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Abstract Observations have shown that tropical convection is influenced by fluctuations in temperature and moisture in the lower free troposphere (LFT; 600–850 hPa), as well as moist enthalpy (ME) fluctuations beneath the 850 hPa level, referred to as the deep boundary layer (DBL; 850–1000 hPa). A framework is developed that consolidates these three quantities within the context of the buoyancy of an entraining plume. A “plume buoyancy equation” is derived based on a relaxed version of the weak temperature gradient (WTG) approximation. Analysis of this equation using quantities derived from the Dynamics of the Madden–Julian Oscillation (DYNAMO) sounding array data reveals that processes occurring within the DBL and the LFT contribute nearly equally to the evolution of plume buoyancy, indicating that processes that occur in both layers are critical to the evolution of tropical convection. Adiabatic motions play an important role in the evolution of buoyancy both at the daily and longer time scales and are comparable in magnitude to horizontal moisture advection and vertical moist static energy advection by convection. The plume buoyancy equation may explain convective coupling at short time scales in both temperature and moisture fluctuations and can be used to complement the commonly used moist static energy budget, which emphasizes the slower evolution of the convective envelope in tropical motion systems. 

This study examines thermodynamic–convection coupling in observations and reanalyses, and attempts to establish process-level benchmarks needed to guide model development. Thermodynamic profiles obtained from the NOAA Integrated Global Radiosonde Archive, COSMIC-1 GPS radio occultations, and several reanalyses are examined alongside Tropical Rainfall Measuring Mission precipitation estimates. Cyclical increases and decreases in a bulk measure of lower-tropospheric convective instability are shown to be coupled to the cyclical amplification and decay of convection. This cyclical flow emerges from conditional-mean analysis in a thermodynamic space composed of two components: a measure of “undiluted” instability, which neglects lower-free-tropospheric (LFT) entrainment, and a measure of the reduction of instability by LFT entrainment. The observational and reanalysis products examined share the following qualitatively robust characterization of these convective cycles: increases in undiluted instability tend to occur when the LFT is less saturated, are followed by increases in LFT saturation and precipitation rate, which are then followed by decreases in undiluted instability. Shallow, convective, and stratiform precipitation are coupled to these cycles in a manner consistent with meteorological expectations. In situ and satellite observations differ systematically from reanalyses in their depictions of lower-tropospheric temperature and moisture variations throughout these convective cycles. When using reanalysis thermodynamic fields, these systematic differences cause variations in lower-free-tropospheric saturation deficit to appear less influential in determining the strength of convection than is suggested by observations. Disagreements among reanalyses, as well as between reanalyses and observations, pose significant challenges to process-level assessments of thermodynamic–convection coupling.

 

Hurricane Matthew locally generated more than 400 mm of rainfall on 8–9 October 2016 over the eastern Carolinas and Virginia as it transitioned into an extratropical cyclone. The heaviest precipitation occurred along a swath situated up to 100–200 km inland from the coast and collocated with enhanced low-tropospheric frontogenesis. Analyses from version 3 of the Rapid Refresh (RAPv3) model indicate that rapid frontogenesis occurred over eastern North and South Carolina and Virginia on 8 October, largely over a 12-h time period between 1200 UTC 8 October and 0000 UTC 9 October. The heaviest rainfall in Matthew occurred when and where spiral rainbands intersected the near-surface front, which promoted the lift of conditionally unstable, moist air. Parallel to the spiral rainbands, conditionally unstable low-tropospheric warm, moist oceanic air was advected inland, and the instability was apparently released as the warm air mass rose over the front. Precipitation in the spiral rainbands intensified on 9 October as the temperature gradient along the near-surface front rapidly increased. Unlike in Hurricane Floyd over the mid-Atlantic states, rainfall totals within the spiral rainbands of Matthew as they approached the near-surface front evidently were not enhanced by release of conditional symmetric instability. However, conditional symmetric instability release in the midtroposphere may have enhanced rainfall 200 km northwest of the near-surface front. Finally, although weak cold-air damming occurred prior to heavy rainfall, damming dissipated prior to frontogenesis and did not impact rainfall totals.

 

Realistically representing the multiscale interactions between moisture and tropical convection remains an ongoing challenge for weather prediction and climate models. In this study, we revisit the relationship between precipitation and column saturation fraction (CSF) by investigating their tendencies in CSF–precipitation space using satellite and radar observations, as well as reanalysis. A well-known, roughly exponential increase in precipitation occurs as CSF increases above a “critical point,” which acts as an attractor in CSF–precipitation space. Each movement away from and subsequent return toward the attractor results in a small net change of the coupled system, causing it to evolve in a cyclical fashion around the attractor. This cyclical evolution is characterized by shallow and convective precipitation progressively moistening the environment and strengthening convection, stratiform precipitation progressively weakening convection, and drying in the nonprecipitating and lightly precipitation regime. This behavior is evident across a range of spatiotemporal scales, suggesting that shortcomings in model representation of the joint evolution of convection and large-scale moisture will negatively impact a broad range of spatiotemporal scales. Novel process-level diagnostics indicate that several models, all implementing versions of the Zhang–McFarlane deep convective parameterization, exhibit unrealistic coupling between column moisture and convection.