Weather challenges a wide spectrum of businesses whose revenues, costs and financial performance are sensitive to weather. This seminar will review the past, present, and future of the weather risk management market -- underscoring key events/drivers that have shaped the marketplace as well as predictions regarding future products and required supporting data/analytics.
With a population of more than 3.75 million over a seven-county area, the Twin Cities Metropolitan Area is used as an example of the challenges of measuring and mitigating urban warming and maintaining a sustainable environment for its citizens, economy, and urban ecosystems. Data from a dense network of temperature sensors is used to characterize the physical behavior of urban warming.
The size of data sets generated through academic and industrial research continues to increase in both the number of observations and the number of variables recorded. Much of this data has a natural temporal ordering. The resulting proliferation of high-dimensional time series has created the need for forecasting methods well-suited to handle the many challenges inherent to this new information landscape. We propose a method of feature selection utilizing conditional inference forests in order to generate the initial input for a back propagation neural network with a focus on optimizing a combination of prediction accuracy and model interpretability.
The COnvective Precipitation Experiment (COPE), occurring in the southwest UK during Summer 2013, was motivated to improve quantitative precipitation forecasting, in part, with the aim to increase understanding of both warm and cold precipitation processes that can lead to heavy convective rainfall.
In this talk, I will present an analysis of emission-driven simulations of Earth system models (ESMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, exhibited a small positive bias in predictions of contemporary atmospheric CO2, due in part to weak ocean carbon uptake.
Canopy- and leaf-scale measurements of plant phenology and solar induced fluorescence (SIF) provide a powerful tool to understand the growing season length, photosynthesis, and carbon dynamics. We developed new tools and methods to estimate plant phenology with digital cameras and SIF with high-resolution spectraradiometers.
The analysis of multivariate time series is a fundamental task that arises in numerous ecological and environmental applications. Scientists often need to understand how a variable changes, and how its relationships with other variables evolve over time. Such associations exhibit diurnal and seasonal patterns that need to be discovered and characterized.
Emerging water scarcity concerns in southeastern US are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that water utilities identify regionally coordinated, scarcity-mitigating strategies that trigger the appropriate actions needed to avoid water shortages and financial instabilities.
This seminar will include a brief introduction of hyperspectral remote sensing, our experiences during data collection and manipulation, and our continuing progress in order to set a point of departure for a seminar series on hyperspectral data collection and analytics using the EcoSpec project as a case study.
Critical Zone science aims to discover how Earth's "living skin" is structured, evolves, and provides critical functions that sustain life. The structure and dynamics in this zone encompass the interaction and coevolution between biotic and abiotic constituents from instantaneous to deep time.