Timothy S. Hunter

A dynamic graphical interface for visualizing projected, measured, and reconstructed surface water elevations on the earth's largest lakes

There is a growing need within the international water research and water resources management community, and the general public, for easy access to time-series of projected, measured, and reconstructed marine and freshwater coastal surface water elevations. There is also a need for effectively communicating variability among different surface water elevation data sets, as well as the intrinsic uncertainties in surface water elevation forecasts. Here, we introduce an interactive web-based interface, the Great Lakes Water Level Dashboard (GLWLD), designed to address this need for the North American Laurentian Great Lakes, the largest assemblage of unfrozen fresh surface water bodies on planet Earth, and one with a coastline of over 16,000 km (roughly 10,000 miles). The GLWLD is a Flash-based tool that can simultaneously display time-series of measured monthly and annual water level data and seasonal forecasts for each of the Great Lakes, reconstructed lake levels from paleoclimate research, and decadal lake level projections under alternative climate scenarios. By employing a suite of novel data transfer, processing, and visualization tools, the GLWLD allows users to seamlessly transition not only between alternate displays of Great Lakes water levels over different temporal scales, but between different data sets and forecasts as well. Furthermore, the unique GLWLD interface can help users understand the extent to which decisions regarding the use of the lakes depend on an appreciation of uncertainty and variability within, and between, different sources of Great Lakes water level information.

Impacts of extreme 2013–2014 winter conditions on Lake Michigan's fall heat content, surface temperature, and evaporation

Since the late 1990s, the Laurentian Great Lakes have experienced persistent low water levels and above average over-lake evaporation rates. During the winter of 2013–2014, the lakes endured the most persistent, lowest temperatures and highest ice cover in recent history, fostering speculation that over-lake evaporation rates might decrease and that water levels might rise. To address this speculation, we examined interseasonal relationships in Lake Michigans thermal regime. We find pronounced relationships between winter conditions and subsequent fall heat content, modest relationships with fall surface temperature, but essentially no correlation with fall evaporation rates. Our findings suggest that the extreme winter conditions of 2013–2014 may have induced a shift in Lake Michigans thermal regime and that this shift coincides with a recent (and ongoing) rise in Great Lakes water levels. If the shift persists, it could (assuming precipitation rates remain relatively constant) represent a return to thermal and hydrologic conditions not observed on Lake Michigan in over 15 years.

An expandable web-based platform for visually analyzing basin-scale hydro-climate time series data

Growing demand from the general public for centralized points of data access and analytics tools coincides with similar, well-documented needs of regional and international hydrology research and resource management communities. To address this need within the Laurentian Great Lakes region, we introduce the Great Lakes Dashboard (GLD), a dynamic web data visualization platform that brings multiple time series data sets together for visual analysis and download. The platforms adaptable, robust, and expandable Time Series Core Object Model (GLD-TSCOM) separates the growing complexity and size of Great Lakes data sets from the web application interface. Although the GLD-TSCOM is currently applied exclusively to Great Lakes data sets, the concepts and methods discussed here can be applied in other geographical and topical areas of interest. Solution fulfills documented need in hydrological and resource management communities.Employed visualization paradigm permits easy visual analysis of Great Lakes Data.Data are downloadable for further analysis; Information about data is in application.Novel development model permits significant data and application feature expansion.

Hydrological drivers of record-setting water level rise on Earth's largest lake system

Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan-Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 year period beginning in January and ending in December of the following year. This historic event coincided with below-average air temperatures and extensive winter ice cover across the Great Lakes. It also brought an end to a 15 year period of persistently below-average water levels on Lakes Superior and Michigan-Huron that included several months of record-low water levels. To differentiate hydrological drivers behind the recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferring historical estimates of the major components of each lakes water budget. Our results indicate that, in 2013, the water level rise on Lake Superior was driven by increased spring runoff and over-lake precipitation. In 2014, reduced over-lake evaporation played a more significant role in Lake Superiors water level rise. The water level rise on Lake Michigan-Huron in 2013 was also due to above-average spring runoff and persistent over-lake precipitation, while in 2014, it was due to a rare combination of below-average evaporation, above-average runoff and precipitation, and very high inflow rates from Lake Superior through the St. Marys River. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes, and to Earths other large freshwater basins as well.