Identifying signals in the climate system amidst the “noise” of internal variability is a central challenge for the weather and climate communities. Furthermore, understanding the uncertainty due to internal variability is crucial for risk management and robust decision making as we adapt to our changing climate. The proliferation of initial condition large ensembles has provided the scientific community with a valuable tool with which to address this challenge: by design, the spread across the ensemble provides a metric of the noise and the mean of the ensemble can be viewed as the signal. Large ensembles also have proved to be helpful testbeds for hypotheses and methodologies focused on interpreting our single observational record. Our session aims to bring together a diverse set of large ensemble users with foci on (1) the development and application of methods using large ensembles to parse the signal and the noise in the observational record, and (2) the use of large ensembles to aid in decision making. We welcome contributions from a range of scientific fields.

- Indicates paper has been withdrawn from meeting

- Indicates an Award Winner