Foundation models for weather and climate data understanding: A comprehensive survey

S Chen, G Long, J Jiang, D Liu, C Zhang - arXiv preprint arXiv:2312.03014, 2023 - arxiv.org
As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric
sciences is increasingly adopting data-driven models, powered by progressive …

Artificial intelligence for climate change biology: from data collection to predictions

O Levy, S Shahar - Integrative and Comparative Biology, 2024 - academic.oup.com
In the era of big data, ecological research is experiencing a transformative shift, yet big-data
advancements in thermal ecology and the study of animal responses to climate conditions …

Groundwater drought risk assessment in the semi-arid Kansai river basin, West Bengal, India using SWAT and machine learning models

A Bera, NK Baranval, R Kumar, SK Pal - Groundwater for Sustainable …, 2024 - Elsevier
Increasing concerns over groundwater drought risks, which threaten water availability and
adversely impact ecosystems, agriculture, and human activities, underscore the necessity of …

Harnessing machine learning for sustainable futures: advancements in renewable energy and climate change mitigation

K Ukoba, OR Onisuru, TC Jen - Bulletin of the National Research Centre, 2024 - Springer
Background Renewable energy and climate change are vital aspects of humanity. Energy is
needed to sustain life on Earth. The exploration and utilisation of traditional fossil-based …

Enhancing Regional Climate Downscaling through Advances in Machine Learning

N Rampal, S Hobeichi, PB Gibson… - … Intelligence for the …, 2024 - journals.ametsoc.org
Despite the sophistication of global climate models (GCMs), their coarse spatial resolution
limits their ability to resolve important aspects of climate variability and change at the local …

[HTML][HTML] A Performance Comparison Study on Climate Prediction in Weifang City Using Different Deep Learning Models

Q Guo, Z He, Z Wang, S Qiao, J Zhu, J Chen - Water, 2024 - mdpi.com
Climate change affects the water cycle, water resource management, and sustainable socio-
economic development. In order to accurately predict climate change in Weifang City, China …

[HTML][HTML] Auto-Machine-Learning Models for Standardized Precipitation Index Prediction in North–Central Mexico

R Magallanes-Quintanar, CE Galván-Tejada… - Climate, 2024 - mdpi.com
Certain impacts of climate change could potentially be linked to alterations in rainfall
patterns, including shifts in rainfall intensity or drought occurrences. Hence, predicting …

[PDF][PDF] Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting.

R Magallanes-Quintanar, CE Galván-Tejada… - …, 2024 - researchgate.net
In the context of climate change, studying changes in rainfall patterns is a crucial area of
research, remarkably so in arid and semi-arid regions due to the susceptibility of human …

Assessing uncertainties and discrepancies in agricultural greenhouse gas emissions estimation in China: A comprehensive review

H Li, X Jin, R Zhao, B Han, Y Zhou, P Tittonell - … Impact Assessment Review, 2024 - Elsevier
Due to diverse methodologies and data sources, China's agricultural greenhouse gas
(AGHG) emissions estimates demonstrate significant variability. A quantitative review was …

Machine learning and CORDEX-Africa regional model for assessing the impact of climate change on the Gilgel Gibe Watershed, Ethiopia

AK Bojer, M Woldetsadik, BH Biru - Journal of Environmental Management, 2024 - Elsevier
Climate change is one of the most pressing challenges of our time, profoundly impacting
global water resources and sustainability. This study aimed to predict the long-term effects of …