This dataset contains a 30-year average of annual average minimum and maximum temperatures across all ten models and two greenhouse gas (RCP) scenarios in the ten model ensemble. Three named time periods are included “Historic Baseline (1961-1990)”, “Mid-Century (2035-2064)”, and “End of Century (2070-2099).” The downscaling and selection of models for inclusion in ten and four model ensembles is described in 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 (Table 1, Pierce et al. 2018) and to form a ten model ensemble. 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.

This dataset contains 30-year rolling average of annual average precipitation across all four models and two greenhouse gas (RCP) scenarios in the four model ensemble. The year identified for a 30 year rolling average 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.

This dataset contains annual average precipitation from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099. The downscaling and selection of models for inclusion in ten and four model ensembles is described in 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 (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.

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.

This dataset contains a 30-year rolling average of annual average precipitation 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.

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.

This dataset contains a 30-year average of annual average precipitation across all ten models and two greenhouse gas (RCP) scenarios in the ten model ensemble. Three named time periods are included “Historic Baseline (1961-1990)”, “Mid-Century (2035-2064)”, and “End of Century (2070-2099).”

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.

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.

This dataset contains 30-year rolling averages of annual average minimum and maximum temperatures across all four models and two greenhouse gas (RCP) scenarios in the four model ensemble. The year identified for a 30 year rolling average 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 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 (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 0 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.

🇺🇸 미국 English This dataset contains annual average precipitation from the four models and two greenhouse gas (RCP) scenarios included in the four model ensemble for the years 1950-2099. The downscaling and selection of models for inclusion in ten and four model ensembles is described in 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 (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.

There is a metadata spreadsheet that lists each data file by name, the source of the file, and explains the contents of the file.

California is doubling down on efforts to achieve carbon neutrality and build resilience to the impacts of climate change. While the impacts vary in different regions of California, every area of the state is already experiencing climate change impacts. The best available science tells us that impacts will continue into the future and will include increases in annual temperatures, changes to precipitation patterns such as longer and more intense droughts, increases in wildfire areas and severity, sea level rise, ocean warming, and the spread of invasive species. The Climate Explorer contains interactive viewers allowing users to explore predicted changes in temperature and precipitation, sea level rise and storm severity, and opportunities to implement nature-based solutions, which are actions that work with and enhance nature to help address societal challenges on California’s landscapes. The temperature and precipitation viewer provides access to a subset of the data developed for the 4th California Climate Assessment and made available through Cal-Adapt. The Sea Level Rise viewer includes data from the U.S. Geological Survey’s Coastal Storm Modeling System (CoSMoS), with more variables available for exploration at Our Coast, Our Future.

Climatic changes in California require farmers to develop adaptation strategies to sustain their production. Decision support is a key element of climate adaptation but requires a robust understanding of producer needs and priorities. One approach to sharing adaptation information and gathering stakeholder interests and needs is through workshops. This investigation was conducted among 78 technical service providers in a session on adaptation decision support during the 2023 California Adaptation Forum. We adopted a constructivist orientation to understand stakeholder interests and needs on decision support during a 30-minutes dialogue. Four questions were discussed, and participants recorded their responses on different colored sticky notes which were analyzed thematically. Five interrelated themes were uncovered relating to the lived experiences of service providers in making decisions including climate impacts, community engagement and equity, adaptation programs, resources, and cost-benefit analysis. In making those decisions, the most used information sources and tools were community and tribal knowledge, reports like climate assessment reports, and specialized data portals such as Cal-Adapt, CalEnviroScreen, and Healthy Places Index. Several interconnected themes emerged around stakeholder perceptions of gaps in existing decision support resources, the relevance of decision support, and what researchers should focus on. These themes underscore the importance of data translation, visualization, and community engagement to harness stakeholder lived experiences, dissemination, and training to improve data access. We conclude there is a need to engage technical service providers in extension programs on adaptation decision support, equip them with necessary tools such as curricula and resources that will help in advising.

This dataset contains 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 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.

Extreme heat data from Cal-Adapt. Includes baseline, mid-century, and late-century projections by 6km grid cell. IndicatorDescriptionExtreme Heat, Baseline95th percentile daily maximum temperature, 30-year average for 1976-2005Extreme Heat, RCP 4.5 Mid-Century95th percentile daily maximum temperature, 30-year average for 2036-2065Extreme Heat, RCP 8.5 Mid-Century95th percentile daily maximum temperature, 30-year average for 2036-2065Extreme Heat, RCP 4.5 Late-Century95th percentile daily maximum temperature, 30-year average for 2066-2095Extreme Heat, RCP 8.5 Late-Century95th percentile daily maximum temperature, 30-year average for 2066-2095Source: Cal-Adapt. Data: LOCA Downscaled CMIP5 Projections (Scripps Institution of Oceanography), Gridded Observed Meteorological Data (University of Colorado, Boulder).

Extreme precipitation data from Cal-Adapt. Includes baseline, mid-century, and late-century projections by 6km grid cell. IndicatorDescriptionExtreme Precipitation, Baseline95th percentile daily maximum precipitation, 30-year average for 1976-2005Extreme Precipitation, RCP 4.5 Mid-Century95th percentile daily maximum precipitation, 30-year average for 2036-2065Extreme Precipitation, RCP 8.5 Mid-Century95th percentile daily maximum precipitation, 30-year average for 2036-2065Extreme Precipitation, RCP 4.5 Late-Century95th percentile daily maximum precipitation, 30-year average for 2066-2095Extreme Precipitation, RCP 8.5 Late-Century95th percentile daily maximum precipitation, 30-year average for 2066-2095Source: Cal-Adapt. Data: LOCA Downscaled CMIP5 Projections (Scripps Institution of Oceanography), Gridded Observed Meteorological Data (University of Colorado, Boulder).

This spatial data identifies connectivity potential between natural lands in the present climate and natural lands with future analogous climate following topo-climatically diverse routes. Present-day land use, topographic diversity, and projections of shifting climate regimes were combined into a single connectivity modeling approach to identify pathways for mid-century shifts in species ranges. Climate linkages, or areas important for climate change-driven movement, were identified as the areas where the Omniscape model indicated more current flow than would be expected in the absence of climate considerations. The model was run for two different projections of future climate (CNRM_CM5 and HADGEM2-ES). Climate linkages from both models were overlaid with a strategic present-day connectivity framework to improve interpretation and to facilitate a more direct connection with conservation action.

This connectivity model is a structural, coarse filter approach that explicitly incorpora...

Extreme precipitation data from Cal-Adapt. Includes baseline, mid-century, and late-century projections by 6km grid cell. Indicator Description

Extreme Precipitation, Baseline 95th percentile daily maximum precipitation, 30-year average for 1976-2005

Extreme Precipitation, RCP 4.5 Mid-Century 95th percentile daily maximum precipitation, 30-year average for 2036-2065

Extreme Precipitation, RCP 8.5 Mid-Century 95th percentile daily maximum precipitation, 30-year average for 2036-2065

Extreme Precipitation, RCP 4.5 Late-Century 95th percentile daily maximum precipitation, 30-year average for 2066-2095

Extreme Precipitation, RCP 8.5 Late-Century 95th percentile daily maximum precipitation, 30-year average for 2066-2095 Source: Cal-Adapt. Data: LOCA Downscaled CMIP5 Projections (Scripps Institution of Oceanography), Gridded Observed Meteorological Data (University of Colorado, Boulder).

As communities everywhere experience accelerating climate change impacts, local governments must proactively plan and implement adaptation or resilience strategies. A significant challenge is effectively scaling up these efforts in diverse communities. In 2015, the State of California passed Senate Bill 379 (SB379), requiring climate change adaptation and resilience strategies in local plans, making it the first U.S. state to broadly mandate such requirements locally. Our study measured the effects of SB379 on the quality of local plans that address climate change adaptation or resilience and assessed which types of plans jurisdictions selected to meet the requirements. Using a longitudinal study, we analyzed plan quality before and after SB379 took effect using criteria developed for earlier studies of voluntary climate adaptation plans. We found that California plans have significantly improved when assessed against theoretical criteria, and most jurisdictions have chosen their local hazard mitigation plans to meet the requirements. The flexible and cooperative design of the mandate and its loose enforcement suggest local jurisdictions are willing to address climate change, even when challenged with more stringent requirements if incentives align. As a natural policy experiment, California’s experience offers a unique opportunity to examine the effects of a state planning mandate and the choices local jurisdictions make to comply. Cooperative mandates that require local governments to address climate change adaptation and resilience in their plans but offer flexibility in how they do so may improve the quality of plans. Practitioners should seek to leverage flexibility in such mandates to the advantage of their local communities.

Extreme heat data from Cal-Adapt. Includes baseline, mid-century, and late-century projections by 6km grid cell. Indicator Description

Extreme Heat, Baseline 95th percentile daily maximum temperature, 30-year average for 1976-2005

Extreme Heat, RCP 4.5 Mid-Century 95th percentile daily maximum temperature, 30-year average for 2036-2065

Extreme Heat, RCP 8.5 Mid-Century 95th percentile daily maximum temperature, 30-year average for 2036-2065

Extreme Heat, RCP 4.5 Late-Century 95th percentile daily maximum temperature, 30-year average for 2066-2095

Extreme Heat, RCP 8.5 Late-Century 95th percentile daily maximum temperature, 30-year average for 2066-2095 Source: Cal-Adapt. Data: LOCA Downscaled CMIP5 Projections (Scripps Institution of Oceanography), Gridded Observed Meteorological Data (University of Colorado, Boulder).