Populous areas of America's coast that are at risk of rising sea levels may see large migration events by the end of the century. Climate change impacts on Florida's cities like Miami and Fort Lauderdale are likely to cause millions of migrants to move further inland.

The Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, 2020-2100 consists of county-level population projection scenarios of total population, and by age, sex, and race in five-year intervals for all U.S. counties for the period 2020 - 2100. These data have numerous potential uses and can serve as inputs for addressing questions involving sub-national demographic change in the United States in the near, middle- and long-term.

In Miami Beach, Florida, around 40,000 residents live in homes at risk to being flooded by 2060 due to rising sea levels. Florida has many cities that may be lost to coastal erosion as a result of sea level rise, as well as storm surges. The significance of sea level rise is particularly great for the many cities with high values of assets that are under threat.

Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.5 billion inhabitants on the continent at the beginning of 2024, the number of inhabitants is expected to reach 3.8 billion by 2100. In total, the global population is expected to reach nearly 10.4 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2021. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.

The USGS’s FORE-SCE model was used to produce land-use and land-cover (LULC) projections for the conterminous United States. The projections were originally created as part of the "LandCarbon" project, an effort to understand biological carbon sequestration potential in the United States. However, the projections are being used for a wide variety of purposes, including analyses of the effects of landscape change on biodiversity, water quality, and regional weather and climate. The year 1992 served as the baseline for the landscape modeling. The 1992 to 2005 period was considered the historical baseline, with datasets such as the National Land Cover Database (NLCD), USGS Land Cover Trends, and US Department of Agriculture's Census of Agriculture used to guide the recreation of historical land cover for this period. 2006 to 2100 was considered the future projection time frame. Four scenarios were modeled for 2006 to 2100, corresponding to four major scenario storylines from the In ...

County population projections broken down by year, age, race, and gender (2020-2100) for use with GIS mapping software, databases, and web applications.

This dataset holds modeled estimates of soil accretion for the Atchafalaya and Terrebonne basins in the Mississippi River Delta of coastal Louisiana, U.S. Soil accretion was predicted from 2021-2100 using the Numerical Understanding of Marsh Accretion Resilience (NUMAR) model. This process-based model is an adaptation of the NUMAN model that was modified for marsh environments. The input parameters were aggregated within ecogeomorphic cells, areas of similar vegetation and elevation. The dataset includes spatially explicit input values, description of important parameters, and a shapefile of model outputs.

Future county population was based on projections for 2100 from the Spatially Explicit Regional Growth Model (SERGoM; Theobald 2005). SERGoM simulates population based on existing patterns of growth by census block, groundwater well and road density, and transportation distance to urban areas, while constraining the pattern of development to areas outside of protected areas and urban areas (Theobald 2005). The dataset here is a projection for a “baseline” growth scenario that assumes a similar trajectory to that of current urban growth (Bierwagen et al. 2010). SERGoM accuracy is estimated as 79–99% when compared to 1990 and 2000 census data, with the accuracy varying by urban/exurban/rural categories and increasing slightly with coarser resolution (Theobald 2005). The accuracy of future model predictions with different economic scenarios is most sensitive to fertility rates, which are subject to cultural change, economic recessions, and the current pattern of lands protected from development (Bierwagen et al. 2010). Bierwagen, B. G., D. M. Theobald, C. R. Pyke, A. Choate, P. Groth, J. V. Thomas, and P. Morefield. 2010. National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences of the United States of America 107:20887-20892. Theobald, D. M. 2005. Landscape patterns of exurban growth in the USA from 1980 to 2020. Ecology and Society 10: article 32.

This statistic projects the number of homes affected by rising sea levels due to climate change in the United States in 2100, by selected city. It is estimated, that more than 38 thousand homes will be affected by rising sea levels in Fort Lauderdale, Florida.

From now until 2100, India and China will remain the most populous countries in the world, however China's population decline has already started, and it is on course to fall by around 50 percent in the 2090s; while India's population decline is projected to begin in the 2060s. Of the 10 most populous countries in the world in 2100, five will be located in Asia, four in Africa, as well as the United States. Rapid growth in Africa Rapid population growth across Africa will see the continent's population grow from around 1.5 billion people in 2024 to 3.8 billion in 2100. Additionally, unlike China or India, population growth in many of these countries is not expected to go into decline, and instead is expected to continue well into the 2100s. Previous estimates had projected these countries' populations would be much higher by 2100 (the 2019 report estimated Nigeria's population would exceed 650 million), yet the increased threat of the climate crisis and persistent instability is delaying demographic development and extending population growth. The U.S. as an outlier Compared to the nine other largest populations in 2100, the United States stands out as it is more demographically advanced, politically stable, and economically stronger. However, while most other so-called "advanced countries" are projected to see their population decline drastically in the coming decades, the U.S. population is projected to continue growing into the 2100s. This will largely be driven by high rates of immigration into the U.S., which will drive growth despite fertility rates being around 1.6 births per woman (below the replacement level of 2.1 births per woman), and the slowing rate of life expectancy. Current projections estimate the U.S. will have a net migration rate over 1.2 million people per year for the remainder of the century.

This map shows the projected average change in mean temperature (°C) for 2081-2100, with respect to the reference period of 1986-2005 for RCP8.5. The median projected change across the ensemble of CMIP5 climate models is shown.

For more maps on projected change, please visit the Canadian Climate Data and Scenarios (CCDS) site: http://ccds-dscc.ec.gc.ca/index.php?page=download-cmip5.

Sagebrush (Artemisia spp.) ecosystems provide critical habitat for the near-threatened Greater sage-grouse (Centrocercus urophasianus), and future loss of sagebrush habitat because of land use change and global climate change is of concern. We used a dynamic additive spatio-temporal model to estimate effects of climate (spring-summer temperatures and precipitation) on sagebrush cover dynamics at 32 sage-grouse management (core) areas in Wyoming, 1985-2018. We then use the fitted models to make probabilistic projections of sagebrush cover in each core area across three time intervals (2018-2040, 2041-2070, 2071-2100) and under three climate change scenarios and weighted averages of 18 Global Circulation Models (ssp126, ssp245, and ssp585), producing 351 netCDF files (USGS_SageCastWY.zip).

In terms of the share of its total population, the Lower Florida Keys are most at risk to homes being flooded by rising sea levels, with 81 percent of its residents living in dwellings expected to be flooded by 2060. Although Chesapeake, Virginia has a relatively small percentage of its population at risk, the number of inhabitants living in homes expected to be flooded is very large.

Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline ("base case"). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use Scenarios (ICLUS) project.

Projections of extreme event metrics and threshold exceedances are produced by analyzing the Climate Model Intercomparison Program Phase 6 Localized Constructed Analogs (CMIP6-LOCA2) data set. The primary daily temperature and precipitation data are summarized to 36 annual metrics and 4 monthly metrics. This data set includes output from 27 GCMs for the period 1950-2100 under ssp245, ssp370, and ssp585 scenarios for the Contiguous United States with partial coverage in Mexico and Canada. To support climate research within and outside the Department of Interior these data are distributed in a variety of formats: individual model grids for all years, gridded climatologies (1961-1990, 1971-2000, 1981-2010, 1991-2020, and Global Warming Levels +1.5 °C, +2.0 °C, +3.0 °C), and time series spatially averaged to United States county and watershed boundaries (HUC8 from the Watershed Boundary Dataset). Ensemble averages are provided for the Weighted Multi-Model Mean (WMMM) and Multi-Model Mean (MMM) where appropriate. Many of the threshold exceedance variables stem from the Climdex project (https://www.climdex.org), which predominately uses metric units. Additional English-based thresholds were included to support Department of Interior research. There are 72 simulations in total (ssp245=24, ssp370=23, ssp585=25). While the CMIP6-LOCA2 data set supports multiple realizations per model; one realization per model is provided herein (predominately r1i1p1f1, except when this realization was not available). Users interested in the source downscaled temperature and precipitation files are referred to the data set home page: https://loca.ucsd.edu. The 27 included GCMs are: ACCESS-CM2, ACCESS-ESM1-5, AWI-CM-1-1-MR, BCC-CSM2-MR, CESM2-LENS, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, CanESM5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, IPSL-CM6A-LR, KACE-1-0-G, MIROC6, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, TaiESM1

Sea level rise projections for New York City in the 2100s from the New York City Panel on Climate Change (2019).

This map shows the projected average change in mean temperature (°C) for 2081-2100, with respect to the reference period of 1986-2005 for RCP2.6. The median projected change across the ensemble of CMIP5 climate models is shown.

For more maps on projected change, please visit the Canadian Climate Data and Scenarios (CCDS) site: http://ccds-dscc.ec.gc.ca/index.php?page=download-cmip5.

A monthly water-balance model (MWBM) is applied to simulate components of the water balance for the period 1950-2100 under ssp245, ssp370, and ssp585 scenarios for the Contiguous United States. The statistically downscaled LOCA2 temperature and precipitation projections from 27 GCMs from the Climate Model Intercomparison Program Phase 6 (CMIP6) are use as input to the water balance model. This data set supports the USGS National Climate Change Viewer (ver. 2). The statistically downscaled data set is: CMIP6-LOCA2: Localized Constructed Analogs (Pierce et al. 2023, bias corrected by a modified version of Livneh et al. 2013) Users interested in the downscaled temperature and precipitation files are referred to the data set home page: LOCA: https://loca.ucsd.edu Bias correction data set: https://cirrus.ucsd.edu/~pierce/nonsplit_precip/ The 27 included GCMs are: ACCESS-CM2, ACCESS-ESM1-5, AWI-CM-1-1-MR, BCC-CSM2-MR, CESM2-LENS, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, CanESM5, EC-Earth3, EC-Earth3-Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, IPSL-CM6A-LR, KACE-1-0-G, MIROC6, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, NorESM2-MM, TaiESM1 There are 72 simulations in total (ssp245=24, ssp370=23, ssp585=25). While the LOCA2 data set supports multiple realizations per model; one MWBM realization per model is provided herein (predominately r1i1p1f1, except when this realization was not available).

This dataset consist of annual (2020-2100) county-level population projections for the United States (U.S.) for Shared Socioeconomic Pathways (SSPs) 3 and 5. The original decadal state-level data is used as an input to the gridded population data model to downscale the state-level projections for each SSP to a 1 km grid. The 1 km data is then aggregated to the county-level using the 2020 TIGER/Line county shapefiles from the U.S. Census Bureau. The two data files are shared as .csv files with the following structure: Rows = Data for individual counties which are identified using their Federal Information Processing Standard (FIPS) code. The FIPS code is stored in the first column. Columns = Each year from 2020-2100 is an individual column. For easier reference, the state name associated with each row is stored in the last column. Values in each cell are the downscaled estimated population for that county-year combination. Values are fractional due to the weighting scheme used in the downscaling. The paper and model source code cited in the "Related Works" section describes the initial source of the population projections.

US Census Projection: Population: Mid Year data was reported at 204,461,198.000 Person in 2100. This records a decrease from the previous number of 205,458,306.000 Person for 2099. US Census Projection: Population: Mid Year data is updated yearly, averaging 211,450,473.000 Person from Jun 1950 (Median) to 2100, with 151 observations. The data reached an all-time high of 238,504,547.000 Person in 2052 and a record low of 53,443,075.000 Person in 1950. US Census Projection: Population: Mid Year data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s Brazil – Table BR.GAB038: Population: Projection: US Census Bureau.