- 1NVIDIA, Seoul, Korea, Republic of (hryu@nvidia.com)
- 2DILab, Seoul, , Repulic of Korea
Recent trends in climate change and global warming have amplified the occurrence of severe convective initiation (CI) and other extreme weather events, underscoring the importance of high-frequency remote sensing. Modern satellite constellations such as EUMETSAT, GOES, Himawari, and GK2A now offer global monitoring intervals of 10 minutes and regional updates as frequent as 1–2 minutes. However, these capabilities are not universally accessible—many developing countries lack in-orbit assets or historical high-frequency data archives.
This study presents a zero-shot video frame interpolation (VFI) approach to generate high-frequency (1–10 minute) satellite imagery from legacy or sparsely sampled observations. Leveraging a flexible Many-to-Many Splatting VFI model, our framework avoids domain-specific retraining while delivering reliable intermediate frames. We validate the method using overlapping data from the KMA GK2A (10-minute full-disk, 2-minute Asia-Pacific) and KMA COMS (3-hour full-disk, 15-minute Asia-Pacific) satellites over the period July 25, 2019, to March 31, 2020.
Our results indicate significant improvements in both PSNR and SSIM metrics, confirming the model’s efficacy in three critical applications:
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Up-sampling Archived Geostationary Data
- Enhancing the temporal resolution of older satellite imagery (e.g., COMS 30-minute or 3-hour intervals) to match or approximate modern satellite capabilities (e.g., GK2A 10-minute intervals). This harmonization facilitates unified climatology analyses spanning multiple generations of instruments.
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Sensor-Error Correction and Gap Filling
- Recovering missing or corrupted frames resulting from attitude adjustments, sensor calibrations, or malfunctions on geostationary satellites. Ensuring a continuous record provides more robust inputs to operational forecasting and climate assessments.
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Delayed High-Frequency Observation Services
- Enabling resource-constrained meteorological agencies to retrospectively produce and disseminate high-frequency satellite products (e.g., near 1-minute intervals) to improve nowcasting, risk assessment, and disaster preparedness.
Our preliminary findings show minimal computational overhead per inference step, making this cost-effective method feasible for near-real-time deployment and post-event analyses alike. By bridging temporal gaps in global satellite datasets, this technique supports advanced level-2 products such as cloud-tracking and convective-initiation alerts, thereby driving broader socioeconomic and scientific benefits in both developed and developing regions.
How to cite: Ryu, H. and Choi, Y.: Toward High-Frequency Satellite Observations in Data-Sparse Regions: A Zero-Shot Interpolation Framework for Missing and Historical Imagery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17456, https://doi.org/10.5194/egusphere-egu25-17456, 2025.