessed by measuring chlorophyll concentrations. When phytoplankton populations are large, the color of the water appears greener because of high concentrations of chlorophyll.   \r\n\r\nPhytoplankton populations, as indicated by chlorophyll concentrations, respond to both seasonal (short-term) and climatic (long-term) changes. Primary production by phytoplankton can be affected indirectly by climatic factors, such as changes in water temperatures and surface winds, which affect mixing within the water column and the availability of nutrients. Changes in cloud cover, which can reduce or increase solar energy available for photosynthesis, can also affect primary production.  \r\n\r\nThe map shows average chlorophyll concentrations for the period 1998–2017. Some of the highest average chlorophyll concentrations for this time period are located near continental coasts of the Pacific and Atlantic Oceans. The graphs below the map show trends in chlorophyll concentrations (percent change relative to the 1998–2017 average) for different regions over the same time period. The Hawaiian Islands (Graph 6) is the only region pictured with a downward trend in chlorophyll concentrations between 1998 and 2017.  \r\n\r\nThe chlorophyll concentration data shown here were obtained from global satellite measurements by the SeaWiFS and MODIS-Aqua projects of the National Aeronautics and Space Administration (NASA). Satellite data collection allows for large spatial coverage and frequent measurements over time, which is useful for assessing long-term changes. One limitation, however, is that satellites can only measure near-surface chlorophyll concentrations, thus potentially underestimating the total amount of phytoplankton present at all water depths. Chlorophyll concentrations also do not provide information on the composition of phytoplankton communities (for example, the abundance of larger versus smaller species).    \r\n\r\nThis indicator provides proxy information on the amount of primary production occurring in the ocean, which influences ecosystem-wide productivity. Reduced primary production may negatively impact fish and other marine life, which can affect food availability and economic sectors such as fishing and aquaculture. This indicator, in combination with in situ sampling of phytoplankton community composition, can be used by decision makers to assess the health and productivity of natural resources and marine life that depend on plankton."
  title: 'Indicator: Ocean Chlorophyll Concentrations'
  topic: ~
  uri: /report/indicator-ocean-chlorophyll-concentrations-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-sea-level-rise-2018.yaml
  identifier: indicator-sea-level-rise-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Messages: \r\n\r\n1. Global sea level has risen by about 8 inches since scientific record keeping began in the 1880s. The rate of global sea level rise has increased in recent decades. The current rate is a little more than an inch per decade. \r\n\r\n2. Sea level rise is primarily driven by two factors related to climate change. The first factor is “thermal expansion” – as ocean temperatures rise, the water expands. The second factor is melting of land ice (ice sheets and glaciers), which adds water to the world’s oceans. \r\n\r\n3. Sea level rise is not uniform across the globe. Coastal communities are affected by their local sea level rise, which combines global sea level rise, changes in local land elevation, tides and winds. In Louisiana, for example, local sea level is rising about 4 inches per decade because the land is sinking and sea level is rising. \r\n\r\n4. Sea level rise and climate change-related threats like high tide and storm-surge flooding are affecting social, economic, and ecological systems along the U.S. coasts.  \r\n\r\nFull Summary: \r\n\r\nRising global sea level is a critical consequence of climate change. As the ocean waters warm, they expand. Also, as air temperatures warm, water from melting ice sheets, polar ice caps, and glaciers, enter into our ocean basins. Global sea level rise is measured by tide gauges, which provide global estimates since the 1880s, and by satellites, which do so since 1993.  \r\n\r\nGlobal mean sea level (GMSL) has risen by about 7–8 inches (about 16–21 cm) since 1900, with about 3 of those inches (about 7 cm) occurring since 1993. Human-caused climate change has made a substantial contribution to GMSL rise since 1900, contributing to a rate of rise greater than during any preceding century in at least 2,800 years. In addition to the global average sea level rise, local sea level rise – sometimes called “relative sea level rise” – happens at different rates in different places. Local sea level rise is affected by the global sea level rise, but also by local land motions, and the effects of tides, currents, and winds. Many places along the United States coast have seen their local sea levels rise faster than the GMSL. As sea levels have risen, the number of tidal floods each year that cause minor impacts, often called “nuisance floods,” have increased 5- to 10-fold since the 1960s in several U.S. coastal cities (very high confidence). Rates of increase are accelerating in over 25 Atlantic and Gulf Coast cities (very high confidence)."
  title: 'Indicator: Sea Level Rise'
  topic: ~
  uri: /report/indicator-sea-level-rise-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-sea-surface-temperature-2018.yaml
  identifier: indicator-sea-surface-temperature-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. Changes in sea surface temperatures reflect the overall warming trend in the climate system and, in turn, influence weather and climate patterns worldwide. The bars on the graph show the number of degrees by which the average sea surface temperature for each year differs from the average sea surface temperature during the last century. \r\n\r\n2. During the past three decades, sea surface temperatures have exceeded the last century’s average every year.  \r\n\r\n3. Sea surface temperature data can be used to understand the response of the ocean to global warming and, in turn, how that response may influence other changes in climate.  \r\n\r\nFull Summary:  \r\n\r\nOver 70% of Earth’s surface area is ocean, which plays a major role in regulating Earth’s climate system. Much of the heat trapped by increasing atmospheric greenhouse gas levels is absorbed by the ocean, causing ocean temperatures to rise. Changes in sea surface temperatures influence atmospheric circulation and the amount of water vapor present in the air, thereby affecting weather and climate patterns worldwide.  \r\n\r\nThe bars on the graph show the number of degrees by which the average sea surface temperature for each year differs from the average sea surface temperature during the last century. During the past three decades, global average sea surface temperatures have exceeded the last century’s average every year and have been higher than at any other time since records began. The data shown represent temperatures in the upper 10 meters of the ocean and were drawn from the National Oceanic and Atmospheric Administration (NOAA) Merged Land–Ocean Surface Temperature Analysis (MLOST) dataset.  \r\n\r\nSea surface temperature data can be used to understand the response of the ocean to global warming and, in turn, how that response may influence other changes in climate."
  title: 'Indicator: Sea Surface Temperatures'
  topic: ~
  uri: /report/indicator-sea-surface-temperature-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-start-of-spring-2018.yaml
  identifier: indicator-start-of-spring-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points:  \r\n\r\n1. This indicator tracks the start of spring for each year, using model estimations of when enough heat has accumulated to initiate growth (leafing and flowering) in temperature-sensitive plants. The bars on the graph show the number of days by which the start of spring differs from the average start of spring during the last century. The earlier arrival of the start of spring has been linked to recent warming trends in global climate.  \r\n\r\n2. Since 1900, the start of spring (averaged over the contiguous United States) has varied within a three-week range. Since 1984, it typically has occurred earlier relative to the last century’s average, with the earliest spring start occurring in 2012.  \r\n\r\n3. This indicator can help decision makers understand and anticipate climate impacts on habitats and species, agricultural production, recreation, and the management of natural hazards such as wildfires.  \r\n\r\nFull Summary:  \r\n\r\nThis indicator estimates the annual start of spring on the basis of when growth can begin for temperature-sensitive native and cultivated plants. It can be used to monitor, assess, and predict variations and trends in spring timing at the national scale. Since 1900, the modeled start of spring (averaged over the contiguous United States) has varied within a three-week range. Since 1984, it typically has occurred earlier relative to the last century’s average, with the earliest spring start occurring in 2012. The bars on the graph show the number of days by which the start of spring differs from the average start of spring during the last century. These values are calculated from a numerical model that simulates the accumulation of heat needed to bring plants out of winter dormancy and into vegetative and reproductive growth. The model is based on (1) long-term observations of lilac and honeysuckle first-leaf and first-bloom, collected by citizen science volunteers at hundreds of sites across the contiguous United States, and (2) daily minimum and maximum temperatures measured at weather stations. The annual start of spring can be estimated for any location where daily minimum and maximum temperatures are recorded. The modeled values correlate well with observed leafing and flowering in a number of native and cultivated species, such as winter wheat, pear, and peach varieties. \r\n\r\nA trend toward earlier springs could have significant implications for agriculture, natural resource and hazard management, and recreation. Since phenological events such as leafing and flowering is closedly connected to climate, this indicator can used to better understand and anticipate climate impacts on habitats and species, optimize crop selection and yield, and assess the potential vulnerability of ecosystems to drought and wildfire."
  title: 'Indicator: Start of Spring'
  topic: ~
  uri: /report/indicator-start-of-spring-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-terrestrial-carbon-storage-2018.yaml
  identifier: indicator-terrestrial-carbon-storage-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points: \r\n\r\n1. Terrestrial ecosystems store large amounts of carbon. Changes affecting these ecosystems—such as alterations in climate or land use—can contribute to changes in carbon storage, which in turn can affect the climate system through the release of greenhouse gases.   \r\n\r\n2. Forests (not including urban forests) annually store the majority of terrestrial carbon dioxide in the United States. Croplands and grasslands are generally net carbon dioxide sources, releasing more carbon dioxide than they are storing.  \r\n\r\n3. This indicator can help decision makers understand how climate change, land management, natural disturbances, and ecosystem dynamics affect annual terrestrial carbon storage in the United States.  \r\n\r\nFull Summary:  \r\n\r\nCarbon is stored in living and dead organic matter above and below the ground. Changes in terrestrial (or land-based) ecosystems—for instance, as a result of climate or land use changes—can contribute to changes in carbon storage, which in turn can affect the climate system through the release of greenhouse gases such as carbon dioxide.  This indicator shows that terrestrial ecosystems store large amounts of carbon dioxide each year: for example, net annual carbon dioxide storage by forests, urban forests, croplands, and grasslands totaled 746.9 million metric tons in 2016. \r\n\r\nForests (not including urban forests) accounted for more than 99% of that net annual storage. With the exception of two years since 1990, croplands and grasslands have been net carbon dioxide sources, annually releasing more carbon dioxide than they are storing. \r\n\r\nThe data shown in the graph were drawn from the U.S. Environmental Protection Agency (EPA) Inventory of Greenhouse Gas Emissions and Sinks, in which annual carbon dioxide storage is estimated using three complementary datasets: the U.S. Department of Agriculture (USDA) National Resources Inventory, the USDA Forest Service Forest Inventory and Analysis, and the Multi-Resolution Land Characteristics Consortium National Land Cover Dataset. These datasets represent a combination of statistical survey approaches and satellite data. Changes to terrestrial carbon storage reflect the impacts of many factors.  \r\n\r\nThis indicator can help decision makers understand how annual terrestrial carbon storage in the United States is changing as a result of climate change, land management, natural disturbances, and ecosystem dynamics."
  title: 'Indicator: Terrestrial Carbon Storage'
  topic: ~
  uri: /report/indicator-terrestrial-carbon-storage-2018
  url: ~
- _public: 1
  contact_email: ~
  contact_note: ~
  doi: ~
  frequency: ~
  href: https://data.globalchange.gov/report/indicator-us-surface-temperature-2018.yaml
  identifier: indicator-us-surface-temperature-2018
  in_library: ~
  publication_year: 2018
  report_type_identifier: indicator
  summary: "Key Points: \r\n\r\n1. Observed changes in U.S. temperatures reflect the overall warming trend in the climate system. The bars on the graph show the number of degrees by which the average U.S. temperature for each year differs from the average U.S. temperature during the last century. \r\n\r\n2. In the contiguous United States, temperatures during this century have been, on average, 1.5°F warmer than during the last century. \r\n\r\n3. This indicator can inform preparedness decisions in a wide variety of sectors, such as energy production, agriculture, and human health.  \r\n\r\nFull Summary: \r\n\r\nRising temperatures in the United States are indicative of warming in the global climate system. In the contiguous United States, temperatures during this century have been, on average, 1.5°F warmer than during the last century. Human activities have contributed to this increase in temperature through the addition of carbon dioxide and other heat-trapping greenhouse gases into the atmosphere. The bars on the graph show the number of degrees by which the average U.S. temperature for each year differs from the average U.S. temperature during the last century (52°F). These data were obtained from the National Oceanic and Atmospheric Administration (NOAA) nClimDiv dataset. The nClimDiv is based on daily data from the Global Historical Climatology Network (GHCN), which includes temperature and other climatic measurements from stations located around the world. Increased temperatures across the United States affect a wide variety of sectors, such as energy production, agriculture, and human health. This indicator can inform planning and preparedness decisions in these sectors."
  title: 'Indicator: U.S. Surface Temperatures'
  topic: ~
  uri: /report/indicator-us-surface-temperature-2018
  url: ~