This dataset contains a 30-year rolling average of annual average minimum and maximum temperatures from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099.The year identified is the mid-point of the 30-year average. eg. The year 2050 includes the values from 2036 to 2065.

The downscaling and selection of models for inclusion in ten and four model ensembles is described in 'https://www.energy.ca.gov/sites/default/files/2019-11/Projections_CCCA4-CEC-2018-006_ADA.pdf#page=11' rel='nofollow ugc'>Pierce et al. 2018, but summarized here. Thirty two global climate models (GCMs) were identified to meet the modeling requirements. From those, ten that closely simulate California’s climate were selected for additional analysis ('https://www.energy.ca.gov/sites/default/files/2019-11/Projections_CCCA4-CEC-2018-006_ADA.pdf#page=11' rel='nofollow ugc'>Table 1, Pierce et al. 2018) and to form a ten model ensemble. From the ten model ensemble, four models, forming a four model ensemble, were identified to provide coverage of the range of potential climate outcomes in California. The models in the four model ensemble and their general climate projection for California are:

• HadGEM2-ES (warm/dry),
• CanESM2 (average),
• CNRM-CM5 (cooler/wetter),
• and MIROC5 the model least like the others to improve coverage of the range of outcomes.

These data were downloaded from Cal-Adapt and prepared for use within CA Nature by California Natural Resource Agency and ESRI staff.

Cal-Adapt. (2018). LOCA Derived Data [GeoTIFF]. Data derived from LOCA Downscaled CMIP5 Climate Projections. Cal-Adapt website developed by University of California at Berkeley’s Geospatial Innovation Facility under contract with the California Energy Commission. Retrieved from https://cal-adapt.org/

Pierce, D. W., J. F. Kalansky, and D. R. Cayan, (Scripps Institution of Oceanography). 2018. Climate, Drought, and Sea Level Rise Scenarios for the Fourth California Climate Assessment. California’s Fourth Climate Change Assessment, California Energy Commission. Publication Number: CNRA-CEC-2018-006.

Wildfire projections for California and her environs in support of California's Fifth Climate Assessment supported with historical weather observations and renewable energy capacity profiles for grid operations.

The regional flooding and shoreline overtopping analysis maps provided in the ART Bay Shoreline Flood Explorer website capture permanent and temporary flooding impacts from sea level rise scenarios from 0- to 108-inches above MHHW (mean higher high water) and storm surge events from the 1-year to the 100-year storm surge. The process used to develop the maps included discussions with key stakeholders in each county, who reviewed the preliminary maps and provided on-the-ground verification and supplemental data to improve the accuracy of the maps. The maps and information produced through this effort can inform adaptation planning, assist in managing climate change risks, and help identify trigger points for implementing adaptation strategies to address sea level rise and flooding hazards, at both local and regional scales.

The Flood Explorer maps were produced using the latest LiDAR topographic data sets, water level outputs from the FEMA San Francisco Bay Area Coastal Study (which relied in hydrodynamic modeling using MIKE21) and the San Francisco Tidal Datums Study. The 2010/2011 LIDAR applied (collected by USGS and NOAA at a 1-m resolution) was further refined through the stakeholder review process and integration of additional elevation data where available. The Flood Explorer also includes the regional shoreline delineation developed by the San Francisco Estuary Institute to represent coastal flooding and overtopping throughout the Bay Area. In sum, the maps include: 1) Flooding at ten total water levels that capture over 90 combinations of future sea level rise and storm surge scenarios; 2) Shoreline overtopping maps for all ten total water levels that depict where the Bay may overtop the shoreline and its depth of overtopping at that specific location. Coupled with the flood maps, the overtopping data can help identify vulnerable shoreline locations and their respective flow paths that could lead to inland flooding, and; 3) Hydraulically disconnected low-lying areas that represent areas that may be vulnerable to flooding due to their low elevation. These areas are not directly within flooding locations, but could be connected to flood waters through culverts and storm drains that are not captured in this analysis.