The NA-CORDEX dataset contains regional climate change scenario data and guidance for North America, for use in impacts, decision-making, and climate science. The NA-CORDEX data archive contains output from regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950–2100 with a spatial resolution of 0.22°/25km or 0.44°/50km. This AWS S3 version of the data includes selected variables converted to Zarr format from the original NetCDF. Only daily data are currently available; all daily data were mapped to the Gregorian calendar. Sub-daily data may be added later. Both raw and bias-corrected data are available. Further details about this version of the dataset are available at the documentation link below.

The NA-CORDEX data archive contains output from 7 regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from different global climate model (GCM) simulations in the CMIP5 archive and ERA-Interim reanalysis. These simulations run from 1950-2100 with a spatial resolution of 0.22 degrees (25km) or 0.44 degrees (50km). Data is available for impacts-relevant variables at daily and longer frequencies in CF-compliant netCDF format.

The NA-CORDEX dataset contains output from high-resolution regional climate models run over North America using boundary conditions from global simulations in the CMIP5 archive. The subset of the NA-CORDEX data on AWS (data volume ~15 TB) includes daily data from 1950-2100 for impacts-relevant variables on a 0.25 degree or 0.50 degree common lat-lon grid. This data is freely available on AWS S3 thanks to the AWS Open Data Sponsorship Program and the Amazon Sustainability Data Initiative, which provide free storage and egress. The data on AWS is stored in Zarr format. This format supports the same data model as netCDF and is well suited to object storage and distributed computing in the cloud using the Pangeo libraries in Python. An Intake-ESM Catalog listing all available data can be found at: [https://ncar-na-cordex.s3-us-west-2.amazonaws.com/catalogs/aws-na-cordex.json] The full dataset (data volume ~35 TB) can be accessed for download or via web services on the NCAR Climate Data Gateway. [https://www.earthsystemgrid.org/search/cordexsearch.html]

This resource includes the 25-year return level extreme maps of 4-km gridded snow water equivalent (SWE) and 7-day snowmelt and runoff potential (RP) and over North America. The maps are developed by using 25-km gridded historical and future simulation data sets from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) under the Representative Concentration Pathway [RCP] 8.5. For full details, please see Cho et al. (2021) in Geophysical Research Letters.

Map Metadata (+proj=longlat +ellps=WGS84 +towgs84=0,0,0,-0,-0,-0,0 +no_defs) SWE maps (unit: mm) 7-day snowmelt maps (unit: mm/7-day) 7-day runoff potential maps (unit: mm/7-day)

Preferred citation: Cho, E., McCrary R. R., and Jacobs, J. M. (2021). Future Changes in Snowpack, Snowmelt, and Runoff Potential Extremes over North America. Geophysical Research Letters

Corresponding author: Eunsang Cho (eunsang.cho@nasa.gov; escho@umd.edu)

The North America CORDEX (NA-CORDEX) dataset contains regional climate change scenario data and guide for North America, for use in impacts, decision-making, and climate science. This dataset contains output from regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950 to 2100 with a spatial resolution of 0.22 degree (25km) or 0.44 degree (50km). This version of the data is the same as the AWS S3 version. It includes selected variables converted to the Zarr format from the original NetCDF. Only daily data are currently available; all daily data were mapped to the standard calendar.

This dataset contains derived data and model data necessary for reproducing the results found in "SSP-Based Land Use Change Scenarios: A Critical Uncertainty in Future Regional Climate Change Projections" by Melissa S. Bukovsky, Jing Gao, Linda O. Mearns, and Brian C. O'Neill. This dataset contains data not otherwise available in other public archives, as noted in Bukovsky et al. (2021, Earth's Future; preprint available at https://doi.org/10.1002/essoar.10504141.2). That is, this dataset contains data from the land-use change simulations that are not part of NA-CORDEX (na-cordex.org), but which are complementary to those published in the NA-CORDEX archive.

2000+ color maps of seasonal and annual temperature and precipitation climatology and change for regional climate simulations over North America in the NA-CORDEX Data Archive.

The North America CORDEX (NA-CORDEX) dataset contains regional climate change scenario data and guide for North America, for use in impacts, decision-making, and climate science. This dataset contains output from ... regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950 to 2100 with a spatial resolution of 0.22 degree (25km) or 0.44 degree (50km). This version of the data is the same as the AWS S3 version. It includes selected variables converted to the Zarr format from the original NetCDF. Only daily data are currently available; all daily data were mapped to the standard calendar.

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

This dataset contains change factors for the 2- to 100-year daily (24-hour) extreme rainfall storms for the Continental United States from publicly available downscaled climate projections, namely BCCAv.2, LOCA, MACA and NA-CORDEX data sets. Change factors were estimated as the ratio between the historical (period between1950-2005) climate simulations of extreme rainfall and the future (period between 2044-2099) climate simulations of rainfall depths corresponding to the average recurrence interval (e.g. 2-, 5-year). These change factors were computed using the Generalized Extreme Value Distribution, which is widely used to describe rainfall extremes.This data archive was prepared as part of the outputs of the published article Lopez‐Cantu, T., Prein, A. F., & Samaras, C. (2020). Uncertainties in Future U.S. Extreme Precipitation from Downscaled Climate Projections. Geophysical Research Letters. https://doi.org/10.1029/2019GL086797. When using the data in this archive, citation must be given to the original article.

The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.

The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation.

The directory structure of the data is as follows
[cmip_version]/[scenario]/[climate_model]/[ensemble_member]/
The realizations are as follows
prcp_[realization_number][year].nc temp[realization_number][year].nc
The time mean files averaged over certain year bounds are as follows
prcp_mean[year_bound_1][year_bound_2].nc temp_mean[year_bound_1][year_bound_2].nc
The time-mean Cumulative Distribution Function (CDF) files are as follows
prcp_cdf[year_bound_1][year_bound_2].nc temp_cdf[year_bound_1][year_bound_2].nc
The CDF of the annual maximum precipitation is given for each year in the record prcp_annual_max_cdf[start_year_of_scenario]_[end_year_of_scenario].nc

This dataset comprises a collection of modified secondary datasets that were used to construct the Weather and Climate Profiles for the FloodWise Communities project. The nature and source for each dataset is summarized below.

1. "Climate Trend Graph Data". Contains annual average temperature and rainfall for various regions of the Gulf Coast, regions defined by the Southern Climate Impacts Planning Program. Comma Separated (csv) temperature and precipitation data were downloaded for each region from 1895-2021, though only data values from 1950-2020 were used for the Weather and Climate Profiles. These data were used to create versions of SCIPP's Climate Trend Graphs that were bespoke to these Profiles, so that contrasts between regional and city/county-level climate trends in each Profile could be drawn.

2a. "Observations and Projections". Contains annually and seasonally averaged temperature and rainfall metrics for each recruited city/county for the FloodWise Communities project, as available through the South Central Applied Climate Information System (SC-ACIS). Observations from 1991 to 2020 of various temperature and precipitation metrics were extracted, in order to compute an historical average climate state, and an historical average climate change, for each recruited city/county. These data were prepared in csv format.

2b. "Observations and Projections". Contains annually and seasonally averaged temperature and rainfall metrics obtained from an ensemble of the GCM-RCMs that contributed to the North American CORDEX (NA-CORDEX) project. These climate model data were averaged over a Mid-Century (2041-2070) and an End-Century (2071-2100) period, in order to produce a range of projected changes in temperature and precipitation for each recruited city/county. The grid points from the NA-CORDEX's regular grid that were nearest to each recruited city/county were used to compute the same metrics as those using the SC-ACIS data, and saved to the same respective csv files. Each csv file was used to produce a table of historical and projected changes in temperature and precipitation, for inclusion in each recruited city/county's Weather and Climate Profile.

1. "FloodFactor Maps". Contains maps of categorical flood risk for each city/county recruited for the FloodWise Communities project, as produced by First Street Foundation. Permission was given by First Street Foundation to use and modify outputs from their FloodFactor product for the purpose of this project. FloodFactor maps for each recruited city/county were modified by circling properties at particular risk of being flooded, in order to draw the readers' attention to these properties.

2. "Sea Level Rise Maps". Contains maps of flooded land areas resulting from a potential 10 feet of sea level rise, as available in NOAA's Sea Level Rise Viewer. These maps were modified by circling particular areas of cities/counties that would be badly affected by this much sea level rise (e.g., bridges, properties surrounding river deltas, urban centers), again to draw the readers' attention to them.

3. "Severe Weather Tables". Contains tables of severe weather events that affected each city/county between 1991 and 2020, drawn from event summaries available in NOAA NCEI's Storm Events Database. Each table contains five specific weather events (e.g., hurricanes, thunderstorms, floods) that had high financial impact, and/or caused many human casualties, within this 30-year period. These tables serve to contextualize the types of severe weather that each recruited city/county has the potential to experience for its respective Profile.

#Données of the 2022 Hydroclimatic Atlas ## #Description The Hydroclimatic Atlas describes the current and future water regime of southern Quebec in order to support the implementation of water management practices that are resilient to climate change. These data are from the most recent version of the Hydroclimatic Atlas. ## #Nouveautés * Improvement of the spatial resolution of the hydrographic network; * Greater spatial coverage; * Addition of the CliMEX and CORDEX-NA sets, in addition to the scenarios in the CMIP5 set; * Use of six hydrological platforms; * * Addition of indicators, especially annual ones. * Etc. ## #Liste data available * Link to the new Hydroclimatic Atlas website. * Map of the 24,604 river sections of the Hydroclimatic Atlas with their attributes, available in GeoJSON and shapefile format. To facilitate download and display, the map is divided into 11 GeoJSON files: ABIT (Abitibi and Lac Abitibi region), CND west (North Shore A and B regions), CND east (North Shore regions C, D and E), GASP (North Shore regions C, D and E), GASP (Gaspésie), MONT (Gaspesie), MONT (Montégérie), OUTM (Outaouais Upstream), OUTV (Outaouais Downstream), OUTV (Outaouais Downstream), SAGU (Saguenay), SLNO (St-Laurent Nord-Ouest), SLSO (St-Laurent Sud-Ouest), and VAUD (Vaudreuil). * The CSV tables (“Magnitude...”) for each of the 76 hydrological indicators describing the amplement, the direction and the dispersion for RCP 4.5 and RCP8.5, for the three future horizons (see the documentation for details). * The CSV tables (“Projected indicator...”) for each of the 76 hydrological indicators detailing the flow values with their uncertainty for the historical period and the three future horizons (RCP4.5 and 8.5). See the documentation for more details. * A PDF with the metadata and a more detailed description of the data. ## #Note The 2018 version data is archived on Data Quebec for reference, for example for old reports or analyses referring to this version of the data. Any new study or analysis should use the most recent data available below or on the Atlas website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Áirítear ar na sonraí athróga laethúla, míosúla agus séasúracha de thurgnaimh CORDEX arna scála síos ar ghreille ca. 50 km thar an Eoraip (acrainm: EUR-44) bunaithe ar shamhail aeráide réigiúnach ALARO-0. Tá athróg amháin i ngach comhad agus formáidítear é de réir phrótacal sonraí CORDEX — rud a chiallaíonn NetCDF-4 comhbhrúite, CF-1.4 comhlíontach, le tréithe agus ainmneacha comhaid de réir an DRS sonraithe. Is iad na turgnaimh a chuirtear ar fáil ná meastóireacht, stairiúil, rcp85, rcp45 agus rcp26 ag baint úsáide as sonraí a dhíorthaítear ón tsamhail CMIP5 CNRM-CM5. Na sonraí ar fáil ar an tsamhail ríomhaireachtúil (dúchasach) greille.

Os dados incluem variáveis diárias, mensais e sazonais das experiências CORDEX reduzidas para uma rede de cerca de 50 km na Europa (acrónimo: EUR-44) com base no modelo climático regional ALARO-0. Cada arquivo contém uma única variável e é formatado de acordo com o protocolo de dados CORDEX — ou seja, NetCDF-4 comprimido, CF-1.4 compatível, com atributos e nomes de arquivos de acordo com o DRS especificado. Os experimentos fornecidos são avaliação, histórico, rcp85, rcp45 e rcp26 usando dados de forçamento derivados do modelo CMIP5 CNRM-CM5. Os dados são fornecidos na grelha computacional (nativa) do modelo.

Données of the 2022 Hydroclimatic Atlas ## #Description The Hydroclimatic Atlas describes the current and future water regime of southern Quebec in order to support the implementation of water management practices that are resilient to climate change. These data are from the most recent version of the Hydroclimatic Atlas. ## #Nouveautés * Improvement of the spatial resolution of the hydrographic network; * Greater spatial coverage; * Addition of the CliMEX and CORDEX-NA sets, in addition to the scenarios in the CMIP5 set; * Use of six hydrological platforms; * Addition of indicators, especially annual ones. * Etc. ## #Liste data available * Link to the new Hydroclimatic Atlas website. * Map of the 24,604 river sections of the Hydroclimatic Atlas with their attributes, available in GeoJSON and shapefile format. To facilitate download and display, the map is divided into 11 GeoJSON files: ABIT (Abitibi and Lac Abitibi region), CND west (North Shore A and B regions), CND east (North Shore regions C, D and E), GASP (North Shore regions C, D and E), GASP (Gaspésie), MONT (Gaspesie), MONT (Montégérie), OUTM (Outaouais Upstream), OUTV (Outaouais Downstream), OUTV (Outaouais Downstream), SAGU (Saguenay), SLNO (St-Laurent Nord-Ouest), SLSO (St-Laurent Sud-Ouest), and VAUD (Vaudreuil). * The CSV tables (“Magnitude...”) for each of the 76 hydrological indicators describing the amplement, the direction and the dispersion for RCP 4.5 and RCP8.5, for the three future horizons (see the documentation for details). * The CSV tables (“Projected indicator...”) for each of the 76 hydrological indicators detailing the flow values with their uncertainty for the historical period and the three future horizons (RCP4.5 and 8.5). See the documentation for more details. * A PDF with the metadata and a more detailed description of the data. ## #Note The 2018 version data is archived on Data Quebec for reference, for example for old reports or analyses referring to this version of the data. Any new study or analysis should use the most recent data available below or on the Atlas website.This third party metadata element was translated using an automated translation tool (Amazon Translate).*