All plots are made to order from raw daily inputs with subsequent calculations. Please be patient.
New indicies are also slowly being added.
This display shows a various climate metrics by US State Climate Divisions. The indicies include those developed for Expert Team on Climate Change Detection and Indices (ETCCDI) (), and Environment and Climate Change Canada (ECCC).
Climate Indicies were Calculated with the xclim Python package developed by Bourgault et al., 2023.
The data is derived from climate simulations from the CMIP6 Climate Model Ensembles and are a collection of the best simulations from each center's model participating in CMIP6.
The output from these models were 'downscaled' from the global to regional scale using the Localized Constructed Analog Method (LOCA) by Pierce et al. (2023).
The results for the downscaling have been averaged over State Climate Divisions chosen by the user.
The user may select a variable from the pulldown menus, and also select a future 30-year period by which to view the monthly trends and compare them to a fixed historical period (1981-2010).
For both the annual and monthly plots, the solid lines represent the ensemble means, while the shading represents the middle 50% range of the collected ensembles.
Pierce, D.W., D.R. Cayan, D.R. Feldman, and M.D. Risser, 2023: Future increases in North American extreme precipitation in CMIP6 downscaled with LOCA, Journal of Hydrometeorology, 24(5), 951-975, doi:10.1175/JHM-D-22-0194.1.
Bourgault, P., et al. 2023: Xclim: Xarray-based climate data analytics, Journal of Open Source Software, 8(85), 5415, doi:10.21105/joss.05415.