Overview

The Capacity Center for Climate and Weather Extremes (C3WE) advances our understanding of high-impact events across the weather and climate continuum. C3WE advances and shares methods to create capacity for community investigations into high-impact events across the weather and climate continuum. We work with stakeholders to pursue new fundamental science questions while at the same time create usable and useful research outcomes.

Research

Process-Based Understanding

We develop and implement research frameworks based on observations, theory, and numerical modeling to understand the local-to-global Earth system process interactions that drive high-impact events across the weather and climate continuum. This includes analyzing process representation in a hierarchy of WRF and MPAS experiments from the tropics to the mid-latitudes and from large-eddy to global scales. We focus on processes that bring extreme rainfall, large hail, wind, coastal surge, and wildfire.

Predictability

Using operational and experimental sub-seasonal to seasonal (S2S) forecasting systems we quantify the S2S predictability of high-impact weather. We focus on the sources and scales of predictability. Specific forecasting systems are the seasonal-to-multiyear large ensemble using CESM2, the ECMWF integrated forecasting system, and experimental systems using MPAS informed by outputs from the research frameworks above.

Useable Science

We engage private industry and government entities to identify new fundamental science investigations into weather-climate-water connections and identify characteristics of usable and useful research. Adopting a convergence science approach we engage with stakeholders broadly to expand the problem space and also the solution space. This creates new, useful information arising from NSF NCAR’s community models, tools, and datasets.

Shareable Workflows

We develop and share workflows – including pre- and post-processing software for simulations and big data analysis tools – to create capacity for investigations into weather-climate connections. We create and share Jupyter notebooks using python, xarray, and Dask to analyze NSF NCAR community model datasets efficiently.

People

If you are interested in learning more please contact James Done.