Accuracy evaluation and comparison of GSMaP series for retrieving precipitation on the eastern edge of the Qinghai-Tibet Plateau DOI Creative Commons

Chun Zhou,

Li Zhou, Juan Du

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 56, P. 102017 - 102017

Published: Oct. 19, 2024

Language: Английский

A state-of-the-art review of long short-term memory models with applications in hydrology and water resources DOI
Zhong-kai Feng, J. Zhang, Wen-jing Niu

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: unknown, P. 112352 - 112352

Published: Oct. 1, 2024

Language: Английский

Citations

8
From bias to accuracy: Transforming satellite precipitation data in arid regions with machine learning and topographical insights DOI Creative Commons
Faisal Baig, Luqman Ali, Muhammad Abrar Faiz

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132801 - 132801

Published: Feb. 1, 2025

Language: Английский

Citations

0
Hourly calibration algorithm for Fengyun-2G quantitative precipitation estimates using spatial random forest and improved temporal disaggregation scheme DOI
Hao Wu, Bin Yong, Zhehui Shen

et al.

Atmospheric Research, Journal Year: 2025, Volume and Issue: unknown, P. 108061 - 108061

Published: March 1, 2025

Language: Английский

Citations

0
Artificial Intelligence for Climate Change Biology: From Data Collection to Predictions DOI
Ofir Levy,

Shimon Shahar

Integrative and Comparative Biology, Journal Year: 2024, Volume and Issue: 64(3), P. 953 - 974

Published: July 30, 2024

Synopsis In the era of big data, ecological research is experiencing a transformative shift, yet big-data advancements in thermal ecology and study animal responses to climate conditions remain limited. This review discusses how data analytics artificial intelligence (AI) can significantly enhance our understanding microclimates behaviors under changing climatic conditions. We explore AI’s potential refine microclimate models analyze from advanced sensors camera technologies, which capture detailed, high-resolution information. integration allow researchers dissect complex physiological processes with unprecedented precision. describe AI modeling through improved bias correction downscaling techniques, providing more accurate estimates that animals face various scenarios. Additionally, we capabilities tracking these conditions, particularly innovative classification utilize such as accelerometers acoustic loggers. For example, widespread usage traps benefit AI-driven image accurately identify thermoregulatory responses, shade panting. therefore instrumental monitoring interact their environments, offering vital insights into adaptive behaviors. Finally, discuss data-driven approaches inform conservation strategies. particular, detailed mapping microhabitats essential for species survival adverse guide design climate-resilient restoration programs prioritize habitat features crucial biodiversity resilience. conclusion, convergence AI, science heralds new precision conservation, addressing global environmental challenges 21st century.

Language: Английский

Citations

3
Enhanced rainfall nowcasting of tropical cyclone by an interpretable deep learning model and its application in real-time flood forecasting DOI
Li Liu, Xiao Liang, Yue‐Ping Xu

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 131993 - 131993

Published: Sept. 1, 2024

Language: Английский

Citations

3
Accuracy evaluation and comparison of GSMaP series for retrieving precipitation on the eastern edge of the Qinghai-Tibet Plateau DOI Creative Commons

Chun Zhou,

Li Zhou, Juan Du

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 56, P. 102017 - 102017

Published: Oct. 19, 2024

Language: Английский

Citations

1