This dataset provides projections of land use and land cover (LULC) change within the Arctic Boreal Vulnerability Experiment (ABoVE) _domain, spanning from 2015 to 2100 with a spatial resolution of 0.25 degrees. It includes LULC change under two Shared Socioeconomic Pathways (SSP126 and SSP585) derived from Global Change Analysis Model (GCAM) at an annual scale. The specific land types include: needleleaf evergreen tree-temperate, needleleaf evergreen tree-boreal, needleleaf deciduous tree-boreal, broadleaf evergreen tree-tropical, broadleaf evergreen tree-temperate, broadleaf deciduous tree-tropical, broadleaf deciduous tree-temperate, broadleaf deciduous tree-boreal, broadleaf evergreen shrub-temperate, broadleaf deciduous shrub-temperate, broadleaf deciduous shrub-boreal, C3 arctic grass, C3 grass, C4 grass, and C3 unmanaged rainfed crop. The data were generated by integrating regional LULC projections from GCAM with high-resolution MODIS land cover data and applying two alternative spatial downscaling models: FLUS and Demeter. Data are provided in NetCDF format.

This dataset is the output data of GCM60, the global climate change projection model provided by Meteorological Research Institute, as part of the project which aims to provide detailed climate change projections around Japan for adaptation planning.

This data release consists of Microsoft Excel workbooks, shapefiles, and a figure (png format) related to a cooperative project between the U.S. Geological Survey (USGS) and the Florida Flood Hub for Applied Research and Innovation at the University of South Florida to derive projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future (2020-59, 2030-69, 2050-89, or 2060-99) to historical (1966-2005) extreme-precipitation depths fitted to extreme-precipitation data using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors are tabulated by duration (1, 3, and 7 days) and return period (5, 10, 25, 50, 100, 200, and 500 years). The official historical NOAA Atlas 14 DDF curves based on partial-duration series (PDS) can be multiplied by the change factors derived in this project to determine projected future extreme precipitation for events of a given duration and return period. Various statistical, dynamical and hybrid downscaled precipitation datasets from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to derive the change factors at the grid cells closest to the NOAA Atlas 14 stations including (1) the Coordinated Regional Downscaling Experiment (CORDEX), (2) the Localized Constructed Analogues (LOCA) dataset, (3) the Multivariate Adaptive Constructed Analogs (MACA) dataset, (4) the Analog Resampling and Statistical Scaling Method by Jupiter Intelligence using the Weather Research and Forecasting Model (JupiterWRF). The emission scenarios evaluated include representative concentration pathways RCP4.5 and RCP8.5 from the Coupled Model Intercomparison Project Phase 5 (CMIP5) for the downscaled climate datasets CORDEX, LOCA, and MACA. The emission scenarios evaluated for the JupiterWRF downscaled dataset include RCP8.5 from CMIP5, and shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Only daily durations are evaluated for JupiterWRF. Statistically downscaled precipitation datasets from CMIP6 were also used to derive change factors and include (1) the NASA Earth Exchange Global Daily Downscaled Projections (NASA), and (2) the Localized Constructed Analogues version 2 (LOCA2) dataset. The emission scenarios available for LOCA2 include SSP2-4.5, SSP3-7.0, and SSP5-8.5. The NASA dataset includes these in addition to the SSP1-2.6 scenario. DDF and change factors for the projected future ranges 2030-69 and 2060-99 were computed for LOCA2 only. When applying change factors to the historical NOAA Atlas 14 DDF curves to derive projected future precipitation DDF curves for the entire range of durations and return periods evaluated as part of this project, there is a possibility that the resulting projected future DDF curves may be inconsistent across duration and return period. By inconsistent it is meant that the precipitation depths may decrease for longer durations instead of increasing. Depending on the change factors used, this may happen in up to 6% of cases. In such a case, it is recommended that users use the higher of the projected future precipitation depths derived for the duration of interest and the previous shorter duration. This data release consists of three shapefiles: (1) polygons of climate regions (Climate_regions.shp); (2) polygons of Areal Reduction Factor (ARF) regions for the state of Florida (ARF_regions.shp); and (3) point locations of NOAA Atlas 14 stations in Florida for which depth-duration-frequency curves and change factors of precipitation depths were developed as part of this project (Atlas14_stations.shp). This data release also includes 70 tables. Fourteen tables contain computed change factors for the four downscaled climate datasets for the four future projection periods: (1) CORDEX 2020-59 (CF_CORDEX_2040_to_historical.xlsx); (2) CORDEX 2050-89 (CF_CORDEX_2070_to_historical.xlsx);(3) LOCA 2020-59 (CF_LOCA_2040_to_historical.xlsx); (4) LOCA 2050-89 (CF_LOCA_2070_to_historical.xlsx); (5) MACA 2020-59 (CF_MACA_2040_to_historical.xlsx); (6) MACA 2050-89 (CF_MACA_2070_to_historical.xlsx); (7) JupiterWRF 2038-42 (CF_JupiterWRF_2040_to_historical.xlsx); (8) JupiterWRF 2068-72 (CF_JupiterWRF_2070_to_historical.xlsx); (9) NASA 2020-59 (CF_NASA_2040_to_historical.xlsx); (10) NASA 2050-89 (CF_NASA_2070_to_historical.xlsx);(11) LOCA2 2020-59 (CF_LOCA2_2040_to_historical.xlsx); (12) LOCA2 2050-89 (CF_LOCA2_2070_to_historical.xlsx); (13) LOCA2 2030-69 (CF_LOCA2_2050_to_historical.xlsx); and (14) LOCA2 2060-99 (CF_LOCA2_2080_to_historical.xlsx) Twenty tables contain the corresponding DDF values for the historical and future projection periods in each of the four downscaled climate datasets: (1) CORDEX historical (DDF_CORDEX_historical.xlsx); (2) CORDEX 2020-59 (DDF_CORDEX_2040.xlsx); (3) CORDEX 2050-89 (DDF_CORDEX_2070.xlsx); (4) LOCA historical (DDF_LOCA_historical.xlsx); (5) LOCA 2020-59 (DDF_LOCA_2040.xlsx); (6) LOCA 2050-89 (DDF_LOCA_2070.xlsx); (7) MACA historical (DDF_MACA_historical.xlsx); (8) MACA 2020-59 (DDF_MACA_2040.xlsx); (9) MACA 2050-89 (DDF_MACA_2070.xlsx); (10) JupiterWRF historical (DDF_JupiterWRF_historical.xlsx); (11) JupiterWRF 2038-42 (DDF_JupiterWRF_2040.xlsx); (12) JupiterWRF 2068-72 (DDF_JupiterWRF_2070.xlsx); (13) NASA historical (DDF_NASA_historical.xlsx); (14) NASA 2020-59 (DDF_NASA_2040.xlsx); (15) NASA 2050-89 (DDF_NASA_2070.xlsx); (16) LOCA2 historical (DDF_LOCA2_historical.xlsx); (17) LOCA2 2020-59 (DDF_LOCA2_2040.xlsx); (18) LOCA2 2050-89 (DDF_LOCA2_2070.xlsx); (19) LOCA2 2030-69 (DDF_LOCA2_2050.xlsx); and (20) LOCA2 2060-99 (DDF_LOCA2_2080.xlsx). Twelve tables contain quantiles of change factors at 242 NOAA Atlas 14 stations in Florida derived primarily from CMIP5 downscaled climate datasets (CORDEX, LOCA, MACA, and JupiterWRF) considering: (1) all models and all emission scenarios evaluated for 2020-59 (CFquantiles_2040_to_historical_all_models_allRCPs.xlsx); (2) all models and all emission scenarios evaluated for 2050-89 (CFquantiles_2070_to_historical_all_models_allRCPs.xlsx); (3) all models and only the RCP4.5 and SSP2-4.5 emission scenarios for 2020-59 (CFquantiles_2040_to_historical_all_models_RCP4.5.xlsx); (4) all models and only the RCP4.5 and SSP2-4.5 emission scenarios for 2050-89 (CFquantiles_2070_to_historical_all_models_RCP4.5.xlsx); (5) all models and only the RCP8.5 and SSP5-8.5 emission scenarios for 2020-59 (CFquantiles_2040_to_historical_all_models_RCP8.5.xlsx); (6) all models and only the RCP8.5 and SSP5-8.5 emission scenarios for 2050-89 (CFquantiles_2070_to_historical_all_models_RCP8.5.xlsx); (7) best models and all emission scenarios evaluated for 2020-59 (CFquantiles_2040_to_historical_best_models_allRCPs.xlsx); (8) best models and all emission scenarios evaluated for 2050-89 (CFquantiles_2070_to_historical_best_models_allRCPs.xlsx); (9) best models and only the RCP4.5 and SSP2-4.5 emission scenarios for 2020-59 (CFquantiles_2040_to_historical_best_models_RCP4.5.xlsx); (10) best models and only the RCP4.5 and SSP2-4.5 emission scenarios for 2050-89 (CFquantiles_2070_to_historical_best_models_RCP4.5.xlsx); (11) best models and only the RCP8.5 and SSP5-8.5 emission scenarios for 2020-59 (CFquantiles_2040_to_historical_best_models_RCP8.5.xlsx); and (12) best models and only the RCP8.5 and SSP5-8.5 emission scenarios for 2050-89 (CFquantiles_2070_to_historical_best_models_RCP8.5.xlsx). Twenty tables contain quantiles of change factors at 242 NOAA Atlas 14 stations in Florida derived from CMIP6 downscaled climate datasets (NASA and LOCA2) considering: (1) all models and all emission scenarios evaluated for 2020-59 (CFquantiles_2040_to_historical_all_models_allSSPs_CMIP6.xlsx); (2) all models and all emission scenarios evaluated for 2050-89 (CFquantiles_2070_to_historical_all_models_allSSPs_CMIP6.xlsx); (3) all models and only the SSP1-2.6 emission scenario for 2020-59 (CFquantiles_2040_to_historical_all_models_SSP1-2.6_CMIP6.xlsx); (4) all models and only the SSP1-2.6 emission scenario for 2050-89 (CFquantiles_2070_to_historical_all_models_SSP1-2.6_CMIP6.xlsx); (5) all models and only the SSP2-4.5 emission scenario for 2020-59 (CFquantiles_2040_to_historical_all_models_SSP2-4.5_CMIP6.xlsx); (6) all models and only the SSP2-4.5 emission scenario for 2050-89 (CFquantiles_2070_to_historical_all_models_SSP2-4.5_CMIP6.xlsx); (7) all models and only the SSP3-7.0 emission scenario for 2020-59 (CFquantiles_2040_to_historical_all_models_SSP3-7.0_CMIP6.xlsx); (8) all models and only the SSP3-7.0 emission scenario for 2050-89 (CFquantiles_2070_to_historical_all_models_SSP3-7.0_CMIP6.xlsx); (9) all models and only the SSP5-8.5 emission scenarios for 2020-59 (CFquantiles_2040_to_historical_all_models_SSP5-8.5_CMIP6.xlsx); (10) all models and only the SSP5-8.5 emission scenario for 2050-89 (CFquantiles_2070_to_historical_all_models_SSP5-8.5_CMIP6.xlsx); (11) best models and all emission scenarios evaluated for 2020-59 (CFquantiles_2040_to_historical_best_models_allSSPs_CMIP6.xlsx); (12) best models and all emission scenarios evaluated for 2050-89 (CFquantiles_2070_to_historical_best_models_allSSPs_CMIP6.xlsx); (13) best models and only the SSP1-2.6 emission scenario for 2020-59 (CFquantiles_2040_to_historical_best_models_SSP1-2.6_CMIP6.xlsx); (14) best models and only the SSP1-2.6 emission scenario for 2050-89 (CFquantiles_2070_to_historical_best_models_SSP1-2.6_CMIP6.xlsx); (15) best models and only the SSP2-4.5 emission scenario for 2020-59 (CFquantiles_2040_to_historical_best_models_SSP2-4.5_CMIP6.xlsx); (16) best models and only the SSP2-4.5 emission scenario for 2050-89 (CFquantiles_2070_to_historical_best_models_SSP2-4.5_CMIP6.xlsx); (17) best models and only the SSP3-7.0 emission scenario for 2020-59

This dataset provides the components of change involved in the calculation of the population projections for local authorities in Wales. Data cover the change between each successive projection year and relate to the change from the middle of each year to the middle of the following year. The first year's data represent the change from the base year of mid-2018 to mid-2019, through the projection period to show the change for mid-2042 to mid-2043. This is the fifth set of population projections published for the 22 local authorities in Wales. Note that the projections become increasingly uncertain the further we try to look into the future.

“Ensemble” temperature and precipitation data are derived from multiple global circulation models (GCMs). The ensemble data depict the range (10th percentile, median and 90th percentile) of model outputs run under each of two scenarios, A2 and B1, for four future time periods. The first listed download contains data aggregated to the country level; the remaining downloads are gridded data in shapefile format.

Duplicate the Projection.prj file and rename the duplicate to the same name as the ASCII grid, e.g. MAT.asc and MAT.prj. When MAT.asc is imported to ESRI ArcGIS or QGIS, the GIS systems will automatically pick-up the correct grid projection.

This dataset includes processed climate change datasets related to climatology, hydrology, and water operations. The climatological data provided are change factors for precipitation and reference evapotranspiration gridded over the entire State. The hydrological data provided are projected stream inflows for major streams in the Central Valley, and streamflow change factors for areas outside of the Central Valley and smaller ungaged watersheds within the Central Valley. The water operations data provided are Central Valley reservoir outflows, diversions, and State Water Project (SWP) and Central Valley Project (CVP) water deliveries and select streamflow data. Most of the Central Valley inflows and all of the water operations data were simulated using the CalSim II model and produced for all projections.

These data were originally developed for the California Water Commission’s Water Storage Investment Program (WSIP). The WSIP data used as the basis for these climate change resources along with the technical reference document are located here: https://data.cnra.ca.gov/dataset/climate-change-projections-wsip-2030-2070. Additional processing steps were performed to improve user experience, ease of use for GSP development, and for Sustainable Groundwater Management Act (SGMA) implementation. Furthermore, the data, tools, and guidance may be useful for purposes other than sustainable groundwater management under SGMA.

Data are provided for projected climate conditions centered around 2030 and 2070. The climate projections are provided for these two future climate periods, and include one scenario for 2030 and three scenarios for 2070: a 2030 central tendency, a 2070 central tendency, and two 2070 extreme scenarios (i.e., one drier with extreme warming and one wetter with moderate warming). The climate scenario development process represents a climate period analysis where historical interannual variability from January 1915 through December 2011 is preserved while the magnitude of events may be increased or decreased based on projected changes in precipitation and air temperature from general circulation models.

2070 Extreme Scenarios Update, September 2020

DWR has collaborated with Lawrence Berkeley National Laboratory to improve the quality of the 2070 extreme scenarios. The 2070 extreme scenario update utilizes an improved climate period analysis method known as "quantile delta mapping" to better capture the GCM-projected change in temperature and precipitation. A technical note on the background and results of this process is provided here: https://data.cnra.ca.gov/dataset/extreme-climate-change-scenarios-for-water-supply-planning/resource/f2e1c61a-4946-4863-825f-e6d516b433ed.

Note: the original version of the 2070 extreme scenarios can be accessed in the archive posted here: https://data.cnra.ca.gov/dataset/sgma-climate-change-resources/resource/51b6ee27-4f78-4226-8429-86c3a85046f4

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of projected change in mean temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in mean temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

United States FOMC Projection: Change in Real GDP: Range: Y3: Upper End data was reported at 2.500 % in Dec 2024. This stayed constant from the previous number of 2.500 % for Sep 2024. United States FOMC Projection: Change in Real GDP: Range: Y3: Upper End data is updated quarterly, averaging 2.400 % from Sep 2015 (Median) to Dec 2024, with 21 observations. The data reached an all-time high of 4.000 % in Sep 2020 and a record low of 2.000 % in Sep 2017. United States FOMC Projection: Change in Real GDP: Range: Y3: Upper End data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.A026: NIPA 2023: GDP by Expenditure: Constant Price: saar: QoQ: Projection: Federal Reserve Board.

New employment concentration projection (for 2000 to 2040) overlaid onto the total employment projections (2040) from the Going Places 2040 Concentrated Development Vision.The 2040 Concentrated Development Vision was developed during phase 3 of the Going Places Land Use Planning Initiative (http://www.mvrpc.org/land-use/vision).

Seasonal and annual multi-model ensembles of projected relative change (also known as anomalies) in mean precipitation based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected relative change in mean precipitation is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of mean precipitation change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in mean precipitation (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

These data sets contain the sea level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. The dataset groups contain the full set of samples for the global projections (see IPCC AR6 WGI Sea Level Projections global) as well as summary relative sea level projections (see IPCC AR6 WGI Sea Level Projections regional and, without the AR6 estimate of background sea level process rates, see IPCC AR6 WGI Sea Level Projections regional novlm). The confidence output files correspond most directly to the figures and tables in the report. The IPCC AR6 sea level change projection files are provided in a simplified format but represent a more complicated workflow involving combinations of multiple lines of evidence for the various individual contributors to sea level change. It's highly recommended using the data as provided in the confidence output files to remain consistent with the assessment in IPCC AR6 Chapter 9 (see IPCC AR6 WGI Sea Level Projections HowTos for details).

Required Acknowledgements and Citation: In order to document the impact of these sea level rise projections, users of the data are obligated to cite chapter 9 of WGI contribution to the IPCC AR6, the FACTS model description paper, and the version of the data set used. When using these data in a publication, please include the information provided in IPCC AR6 WGI Sea Level Projections Acknowledgments.

Disclaimer: The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in surface wind speed based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in wind speed is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of wind speed change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in wind speed (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

As part of this national strategy, the Ministry of Education, Culture, Sports, Science and Technology (MEXT) had launched a 5-year (FY2007 - 2011) initiative called the Innovative Program of Climate Change Projection for the 21st Century (KAKUSHIN Program), using the Earth Simulator (ES) to address emerging research challenges, such as those derived from the outcomes of the MEXT's Kyosei Project (FY2002 - 2006), that had made substantial contributions to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The KAKUSHIN Program was expected to further contribute to the Fifth Assessment Report (AR5).

The research items include the advancement and forecasting of global warming models, the quantification and reduction of model uncertainty, and the evaluation of the impacts of natural disasters based on forecast information. Much of the data submitted to CMIP5 from Japan were generated under this KAKUSHIN program using the global climate models and the Earth system models developed in Japan. This dataset is the result of using the Global Climate Model MIROC4h.

All CMIP5 data are collected, managed, and published by the Earth System Grid Federation (ESGF), and DIAS serves as an ESGF node. All public datasets, including this dataset, are available from ESGF. For information on how to use these datasets, including this dataset, see "CMIP5 Data - Getting Started" (URL is available in the online information below). Please note that an ESGF account is required to download the CMIP5 data.

Because the terms of use for CMIP5 data are different from CMIP6 in many respects, please check the following Terms of Use carefully: https://pcmdi.llnl.gov/mips/cmip5/terms-of-use.html Currently, all CMIP5 data, including this dataset, is classified as "unrestricted" within it.

Projections over the TP from different RCMs

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in snow depth based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in snow depth is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of snow depth change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in snow depth (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Climate change projection for Japan using a non-hydrostatic regional climate model under IPCC A1B emission scenario

To aid applicants with quantification and monetization of benefits of proposed water storage projects per Chapter 8 of Proposition 1 (Water Code section 79750 et. seq.), the California Water Commission (Commission) developed a Technical Reference which was released in August 2016. These data and model products are companion information to the Technical Reference and were developed to assist applicants for funding under the Water Storage Investment Program (WSIP). The WSIP required applicants for public funding to analyze their proposed projects using climate and sea level conditions for California projected at years 2030 and 2070. The data and model products were developed for the following climate and sea level conditions: Without-Project 2030 Future Conditions – Year 2030 future condition with projected climate and sea level conditions for a thirty-year period centered at 2030 (climate period 2016-2045) Without-Project 2070 Future Conditions – Year 2070 future condition with projected climate and sea level conditions for a thirty-year period centered at 2070 (climate period 2056-2085) 1995 Historical Temperature-detrended Conditions (reference) – Year 1995 historical condition with climate and sea level conditions for a thirty-year period centered at 1995 (reference climate period 1981-2010)   California Water Commission The California Water Commission consists of nine members appointed by the Governor and confirmed by the State Senate. Seven members are chosen for their expertise related to the control, storage, and beneficial use of water and two are chosen for their knowledge of the environment. The Commission provides a public forum for discussing water issues, advises the Director of the Department of Water Resources on matters within the Department’s jurisdiction, approves rules and regulations, and monitors and reports on the construction and operation of the State Water Project. Proposition 1: The Water Quality, Supply, and Infrastructure Improvement Act approved by voters in 2014, gave the Commission new responsibilities regarding the distribution of public funds set aside for the public benefits of water storage projects, and developing regulations for the quantification and management of those benefits. In 2018, the Commission approved maximum conditional funding amounts for eight projects in the Water Storage Investment Program.

TRCA Climate Change Projections under RCP8.5 and RCP4.5 (1971-2100)

These datasets represent future climate change projections for TRCA. The summary information can be used by various audiences to better understand the climate trends expected to be seen within TRCA by the end of the century. It is also anticipated that the data will be used to inform various adaptation initiatives across the TRCA jurisdiction.

"For the RCP8.5 tabs and the TRCA Baseline tab, Column A represents the climate parameters. Columns C-R represent the individual climate models. Column S is the overall ensemble average of all the climate models. Columns T and U represent the 10th and 90th Percentiles respectively.

This repository contains the data and results from the paper Estimating future heat-related and cold-related mortality under climate change, demographic and adaptation scenarios in 854 European cities published in Nature Medicine (https://doi.org/10.1038/s41591-024-03452-2).

It provides projections of excess death rates and burden for the period 2015-2099 for five age groups in 854 cities across 30 countries, under three Shared Socioeconomic Pathway (SSP) scenarios, and four adaptation scenarios. The results include point estimates for five-year periods and four global warming levels, along with 95% empirical confidence intervals.

The fully reproducible analysis code using the data and producing the results included in this repository is provided in GitHub. The results can be visualised and explored in a dedicated Shiny app.

Content

This repository contains three zip files, each with an internal codebook:

• data.zip: contains the input data necessary to run the analysis. It includes historical and projected daily temperature at the city level, age-group specific projections of population and survival rates at the country level, and exposure-response functions extracted from another Zenodo repository (https://doi.org/10.5281/zenodo.10288665). This file also include a script showing how each dataset was extracted for the purpose of this projection study.
• results_csv.zip: contains the full results from the health impact projections. It includes one file for each combination of geographical level (city, country, region or European wide) and scale of reporting (five year periods or global warming levels).
• results_parquet.zip: contains the same information as the results_csv.zip but in a parquet format. This allows for more efficient storage and data reading.

It is recommended to only download results_csv.zip for a quick exploration of the results, or only results_parquet.zip when the results are to be loaded into a software for deeper analysis.