Articles | Volume 25, issue 13
https://doi.org/10.5194/acp-25-6857-2025
https://doi.org/10.5194/acp-25-6857-2025
Research article
 | 
04 Jul 2025
Research article |  | 04 Jul 2025

Relationship between latent and radiative heating fields of tropical cloud systems using synergistic satellite observations

Xiaoting Chen, Claudia J. Stubenrauch, and Giulio Mandorli

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Cited articles

Adler, R., Wang, J.-J., Sapiano, M., Huffman, G., Chiu, L., Xie, P. P., Ferraro, R., Schneider, U., Becker, A., Bolvin, D., Nelkin, E., Gu, G., and Program, N. C.: Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly), NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/V56971M6, 2016. a, b
August, T., Klaes, D., Schlüssel, P., Hultberg, T., Crapeau, M., Arriaga, A., O'Carroll, A., Coppens, D., Munro, R., and Calbet, X.: IASI on Metop-A: Operational Level 2 retrievals after five years in orbit, J. Quant. Spectrosc. Ra., 113, 1340–1371, https://doi.org/10.1016/j.jqsrt.2012.02.028, 2012. a
Bayr, T., Latif, M., Dommenget, D., Wengel, C., Harlaß, J., and Park, W.: Mean-state dependence of ENSO atmospheric feedbacks in climate models, Clim. Dynam., 50, 3171–3194, https://doi.org/10.1007/s00382-017-3799-2, 2018. a
Bergman, J. W. and Hendon, H. H.: Cloud Radiative Forcing of the Low-Latitude Tropospheric Circulation: Linear Calculations, J. Atmos. Sci., 57, 2225–2245, https://doi.org/10.1175/1520-0469(2000)057<2225:CRFOTL>2.0.CO;2, 2000. a
Bouniol, D., Roca, R., Fiolleau, T., and Raberanto, P.: Life Cycle–Resolved Observation of Radiative Properties of Mesoscale Convective Systems, J. Appl. Meteorol. Clim., 60, 1091–1104, https://doi.org/10.1175/JAMC-D-20-0244.1, 2021. a
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Short summary
Strongly precipitating mesoscale convective systems produce a large amount of diabatic heating of the atmosphere, influencing atmospheric circulation. Their complete 3D description, attained by machine learning techniques in combination with satellite observations, has enabled a detailed study of the relationship between latent and radiative heating in these cloud systems. Convective organization increases both the average and the vertical gradient of radiative effects of the mesoscale convective systems.
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