Likelihood-Based Climate Model Evaluation
No abstract available
Pacific Cross-section Intercomparison Project (GPC↗
Engineering topics
Teixeira, Joao
Publications and source records attributed to Teixeira, Joao.
Likelihood-Based Climate Model Evaluation
Climate models are deterministic, mathematical descriptions of the physics of climate. Confidence in predictions of future climate is increased if the physics are verifiably correct. A necessary, (but not sufficient) condition is that past and present climate be simulated well. Quantify the likelihood that a (summary statistic computed from a) set of observations arises from a physical system with the characteristics captured by a model generated time series. Given a prior on models, we can go further: posterior distribution of model given observations.
climate models↗
Converting NASA Satellite Datasets for the CMIP5/IPCC Assessment
No abstract available
Satellite observations↗
Frequency of Deep Convective Clouds and Global Warming
This slide presentation reviews the effect of global warming on the formation of Deep Convective Clouds (DCC). It concludes that nature responds to global warming with an increase in strong convective activity. The frequency of DCC increases with global warming at the rate of 6%/decade. The increased frequency of DCC with global warming alone increases precipitation by 1.7%/decade. It compares the state of the art climate models' response to global warming, and concludes that the parametrization of climate models need to be tuned to more closely emulate the way nature responds to global warming.
infrared↗