Jim Hansen's Projects
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Interpreting, improving, and augmenting multi-model ensembles for numerical weather prediction. The
aim is to better understand the important properties of multi-model ensembles, to use multi-model
ensembles to inform about model inadequacies, and to develop methods for intelligently adding new
ensemble members to existing multi-model ensembles.
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Model Bending: Towards dealing with model inadequacies in data
assimilation and forecasting using a single model structure. Model
output statistics, data assimilation, parameter estimation, and stochastic
differential equations are combined in an effort to understand how best to
account for and reduce model inadequacies in a single model.
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Data assimilation in the earth sciences. An investigation of data assimilation issues that cut
across traditional earth science disciplines. Research focuses on high dimensionality,
nonlinearity, model representation, and uncertainty.
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Tropical predictability and observability. Models of the coupled tropical
system are utilized to address zeroth-order questions about the type,
frequency, and spatial distribution of observations that are necessary to
adequately constrain the system.
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Quantifying Uncertainty in the Attribution of Recent Climate Change (QUARCC) in collaboration with
the Hadley Centre for
Climate Prediction and Research at the UK Meteorological Office and
the Max-Planck-Institut für Meteorologie
/ Deutsches Klimarechenzentrum in Hamburg.
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climateprediction.com: run a climate model at home!
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Climate@Home: Leveraging the gains made by climateprediction.net,
Climate@Home aims to complement and extend the science and outreach using
NCAR's Community Climate System Model (CCSM).
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Last modified: Feb 2005