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Physical Sciences and Mathematics Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Mountain Lakes: Eyes On Global Environmental Change, Katrina A. Moser, Jill S. Baron, Janice Brahney, Isabella A. Olesky, Jasmine E. Saros, Elizabeth J. Hundey, Steven A. Sadro, Jiri Kopácek, Ruben Sommaruga, Martin J. Kainz, Angela L. Strecker, Sudeep Chandra, David M. Walters, Daniel L. Preston, Neal Michelutti, Fabio Lepori, Sarah A. Spaulding, Kyle R. Christianson, John M. Melack, J. P. Smol
Mountain Lakes: Eyes On Global Environmental Change, Katrina A. Moser, Jill S. Baron, Janice Brahney, Isabella A. Olesky, Jasmine E. Saros, Elizabeth J. Hundey, Steven A. Sadro, Jiri Kopácek, Ruben Sommaruga, Martin J. Kainz, Angela L. Strecker, Sudeep Chandra, David M. Walters, Daniel L. Preston, Neal Michelutti, Fabio Lepori, Sarah A. Spaulding, Kyle R. Christianson, John M. Melack, J. P. Smol
Environmental Science and Management Faculty Publications and Presentations
Mountain lakes are often situated in protected natural areas, a feature that leads to their role as sentinels of global environmental change. Despite variations in latitude, mountain lakes share many features, including their location in catchments with steep topographic gradients, cold temperatures, high incident solar and ultraviolet radiation (UVR), and prolonged ice and snow cover. These characteristics, in turn, affect mountain lake ecosystem structure, diversity, and productivity. The lakes themselves are mostly small and shallow, and up until recently, have been characterized as oligotrophic. This paper provides a review and update of the growing body of research that shows that …
Watershed Response To Climate Change And Fire-Burns In The Upper Umatilla River Basin, Usa, Kimberly Crystal Yazzie, Heejun Chang
Watershed Response To Climate Change And Fire-Burns In The Upper Umatilla River Basin, Usa, Kimberly Crystal Yazzie, Heejun Chang
Geography Faculty Publications and Presentations
This study analyzed watershed response to climate change and forest fire impacts in the upper Umatilla River Basin (URB), Oregon, using the precipitation runoff modeling system. Ten global climate models using Coupled Intercomparison Project Phase 5 experiments with Representative Concentration Pathways (RCP) 4.5 and 8.5 were used to simulate the effects of climate and fire-burns on runoff behavior throughout the 21st century. We observed the center timing (CT) of flow, seasonal flows, snow water equivalent (SWE) and basin recharge. In the upper URB, hydrologic regime shifts from a snow-rain-dominated to rain-dominated basin. Ensemble mean CT occurs 27 days earlier in …
Multiple New-Particle Growth Pathways Observed At The Us Doe Southern Great Plains Field Site, Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. Mcmurry, James N. Smith, Jeffery R. Pierce
Multiple New-Particle Growth Pathways Observed At The Us Doe Southern Great Plains Field Site, Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. Mcmurry, James N. Smith, Jeffery R. Pierce
Civil and Environmental Engineering Faculty Publications and Presentations
New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low volatility species, from diameters ∼ 1 to 30–100 nm in order to potentially impact climate. There are currently uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in aerosol-climate modeling. Four main pathways for new-particle growth have been identified: condensation of sulfuric-acid vapor (and associated bases when available), condensation of organic vapors, uptake of organic acids …
Utilizing Humidity And Temperature Data To Advance Monitoring And Prediction Of Meteorological Drought, Ali Behrangi, Paul C. Loikith, Eric J. Fetzer, Hai M. Nguyen, Stephanie L. Granger
Utilizing Humidity And Temperature Data To Advance Monitoring And Prediction Of Meteorological Drought, Ali Behrangi, Paul C. Loikith, Eric J. Fetzer, Hai M. Nguyen, Stephanie L. Granger
Geography Faculty Publications and Presentations
The fraction of land area over the Continental United States experiencing extreme hot and dry conditions has been increasing over the past several decades, consistent with expectation from anthropogenic climate change. A clear concurrent change in precipitation, however, has not been confirmed. Vapor pressure deficit (VPD), combining temperature and humidity, is utilized here as an indicator of the background atmospheric conditions associated with meteorological drought. Furthermore, atmospheric conditions associated with warm season drought events are assessed by partitioning associated VPD anomalies into the temperature and humidity components. This approach suggests that the concurrence of anomalously high temperature and low humidity …
Application Of Tree-Structured Regression For Regional Precipitation Prediction Using General Circulation Model Output, Xiangshang Li, David J. Sailor
Application Of Tree-Structured Regression For Regional Precipitation Prediction Using General Circulation Model Output, Xiangshang Li, David J. Sailor
Mechanical and Materials Engineering Faculty Publications and Presentations
This study presents a tree-structured regression (TSR) method to relate daily precipitation with a variety of free-atmosphere variables. Historical data were used to identify distinct weather patterns associated with differing types of precipitation events. Models were developed using 67% of the data for training and the remaining data for model validation. Seasonal models were built for each of 2 US sites: San Francisco, California, and San Antonio, Texas. The average correlation between observed and simulated daily precipitation data series is 0.75 for the training set and 0.68 for the validation set. Relative humidity was found to be the dominant variable …