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An algorithm used to classify precipitation echoes by rain type without interpolating radar data to a constant height is detailed. The method uses reflectivity data without clutter along the lowest available scan angle so that the classifications yield a more accurate representation of the rain type observed at the surface. The algorithm is based on that of Steiner et al. but is executed within a polar coordinate system. An additional procedure allows for more small, isolated, and/or weak echo objects to be appropriately identified as convective. Echoes in the immediate vicinity of convective cores are included in a new transition category, which consists mostly of echoes for which a convective or stratiform determination cannot be confidently made. The new algorithm more effectively identifies shallow convection embedded within large stratiform regions, correctly identifies isolated shallow and weak convection as such, and more often appropriately identifies periods during which no stratiform precipitation is present.

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.

An idealized large-eddy simulation of a tropical marine cloud population was performed. At any time, it contained hundreds of clouds, and updraft width in shallow convection emerging from a subcloud layer appeared to be an important indicator of whether specific convective elements deepened. In an environment with 80%–90% relative humidity below the 0°C level, updrafts that penetrated the 0°C level were larger at and above cloud base, which occurred at the lifting condensation level near 600 m. Parcels rising in these updrafts appeared to emerge from boundary layer eddies that averaged ∼200 m wider than those in clouds that only reached 1.5–3 km height. The deeply ascending parcels (growers) possessed statistically similar values of effective buoyancy below the level of free convection (LFC) as parcels that began to ascend in a cloud but stopped before reaching 3000 m (nongrowers). The growers also experienced less dilution above the LFC. Nongrowers were characterized by negative effective buoyancy and rapid deceleration above the LFC, while growers continued to accelerate well above the LFC. Growers occurred in areas with a greater magnitude of background convergence (or weaker divergence) in the subcloud layer, especially between 300 m and cloud base, but whether the convergence actually led to eddy widening is unclear.

Idealized simulations of tropical, marine convection depict shallow, nonprecipitating cumuli located beneath the 0°C level transitioning into cumulonimbi that reach up to 12 km and higher. The timing of the transition was only weakly related to environmental stability, and 13 of the 15 simulations run with 5 different lapse-rate profiles had rain develop at nearly the same time after model start. The key quantity that apparently controlled deep convective formation was vertical acceleration inside cloudy updrafts between cloud base and the 0°C level. Below a critical value of updraft vertical acceleration, little rainfall occurred. Just as the domain-mean updraft acceleration reached the critical value, the first convection quickly grew to past 12 km altitude. Then, as acceleration increased above the critical value, rain rate averaged in the model domain increased quickly over about a 3-h-long period. The specific value of the critical updraft acceleration depended on how updrafts were defined and in what layer the acceleration was averaged; however, regardless of how criticality was defined, a robust relationship between domain-mean updraft vertical acceleration and rain rate occurred. Positive acceleration of updrafts below the 0°C level was present below 2.75 km and was largest in the 500 m above cloud base. However, the maximum difference between updraft and environmental temperatures occurred between 2 and 3 km. The domain-mean Archimedean buoyancy of updrafts relative to some reference state was a poor predictor for domain-mean rain rate. The exact value of the critical updraft acceleration likely depends on numerous other factors that were not investigated.

Radar and rawinsonde data from four ground-based observing stations in the tropical Indo-Pacific warm pool were used to identify possible associations of environmental state variables and their vertical profiles with radar-derived rain rate inside a mesoscale radar domain when the column-integrated relative humidity (CRH) exceeds 80%. At CRH exceeding 80%, a wide range—from near 0 to ~50 mm day−1—in rain rate is observed; therefore, tropospheric moisture was a necessary but insufficient condition for deep convection. This study seeks to identify possible factors that inhibit rainfall when the atmosphere is sufficiently moist to support large precipitation rates. The domain-mean rain rate was highly sensitive to the areal coverage of intense, convective rainfall that occurs. There were two fundamentally different instances in which convective area was low. One was when the radar domain is primarily occupied by weakly precipitating, stratiform echoes. The other was when the radar domain contained almost no precipitating echoes of any type. While the former was dependent upon the stage of the convective life cycle seen by radar, the latter was probably dependent upon the convective environment. Areal coverage of convective echoes was largely determined by the number of individual convective echoes rather than their sizes, so changes in the clear-air environment of updrafts might have governed how many updrafts grew into deep cumulonimbi. The most likely environmental influence on convective rainfall identified using rawinsonde data was 900–700-hPa lapse rate; however, processes occurring on spatial scales smaller than a radar domain were probably also important but not investigated.

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.

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.

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.

A mesoscale numerical model with an idealized tropical channel environment is used to study the dynamics of intertropical convergence zones (ITCZs) and the recently identified shallow return flow (SRF) and midlevel inflow (MLI). Four idealized sea surface temperature (SST) distributions are used: a meridionally symmetric SST profile with a sharply peaked SST maximum at the equator, a similar profile with the maximum SST shifted off the equator, a cosine-shaped SST profile with zero gradient at the equator, and an idealized SST profile modeled after the observed SST of the eastern Pacific. The simulations show that both the SRF and the MLI are robust features of the ITCZ. The prior result that the SRF is a sea-breeze-like response to surface temperature gradients is further supported, whereas the MLI is caused by the upper-level maxima in diabatic heating and vertical motion. Simulations with the SST maximum at the equator generate long-lasting, convectively coupled Kelvin waves. When the SST maximum is off the equator, the meridional circulations become highly asymmetric with strong cross-equatorial flow. Tropical cyclones are frequently generated by dynamic instability of the off-equatorial ITCZs. The contributions of the multilevel circulations to regional budgets of mass, water, and moist static energy (MSE) are computed. About 10% of the total water transported into the ITCZ region is transported out by the SRF. The water transport of the MLI is minimal, but its mass and MSE transports are significant, accounting for about ⅓ of the mass and MSE entering the ITCZ region. Eddy fluxes are found to be a large component of the net vertically integrated transport of MSE out of the ITCZ.

This study uses high-resolution rainfall estimates from the S-Polka radar during the DYNAMO field campaign to examine variability of the diurnal cycle of rainfall associated with MJO convection over the Indian Ocean. Two types of diurnal rainfall peaks were found: 1) a late afternoon rainfall peak associated with the diurnal peak in sea surface temperatures (SSTs) and surface fluxes and 2) an early to late morning rainfall peak associated with increased low-tropospheric moisture. Both peaks appear during the MJO suppressed phase, which tends to have stronger SST warming in the afternoon, while the morning peak is dominant during the MJO enhanced phase. The morning peak occurs on average at 0000–0300 LST during the MJO suppressed phase, while it is delayed until 0400–0800 LST during the MJO enhanced phase. This delay partly results from an increased upscale growth of deep convection to broader stratiform rain regions during the MJO enhanced phase. During the MJO suppressed phase, rainfall is dominated by deep and isolated convective cells that are short-lived and peak in association with either the afternoon SST warming or nocturnal moisture increase. This study demonstrates that knowledge of the evolution of cloud and rain types is critical to explaining the diurnal cycle of rainfall and its variability. Some insights into the role of the complex interactions between radiation, moisture, and clouds in driving the diurnal cycle of rainfall are also discussed.