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- Hail detection (1)
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Articles 1 - 4 of 4
Full-Text Articles in Meteorology
Hail Detection Using Dual Polarization Weather Radar, Alfonso Ladino Rincon
Hail Detection Using Dual Polarization Weather Radar, Alfonso Ladino Rincon
English Language Institute
This poster highlights how active remote sensors such as weather radar are completely useful for hail detection given its feature and the information they produce. Hail detection is already well studied by the atmospheric scientific community and dual polarimetric variables values for hail signature are presented according to those advances. Then, a supervised classification technique is showed to illustrated how machine learning can be integrated to radar information for automatic hail detection. However, this fuzzy logic algorithm has the capability to distinguish between meteorological and non-meteorological echoes. This automatic information might help forecasters from National Weather Services – NWS to …
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Faculty Publications
Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …
Internet Of Things For Environmental Sustainability And Climate Change, Abdul Salam
Internet Of Things For Environmental Sustainability And Climate Change, Abdul Salam
Faculty Publications
Our world is vulnerable to climate change risks such as glacier retreat, rising temperatures, more variable and intense weather events (e.g., floods, droughts, and frosts), deteriorating mountain ecosystems, soil degradation, and increasing water scarcity. However, there are big gaps in our understanding of changes in regional climate and how these changes will impact human and natural systems, making it difficult to anticipate, plan, and adapt to the coming changes. The IoT paradigm in this area can enhance our understanding of regional climate by using technology solutions, while providing the dynamic climate elements based on integrated environmental sensing and communications that …
Historical Trends In Air Temperature, Precipitation, And Runoff Of A Plateau Inland River Watershed In North China, Along Zhang, Ruizhong Gao, Xixi Wang, Tingxi Liu, Lijing Fang
Historical Trends In Air Temperature, Precipitation, And Runoff Of A Plateau Inland River Watershed In North China, Along Zhang, Ruizhong Gao, Xixi Wang, Tingxi Liu, Lijing Fang
Civil & Environmental Engineering Faculty Publications
Understanding historical trends in temperature, precipitation, and runoff is important but incomplete for developing adaptive measures to climate change to sustain fragile ecosystems in cold and arid regions, including the Balagaer River watershed on the Mongolian Plateau of northeast China. The objective of this study was to detect such trends in this watershed from 1959 to 2017. The detection was accomplished using a Mann-Kendall sudden change approach at annual and seasonal time scales. The results indicated that the abrupt changes in temperature preceded that in either runoff or precipitation; these abrupt changes occurred between 1970 and 2004. Significant (α = …