Mesoscale Feature Detection

Mesoscale Feature Detection is a methodological framework in meteorological analysis that identifies and characterizes atmospheric phenomena of intermediate spatial and temporal scales, such as mesoscale convective systems and fronts, by distinguishing them from synoptic-scale patterns and microscale turbulence through targeted observational and computational techniques.

35

Publications

1.7K

Citations

125

Authors

76

Institutions

Publications per year

2017–2026

13

Authors

125

  1. HY
    Haiqing Yu

    Ocean University of China, China

    2 publications · 57 citations

    2

    h-index

  2. QX
    Qinwang Xing

    Ocean University of China, China

    2 publications · 57 citations

    2

    h-index

  3. JN
    Jakub Nowosad

    Adam Mickiewicz University in Poznań, Poland

    2 publications · 63 citations

    2

    h-index

  4. PN
    Paweł Netzel

    University of Cincinnati, United States

    2 publications · 63 citations

    2

    h-index

  5. HW
    Hui Wang

    Xiamen University, China

    2 publications · 57 citations

    2

    h-index

1–5 of 125

Venues

  1. Remote Sensing of Environment

    4 publications · 219 citations

    4

    h-index

  2. Journal of Geophysical Research Atmospheres

    JGR · 3 publications · 59 citations

    3

    h-index

  3. Monthly Weather Review

    2 publications · 183 citations

    2

    h-index

  4. Progress In Oceanography

    2 publications · 45 citations

    2

    h-index

  5. Atmospheric measurement techniques

    2 publications · 40 citations

    2

    h-index

1–5