The U.S. Department of Energy's Office of Scientific and Technical Information

Glacier area and volume changes were quantified through the use of historical aerial photographs in the Wind River Range, Wyoming. Forty-four glaciers in the Wind River Range were analyzed using orthorectified aerial photography from 2012. This is an update to the work of Thompson et al. [1] in which the surface area changes of the 44 glaciers were estimated from 1966 to 2006. The total surface area of the glaciers was estimated to be 27.8 ± 0.8 km², a decrease of 39% from 1966 and a decrease of 2% from 2006. The 2012 volume changes for the 44 glaciers were estimated using the Bahr et al. [2] volume-area scaling technique. The total glacier volume in 2012 was calculated to be 1.01 ± 0.21 km³, a decrease of 63% from 1966. These results, once compared to temperature and snowpack trends, suggest that the downward trend in snowpack as well as increasing temperatures seem to be the most likely driver of the glacier recessions. With Global Circulation Models (GCMs) forecasting higher temperatures and lower precipitation in the western U.S., it is likely that glaciers will continue to recede.Glacier area and volume changes were quantified through the use of historical aerial photographs in the Wind River Range, Wyoming. Forty-four glaciers in the Wind River Range were analyzed using orthorectified aerial photography from 2012. This is an update to the work of Thompson et al. [1] in which the surface area changes of the 44 glaciers were estimated from 1966 to 2006. The total surface area of the glaciers was estimated to be 27.8 ± 0.8 km², a decrease of 39% from 1966 and a decrease of 2% from 2006. The 2012 volume changes for the 44 glaciers were estimated using the Bahr et al. [2] volume-area scaling technique. The total glacier volume in 2012 was calculated to be 1.01 ± 0.21 km³, a decrease of 63% from 1966. These results, once compared to temperature and snowpack trends, suggest that the downward trend in snowpack as well as increasing temperatures seem to be the most likely driver of the glacier recessions. With Global Circulation Models (GCMs) forecasting higher temperatures and lower precipitation in the western U.S., it is likely that glaciers will continue to recede.

In the opening months of the pandemic, the need for situational awareness was urgent. Forecasting models such as the Susceptible-Infectious-Recovered (SIR) model were hampered by limited testing data and key information on mobility, contact tracing, and local policy variations would not be consistently available for months. New case counts from sources like John Hopkins University and the NY Times were systematically reliable. Using these data, we developed the novel COVID County Situational Awareness Tool (CCSAT) for reliable monitoring and decision support. In CCSAT, we developed a retrospective seven-day moving window semantic map of county-level disease magnitude and acceleration that smoothed noisy daily variations. We also developed a novel Bayesian model that reliably forecasted county-level magnitude and acceleration for the upcoming week based on population and new case count data. Together these formed a robust operational update including county-level maps of new case rate changes, estimates of new cases in the upcoming week, and measures of model reliability. We found CCSAT provided stable, reliable estimates across the seven-day time window, with the greatest errors occurring in cases of anomalous, single day spikes. In this paper, we provide CCSAT details and apply it to a single week in June 2020.

The U.S. Department of Energy's Office of Scientific and Technical Information

The built environment continues to expand due to increasing human populations with some projections indicating additional growth of 2.5 billion persons by 2050. Buildings are a key component of the built environment and information on building height and urban morphology in general can help to better understand and address a host of development and urban planning issues including energy consumption, urbanization, population dynamics, urban heat islands, environmental degradation, and others. To date, several approaches have been developed to address the need for mapping building height at scale. These approaches can be grouped into two main categories: 1) directly measure height from remote sensing products or 2) indirectly estimate height from footprint morphology features at the building-by-building level. Due to a number of these global height datasets now being available for consumption and use across domains, there is a critical need to understand the differences displayed between these products and how the use of these may influence the outcome when applied. In this analysis, we compare and evaluate 5 global building height datasets: Global Human Settlement, World Settlement Footprint 3D, Global Building Morphology dataset, three-dimensional Global Building Footprints, and an approach developed at Oak Ridge National Laboratory (ORNL). Our analysis shows that, across 5 cities at a global scale with high-quality building height reference data, the approach developed by ORNL of inferring height at the building-by-building level is more accurate and consistent. This was evidenced by the ORNL product improving upon the baseline in all 5 cities, the only product to do so. These findings will aid researchers in choosing a global building height product that best meets their needs and provides global availability, consistency, and accuracy.