Pattanaik et al. (2025) Weather prediction models for scatterometer satellite data

Identification

• Journal: Elsevier eBooks
• Year: 2025
• Date: 2025-11-14
• Authors: Srinibas Pattanaik, K. K. Gupta, Disha Sharma, Alessandro Vinciarelli
• DOI: 10.1016/b978-0-443-31380-6.00009-x

Research Groups

Department of Computer Science & Engineering, Chandigarh University, Mohali, Punjab, India

Short Summary

This paper highlights the critical role of scatterometer satellite data in enhancing weather prediction models by providing accurate ocean surface wind speed and direction, thereby improving the performance of numerical weather prediction systems.

Objective

• To describe the fundamental role and application of scatterometer satellite data in improving the accuracy and capabilities of modern weather prediction models, particularly for ocean surface wind analysis.

Study Configuration

• Spatial Scale: Global (covering the entire Earth's surface and oceans).
• Temporal Scale: Short to medium-range weather forecasts (days in advance).

Methodology and Data

• Models used: Numerical Weather Prediction (NWP) models, specifically GFS (Global Forecast System) and ECMWF (European Centre for Medium-Range Weather Forecasts).
• Data sources: Satellite scatterometer data (measuring backscattered microwave signals), other observational data.

Main Results

• Scatterometer satellite data is crucial for accurately determining ocean surface wind speed and direction.
• The assimilation of scatterometer data into NWP models like GFS and ECMWF significantly enhances the accuracy and resolution of global weather and ocean forecasts.
• This data provides essential information about ocean surface roughness, which is directly correlated with wind conditions.

Contributions

• This chapter synthesizes the established importance and application of scatterometer satellite data in modern weather prediction, highlighting its role in improving global numerical weather prediction models and oceanographic research.

Funding

• Not explicitly stated in the provided text.

Citation

@article{Pattanaik2025Weather,
  author = {Pattanaik, Srinibas and Gupta, K. K. and Sharma, Disha and Vinciarelli, Alessandro},
  title = {Weather prediction models for scatterometer satellite data},
  journal = {Elsevier eBooks},
  year = {2025},
  doi = {10.1016/b978-0-443-31380-6.00009-x},
  url = {https://doi.org/10.1016/b978-0-443-31380-6.00009-x}
}