Browsing UMBC Physics Department by Author "Gangopadhyay, Aryya"
Now showing items 1-6 of 6
-
Assessing Water Budget Sensitivity to Precipitation Forcing Errors in Potomac River Basin Using the VIC Hydrologic Model CyberTraining: Big Data + High-Performance Computing + Atmospheric Sciences
Majumder, Reetam; Walid, Redwan; Zheng, Jianyu; Zhang, Zhibo; Wang, Jianwu; Gobbert, Matthias K.; Gangopadhyay, Aryya; Barajas, Carlos; Guo, Pei; Rajapakshe, Chamara; Markert, Kel; Mehta, Amita; Neerchal, Nagaraj K. (2019)The Potomac River Basin is a watershed located on the East Coast of the USA across West Virginia, Virginia, Pennsylvania, Maryland, and the District of Columbia. Inter-annual variations in precipitation makes it challenging ... -
Benchmarking parallel implementations of cloud type clustering from satellite data
Barajas, Carlos A.; Mukherjee, Lipi; Guo, Pei; Hoban, Susan; Jin, Daeho; Gangopadhyay, Aryya; Wang, JianwuThe study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. The aim of this project is to use machine learning in conjunction with parallel ... -
Benchmarking Parallel K-Means Cloud Type Clustering from Satellite Data
Barajas, Carlos; Guo, Pei; Mukherjee, Lipi; Hoban, Susan; Wang, Jianwu; Jin, Daeho; Gangopadhyay, Aryya; Gobbert, Matthias K. (Springer, Cham, 2019-10-08)The study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. Clustering is a common machine learning technique used in atmospheric science to ... -
A Deep Learning Model for Detecting Dust in Earth's Atmosphere from Satellite Remote Sensing Data
Hou, Ping; Guo, Pei; Wu, Peng; Wang, Jianwu; Gangopadhyay, Aryya; Zhang, Zhibo (IEEE, 2020-11-06)In this paper we develop a deep learning model to distinguish dust from cloud and surface using satellite remote sensing image data. The occurrence of dust storms is increasing along with global climate change, especially ... -
Machine Learning Based Algorithms for Global Dust Aerosol Detection From Satellite Images: Inter-Comparisons and Evaluation
Lee, Jangho; Shi, Yingxi Rona; Cai, Changjie; Ciren, Pubu; Wang, Jianwu; Gangopadhyay, Aryya; Zhang, Zhibo (2020-12-08)Identifying dust aerosols from passive satellite images is of great interest for many applications. In this study, we developed 5 different machine-learning (ML) and deep-learning (DL) based algorithms, including Logistic ... -
Multidisciplinary Education on Big Data + HPC + Atmospheric Sciences
Wang, Jianwu; Gobbert, Matthias K.; Zhang, Zhibo; Gangopadhyay, Aryya; Page, Glenn G. (National Science Foundation, 2017-11-01)We present a new initiative to create a training program or graduate-level course (cybertraining.umbc.edu) in big data applied to atmospheric sciences as application area and using high-performance computing as indispensable ...