29 July 2016

Uncertainty Quantification in Climate Modeling and Projection

International workshop brings together climate modeling researchers to gain understanding of the current state of uncertainty in model projections and map a path forward in model development.


The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced.


The UQ workshop underscored the importance of recognizing and quantifying uncertainty in climate models to increase the validation of climate projections and impact assessments. Many underdeveloped nations lack the infrastructure and resources to recover physically and economically from climate-change extremes, such as storms, drought and other natural disasters. For this reason, UNESCO provided funding to bring 30 representatives to the workshop from countries across Africa, Asia, and South America, whose populations are especially vulnerable to the effects of climate change.


The workshop provided a unique opportunity to gain insights on climate UQ topics from the perspective of a very diverse group of scientists from all over the world. Approximately 70 participants from 30 countries in all five continents met to discuss the need, approaches and challenges in UQ in Climate Modeling and Projection. The workshop, organized and directed by a Department of Energy (DOE) scientist at Pacific Northwest National Laboratory, aimed to provide participants information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer exercises on importance sampling, Bayesian inference, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progresses in quantifying uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales were reviewed. Significant challenges still remain in applying the various UQ approaches to climate models and their projections. One way forward could be to make use of information at shorter, weather timescales. An increasing number of modeling groups now make use of a 'seamless' approach of using model evaluation across weather, seasonal, and climate timescales to inform model development. Uncertainty quantification is also a focus for the DOE as eight national laboratories and six partner institutions collaborate to develop and apply the next generation of climate and Earth-system models to the challenges and demands of climate-change research. DOE's Accelerated Climate Modeling for Energy, or ACME, project is focused on how global water cycles, water resources, biogeochemical cycles, and rapidly changing ice or snow interact with climate systems and climate change.

Yun Qian
Pacific Northwest National Laboratory
Qian, Y., Jackson, C., Giorgi, F., et al. "Uncertainty Quantification in Climate Modeling and Projection." Bulletin of the American Meteorological Society May 2016, (2016). [10.1175/BAMS-D-15-00297.1].