Growing Cumulus Clouds Research Articles

An Analysis of the Impact of Vertical Wind Shear on Convection Initiation Using Large-Eddy Simulations: Importance of Wake Entrainment

Abstract The initiation of thunderstorms in environments characterized by strong wind shear presents a forecast challenge because of the complexities of the interactions between growing cumulus clouds and wind shear. Thunderstorms that develop in such environments are often capable of producing high-impact hazards, highlighting the importance of convection initiation in sheared environments. Although recent research has greatly improved understanding of the structure and evolution of rising thermals in unsheared environments, there remains uncertainty in how wind shear influences the convection initiation process. Two large-eddy simulations (75-m horizontal grid spacing) were performed to study this problem. Convection initiation attempts are forced in the simulations through prescribed surface heat fluxes (the initial boundary layers are statistically horizontally homogeneous and quasi–steady state but contain turbulent eddies as a result of random initial temperature perturbations). The only difference between the two simulations is the presence or absence of wind shear above 2 km. Important differences in the entrainment patterns are present between sheared and unsheared growing cumulus clouds. As found in previous research, the overturning circulation associated with rising thermals drives dynamic entrainment in the unsheared clouds. However, in sheared clouds, wake entrainment resulting from the tilting of environmental vorticity is an important dynamic entrainment pathway. This result has implications for both the structure of sheared growing cumulus clouds and for convection initiation in sheared environments. Significance Statement Forecasts of thunderstorm hazards such as tornadoes, hail, and strong winds, require the accurate prediction of when and where thunderstorms form. Unfortunately, predicting thunderstorm formation is not easy, as there are a lot of different factors to consider. One such factor is environmental vertical wind shear, which describes how winds change speed and direction with height. The purpose of this study is to better understand how wind shear impacts developing clouds. Our results demonstrate a specific mechanism, called “wake entrainment,” through which wind shear can weaken developing clouds and potentially prevent them from becoming strong thunderstorms entirely. Understanding this mechanism may be useful for thunderstorm prediction in environments characterized by wind shear.

Entrainment in dry and moist thermals

We study entrainment in dry thermals in neutrally and unstably stratified ambients, and moist thermals in dry-neutrally stratified ambients using direct numerical simulations (DNS). We find, in agreement with results of Lecoanet and Jeevanjee \tb{[J. Atmos. Sci. 76(12), 3785-3801, (2019)]} that turbulence plays a minor role in entrainment in dry thermals in a neutral ambient for Reynolds numbers $Re \lesssim 10^4$. We then show that the net entrainment rate increases when the buoyancy of the thermals increases, either by condensation heating or because of an unstably stratified ambient. This is in contrast with the findings of Morrison et al. [J. Atmos. Sci. 78(3), 797-816, (2021)]. We also show that the role of turbulence is greater in these cases than in dry thermals and, significantly, that the combined action of condensation heating and turbulence creates intense small scale vorticity, destroying the {coherent} vortex ring that is seen in dry and moist laminar thermals. These findings suggest that fully resolved simulations at Reynolds numbers significantly larger than the mixing transition Reynolds number $Re=10^4$ are necessary to understand the role of turbulence in the entrainment in growing cumulus clouds, which consist of a series of thermals rising and decaying in succession.

Evaluation of geostationary satellite observations and the development of a 1–2 h prediction model for future storm intensity

AbstractA study was conducted to gain insights into the use of geostationary satellite‐based indicators for characterizing and identifying growing cumulus clouds that evolve into severe weather producing convective storms. Eleven convective initiation (CI), 41 cloud top temperature–effective radius (T‐re), and 9 additional fields were formed for 340 growing cumulus clouds that were manually tracked for 2 h and checked for association with severe weather to 2–3 h into the future. The geostationary satellite data were at 5 min resolution from Meteosat‐8 on six convectively active days in 2010, 2012, and 2013. The study's goals were to determine which satellite fields are useful to forecasting severe storms and to form a simple model for predicting future storm intensity. The CI fields were applied on 3 × 3 pixel regions, and the T‐re fields were analyzed on 9 × 9 and 51 × 51 pixel domains (needed when forming T‐re vertical profiles). Of the 340 growing cumulus clouds examined, 34 were later associated with severe weather (using European Severe Weather Database reports), with the remaining being nonsevere storms. Using a multivariate analysis, transforming predictors into their empirical posterior probability, and maximizing the Peirce skill score, the best predictors were T1451 (51 × 51 pixel T, where re exceeds 14 µm), TG9 (9 × 9 pixel glaciation T surrounding a growing cloud), and ReBRTG51 (51 × 51 pixel re at the breakpoint T in the T‐re profile). Rapid cloud growth prior to severe storm formation leads to delayed particle growth, colder temperatures of the first 14 µm particles, and lower TG values.

Analysis of Cumulus Cloud Updrafts as Observed with 1-Min Resolution Super Rapid Scan GOES Imagery

Abstract A study was undertaken to examine growing cumulus clouds using 1-min time resolution Super Rapid Scan Operations for Geostationary Operational Environmental Satellite-R (GOES-R) (SRSOR) imagery to diagnose in-cloud processes from cloud-top information. SRSOR data were collected using GOES-14 for events in 2012–14. Use of 1-min resolution SRSOR observations of rapidly changing scenes provides far more insights into cloud processes as compared to when present-day 5–15-min time resolution GOES data are used. For midday times on five days, cloud-top temperatures were cataloged for 71 cumulus clouds as they grew to possess anvils and often overshooting cloud tops, which occurred over 33–152-min time periods. Characteristics of the SRSOR-observed updrafts were examined individually, on a per day basis, and collectively, to reveal unique aspects of updraft behavior, strength, and acceleration as related to the ambient stability profile and cloud-top glaciation. A conclusion is that the 1-min observations capture two specific cumulus cloud growth periods, less rapid cloud growth between the level of free convection and the 0°C isotherm level, followed by more rapid growth shortly after the time of cloud-top glaciation. High correlation is found between estimated vertical motion (w) and the amount of convective available potential energy (CAPE) realized to the cloud-top level as clouds grew, which suggests that updrafts were responding to the local buoyancy quite strongly. Influences of the environmental buoyancy profile shape and evidence of entrainment on cloud growth are also found through these SRSOR data analyses.

Quantitative Differences between Lightning and Nonlightning Convective Rainfall Events as Observed with Polarimetric Radar and MSG Satellite Data

Abstract To increase understanding of the relationships between lightning and nonlightning convective storms, lightning observations from the National Aeronautics and Space Administration (NASA) African Monsoon Multidisciplinary Analyses (NAMMA) campaign were analyzed with Meteosat Second Generation (MSG) geostationary satellite and S-band NASA Polarimetric Doppler Weather Radar (NPOL) data. The study’s goal was to analyze the time evolution of infrared satellite fields and ground-based polarimetric radar during NAMMA to quantify relationships between satellite and radar observations for lightning and nonlightning convective clouds over equatorial Africa. Using NPOL data, very low-frequency arrival time difference lightning data, and MSG Spinning Enhanced Visible and Infrared Imager observations, the physical attributes of growing cumulus clouds, including ice mass production, updraft strength, cloud depth, and cloud-top glaciation were examined. It was found that, on average, the lightning storms had stronger updrafts (seen in the satellite and radar fields), which lead to the formation of deeper clouds (seen in the satellite and radar fields) and subsequently much more ice in the mixed-phase region (as confirmed in radar observations), as well as much more nonprecipitating ice in the top 1 km of the cloud (as quantified in both satellite and radar fields) than the nonlightning storms. Computed radar-derived ice masses in cumulus clouds verifies the traditional MSG indicators of cloud-top glaciation, while NPOL verifies internal structures (i.e., large amounts of graupel) where satellite and radar show strong updrafts.

An Empirical Model for Assessing the Severe Weather Potential of Developing Convection

Abstract The formation and maintenance of thunderstorms that produce large hail, strong winds, and tornadoes are often difficult to forecast due to their rapid evolution and complex interactions with environmental features that are challenging to observe. Given inherent uncertainties in storm development, it is intuitive to predict severe storms in a probabilistic manner. This paper presents such an approach to forecasting severe thunderstorms and their associated hazards, fusing together data from several sources as input into a statistical model. Mesoscale numerical weather prediction (NWP) models have been developed in part to forecast environments favorable to severe storm development. Geostationary satellites, such as the Geostationary Operational Environmental Satellite (GOES) series, maintain a frequently updating view of growing cumulus clouds over the contiguous United States to provide temporal trends in developing convection to forecasters. The Next Generation Weather Radar (NEXRAD) network delivers repeated scans of hydrometeors inside storms, monitoring the intensification of hydrometeor size and extent, as well as hydrometeor motion. Forecasters utilize NWP models, and GOES and NEXRAD data, at different stages of the forecast of severe storms, and the model described in this paper exploits data from each in an attempt to predict severe hazards in a more accurate and timely manner while providing uncertainty information to the forecaster. A preliminary evaluation of the model demonstrates good skill in the forecast of storms, and also displays the potential to increase lead time on severe hazards, as measured relative to the issuance times of National Weather Service (NWS) severe thunderstorm and tornado warnings and occurrence times of severe events in local storm reports.

Adjusting thresholds of satellite‐based convective initiation interest fields based on the cloud environment

The Time‐Space Exchangeability (TSE) concept states that similar characteristics of a given property are closely related statistically for objects or features within close proximity. In this exercise, the objects considered are growing cumulus clouds, and the data sets to be considered in a statistical sense are geostationary satellite infrared (IR) fields that help describe cloud growth rates, cloud top heights, and whether cloud tops contain significant amounts of frozen hydrometeors. In this exercise, the TSE concept is applied to alter otherwise static thresholds of IR fields of interest used within a satellite‐based convective initiation (CI) nowcasting algorithm. The convective environment in which the clouds develop dictate growth rate and precipitation processes, and cumuli growing within similar mesoscale environments should have similar growth characteristics. Using environmental information provided by regional statistics of the interest fields, the thresholds are examined for adjustment toward improving the accuracy of 0–1 h CI nowcasts. Growing cumulus clouds are observed within a CI algorithm through IR fields for many 1000 s of cumulus cloud objects, from which statistics are generated on mesoscales. Initial results show a reduction in the number of false alarms of ~50%, yet at the cost of eliminating approximately ~20% of the correct CI forecasts. For comparison, static thresholds (i.e., with the same threshold values applied across the entire satellite domain) within the CI algorithm often produce a relatively high probability of detection, with false alarms being a significant problem. In addition to increased algorithm performance, a benefit of using a method like TSE is that a variety of unknown variables that influence cumulus cloud growth can be accounted for without need for explicit near‐cloud observations that can be difficult to obtain.

Geostationary infrared methods for detecting lightning‐producing cumulonimbus clouds

This study documents the behavior of cloud top infrared (IR) fields known to describe physical processes associated with growing convective clouds, for 30 nonlightning and 33 cloud‐to‐ground (CG) lightning‐producing convective storms. The goal is to define “critical” threshold values for up to 10 IR fields that delineate lightning from nonlightning convective storms. Meteosat Second Generation and United Kingdom Meteorological Office very low frequency arrival time difference satellite and lightning data, respectively, were used in this study. These were collected during the National Aeronautics and Space Administration (NASA) African Monsoon Multidisciplinary Analyses (NAMMA) field campaign in August–September 2006 in Equatorial Africa. The main conclusions show that eight of 10 IR fields that describe updraft strength, cloud depth, and glaciation (or ice at cloud top) are significantly different between the nonlightning and lightning‐producing convective clouds. The lack of notch overlap in “box and whiskers” plots confirms a 95% confidence that the two data sets are different. Nonlightning‐producing clouds are far less vertically developed and possess >50% weaker updrafts (as estimated from satellite trends), as well as little to no evidence of ice or glaciation at cloud top. Results from this study therefore can be used to nowcast and identify with high confidence convective clouds that are producing or are going to produce CG lightning using Meteosat data, assuming appropriate tracking of growing cumulus clouds is performed.

Use of satellite derived cloud properties to quantify growing cumulus beneath cirrus clouds

The accurate prediction of convective cloud development in advance of thunderstorm formation (so‐called “convective initiation,” CI) is a challenging forecast problem, one in which the processing of 5–15min interval imagery from geostationary satellites (e.g., Meteosat Second Generation) offers considerable promise. A present drawback to using sequences of visible or infrared (IR) satellite images to monitor growing cumulus clouds is that higher altitude cirrus clouds often obscure the view of the low‐level cumulus in the pre‐convective environment. In particular, cirrus anvils from pre‐existing convection, and cirrus caused by deep layer quasi‐geostrophic ascent, are very common in pre‐CI environments. Cloud derived parameters from GOES are used here to demonstrate how quantities like visible optical depth (τ), emittance, liquid water path, and effective particle size can be used to quantify cumulus cloud growth in advance of CI. Time rates of change of these derived quantities, as well as IR interest fields that describe cumulus cloud development rates beneath cirrus, are analyzed as τ of the cirrus are binned from 1 to >50. Results confirm that if cirrus possess τ<20, up to >90% of the “signal” in the IR interest field remains, compared to clear‐sky values, and it is proposed that CI can still be adequately nowcasted using IR channel data similar to what is done in the absence of cirrus. Similarly, cloud derived parameters become valuable as their time rates of change measure cumulus cloud growth beneath the higher clouds. In contrast, once τ values increase beyond ∼20, cumulus cloud growth signals decrease significantly through cirrus, and as τ becomes >40, little information from the cumulus remains.

Use of Meteosat Second Generation optimal cloud analysis fields for understanding physical attributes of growing cumulus clouds

This study develops an understanding on how retrieved cloud parameter fields from the Optimal Cloud Analysis (OCA) algorithm, operating on Meteosat Second Generation (MSG), Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, behave at 5-min time resolutions for growing cumulus clouds. Fields retrieved by the OCA algorithm include cloud optical thickness (τ), cloud-top particle effective radius (r e), cloud-top pressure (p c), and cloud-top phase. OCA is based on a one-dimensional optimal estimation methodology, and a measure of radiance fit, the cost function (J m), is a quantity developed as part of the retrieval process and is shown to be useful in delineating mixed phase clouds; it too is evaluated (at 5-min intervals) for the information it provides. Data for 94 growing cumulus cloud events are processed. An “event” is defined as a cumulus cloud that is monitored at 5-min intervals with OCA, as it grows from the “fair weather” or “towering cumulus” stage to near the cumulonimbus stage when precipitation begins. The hypothesis is that OCA products are of high-enough quality to provide unique information about microphysical processes occurring at and near cloud top. The goal through analysis of the 94 events is to identify consistent, repeating patterns in OCA fields during cloud growth that can be in turn used to infer physical processes. Data from the Convective and Orographically-induced Precipitation Study (June and July 2007) and in four regions of Europe on 25 May 2009 are used. The validity of the OCA data is presented with a comparison to CloudSat Precipitation Radar and MODerate resolution Imaging Spectroradiometer retrieved cloud properties, showing good statistical agreements. Subsequently, results from the analysis of OCA fields for all events show that as cumuli deepen, r e values tend to increase, and then decrease in size as cloud tops glaciate and particle settling begins. The τ magnitudes generally increase as clouds deepen, while p c values and cloud-top temperatures fall as expected. The J m values exhibit the pattern of spiking in magnitude (over a 5–10-min period), which indicates the increase “misfit” within OCA during the mixed phase, at about the time τ values increase substantially as clouds deepen.

The Definition of GOES Infrared Lightning Initiation Interest Fields

Abstract Within cumulus cloud fields that develop in conditionally unstable air masses, only a fraction of the cumuli may eventually develop into deep convection. Identifying which of these convective clouds is most likely to generate lightning often starts with little more than a qualitative visual satellite analysis. The goal of this study is to identify the observed satellite infrared (IR) signatures associated with growing cumulus clouds prior to the first lightning strike, or lightning initiation (LI). This study quantifies the behavior of 10 Geostationary Operational Environmental Satellite-12 (GOES-12) IR fields of interest in the 1 h in advance of LI. A total of 172 lightning-producing storms, which occurred during the 2009 convective season, are manually tracked and studied over four regions: northern Alabama, central Oklahoma, the Kennedy Space Center, and Washington, D.C. Four-dimensional and cloud-to-ground lightning array data provide a total cloud lightning picture (in-cloud, cloud-to-cloud, cloud-to-air, and cloud-to-ground) and thus precise LI points for each storm in both time and space. Statistical significance tests are conducted on observed trends for each of the 10 LI fields to determine the unique information each field provides in terms of behavior prior to LI. Eight out of 10 LI fields exhibited useful information at least 15 min in advance of LI, with 35 min being the average. Statistical tests on these eight fields are compared for separate large geographical areas. Median IR temperatures and 3.9-μm reflectance values are then determined for all 172 events as an outcome, which may be valuable when implementing a LI prediction algorithm into real-time satellite-based systems.

Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part II: Use of Visible Reflectance

AbstractThis study is a companion research effort to “Part I,” which emphasized use of infrared data for understanding various aspects of growing convective clouds in the Meteosat Second Generation (MSG) satellite’s Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery. Reflectance and derived brightness variability (BV) fields from MSG SEVIRI are used here to understand relationships between cloud-top signatures and physical processes for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. This study uses daytime SEVIRI visible (VIS) and near-infrared (NIR) reflectances from 0.6 to 3.9 μm (3-km sampling distance), as well as high-resolution visible (1-km sampling distance) fields. Data from 123 CI events observed during the 2007 Convection and Orographically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, so to meet this study’s objectives. These data are those used in Part I. A total of 27 VIS–NIR and BV “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the fields that contain the most unique information for describing principally cloud-top glaciation, as well as the presence of vigorous updrafts. Time changes in 1.6- and 3.9-μm reflectances, as well as BV in advance of CI, are shown to contain the most unique information related to the formation and increase in size of ice hydrometeors. Several methods are proposed on how results from this analysis may be used to monitor growing convective clouds per MSG pixel or per cumulus cloud “object” over 1-h time frames.

Cloud-Top Properties of Growing Cumulus prior to Convective Initiation as Measured by Meteosat Second Generation. Part I: Infrared Fields

Abstract Infrared (IR) data from the Meteosat Second Generation (MSG) satellite are used to understand cloud-top signatures for growing cumulus clouds prior to known convective initiation (CI) events, or the first occurrence of a ≥35-dBZ echo from a new convective cloud. In the process, this study proposes how MSG IR fields may be used to infer three physical attributes of growing cumuli, cloud depth, cloud-top glaciation, and updraft strength, with limited information redundancy. These three aspects are observed as unique signatures within MSG IR data, for which this study seeks to relate to previous research, as well as develop a new understanding on which subset of IR information best identifies these attributes. Data from 123 subjectively identified CI events observed during the 2007 Convection and Orograpically Induced Precipitation Study (COPS) field experiment conducted over southern Germany and northeastern France are processed, per convective cell, to meet this study’s objectives. A total of 67 IR “interest fields” are initially assessed for growing cumulus clouds, with correlation and principal component analyses used to highlight the top 21 fields that are considered the best candidates for describing the three attributes. Using between 6 and 8 fields per category, a method is then proposed on how growing convective clouds may be quantified per 3-km2 pixel (or per cumulus cloud object) toward inferring each attribute. No independent CI-nowcasting analysis is performed, which instead is the subject of ongoing research.

A Statistical Evaluation of GOES Cloud-Top Properties for Nowcasting Convective Initiation

Abstract The goal of this project is to validate and extend a study by Mecikalski and Bedka that capitalized on information the Geostationary Operational Environmental Satellite (GOES) instruments provide for nowcasting (i.e., 0–1-h forecasting) convective initiation through the real-time monitoring of cloud-top properties for moving cumuli. Convective initiation (CI) is defined as the first occurrence of a ≥35-dBZ radar echo from a cumuliform cloud. Mecikalski and Bedka’s study concluded that eight infrared GOES-based “interest fields” of growing cumulus clouds should be monitored over 15–30-min intervals toward predicting CI: the transition of cloud-top brightness temperature to below 0°C, cloud-top cooling rates, and instantaneous and time trends of channel differences 6.5–10.7 and 13.3–10.7 μm. The study results are as follows: 1) measures of accuracy and uncertainty of Mecikalski and Bedka’s algorithm via commonly used skill scoring procedures, and 2) a report on the relative importance of each interest field to nowcasting CI using GOES. It is found that for nonpropagating convective events, the skill scores are dependent on which CI interest fields are considered per pixel and are optimized when three–four fields are met for a given 1-km GOES pixel in terms of probability of detection, and threat and Heidke skill scores. The lowest false-alarm rates are found when one field is used: that associated with cloud-top glaciation 30 min prior to CI. Subsequent recommendations for future research toward improving Mecikalski and Bedka’s study are suggested especially with regard to constraining CI nowcasts when inhibiting factors are present (e.g., capping inversions).

First Radar Echoes and the EarlyZDRHistory of Florida Cumulus

Abstract The early histories of radar echo and polarization differential reflectivity (ZDR) from growing cumulus clouds observed in Florida with a 10-cm-wavelength radar are reported in detail. Raindrops 1 to several millimeters in diameter are present at about cloud-base level in most cases as soon as any identifiable precipitation echo is seen within cloud (distinct from Bragg scattering and echo from cloud droplets). This is in most cases by the time of the first 10-dBZ radar echo aloft. The very early occurrence of large drops is consistent with origination directly from coalescence on ultragiant aerosol. However, they appear to exist so early and so low in the clouds as to be unexpected if the cumulus were single, vigorous thermals. The explanation may lie in the presence of a more gradual, very early cloud stage that is generally not observed in any detail. Simultaneous Ze and ZDR measurements in the early stages of developing, warm cumulus will provide a powerful test of understanding the onset of ...

A comparison of optical measurements of liquid water content and drop size distribution in adiabatic regions of Florida cumuli

Airborne measurements of liquid water content (LWC) and drop size distribution were made in adiabatic regions of small, growing cumulus clouds during the Small Cumulus Microphysics Study (SCMS). A new instrument, the cloud drop spectrometer (CDS), which measures LWC and also drop size from an ensemble of drops, was flown for the first time in the field. Measurements from other sensors, including a Particle Measuring Systems (PMS) forward scattering spectrometer probe (FSSP), the `fast' FSSP (FFSSP) developed by the Centre National De Recherches Meteorologiques (CNRM), and a Gerber Scientific airborne particulate volume monitor (PVM-100A), are compared with the CDS data collected in adiabatic and other regions. The CDS appeared to reliably measure very close to the predicted value of LWC in regions identified as being adiabatic. In addition, the drop size distribution measured by the CDS compared very well with the FSSP and FFSSP measurements, except where the 3–200 μm range of the CDS allowed it to measure larger drops than the nominal 3–45 μm range of the FSSP, and the 2.7 to 38.4 μm range of the FFSSP.

Vertical gust velocities and variations in normal g associated With clear air turbulence and turbulence in cumulus clouds As studied from ‘ESE data’

'Exercise Storm Exchange' (ESE) is a name given to the Project in which an RAF Cauberra-aircraft PR7/9 was lent to India for undertaking atmospheric studies. The aircraft was flown in India during June to September 1972 from Bangalore, Pune, Calcutta and Agra, to study the synoptic and meso-soale systems in the summer monsoon circulation over India.&#x0D; This paper deals with the analysis of the data on variations in normal gravity (g) and vertical gusts (Vg) encountered by the aircraft in two different conditions – (1) in clear air while it was flying at different levels in the upper troposphere between Bangalore and Trivandrum in July 1972 and (2) while it was flying through growing cumulus clouds in the vicinity of Bangalore on 20 September 1972. Using the data extracted at 0.1 second intervals, the vertical gust velocity and the variations in normal gravity were evaluated and this data has been analysed. The analysis showed only light or moderate turbulence in the fast easterly field between 20000 and 50000 ft over Peninsular India. Moderate to severe turbulent conditions were encountered while probing the cumulus clouds. The maximum gust velocity in the former case was 17.5 ft per sec and in the later case 32.5 ft per sec.

On the Observation of Convective Clouds and the Radar-Precipitation Echoes Within Them

Data collected in Illinois on the behavior of growing cumulus clouds and their associated radar echoes are reviewed and the results are compared to findings in other regions. It is shown that the data collection techniques used, involving two panoramic cameras and a RHI-type radar, were not too successful in Illinois because of the high cloud density on days of cumulus activity.