Cloud Microphysical Retrievals

Cloud Microphysical Retrievals is a methodological framework in atmospheric remote sensing that infers the physical characteristics of cloud particles—such as size, phase, concentration, and shape—from measured radiative signals, distinguished by its reliance on the inversion of observed optical and multispectral data to derive microscale properties of clouds.

564

Publications

42.6K

Citations

1.7K

Authors

433

Institutions

Publications per year

2017–2026

115

Authors

1.7K

  1. PM
    Patrick Minnis

    Langley Research Center, United States

    26 publications · 3.1K citations

    23

    h-index

  2. PY
    Ping Yang

    Texas A&M University, United States

    26 publications · 2.8K citations

    21

    h-index

  3. SP
    Steven Platnick

    Goddard Space Flight Center, United States

    21 publications · 5.4K citations

    19

    h-index

  4. AJ
    Andrew J. Heymsfield

    NSF National Center for Atmospheric Research, United States

    20 publications · 2.4K citations

    19

    h-index

  5. GG
    Gerald G. Mace

    University of Utah, United States

    21 publications · 2.2K citations

    18

    h-index

1–5 of 1.7K

Venues

  1. Journal of Geophysical Research Atmospheres

    JGR · 83 publications · 7.6K citations

    46

    h-index

  2. Atmospheric chemistry and physics

    45 publications · 2.8K citations

    31

    h-index

  3. Journal of Applied Meteorology and Climatology

    JAMC · 39 publications · 2.5K citations

    26

    h-index

  4. Journal of the Atmospheric Sciences

    30 publications · 3.2K citations

    26

    h-index

  5. Journal of Geophysical Research Atmospheres

    JGR · 35 publications · 1.5K citations

    25

    h-index

1–5