Analytics Engine Data Catalog

The following tables show a list of all raw projections data available on the Analytics Engine. This includes future climate projections and historical climate downscaled from Global Climate Models (GCMs) and a historical reconstruction (reanalysis data based on modeling and empirical weather observations).

Note: The different datasets are very nuanced, and they are not interchangeable. Please review our upcoming Guidance documentation to understand the available data in full.

Data Selection

The data available on the Analytics Engine were identified and selected through a rigorous skill evaluation process based on the parent GCM’s ability to capture several critical aspects of California climate characteristics. These models were then downscaled via different complex techniques for California. More details on the GCM selection process are available here.

Global Climate Models

Various CMIP6 GCMs are available, each of which may be used to explore possible future climate projections with built-in assumptions, methodologies, and limitations. We recommend, where possible, using as many GCMs in your workflows in order to capture the full range of possibilities.

Downscaling Methods

Downscaled data is available via two methods

• Downscaled by UCLA using a dynamical method with the Weather Research and Forecasting model (WRF)
• Downscaled by Scripps Institution of Oceanography using a hybrid-statistical downscaling method, Localized Constructed Analogs version 2 (LOCA2)

Spatial Resolution

• 45-km (WRF only)
• 9-km - Western Electricity Coordinating Council (WECC) region (WRF only)
• 3-km - California (CA) resolution (WRF and LOCA2)

Of particular note is the nuance that the 3km data is not “just” a narrowing of projections data but a qualitatively more accurate representation of the data than the 45km.

Shared Scenario Pathways

Various Shared Scenario Pathways (SSPs) representing global emissions trajectories from intermediate to higher trajectories are available on the Analytics Engine for the LOCA2 data. SSP2-4.5, SSP3-7.0, and SSP5-8.5 each represent a combination of narratives (2, 3, and 5) and Representative Concentration Pathways (RCP) (4.5, 7.0, and 8.5). For example, SSP2-4.5 utilizes the SSP 2 narrative and RCP 4.5. All the WRF runs use SSP3-7.0.

Details of Available Data

Data Foundation

This table demonstrates the underlying data created by our colleagues at Scripps Institution of Oceanography and UCLA, highlighting the method of downscaling, model availability, and bias correction:

Downscaled Data

The following table showcases data available within Analytics Engine products, including, but not limited to, the Data Catalog and accessible via JupyterHub notebooks.

Hybrid-Statistical Downscaled Data: LOCA2

This downscaling method created data for 15 GCMs with a total of 199 ensemble runs.

The following table shows the LOCA2 data constituents available by variable:

• Per SSP there are two counts
  • GCM is the count of GCMs that were downscaled that have that variable in at least one ensemble run
  • Ensembles is the count of ensemble runs that contain that variable
• All LOCA2 data is downscaled at a native daily resolution. A pre-aggregated version of the LOCA2 data at monthly resolution is also available on the Analytics Engine.

Dynamical Downscaled Data: WRF

This downscaling method created data for 8 GCMs with 1 ensemble run in each emissions scenario.

The following table shows the WRF data simulations available:

• There are two kinds of WRF simulations
  • Projections Simulations is the count of GCMs that were downscaled per emissions scenario and spatial resolution
  • Reanalysis Simulations is a downscaled ensemble run of the ERA5 reanalysis dataset providing an observationally constrained historical reconstruction
• All WRF data is downscaled at a native hourly resolution.

* The Analytics Engine also provides a pre-aggregated version of the WRF data at daily (noted by asterisk) and monthly resolutions for four of the WRF simulations.
** Additional simulations from 1 model (CESM2) for SSP2-4.5 and SSP5-8.5 at 9 km spatial resolution are also available on the Analytics Engine. These simulations are a part of the larger suite of dynamically downscaled GCMs by UCLA, of which the CEC-supported simulations are a subset. More information is available here.

Current Analytics Engine Data Catalog

Datasets available to download and analyze through Cal-Adapt: Analytics Engine

The following table provides information on all available datasets to download and analyze through the Cal-Adapt: Analytics Engine in a searchable format. Each downscaled model is provided and is listed by its "source" GCM, experiment or emissions scenario, variant (the individual ensemble set-up), temporal frequency, and spatial resolution for each variable. Click the magnifying glass icon to begin custom searching of data.