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. Upper tropospheric (UT) cloud systems constructed from AtmosphericInfrared Sounder (AIRS) cloud data provide a horizontal emissivitystructure, allowing the convective core to be linked to anvil properties. By usingmachine learning techniques, we composed a horizontally complete picture ofthe radiative heating rates deduced from CALIPSO lidar and CloudSat radarmeasurements, which are only available along narrow nadir tracks. To trainthe artificial neural networks, we combined the simultaneous AIRS, CALIPSOand CloudSat data with ERA-Interim meteorological reanalysis data in thetropics over a period of 4 years.The resulting non-linear regression models estimate the radiative heatingrates as a function of about 40 cloud, atmospheric and surface properties,with a column-integrated mean absolute error (MAE) of 0.8 K d−1 (0.5 K d−1) for cloudy scenes and 0.4 K d−1 (0.3 K d−1) for clear sky in the longwave(shortwave) spectral domain. Developing separate models for (i) high opaqueclouds, (ii) cirrus, (iii) mid- and low-level clouds and (iv) clear sky,independently over ocean and over land, leads to a small improvement, whenconsidering the profiles. These models were applied to the whole AIRS clouddataset, combined with ERA-Interim, to build 3D radiative heating ratefields. Over the deep tropics, UT clouds have a net radiative heating effectof about 0.3 K d−1 throughout the troposphere from 250 hPa downward. This radiative heating enhances the column-integrated latent heating by about 22±3 %. While in warmer regions the net radiative heatingprofile is nearly completely driven by deep convective cloud systems, it isalso influenced by low-level clouds in the cooler regions. The heating ratesof the convective systems in both regions also differ: in the warm regionsthe net radiative heating by the thicker cirrus anvils is vertically moreextended, and their surrounding thin cirrus heat the entire troposphere byabout 0.5 K d−1. The 15-year time series reveal a slight increase of thevertical heating in the upper and middle troposphere by convective systemswith tropical surface temperature warming, which can be linked to deepersystems. In addition, the layer near the tropopause is slightly more heatedby increased thin cirrus during periods of surface warming. While therelative coverage of convective systems is relatively stable with surfacewarming, their depth increases, measured by a decrease of their near-toptemperature of -3.4±0.2 K K−1. Finally, the data reveal a connection of the mesoscale convective system (MCS) heating in the upper and middle troposphere and the (low-level) cloud cooling in the lower atmosphere in the cool regions, with a correlation coefficient equal to 0.72, which consolidates the hypothesis of an energetic connection between the convective regions and the subsidence regions.

3D radiative heating of tropical upper tropospheric cloud systems derived from synergistic A-Train observations and machine learning