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John E. Bailey

Publications and source records attributed to John E. Bailey.

3 recordsLinked to original sources

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.

Scientific Data

Integrated satellite observations of the 2006 eruption of Augustine Volcano: Chapter 20 in The 2006 eruption of Augustine Volcano, Alaska

Satellite observations played an important role in monitoring the 2006 eruption of Augustine Volcano. It represented the first opportunity for observers to use, in an operational setting, new Web-based tools and techniques developed by the Alaska Volcano Observatory remote sensing group. The 'Okmok Algorithm' was used to analyze thermal infrared satellite data and highlight changes in the style and phases of activity. Temperature measurements were used to estimate ash cloud heights, which compared favorably to radar and ground-based observations, although larger discrepancies were seen when compared to pilot reports. Brightness temperature difference techniques were used to locate and track the 14 ash clouds produced during the explosive phase of the eruption. Stacking of these analyses allowed the creation of composite maps showing the distribution of airborne ash. The data from these maps were further combined with information from local reports and samples of ashfall to create a prototype of a concentration map that could be used to assess the potential hazard an eruption represents to aircraft, infrastructure and human health.

Alaska

Volcanic-ash dispersion modeling of the 2006 eruption of Augustine Volcano using the Puff model: Chapter 21 in The 2006 eruption of Augustine Volcano, Alaska

Volcanic ash is one of the major potential hazards from volcanic eruptions. It can have both short-range effects from proximal ashfall and long range impacts from volcanic ash clouds. The timely tracking and understanding of recently emitted volcanic ash clouds is important, because they can cause severe damage to jet aircraft engines and shut down major airports. Dispersion models play an important role in forecasting the movement of volcanic ash clouds by being the only means to predict a clouds' trajectory. Where available, comparisons are possible to both remote-sensing data and observations from the ground and aircraft. This was demonstrated in January 2006, when Augustine Volcano erupted after about a 20-year hiatus. From January 11 to 28, 2006, there were 13 explosive events, with some lasting as long as 11 minutes and producing ash clouds as high as 10-12 km (33,000-39,000 ft) above mean sea level (a.m.s.l). From January 28 to February 4, 2006, there was a more continuous phase, with ash clouds reaching 4-5 km a.m.s.l (13,000-16,000 ft). During the eruption, the Puff dispersion model was used by the Alaska Volcano Observatory for trajectory forecasting of the associated volcanic ash eruption clouds. The six explosive events on January 13 and 14, 2006, were the first time the 'multiple eruptions' capability of the Puff model was used during an eruption response. Here we show the Puff model predictions made during the 2006 Augustine eruption and compare these predictions to satellite remote-sensing data, Next Generation Radar (NEXRAD) radar, and ashfall measurements. In addition, we discuss how automated predictions for volcanoes at elevated alert status provide a quicker assessment of the risk from the potential ash clouds.

Professional Paper