Within weather and climate systems there are a myriad of spatio-temporal "patterns": cyclic or quasi-cyclic, those which can be predicted within a certain confidence by virtue of preceding patterns, micro patterns, macro patterns, and bounded behaviors. The complexity is such that systems are embedded within systems with their own elements of layered uncertainty. We see mega-scale influences such as solar down to man-made influences in the form of aerosols coming into play in any long-term weather and climate prediction. We will examine climate modeling concerns such as primary vs. auxiliary effects, noise vs. signal, and choosing predictors and thresholds for significance using data mining. What can and cannot be predicted within certain actionable thresholds, and what constitutes a commercially viable product? The statistical modeling of uncertainty and complexity as a departure from deterministic forecasting is discussed in the context of risk assessment for commercial applications in energy, agriculture, and insurance. We will discuss business needs and solutions in light of the scale of weather and climate impacts in the coming years.
.Ria Persad is the Founder and CEO of StatWeather, a weather and climate modeling company. She studied mathematics and physics at Harvard, Princeton, and Cambridge Universities with doctoral study at Rice University.
Ria's experience in climate modeling began at Lawrence Livermore Lab's Supercomputer Center in 1991. She performed earth and solar system modeling at NASA and went on to model geophysical systems at Bell Geospace. She also worked on the trading floors of Lehman Brothers and was a consultant to Goldman Sachs
. As a climatologist at Enron and Duke Energy, she was alerted to the needs of the energy trading sector and weather risk management. She later went on to develop state-of-the-art long-range weather prediction systems which were peer-reviewed among academia and U.S. Department of Defense scientists and rigorously tested for the top meteorological broadcasting station in the Midwest
Ria models complex systems for the U.S. Space Program and is an innovative Subject Matter Expert. She has been collaborating with NOAA National Centers for Environmental Information and their academic research partner, CICS-NC on numerous climate and energy engagement activities to advance environmental intelligence.
She received the Highest Honor from the Society of Women Engineers and Citations from the U.S. Secretary of Energy and the U.S. Senate on Scientific Achievement on her original contributions to computational and applied mathematics.
Ria has also been recently recognized by Platts Global Energy Awards as one of the Top 7 global leaders for Lifetime Achievement and as the International Power-Gen and Renewable Energy Woman of the Year.