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  1. null (Ed.)
    Abstract Using multiple independent satellite and reanalysis datasets, we compare relationships between mesoscale convective system (MCS) precipitation intensity P max , environmental moisture, large-scale vertical velocity, and system radius among tropical continental and oceanic regions. A sharp, nonlinear relationship between column water vapor and P max emerges, consistent with nonlinear increases in estimated plume buoyancy. MCS P max increases sharply with increasing boundary layer and lower free tropospheric (LFT) moisture, with the highest P max values originating from MCSs in environments exhibiting a peak in LFT moisture near 750 hPa. MCS P max exhibits strikingly similar behavior as a function of water vapor among tropical land and ocean regions. Yet, while the moisture– P max relationship depends strongly on mean tropospheric temperature, it does not depend on sea surface temperature over ocean or surface air temperature over land. Other P max -dependent factors include system radius, the number of convective cores, and the large-scale vertical velocity. Larger systems typically contain wider convective cores and higher P max , consistent with increased protection from dilution due to dry air entrainment and reduced reevaporation of precipitation. In addition, stronger large-scale ascent generally supports greater precipitation production. Last, temporal lead–lag analysis suggests that anomalous moisture in the lower–middle troposphere favors convective organization over most regions. Overall, these statistics provide a physical basis for understanding environmental factors controlling heavy precipitation events in the tropics, providing metrics for model diagnosis and guiding physical intuition regarding expected changes to precipitation extremes with anthropogenic warming. 
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  2. Abstract

    Mesoscale convection generates the majority of extreme precipitation in tropical regions. Changes to these precipitation intensities,P, with long‐term modes of climate variability have been hard to assess because they are not well represented in current climate models. Here we stratify a satellite climatology of convective systems by El Niño phase and cloud top temperature. We find that gains (losses) in high precipitation intensity ( 10 mm hr−1) are largest for the deepest (least deep) systems during El Niño relative to La Niña. The surface temperature and wind changes that define El Niño manifest as surface flux changes but are not sufficient to explain thesetrends. We explore also the dynamical component of precipitation generation with a vertical momentum budget. Midtropospheric drying in the vicinity of the deepest systems boosts instability and ascent rates during El Niño, while the strengthened large‐scale ascent minimizes the drag force on their updrafts.

     
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  3. Abstract

    Convective organization has a large impact on precipitation and feeds back on larger‐scale circulations in the tropics. The degree of this convective organization changes with modes of climate variability like the El Niño–Southern Oscillation (ENSO), but because organization is not represented in current climate models, a quantitative assessment of these shifts has not been possible. Here, we construct multidecade satellite climatologies of occurrence of tropical convective organization and its properties and assess changes with ENSO phase. The occurrence of organized deep convection becomes more concentrated, increasing threefold in the eastern and central Pacific during El Niño and decreasing twofold outside of these regions. Both horizontal extent of the cold cloud shield and convective depth increase in regions of positive sea surface temperature anomaly (SSTa); however, the regions of greatest convective deepening are those of large‐scale ascent, rather than those of warmest SSTa. Extent decreases with SSTa at a rate of about 20 km/K, while the SSTa dependence of depth is only about 0.2 K/K. We introduce two values to describe convective changes with ENSO more succinctly: (1) an information entropy metric to quantify the clustering of convective system occurrences and (2) a growth metric to quantify deepening relative to spreading over the system lifetime. Finally, with collocated precipitation data, we see that rainfall attributable to convective organization jumps up to 5% with warming. Rain intensity and amount increase for a given system size during El Niño, but a given rain amount may actually fall with higher intensity during La Niña.

     
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