Wednesday, Jul. 24
8:30 am - 5:00 pm
Thursday, Jul. 25
8:30 am - 5:00 pm
Friday, Jul. 26
8:30 am - 3:00 pm
General Registration: $200
Early Career Scientist: $100
Federal Program Sponsor: $200
Registration is now closed.
Fostering usage of large initial-condition ensembles with
Earth System Models to advance understanding of natural
climate variability, anthropogenic climate change,
and their impacts.
Identifying anthropogenic influences on weather and climate amidst the “noise” of internal variability is a central challenge for the broad climate research community. Since the inception of the Atmospheric and Coupled Model Intercomparison Projects (AMIP and CMIP) two decades ago, substantial progress has been made through coordinated efforts between climate modeling centers and their collaborators on quantifying structural (i.e. model related) uncertainty in climate projections. The advent of large “initial condition” ensemble simulations builds on these earlier efforts by allowing the study of uncertainty associated with internal fluctuations in the climate system. These uncertainties are largely irreducible, and thus pose a limit on our ability to predict and attribute climate change impacts at regional scales and multi-decadal time horizons, with implications for adaptation planning.
At present more than half a dozen modeling centers have produced large “initial condition” ensembles of climate change simulations under historical and future emissions pathways, in which each ensemble member is subject to the same trajectory of external forcing but begins from a slightly different state. These efforts have led to rapid advances in our interpretation of the observational record and approaches to climate model evaluation, and provided new opportunities for addressing outstanding science questions regarding the interplay of forced climate change and internal climate variability. For example, such ensembles have been used to quantify sources of spread within the CMIP archive, provided context for our ability to narrow projections of regional climate in the coming decades, been employed as a test-bed for statistical approaches to separating forced and internal components of climate variability and change in observations, and enabled robust comparison of observed and model simulated internal variability including extreme events through increased sample sizes. Initial progress has centered largely on the atmosphere, with additional applications to oceanic, cryospheric, terrestrial, hydrological and biogeochemical fields.
The Large Ensembles Workshop will bring together a diverse group of researchers in climate and related sciences to achieve the following goals:
- Provide an overview of recent research advances achieved through the application of Large Ensembles;
- Provide a tutorial on effective use of Large Ensembles for interpreting the observed climate record, and for evaluating internal variability and forced climate change in global coupled climate models;
- Identify research challenges and new directions moving forward, including both scientific and methodological questions;
- Provide a forum for discussion of the design of a next-generation Large Ensemble Model Intercomparison Project that is responsive to a wide group of users;
- Identify means by which Large Ensembles can contribute to broader community efforts, including applications to climate impacts and risk assessment, terrestrial and marine ecosystems, and resource management through the use of dynamical and statistical downscaling methods.
The themes of the workshop will include: (i) modeling challenges – assessment of critical processes, scales and parameterizations that impact Large Ensemble studies; (ii) observational challenges – assessment of uncertainties due to the brevity of the instrumental record for evaluating internal variability in models; and (iii) risk assessment strategies – development of methodologies such as regionally downscaled Large Ensembles and observationally-based Large Ensembles - that can be applied to resource management.
Scientists with interests in the application of Large Ensemble methods were welcome to participate in the workshop. The workshop held over 100 in-person participants in diverse fields and many more remotely.
The three (3) day meeting will be held at the Mesa Lab of the National Center for Atmospheric Research (NCAR) in Boulder, CO, and consisted of plenary sessions including invited overview talks and contributed presentations, interactive poster session, in-depth plenary and breakout discussions, and a networking event.
In addition to sharing of knowledge and ideas among the participants, the workshop will result in a report that summarizes recent advances in Large Ensemble based research, discusses new research avenues as they emerge from the workshop presentations and discussions, and formulates a strategy for the design of a next-generation Large Ensemble Model Intercomparison Project. Read the summary produced by the Working Group, as well as the Nature Climate Change Perspective paper that was inspired by discussions from the workshop.
Scientific Organizing Committee
Clara Deser (NCAR, co-chair)
Keith Rodgers (ICCP, co-chair)
Pedro DiNezio (U. Texas at Austin)
Jennifer Kay (U. Colorado at Boulder)
Flavio Lehner (NCAR)
Nikki Lovenduski (U. Colorado at Boulder)
Karen McKinnon (UCLA)
Isla Simpson (NCAR)
Program Organizing Committee
Jeff Becker (US CLIVAR)
Mike Patterson (US CLIVAR)
Jennie Zhu (US CLIVAR)