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- Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research (3)
- Institute for ECHO Articles and Research (2)
- Mathematics, Physics, and Computer Science Faculty Articles and Research (2)
- Department of Biological Systems Engineering: Papers and Publications (1)
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Articles 1 - 9 of 9
Full-Text Articles in Atmospheric Sciences
Understanding The Zonal Variability In Cmip6 Projections Of Sahelian Precipitation, Emmanuel Ogwuche Audu
Understanding The Zonal Variability In Cmip6 Projections Of Sahelian Precipitation, Emmanuel Ogwuche Audu
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
The uncertainty in model projections of future precipitation across the Sahel has persisted across many generations of Earth System Models (ESMs), with some models predicting drying and others moistening across this region. These discrepancies in future projections pose a challenge for stakeholders and decision makers. Many projections of Sahel precipitation found in the ESMs participating in the sixth phase of Coupled Model Intercomparison Project (CMIP6) show a zonal dipole in precipitation trend, with moistening across the Central and Eastern Sahel and drying projected for the Western Sahel. Previous studies have connected precipitation variability across the Sahel to changes in various …
Polarimetric Radar Signatures In Significant Severe Left-Moving Supercells, Raychel Nelson
Polarimetric Radar Signatures In Significant Severe Left-Moving Supercells, Raychel Nelson
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
Left-moving (LM) supercells, though rarer than right-moving (RM) supercells, may produce significant severe weather. However, there are very few existing studies on LM supercells, particularly polarimetric radar analyses. The upgrade of the nationwide Weather Surveillance Radar-1988 Doppler (WSR-88D) network to polarimetric capability and subsequent studies vastly improved understanding of RM supercells, but similar efforts have largely not been made for LM supercells. This study employs an automated polarimetric radar signature detection algorithm to examine a dataset of significant severe (hail ≥ 2.00”, wind ≥ 65 kts) LM supercells to quantify their polarimetric signatures. Comparisons are made with RM supercells to …
A Dual-Polarimetric Analysis Of A Large Sample Of Left-Moving Supercells, Ben Schweigert
A Dual-Polarimetric Analysis Of A Large Sample Of Left-Moving Supercells, Ben Schweigert
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
Supercells have been researched extensively since they were first described over 50 years ago. They are prolific severe weather producers, responsible for the most severe hail, severe wind gusts, and tornadoes. These rotating thunderstorms require attention from forecasters to protect life and property from their threats, most effectively done with Doppler radars. While extensive amounts of radar-based investigations have been completed, they focused almost exclusively on right-moving (RM) supercells, resulting in a knowledge gap surrounding their counter-rotating (left-moving, LM) partners. This study works to fill the void by developing a dataset of LM supercells and analyzing the dual-polarimetric features observed …
Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila
Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila
Faculty Publications
This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …
Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee
Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee
Institute for ECHO Articles and Research
The diagonal squall line that passed through the Korean Peninsula on the 18 May 2020 was examined using wind data retrieved from multiple Doppler radar synthesis focusing on its kinematic and dynamic aspects. The low-level jet, along with warm and moist air in the lower level, served as the primary source of moisture supply during the initiation and formation process. The presence of a cold pool accompanying the squall line played a role in retaining moisture at the surface. As the squall line approached the Korean Peninsula, the convective bands in the northern segment (NS) and southern segment (SS) of …
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Institute for ECHO Articles and Research
The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …
Ground Electric Field, Atmospheric Weather And Electric Grid Variations In Northeast Greece Influenced By The March 2012 Solar Activity And The Moderate To Intense Geomagnetic Storms, Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu, Michael Danakis
Ground Electric Field, Atmospheric Weather And Electric Grid Variations In Northeast Greece Influenced By The March 2012 Solar Activity And The Moderate To Intense Geomagnetic Storms, Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu, Michael Danakis
Mathematics, Physics, and Computer Science Faculty Articles and Research
In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), Interplanetary space (ACE satellite), the Earth’s magnetosphere (Earth-based measurements, NOAA-19 satellite), the top of the clouds (Terra and Aqua satellites), and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather …
Spatial Analyses On Pre-Earthquake Ionospheric Anomalies And Magnetic Storms Observed By China Seismo-Electromagnetic Satellite In August 2018, Jann-Yeng Tiger Liu, Xuhui Shen, Fu-Yuan Chang, Yuh-Ing Chen, Yang-Yi Sun, Chieh‑Hung Chen, Sergey Pulinets, Katsumi Hattori, Dimitar Ouzounov, Valerio Tramutoli, Michel Parrot, Wei-Sheng Chen, Cheng-Yan Liu, Fei Zhang, Dapeng Liu, Xue-Min Zhang, Rui Yan, Qiao Wang
Spatial Analyses On Pre-Earthquake Ionospheric Anomalies And Magnetic Storms Observed By China Seismo-Electromagnetic Satellite In August 2018, Jann-Yeng Tiger Liu, Xuhui Shen, Fu-Yuan Chang, Yuh-Ing Chen, Yang-Yi Sun, Chieh‑Hung Chen, Sergey Pulinets, Katsumi Hattori, Dimitar Ouzounov, Valerio Tramutoli, Michel Parrot, Wei-Sheng Chen, Cheng-Yan Liu, Fei Zhang, Dapeng Liu, Xue-Min Zhang, Rui Yan, Qiao Wang
Mathematics, Physics, and Computer Science Faculty Articles and Research
The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric …
Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer
Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer
Department of Biological Systems Engineering: Papers and Publications
Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N2O and CH4 emissions data. For net CO2 emissions, increases in soil organic C (SOC) were applied as a proxy, …