Spatio-temporal modelling, network design, health effects, and dimensional analysis

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The burgeoning World population, newly predicted under present conditions to continue growing to as much as 15billion by the year 2100, is leading to increasing concerns about elevated levels of environment risk. More incidents e.g. high temperature episodes and the increased consumption of fossil fuels e.g. coal are expected. This dark future portends an increased need to effectively monitor environmental processes over space and time along with accurate methods for predicting these processes where they cannot be monitored in space and in the future, to support the management and mitigation of these risks through effective policy and regulation. Statisticians have a major role to play in this future, particularly in quantifying the uncertainties that abound. The proposed research will continue the applicant's long-term research program on the optimum design of spatio - temporal process monitoring networks and the use of the resulting data for modelling these processes for spatial prediction and future processes. We continue work on algorithms for overcoming the computational challenges associated with selecting optimal locations while ensuring that they are picked in an unbiased. But we will also provide extended theory for addressing the problems that arise with existing monitoring networks that have not bee selected in an unbiased way. In particular, since existing network stations are sometimes sited at preferentially selected geographical locations, we will continue seeking methods to reduce errors in statistical estimates induced by locating stations in that way. The research will also explore a promising objective method for siting them, one that insures they are well distributed over space. The remainder of the research concerns the use of data from these networks, possibly with adjustments for the effects of preferential siting, to create good spatio - temporal models. We will continue current research and seek models for temperature fields that extends their geographical domains of applicability - previous work focused the Pacific Northwest region of North America but now we will be moving into the United Kingdom to work with the UK Met Office on monitoring temperatures, since in the age of climate change, high temperatures are a health hazard. More specifically we will model exposures to extreme temperatures that take account of human behaviour, i.e. by modelling such exposures in micro-environments like car cabins or homes. But climate change is affecting not just the human species. Other research on marine mammals will continue since their numbers in some regions are being depleted for reasons not yet understood. New research on modelling their paths as a basis for determining their energy needs and how well these will be met, given the impact of warming on the food supply for these creatures.