ClimDetect: A Benchmark Dataset for Climate Change Detection and Attribution
Sungduk Yu, Brian L. White, Anahita Bhiwandiwalla, Musashi Hinck, Matthew Lyle Olson, Tung Nguyen, Vasudev Lal
2024-09-02
Summary
This paper talks about ClimDetect, a new dataset designed to help researchers detect and understand climate change by analyzing temperature data.
What's the problem?
Detecting changes in temperature due to climate change is important for understanding global warming, but it's challenging to separate human impacts from natural variations in climate. Traditional methods have struggled with this, making it hard to identify clear signs of climate change.
What's the solution?
ClimDetect provides a standardized dataset of over 816,000 daily climate snapshots to improve the accuracy of models that detect climate change signals. This dataset includes various input and target variables used in previous research, ensuring that comparisons across studies are consistent. The authors also explore using advanced tools called vision transformers to analyze the climate data more effectively.
Why it matters?
This research is significant because it offers a valuable resource for scientists studying climate change. By providing a comprehensive dataset and modern analysis techniques, ClimDetect can help improve our understanding of climate patterns and support efforts to address global warming.
Abstract
Detecting and attributing temperature increases due to climate change is crucial for understanding global warming and guiding adaptation strategies. The complexity of distinguishing human-induced climate signals from natural variability has challenged traditional detection and attribution (D&A) approaches, which seek to identify specific "fingerprints" in climate response variables. Deep learning offers potential for discerning these complex patterns in expansive spatial datasets. However, lack of standard protocols has hindered consistent comparisons across studies. We introduce ClimDetect, a standardized dataset of over 816k daily climate snapshots, designed to enhance model accuracy in identifying climate change signals. ClimDetect integrates various input and target variables used in past research, ensuring comparability and consistency. We also explore the application of vision transformers (ViT) to climate data, a novel and modernizing approach in this context. Our open-access data and code serve as a benchmark for advancing climate science through improved model evaluations. ClimDetect is publicly accessible via Huggingface dataet respository at: https://huggingface.co/datasets/ClimDetect/ClimDetect.