Convolutional Long Short-Term Memory network for generating 100 m daily near-surface air temperature
Abstract Global warming and urbanization serve as critical research themes in fine-scale climate studies, particularly in developed cities. This study aims to provide a high spatiotemporal resolution dataset of near-surface air temperatures for densely developed urban areas. The dataset comprises da...
Saved in:
| Main Authors: | Mengqi Sun, Qingyan Meng, Linlin Zhang, Xinli Hu, Xuewen Lei, Shize Chen, Junyan Hou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05032-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Air quality prediction using stacked bi- long short-term memory and convolutional neural network in India
by: S Karkuzhali, et al.
Published: (2024-12-01) -
Daily rainfall prediction using long short-term memory (LSTM) algorithm
by: B SUDARSAN PATRO, et al.
Published: (2024-12-01) -
Air Temperature Variations Analysis of the Hualian M6.9 Earthquake
by: Xian Lu, et al.
Published: (2024-12-01) -
Cultural Memory: to 100th Anniversary of A. M. Gorky Stay in German Saarov
by: T. V. Kudryavtseva
Published: (2023-02-01) -
Daily inflow forecasting in Asomata reservoir, on Aliakmon River, using Long Short-Term Memory network
by: Neagoe Angela, et al.
Published: (2025-01-01)