The geological records of ancient environmental changes provide crucial archives for testing models of Earth system behavior, including those used to project ongoing and future global change. Yet the archives pose many statistical challenges. The data sources are noisy, diverse, and full of gaps. The locations and ages of observations are controlled in part by natural processes. Indeed, the ages of observations are themselves known only through noisy and diverse measurement techniques.
This workshop will focus on statistical approaches to overcoming these challenges and making inferences about the Earth's past environments. It will bring together Earth scientists, statisticians, applied mathematicians and computer scientists to address these issues. Questions of interest during the workshop include:
How can we combine information from different geological data sources in an efficient and statistically rigorous manner?
What biases are introduced into environmental interpretations by natural spatial and temporal filters, and how can we account for these?
How can we use understanding of natural processes to improve data interpretation?
How can statistical reconstructions of past environmental changes be used to improve estimates of future environmental risks?
The workshop's five thematic sessions will address:
Paleo-temperature and inference about climate sensitivity
Paleo-sea level and inference about ice sheet stability
Paleo-ecology and inference about ecological change
Paleo-environmental reconstructions and the character of the sedimentary record
Spectral analysis and the identification of climatic pacemakers
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