SLS - Claudie Beaulieu (UCSC)
Detecting trends in space-time environmental data: lessons learned from ocean chlorophyll
Quantifying global climate change and its impacts on ecosystems is challenged by the complexity and limitations of environmental data. In marine ecosystems, detecting climate change impacts on ocean chlorophyll, a proxy for primary productivity, is hindered by the shortness of the record and the long timescale of memory within the ocean. As a result, time-series analysis of satellite ocean chlorophyll is still inconclusive as to the sign of change in some regions. Here I show how utilizing both temporal and spatial dependency in the available data through a Bayesian hierarchical space-time model reveals the full uncertainty in chlorophyll trends and highlights regions undergoing significant change. The Bayesian hierarchical model used here provides a framework for integrating different sources of data for detecting trends and estimating their uncertainty in studies of global change. Moving forward, the targeted development of statistical techniques is required to process and make full use of the rapidly growing store of environmental data from models and advancing observational platforms.
About this Series:
The Atmosphere, Ocean and Climate Sack Lunch Seminar Series is an informal seminar series within PAOC that focuses on more specialized topics than the PAOC Colloquium. Seminar topics include all research concerning the science of atmosphere, ocean and climate. The seminars usually take place on Wednesdays from 12-1pm. The presentations are either given by an invited speaker or by a member of PAOC and can focus on new research or discussion of a paper of particular interest.