National Climate Change Viewer (NCCV)

June 22, 2021

What is the National Climate Change Viewer?

The USGS National Climate Change Viewer (NCCV) is a web application for visualizing climate projections from the Climate Model Intercomparison Program (CMIP) that have been statistically downscaled to high spatial resolution for the conterminous United States. The NCCV allows users to visualize projected changes in climate (maximum and minimum air temperature, precipitation) and the water balance (snow water equivalent, runoff, soil water storage, and evaporative deficit) for any state, county and USGS Hydrologic Units (HUC4 and HUC8) using a variety of graphics and tools. We provide monthly time series and averages for the historical period (1981-2010) and three future time periods (2025-2049, 2050-2074, and 2075-2099). The application also provides access to comprehensive summary reports in PDF format and CSV files for the climate and water balance variables for each geographic area.

We provide alternate versions of the application for CMIP6 (current generation) and CMIP5 (previous generation). We suggest using the most current CMIP6 version of the viewer unless you need legacy data. Downscaling methodologies and a user quick start slideshow are below.

NCCV States - CMIP6

NCCV Watersheds - CMIP6

NCCV States - CMIP5

NCCV Watersheds - CMIP5

Climate Projection Downscaling Methods

CMIP6-LOCA2

The Localized Constructed Analogs (LOCA) method is used to statistically downscale CMIP6 projections from 27 Global Climate Models (GCMs) to 6 km spatial resolution. The monthly data span the historical (1950-2014) and 21^st century (2015-2100) periods for three Shared Socioeconomic Pathways (SSPs) greenhouse gas (GHG) emission scenarios (SSP2-4.5, SSP3-7.0, and SSP5-8.5) developed for Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). This is one of the downscaled data sets that is being used to inform the Fifth National Climate Assessment (NCA5). The CMIP6-LOCA2 version of the application includes advancements in the treatment of the Multi-Model Mean, where we include model weighting based on skill, filtering based on Equilibrium Climate Sensitivity (ECS), and the use of Global Warming Levels (GWLs) where all models are averaged together when they reach a specified temperature (e.g., 2°C) above the average preindustrial temperature (see documentation for more details). Climate data files are found here and hydrology data files here.

CMIP5-MACAv2-METDATA

The Multivariate Adapted Constructed Analogs (MACA) is used to statistically downscale CMIP5 projections from 20 Global Climate Models (GCMs) to 4 km spatial resolution. The monthly data span the historical (1950-2005) and 21^st century (2006-2099) periods for two Representative Concentration Pathways (RCP) greenhouse gas (GHG) emission scenarios (RCP4.5, RCP8.5) developed for IPCC Fifth Assessment Report (AR5). Climate data files are found here and hydrology data files here.