Noel Cressie is Distinguished Professor in the Faculty of Engineering and Information Sciences, he is Director of the Centre for Environmental Informatics in the National Institute for Applied Statistics Research Australia (NIASRA), and he is Professor of Statistics in the School of Mathematics and Applied Statistics, at the University of Wollongong (UOW), Australia. He has been awarded over $20 million in extramural funding during his career in the US and Australia. He has (co-)authored four books, which includes the single-authored and widely cited (over 20,330 citations, from Google Scholar; accessed, July 2020) 900-page book "Statistics for Spatial Data" (1991, 1993, 2015). Since the 2000s, Noel has been actively researching and applying spatio-temporal models using a hierarchical statistical framework, with major innovations that make spatial and spatio-temporal modelling computationally feasible for "big data." This research is synthesised in the award-winning (co-authored) books "Statistics for Spatio-Temporal Data" (2011, 2015) and "Spatio-Temporal Statistics with R" (2019). He has published over 330 articles/chapters/discussions in scholarly journals and edited books, which have been cited more than 9,300 times and his h-index is 45 (both from Web of Science; accessed July 2020).
Noel’s research focus is on developing statistical methodology and its applications for spatial and spatio-temporal data. He is a world leader in environmental informatics, particularly in statistical remote sensing developed for the US National Aeronautics and Space Administration (NASA) on contracts and research projects. His methodological research is centrally Bayesian and empirical-Bayesian for big, complex, hierarchical statistical models, such as those used to infer global sources and sinks of carbon dioxide from satellite data. Noel is a Chief Investigator and lead on the 2019 Australian Research Council (ARC) Discovery Project, "Bayesian inversion and computation applied to atmospheric flux fields," which continues the research described in his 2018 discussion paper published in the Journal of the American Statistical Association, a top-three statistics journal. The research is aiming to answer the critical carbon-cycle question, "Where are Earth’s carbon sources and sinks?", for mitigation of greenhouse-gas warming in the twenty-first century. Noel is a Chief Investigator on an ARC Special Research Initiative (SRI) to carry out critical environmental research for Antarctica and the Southern Ocean. The $36 million SRI, "Securing Antarctica’s Environmental Future (SAEF)," which is administered by Monash University, funds a seven-year (2020-2027) research program at UOW. It brings together top Antarctic physical scientists, marine and terrestrial biologists, and statistical scientists, who will use unique data sets and data from national programs in Australia and around the world, to make the best decisions for future Antarctic environmental management. Noel is also using his expertise in spatial design and hierarchical statistical modelling in a new five-year (2020-2025) project with approximately 20 Curtin University researchers. His responsibilities are primarily in designing and analysing data on colour degradation and its causes for the (up-to 35,000-year-old) indigenous rock art of the Murujuga National Park (Pilbara, WA). Noel has received many honours, awards, and fellowships. Among these, in 2009 he received from the Committee of Presidents of Statistical Societies (COPSS) one of the highest awards in statistical science, the R.A. Fisher Award and Lectureship. In 2014, he was awarded the Pitman Medal by the Statistical Society of Australia for his outstanding achievements in the discipline of Statistics, and in 2018 he was elected a Fellow of the Australian Academy of Science. More on Noel Cressie’s background may be found at https://en.wikipedia.org/wiki/Noel_Cressie
Noel Cressie has been Professor and then Distinguished Professor at the University of Wollongong (UOW) since 2012, during which he has supervised and mentored four postdoctoral fellows, two of whom have gone on to be awarded the ARC's Discovery Early Career Research Award (DECRA). Noel was awarded an ARC 2015 Discovery Project (2015-2018; “Spatio-Temporal Statistics and its Application to Remote Sensing”) and an ARC 2019 Discovery Project (2019-2022; “Bayesian Inversion and Computation Applied to Atmospheric Flux Fields”). From 2020-2027, he is a Chief Investigator on an ARC Special Research Initiative (“Securing Antarctica’s Environmental Future”). D/Prof Cressie’s UOW appointment allows him to maintain strong links with colleagues in the USA; from 2013-2017, he was a Distinguished Visiting Scientist at the US National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) in Pasadena, CA. Since 2010, he has been a member of the Science Team of NASA's Orbiting Carbon Observatory-2 satellite. From 2012-2019, Noel was a contractor on a seven-year National Science Foundation (NSF) award on hierarchical multiscale spatio-temporal statistical models for socio-demographic survey data. This led to a 2017-2018 contract with the Australian Bureau of Statistics (ABS) to study Australia's unemployment spatially, temporally, and in small areas. From 2003-2014, he had research contracts with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to study the role of specific agricultural and marine processes in the carbon cycle. He was also a CSIRO Visiting Senior Research Fellow and a CSIRO Distinguished Visiting Scientist during this period of collaboration.
D/Prof Cressie's first and latest academic appointments have been at “younger” Australian universities in schools of mathematics. In between, he was at Iowa State University (1983-1998) and The Ohio State University (1998-2012), which are both large US universities with high-quality Masters and PhD Statistics Programs. During his career, Noel has supervised 14 Masters’ students and 25 PhD students to completion of their degrees, and he has supervised 13 postdoctoral fellows. He has published (or has accepted for publication) 4 books, more than 235 journal articles, and more than 40 book chapters.
<p>We have been looking up at the stars for millennia, trying to figure out our place in space, making small steps out and sending probes out even further. We are space travellers, but for the foreseeable future, Earth is our “mother ship,” and this story is about a mission to our own planet.</p>
<p>To sustain our voyage through space, we need to know the state of our ship, Earth. We need to look for stressors, overheating, and new energy sources. We need to monitor its integrity, repair components that are broken, and establish long-term maintenance protocols.</p><p> Our spaceship is in peril, and no-one is in charge. We have scientific knowledge about different parts with different degrees of certainty, but too often debate is not informed by science and degenerates into fractious disagreements of opinion.</p><p> Carbon is the fourth most abundant element in the universe. Earth's carbon cycle is a closed system, with carbon moving in and out of different “pools.” Carbon causes no harm while it is locked in the ground (the terrestrial pool) but, once extracted and burned as a fossil fuel, it is released into the atmospheric pool to bond with oxygen and become carbon dioxide (CO<sub>2</sub>).</p><p> Odourless, tasteless, and invisible, CO<sub>2</sub> is a leading greenhouse gas that is a major driver of climate change. Although fossil fuel powers much of the human activity on our planet, it leaves an excess of CO<sub>2</sub> in the atmospheric pool. These anthropogenic sources of CO<sub>2</sub> are causing an imbalance between its emission and re-absorption at Earth's surface, and strong science and technology (including Statistical Science) is needed to address this Grand Challenge of what to do about it.</p><p> Inside the ship, the Earth system’s “clubs” (e.g., the carbon club, the aerosol club, the water club) are spinning. In pre-industrial times, there was balance in the carbon club, when about as much carbon was being removed from the atmosphere as was being added. However, in the first decade of this century, the net increase of atmospheric CO<sub>2</sub> was about 4 gigatonnes (Gt) per annum, which is huge – it represents about half of what was produced anthropogenically. The excess CO<sub>2</sub> is spread around the planet by weather systems and accumulates as a fraction of all the atmospheric gases; its presence is measured in parts per million (ppm).</p><p> In the first decade of this century, yearly increases of atmospheric CO<sub>2</sub> were about 2 ppm but, for the years 2015 and later, this has accelerated to almost 3 ppm. In 2015, atmospheric CO<sub>2</sub> officially reached 400 ppm, which is a 26% increase from 1960 levels. (From paleoclimate data, atmospheric CO<sub>2</sub> last reached 400 ppm on Earth in the middle Pliocene, about 3.6 million years ago, before <em>Homo sapiens</em> arrived.) In 2020, our planet’s CO<sub>2</sub> is expected to reach 415 ppm.</p><p> My research impact on this problem began with my membership a decade ago of the NASA Science Team of the Orbiting Carbon Observatory-2 (OCO-2) mission. OCO-2 is a NASA satellite launched in July 2014, whose primary science objective is to estimate the global geographic distribution of CO<sub>2</sub> fluxes (i.e., sources and sinks) at Earth’s surface through time. This knowledge, of how carbon moves in and out of the atmospheric pool, is critical to developing smart mitigation and management strategies that will restore balance to the carbon club.</p><p> The problem is hard because direct measurement of fluxes is globally inadequate. Remote sensing data help, but they give a different measure of CO2, one obtained from looking down at Earth through a narrow, swirling atmospheric column. The approach taken in our Centre is to use Statistical Science to “invert” the globally plentiful satellite data and trace the measured CO<sub>2</sub> back to their sources and sinks. This flux inversion uses a fundamental result in probability theory called Bayes’ Theorem, but it is applied here in an extraordinary setting. It requires handling very high dimensional data; tracking latent unobserved processes globally and through time; sampling from the probability distribution of all the “unknowns” conditional on the data; working in a high-performance computing environment; and collaborating in an interdisciplinary team of statistical and atmospheric scientists.</p><p> Our (<em>Homo sapiens</em>) juggling with the carbon (and aerosols, water, etc.) club is a high-risk act that trades off economic well-being, jobs, and growth (and the fossil fuels that power them) with a very real change in Earth’s climate. It requires a careful characterisation of what we know (the geophysics, the data), their uncertainties, and a decision space with costs and benefits articulated. The devastation of Australia’s “black” Spring–Summer bushfires of 2019–2020 illustrates the enormous cost, ecological as well as financial, of taking little or no action.</p><p> Statistical Science shows how to combine the geophysical and observational uncertainties into an integrative, hierarchical, physical-statistical model. It maps the path from observations to information to knowledge, using conditional probabilities to quantify the uncertainty in the knowledge attained. The Centre for Environmental Informatics at the University of Wollongong has received a three-year ARC Discovery Project to answer the following key questions about carbon fluxes (sources and sinks): Where, when, how much, and how certain?</p><p> This story is fundamentally about saving more (CO<sub>2</sub> absorption) and spending less (CO<sub>2</sub> emission). Every year, the budget is in debt to the tune of 4 Gt of carbon dioxide, a proven greenhouse gas. Our planet is overheating and, to save all who voyage in her, our governments must recognise the threat and collectively work together to enhance its sinks and decrease its sources. There is little chance of a do-over – what our generation does or does not do now will deeply affect our children’s generation and those that follow.</p><p> </p>
Beneficiary
Quantification
Description
Evidence
Description
Supervision
Advisees
Graduate Advising Relationship
Degree
Research Title
Advisee
Doctor of Philosophy
Deep Statistical Models with Applications to Environmental Data
Vu, Quan
Doctor of Philosophy (Integrated)
Statistical Aggregation of Remote Sensing Data for Atmospheric Inversion of CO2
Pearse, Alan
Doctor of Philosophy
Long-and-Short-Term-Memory and Focused Bayesian Inference for Spatio-Temporal Models
Sainsbury-Dale, Matthew
Doctor of Philosophy
Statistical Methods to Predict Atmospheric Carbon Dioxide Fluxes
Noel Cressie has been Professor and then Distinguished Professor at the University of Wollongong (UOW) since 2012, during which he has supervised and mentored four postdoctoral fellows, two of whom have gone on to be awarded the ARC's Discovery Early Career Research Award (DECRA). Noel was awarded an ARC 2015 Discovery Project (2015-2018; “Spatio-Temporal Statistics and its Application to Remote Sensing”) and an ARC 2019 Discovery Project (2019-2022; “Bayesian Inversion and Computation Applied to Atmospheric Flux Fields”). From 2020-2027, he is a Chief Investigator on an ARC Special Research Initiative (“Securing Antarctica’s Environmental Future”). D/Prof Cressie’s UOW appointment allows him to maintain strong links with colleagues in the USA; from 2013-2017, he was a Distinguished Visiting Scientist at the US National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) in Pasadena, CA. Since 2010, he has been a member of the Science Team of NASA's Orbiting Carbon Observatory-2 satellite. From 2012-2019, Noel was a contractor on a seven-year National Science Foundation (NSF) award on hierarchical multiscale spatio-temporal statistical models for socio-demographic survey data. This led to a 2017-2018 contract with the Australian Bureau of Statistics (ABS) to study Australia's unemployment spatially, temporally, and in small areas. From 2003-2014, he had research contracts with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to study the role of specific agricultural and marine processes in the carbon cycle. He was also a CSIRO Visiting Senior Research Fellow and a CSIRO Distinguished Visiting Scientist during this period of collaboration.
D/Prof Cressie's first and latest academic appointments have been at “younger” Australian universities in schools of mathematics. In between, he was at Iowa State University (1983-1998) and The Ohio State University (1998-2012), which are both large US universities with high-quality Masters and PhD Statistics Programs. During his career, Noel has supervised 14 Masters’ students and 25 PhD students to completion of their degrees, and he has supervised 13 postdoctoral fellows. He has published (or has accepted for publication) 4 books, more than 235 journal articles, and more than 40 book chapters.
<p>We have been looking up at the stars for millennia, trying to figure out our place in space, making small steps out and sending probes out even further. We are space travellers, but for the foreseeable future, Earth is our “mother ship,” and this story is about a mission to our own planet.</p>
<p>To sustain our voyage through space, we need to know the state of our ship, Earth. We need to look for stressors, overheating, and new energy sources. We need to monitor its integrity, repair components that are broken, and establish long-term maintenance protocols.</p><p> Our spaceship is in peril, and no-one is in charge. We have scientific knowledge about different parts with different degrees of certainty, but too often debate is not informed by science and degenerates into fractious disagreements of opinion.</p><p> Carbon is the fourth most abundant element in the universe. Earth's carbon cycle is a closed system, with carbon moving in and out of different “pools.” Carbon causes no harm while it is locked in the ground (the terrestrial pool) but, once extracted and burned as a fossil fuel, it is released into the atmospheric pool to bond with oxygen and become carbon dioxide (CO<sub>2</sub>).</p><p> Odourless, tasteless, and invisible, CO<sub>2</sub> is a leading greenhouse gas that is a major driver of climate change. Although fossil fuel powers much of the human activity on our planet, it leaves an excess of CO<sub>2</sub> in the atmospheric pool. These anthropogenic sources of CO<sub>2</sub> are causing an imbalance between its emission and re-absorption at Earth's surface, and strong science and technology (including Statistical Science) is needed to address this Grand Challenge of what to do about it.</p><p> Inside the ship, the Earth system’s “clubs” (e.g., the carbon club, the aerosol club, the water club) are spinning. In pre-industrial times, there was balance in the carbon club, when about as much carbon was being removed from the atmosphere as was being added. However, in the first decade of this century, the net increase of atmospheric CO<sub>2</sub> was about 4 gigatonnes (Gt) per annum, which is huge – it represents about half of what was produced anthropogenically. The excess CO<sub>2</sub> is spread around the planet by weather systems and accumulates as a fraction of all the atmospheric gases; its presence is measured in parts per million (ppm).</p><p> In the first decade of this century, yearly increases of atmospheric CO<sub>2</sub> were about 2 ppm but, for the years 2015 and later, this has accelerated to almost 3 ppm. In 2015, atmospheric CO<sub>2</sub> officially reached 400 ppm, which is a 26% increase from 1960 levels. (From paleoclimate data, atmospheric CO<sub>2</sub> last reached 400 ppm on Earth in the middle Pliocene, about 3.6 million years ago, before <em>Homo sapiens</em> arrived.) In 2020, our planet’s CO<sub>2</sub> is expected to reach 415 ppm.</p><p> My research impact on this problem began with my membership a decade ago of the NASA Science Team of the Orbiting Carbon Observatory-2 (OCO-2) mission. OCO-2 is a NASA satellite launched in July 2014, whose primary science objective is to estimate the global geographic distribution of CO<sub>2</sub> fluxes (i.e., sources and sinks) at Earth’s surface through time. This knowledge, of how carbon moves in and out of the atmospheric pool, is critical to developing smart mitigation and management strategies that will restore balance to the carbon club.</p><p> The problem is hard because direct measurement of fluxes is globally inadequate. Remote sensing data help, but they give a different measure of CO2, one obtained from looking down at Earth through a narrow, swirling atmospheric column. The approach taken in our Centre is to use Statistical Science to “invert” the globally plentiful satellite data and trace the measured CO<sub>2</sub> back to their sources and sinks. This flux inversion uses a fundamental result in probability theory called Bayes’ Theorem, but it is applied here in an extraordinary setting. It requires handling very high dimensional data; tracking latent unobserved processes globally and through time; sampling from the probability distribution of all the “unknowns” conditional on the data; working in a high-performance computing environment; and collaborating in an interdisciplinary team of statistical and atmospheric scientists.</p><p> Our (<em>Homo sapiens</em>) juggling with the carbon (and aerosols, water, etc.) club is a high-risk act that trades off economic well-being, jobs, and growth (and the fossil fuels that power them) with a very real change in Earth’s climate. It requires a careful characterisation of what we know (the geophysics, the data), their uncertainties, and a decision space with costs and benefits articulated. The devastation of Australia’s “black” Spring–Summer bushfires of 2019–2020 illustrates the enormous cost, ecological as well as financial, of taking little or no action.</p><p> Statistical Science shows how to combine the geophysical and observational uncertainties into an integrative, hierarchical, physical-statistical model. It maps the path from observations to information to knowledge, using conditional probabilities to quantify the uncertainty in the knowledge attained. The Centre for Environmental Informatics at the University of Wollongong has received a three-year ARC Discovery Project to answer the following key questions about carbon fluxes (sources and sinks): Where, when, how much, and how certain?</p><p> This story is fundamentally about saving more (CO<sub>2</sub> absorption) and spending less (CO<sub>2</sub> emission). Every year, the budget is in debt to the tune of 4 Gt of carbon dioxide, a proven greenhouse gas. Our planet is overheating and, to save all who voyage in her, our governments must recognise the threat and collectively work together to enhance its sinks and decrease its sources. There is little chance of a do-over – what our generation does or does not do now will deeply affect our children’s generation and those that follow.</p><p> </p>
Beneficiary
Quantification
Description
Evidence
Description
Supervision
Advisees
Graduate Advising Relationship
Degree
Research Title
Advisee
Doctor of Philosophy
Deep Statistical Models with Applications to Environmental Data
Vu, Quan
Doctor of Philosophy (Integrated)
Statistical Aggregation of Remote Sensing Data for Atmospheric Inversion of CO2
Pearse, Alan
Doctor of Philosophy
Long-and-Short-Term-Memory and Focused Bayesian Inference for Spatio-Temporal Models
Sainsbury-Dale, Matthew
Doctor of Philosophy
Statistical Methods to Predict Atmospheric Carbon Dioxide Fluxes