Call for Papers: Themed Joint Session: "Determining the Uncertainty of Climate Predictions and Projections" at AMS (USA)
We would like to invite submissions to the following Themed Joint Session of the AMS Annual Meeting on January 8, 2013.
We would like to invite submissions to the following Themed Joint
Session of the AMS Annual Meeting on January 8, 2013.
Determining the Uncertainty of Climate Predictions and Projections and
Best Practices for Users of Climate Information
We are seeking papers for this session which focus on recent advances
and the state of knowledge in the uncertainty of climate predictions and
projections and best practices for the use of information on
uncertainty. Emphasis will be given to determining cascading uncertainty
in user derived climate products in areas such as hydrological
prediction, the likelihood of extremes, coastal inundation and drought
prediction, as well as downstream impacts, such as health and economics.
Topics of interest include current state-of-the-art probabilistic
predictions, advances in methodologies for determining uncertainty, as
well as best practices for expression of uncertainty in climate services
and incorporating uncertainty in user models. This session is convened
jointly as part of the Symposium on the Role of Statistical Methods in
Weather and Climate Prediction and 25th Conference on Climate
Variability and Change, so presentations that concern the crossover of
probability and statistics with climate variability and change are invited.
Symposium on the Role of Statistical Methods in Weather and Climate
Prediction
Contact: Dan Collins, Dan.Collins@noaa.gov <mailto:Dan.Collins@noaa.gov>
25th Conference on Climate Variability and Change
Contact: Hai Lin, Hai.Lin@ec.gc.ca <mailto:Hai.Lin@ec.gc.ca>
Abstracts are due August 8.
To submit an abstract, follow link for "Symposium on the Role of
Statistical Methods in Weather and Climate Prediction" abstracts here:
<https://ams.confex.com/ams/93Annual/oasys.epl> and choose the linked
session:
"Determining the Uncertainty of Climate Predictions and Projections and
Best Practices for Users of Climate Information"
<mailto:Hai.Lin@ec.gc.ca>
