A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net
Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often cannot accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-01-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/16/3/442 |
_version_ | 1797318315674173440 |
---|---|
author | Liwen Wang Qian Li Xuan Peng Qi Lv |
author_facet | Liwen Wang Qian Li Xuan Peng Qi Lv |
author_sort | Liwen Wang |
collection | DOAJ |
description | Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often cannot accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently can capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods. |
first_indexed | 2024-03-08T03:49:41Z |
format | Article |
id | doaj.art-46cf266ab21b4a4fba85de6ce826a48d |
institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-08T03:49:41Z |
publishDate | 2024-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Remote Sensing |
spelling | doaj.art-46cf266ab21b4a4fba85de6ce826a48d2024-02-09T15:21:07ZengMDPI AGRemote Sensing2072-42922024-01-0116344210.3390/rs16030442A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-NetLiwen Wang0Qian Li1Xuan Peng2Qi Lv3College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, ChinaTemporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often cannot accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently can capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods.https://www.mdpi.com/2072-4292/16/3/442temporal downscalingU-Netflow regularizationresidual blocksERA5 |
spellingShingle | Liwen Wang Qian Li Xuan Peng Qi Lv A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net Remote Sensing temporal downscaling U-Net flow regularization residual blocks ERA5 |
title | A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net |
title_full | A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net |
title_fullStr | A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net |
title_full_unstemmed | A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net |
title_short | A Temporal Downscaling Model for Gridded Geophysical Data with Enhanced Residual U-Net |
title_sort | temporal downscaling model for gridded geophysical data with enhanced residual u net |
topic | temporal downscaling U-Net flow regularization residual blocks ERA5 |
url | https://www.mdpi.com/2072-4292/16/3/442 |
work_keys_str_mv | AT liwenwang atemporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT qianli atemporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT xuanpeng atemporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT qilv atemporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT liwenwang temporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT qianli temporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT xuanpeng temporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet AT qilv temporaldownscalingmodelforgriddedgeophysicaldatawithenhancedresidualunet |