アリゾナ大学の研究者は、2機のNOAA衛星のデータを使って、水蒸気による風を測定するアルゴリズムを開発しました。 Using data from two NOAA satellites, University of Arizona researchers developed an algorithm for measuring wind via water vapor.
2023-04-12 アリゾナ大学
これにより、空気中のすべてのもの、雲、エアロゾル、水蒸気、降水量、放射線を含む風について、新しい知見が得られる可能性がある。これまで風の測定は高価だったが、最近のアルゴリズムの進化により、異なる高度での測定が可能になり、今後衛星による風の測定も進む見込みだ。
＜関連情報＞
- https://news.arizona.edu/story/scientists-develop-new-way-measure-wind
- https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022GL101830
2つの衛星の軌道が重なったハイパースペクトル赤外線サウンダーデータを用いた水平風に対する全球3次元水蒸気フィーチャートラッキング Global Three-Dimensional Water Vapor Feature-Tracking for Horizontal Winds Using Hyperspectral Infrared Sounder Data From Overlapped Tracks of Two Satellites
Amir Ouyed, Nadia Smith, Xubin Zeng, Thomas Galarneau Jr., Hui Su, Ross D. Dixon
Geophysical Research Letters Published: 30 March 2023
DOI:https://doi.org/10.1029/2022GL101830
Abstract
The lack of measurements of three-dimensional (3D) distribution of horizontal wind vectors is a major challenge in atmospheric science. Here, we develop an algorithm to retrieve winds for nine pressure levels at 1° grid spacing from 70°N to 70°S. The retrieval is done by tracking water vapor from the hyperspectral Cross-track Infrared Sounder aboard two polar satellites (NOAA-20 and Suomi-NPP) that have overlapped tracks separated by 50 min. We impose a gross error check by flagging retrievals that are too different from ERA-5 reanalysis. Testing the algorithm for the first week of January and July 2020 indicates that our algorithm yields 104 wind profiles per day and these 3D winds qualitatively agree with ERA-5. Compared with radiosonde data, the errors are within the range of reported errors of cloud-tracking winds.
Key Points
- Horizontal wind vectors are retrieved by tracking water vapor fields from an infrared sounder aboard two polar-orbiting satellites
- Approximately 104 wind profiles are derived per day at nine levels from surface to 100 hPa at 1° resolution from 70°N to 70°S
- Compared to radiosonde data, retrieved winds have similar errors to cloud-tracking winds
Plain Language Summary
We developed an algorithm to derive winds in the tropics and midlatitudes across nine vertical levels from two polar-orbiting satellites carrying high-resolution sounding instruments. Our algorithm yields 104 wind profiles per day. Comparisons with measurements from weather balloons show that our wind retrievals are within the error range of existing satellite wind products (usually at one level at a given time and location) and outperform them in vertical resolution.
