Jim Hansen's Projects

• 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.
• 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.
• 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.
• 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.
• 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.
• climateprediction.com: run a climate model at home!
• 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).