Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach
A method for estimating atmospheric relative humidity using wind profiler radar and a “cascaded” machine learning algorithm is introduced. Unlike existing methods in the literature, the proposed approach uses only I/Q or moment data from the profiler radar to generate an interm...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10173525/ |
| _version_ | 1797776295445135360 |
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| author | Anas Amaireh Yan Zhang P. W. Chan |
| author_facet | Anas Amaireh Yan Zhang P. W. Chan |
| author_sort | Anas Amaireh |
| collection | DOAJ |
| description | A method for estimating atmospheric relative humidity using wind profiler radar and a “cascaded” machine learning algorithm is introduced. Unlike existing methods in the literature, the proposed approach uses only I/Q or moment data from the profiler radar to generate an intermediate pressure profile, which serves as training data for humidity estimations without requiring temperature as an input feature. The study examines the potential of various machine learning algorithms and evaluates their performance using field data collected by the Hong Kong Observatory between January and June 2021. Importantly, this is the first time a cascading machine-learning solution has been successfully applied to the humidity estimation problem, resulting in a simplified model with reduced complexity and fewer required features. |
| first_indexed | 2024-03-12T22:47:57Z |
| format | Article |
| id | doaj.art-324a03bfcf114a2ba3a370c48b16ec0b |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-03-12T22:47:57Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-324a03bfcf114a2ba3a370c48b16ec0b2023-07-20T23:00:18ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352023-01-01166352637110.1109/JSTARS.2023.329235110173525Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning ApproachAnas Amaireh0https://orcid.org/0000-0002-2721-4872Yan Zhang1https://orcid.org/0000-0002-3533-3484P. W. Chan2School of Electrical and Computer Engineering and Advanced Radar Research Center, University of Oklahoma, Norman, OK, USASchool of Electrical and Computer Engineering and Advanced Radar Research Center, University of Oklahoma, Norman, OK, USAHong Kong Observatory, Kowloon, Hong KongA method for estimating atmospheric relative humidity using wind profiler radar and a “cascaded” machine learning algorithm is introduced. Unlike existing methods in the literature, the proposed approach uses only I/Q or moment data from the profiler radar to generate an intermediate pressure profile, which serves as training data for humidity estimations without requiring temperature as an input feature. The study examines the potential of various machine learning algorithms and evaluates their performance using field data collected by the Hong Kong Observatory between January and June 2021. Importantly, this is the first time a cascading machine-learning solution has been successfully applied to the humidity estimation problem, resulting in a simplified model with reduced complexity and fewer required features.https://ieeexplore.ieee.org/document/10173525/Decision treeensemble treemachine learning (ML)neural network (NN)profiler radarrelative humidity (RH) |
| spellingShingle | Anas Amaireh Yan Zhang P. W. Chan Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Decision tree ensemble tree machine learning (ML) neural network (NN) profiler radar relative humidity (RH) |
| title | Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach |
| title_full | Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach |
| title_fullStr | Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach |
| title_full_unstemmed | Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach |
| title_short | Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach |
| title_sort | atmospheric humidity estimation from wind profiler radar using a cascaded machine learning approach |
| topic | Decision tree ensemble tree machine learning (ML) neural network (NN) profiler radar relative humidity (RH) |
| url | https://ieeexplore.ieee.org/document/10173525/ |
| work_keys_str_mv | AT anasamaireh atmospherichumidityestimationfromwindprofilerradarusingacascadedmachinelearningapproach AT yanzhang atmospherichumidityestimationfromwindprofilerradarusingacascadedmachinelearningapproach AT pwchan atmospherichumidityestimationfromwindprofilerradarusingacascadedmachinelearningapproach |