Cloud Tuning

Cloud Tuning is a methodological framework within atmospheric modeling that systematically adjusts cloud parameterization schemes in climate or weather prediction models to better align with observational data or high-resolution simulations.

6

Publications

2K

Citations

55

Authors

15

Institutions

Publications per year

2017–2026

2

Variants

Cloud Parameter Tuning

Authors

55

  1. LW
    Larry W. Horowitz

    NOAA Geophysical Fluid Dynamics Laboratory, United States

    2 publications · 1.9K citations

    2

    h-index

  2. JG
    Jean‐Christophe Golaz

    Lawrence Livermore National Laboratory, United States

    2 publications · 245 citations

    2

    h-index

  3. SM
    Sergey Malyshev

    Princeton University, United States

    1 publications · 1.7K citations

    1

    h-index

  4. PC
    P. C. D. Milly

    United States Geological Survey, United States

    1 publications · 1.7K citations

    1

    h-index

  5. VR
    V. Ramaswamy

    NOAA Geophysical Fluid Dynamics Laboratory, United States

    1 publications · 1.7K citations

    1

    h-index

1–5 of 55

Venues

  1. Geophysical Research Letters

    2 publications · 245 citations

    2

    h-index

  2. Journal of Climate

    1 publications · 1.7K citations

    1

    h-index

  3. Biomacromolecules

    1 publications · 53 citations

    1

    h-index

  4. IEEE Internet Computing

    1 publications · 13 citations

    1

    h-index

  5. IEEE Transactions on Cloud Computing

    1 publications · 12 citations

1–5