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Scott W. Powell

Abstract

Processes responsible for widespread development of moderately deep cumulonimbi during a transition period before onset of two large-scale convective events associated with the Madden–Julian oscillation in late 2011 are investigated. A regional model (WRF) is capable of rapidly producing an approximately 3-day-long transition period prior to MJO convective onset similar to observed transition periods, during which moderately deep cumulonimbi were prevalent. During transition periods, evaporation in precipitating elements and horizontal advection of moisture away from the clouds in the nearby clear-air environment contributed to humidification below 400 hPa. Nonprecipitating clouds were present in the model mostly between 900 and 950 hPa and had no major impact on tropospheric moistening. Whether nonprecipitating cumuli grew into moderately deep cumulonimbi largely depended on the buoyancy of updrafts that extended into the 700–850-hPa layer. As mean environmental temperatures decreased, the mean cumulus updraft buoyancy in this layer became less negative. The start of two simulated transition periods were marked by rapid decreases in environmental temperature caused by reduction in environmental subsidence and/or increased cooling by advection or radiation. Small, widespread changes in the difference between 700- and 850-hPa environmental and updraft temperatures—on the order of 0.1 K and less than 0.4 K—had important ramifications for whether shallow clouds grew vertically into moderately deep clouds that moistened the troposphere and made it conducive to MJO convective onset.

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Scott W. Powell

Abstract

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.

Significance Statement

A numerical model is utilized to investigate potential thermodynamic and dynamic quantities related to the growth of cumulus clouds into cumulonimbus clouds over tropical oceans when the atmosphere is sufficiently moist to support rainfall. Archimedean buoyancy alone cannot be used to predict rain rate reliably. Instead the total buoyancy not relative to an arbitrary reference state must be considered. The simulated relationship between total vertical acceleration in updrafts and rain rate was robust. While the processes that control the vertical acceleration remain unclear, our results highlight the importance of observing processes that occur on spatial scales of tens of meters and temporal scales of a few minutes.

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Scott W. Powell

Abstract

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.

Free access
Scott W. Powell

Abstract

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.

Significance Statement

Cumulonimbus clouds are responsible for many extreme weather phenomena and are important contributors to Earth’s energy balance. However, the processes leading to the growth of individual clouds are not completely understood nor well-represented in weather prediction models. We find that the clouds containing updrafts that start out wider at early stages of their life cycles grow taller, possibly because they are protected more from drier air outside the cloud than narrow clouds. In addition, this work shows how the initial width of clouds might be related to convergence in the lowest part of the atmosphere, at heights where clouds initially develop. However, meteorologists must be careful not to overinterpret these results because numerical simulations inherently include assumptions that may not reflect reality. This reinforces the need to also observe processes occurring at the scales of individual clouds.

Open access
Scott W. Powell
and
Michael M. Bell

Abstract

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.

Full access
Scott W. Powell
,
Robert A. Houze, Jr.
, and
Stella R. Brodzik

Abstract

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.

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Naoko Sakaeda
,
Scott W. Powell
,
Juliana Dias
, and
George N. Kiladis

Abstract

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.

Full access
Pedro Ortiz
,
Eleanor Casas
,
Marko Orescanin
,
Scott W. Powell
,
Veljko Petkovic
, and
Micky Hall

Abstract

Visible and infrared radiance products of geostationary orbiting platforms provide virtually continuous observations of Earth. In contrast, low-Earth orbiters observe passive microwave (PMW) radiances at any location much less frequently. Prior literature demonstrates the ability of a machine learning (ML) approach to build a link between these two complementary radiance spectra by predicting PMW observations using infrared and visible products collected from geostationary instruments, which could potentially deliver a highly desirable synthetic PMW product with nearly continuous spatiotemporal coverage. However, current ML models lack the ability to provide a measure of uncertainty of such a product, significantly limiting its applications. In this work, Bayesian deep learning is employed to generate synthetic Global Precipitation Measurement (GPM) Microwave Imager (GMI) data from Advanced Baseline Imager (ABI) observations with attached uncertainties over the ocean. The study first uses deterministic residual networks (ResNets) to generate synthetic GMI brightness temperatures with as little mean absolute error as 1.72 K at the ABI spatiotemporal resolution. Then, for the same task, we use three Bayesian ResNet models to produce a comparable amount of error while providing previously unavailable predictive variance (i.e., uncertainty) for each synthetic data point. We find that the Flipout configuration provides the most robust calibration between uncertainty and error across GMI frequencies, and then demonstrate how this additional information is useful for discarding high-error synthetic data points prior to use by downstream applications.

Open access
David S. Nolan
,
Scott W. Powell
,
Chidong Zhang
, and
Brian E. Mapes

Abstract

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.

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Scott W. Powell
,
Robert A. Houze Jr.
,
Anil Kumar
, and
Sally A. McFarlane

Abstract

Vertically pointing millimeter-wavelength radar observations of anvil clouds extending from mesoscale convective systems (MCSs) that pass over an Atmospheric Radiation Measurement Program (ARM) field site in Niamey, Niger, are compared to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model using six different microphysical schemes. The radar data provide the statistical distribution of the radar reflectivity values as a function of height and anvil thickness. These statistics are compared to the statistics of the modeled anvil cloud reflectivity at all altitudes. Requiring the model to be statistically accurate at all altitudes is a stringent test of the model performance. The typical vertical profile of radiative heating in the anvil clouds is computed from the radar observations. Variability of anvil structures from the different microphysical schemes provides an estimate of the inherent uncertainty in anvil radiative heating profiles. All schemes underestimate the optical thickness of thin anvils and cirrus, resulting in a bias of excessive net anvil heating in all of the simulations.

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