Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1195-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-1195-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Mar 2023
Research article |
| 08 Mar 2023
| 08 Mar 2023
Optimizing cloud motion estimation on the edge with phase correlation and optical flow
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Paytsar Muradyan
Argonne National Laboratory, Lemont, Illinois, USA
Rajesh Sankaran
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Robert C. Jackson
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Seongha Park
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Sean A. Shahkarami
Argonne National Laboratory, Lemont, Illinois, USA
Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA
Dario Dematties
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Yongho Kim
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Joseph Swantek
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Neal Conrad
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Wolfgang Gerlach
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Sergey Shemyakin
Argonne National Laboratory, Lemont, Illinois, USA
Consortium for Advanced Science and Engineering, University of Chicago, Chicago, Illinois, USA
Pete Beckman
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Nicola J. Ferrier
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Scott M. Collis
Northwestern-Argonne Institute of Science and Engineering, Northwestern University, Evanston, Illinois, USA
Argonne National Laboratory, Lemont, Illinois, USA
Data sets
Total Sky Imager (TSISKYIMAGE) D. Flynn and V. Morris https://doi.org/10.5439/1025309
ceil V. Morris, D. Zhang, and B. Ermold https://doi.org/10.5439/1181954
915-MHz Radar Wind Profiler/RASS (RWP915): wind consensus data P. Muradyan and R. Coulter https://doi.org/10.5439/1025135
Model code and software
RBhupi/plugin-cmv-fftpc: check previouse release for fftpc S. Shahkarami, dariodematties, and B. Raut https://doi.org/10.5281/zenodo.7676068
Short summary
We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion using a total sky imager (TSI). Shorter frame intervals and larger block sizes improve stability, while image resolution and color channels have minor effects. Raindrop contamination can be identified by the rotational motion of the TSI mirror. The correlations of cloud motion vectors (CMVs) from the PC method with wind data vary from 0.38 to 0.59. Optical flow vectors are more stable than PC vectors.
We studied the stability of a blockwise phase correlation (PC) method to estimate cloud motion...
