an improvement of wind velocity estimation from radar doppler spectra in the upper mesosphere

Clicks: 78
ID: 244693
2001
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #365 of 484 articles by views in journal of food measurement and characterization

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 484 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
We have developed a new parameter estimation method for Doppler wind spectra in the mesosphere observed with an MST radar such as the MU radar in the DBS (Doppler Beam Swinging) mode. Off-line incoherent integration of the Doppler spectra is carried out with a new algorithm excluding contamination by strong meteor echoes. At the same time, initial values on a least square fitting of the Gaussian function are derived using a larger number of integration of the spectra for a longer time and for multiple heights. As a result, a significant improvement has been achieved with the probability of a successful fitting and parameter estimation above 80 km. The top height for the wind estimation has been improved to around 95 km. A comparison between the MU radar and the High Resolution Doppler Imager (HRDI) on the UARS satellite is shown and the capability of the new method for a validation of a future satellite mission is suggested.

Key words. Meteorology and atmospheric dynamics (middle atmosphere dynamics) – Radio science (remote sensing; signal processing)
Reference Key
takeda2001annalesan Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;S. Takeda;S. Takeda;T. Nakamura;T. Tsuda
Journal journal of food measurement and characterization
Year 2001
DOI
10.5194/angeo-19-837-2001
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.