Projects
Climate Data Guide
The Climate Data Guide enables researchers and students to identify and make effective use of climate data sets by providing a focal point for expert-user guidance, commentary, and questions on the strengths and limitations of selected observational datasets and their applicability to model evaluations.
Climate Variability Diagnostics Package (CVDP)
The Climate Variability Diagnostics Package (CVDP) is a metrics package that documents the major modes of climate variability in models and observations, including ENSO, Pacific Decadal Oscillation, Atlantic Multi-decadal Oscillation, Northern and Southern Annular Modes, North Atlantic Oscillation, Pacific North and South American teleconnection patterns. Time series, spatial patterns and power spectra are displayed graphically via webpages and saved as NetCDF files for later use. Documentation is provided for all calculations. The CVDP can be run on any set of model simulations from any modeling center (as long as the files meet CMIP5 or CMIP6 output metadata requirements), allowing inter-model comparisons..
Climate Variability Diagnostics Package for Large Ensembles (CVDP-LE)
The Climate Variability Diagnostics Package for Large Ensembles (CVDP-LE) developed by NCAR's Climate Analysis Section is an automated analysis tool and data repository for exploring internal and forced contributions to climate variability and change in coupled model “initial-condition” Large Ensembles and observations. The package computes a wide range of modes of interannual-to-multidecadal variability in the atmosphere, ocean and cryosphere, as well as long-term trends and key indices of global and regional climate....
Coupled Model Intercomparison Project (CMIP)
The objective of the Coupled Model Intercomparison Project (CMIP) is to better understand past, present and future climate changes arising from either natural, unforced variability or in response to changes in radiative forcing in a multi-model context.
This understanding includes assessments of model performance during the historical period and quantifications of the causes of the spread in future projections. Idealized experiments are also used to increase understanding of the model responses. In addition to these long time scale responses, experiments are performed to investigate the predictability of the climate system on various time and space scales as well as making predictions from observed climate states.
An important part of CMIP is to make the multi-model output publicly available in a standardized format.
This understanding includes assessments of model performance during the historical period and quantifications of the causes of the spread in future projections. Idealized experiments are also used to increase understanding of the model responses. In addition to these long time scale responses, experiments are performed to investigate the predictability of the climate system on various time and space scales as well as making predictions from observed climate states.
An important part of CMIP is to make the multi-model output publicly available in a standardized format.
Earth System Modeling Program (EaSM)
The Earth System Modeling (EaSM) Program supports the development of innovative Earth system modeling capabilities, with the ultimate goal of providing accurate and computationally advanced representations of the fully coupled and integrated Earth system, as needed for energy and related sectoral infrastructure planning.
Key examples of critical information for energy include accurate projections of water availability, drought incidence and persistence, temperature extremes including prolonged heat stress, probability of storms, opening of the Arctic Ocean, and sea level and storm-surge at coastal regions.
In order to provide this information, considerable effort is needed to develop optimal-fidelity climate and Earth system simulations, with suitably-accurate representation of atmospheric dynamics, clouds and chemistry, ocean circulation and biogeochemistry, land biogeochemistry and hydrology, sea-ice and dynamic land-ice, and in each case including elements of human activities that affect these systems such as water management and land-use.
Key examples of critical information for energy include accurate projections of water availability, drought incidence and persistence, temperature extremes including prolonged heat stress, probability of storms, opening of the Arctic Ocean, and sea level and storm-surge at coastal regions.
In order to provide this information, considerable effort is needed to develop optimal-fidelity climate and Earth system simulations, with suitably-accurate representation of atmospheric dynamics, clouds and chemistry, ocean circulation and biogeochemistry, land biogeochemistry and hydrology, sea-ice and dynamic land-ice, and in each case including elements of human activities that affect these systems such as water management and land-use.