2 citations · 3 across the 6 of their papers we have counts for
6 papers
A Dataset of Weather Station-Scale Photosynthetic Phenology in Mid- to High-Latitude Regions of the Northern Hemisphere
Haiyang Shi
This study extracted photosynthetic phenology indicators (SOS, POS, EOS) from daily GPP data at the weather-station scale for the mid- to high-latitude regions of the Northern Hemi…
Approaches for enhancing extrapolability in process-based and data-driven models in hydrology
Haiyang Shi
The application of process-based and data-driven hydrological models is crucial in modern hydrological research, especially for predicting key water cycle variables such as runoff,…
Evapotranspiration trends over the last 300 years reconstructed from historical weather station observations via machine learning
Haiyang Shi
Estimating historical evapotranspiration (ET) is essential for understanding the effects of climate change and human activities on the water cycle. This study used historical weath…
Extrapolability Improvement of Machine Learning-Based Evapotranspiration Models via Domain-Adversarial Neural Networks
Haiyang Shi
Machine learning-based hydrological prediction models, despite their high accuracy, face limitations in extrapolation capabilities when applied globally due to uneven data distribu…
Impacts of extreme weather events on terrestrial carbon sequestration revealed by weather stations in the Northern Hemisphere
Haiyang Shi
The increasing frequency of global climate extremes has significantly impacted the terrestrial carbon cycle. Extreme weather events such as heatwaves, droughts, and extreme precipi…
Potential of Domain Adaptation in Machine Learning in Ecology and Hydrology to Improve Model Extrapolability
Haiyang Shi
Due to the heterogeneity of the global distribution of ecological and hydrological ground-truth observations, machine learning models can have limited adaptability when applied to…