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At least 19 records

Causal Directions Matter: How Environmental Factors Drive Convective Cloud Detrainment Heights

This study investigates how environmental factors influence the level of maximum detrainment (LMD) in deep convective clouds. Through a novel application of the Linear Non‐Gaussian Acyclic Model (LiNGAM), we discover causal structures between environmental variables and LMD, observed at six tropical sites operated by the Atmospheric Radiation Measurement (ARM) user facility. LiNGAM effectively identifies causal directions among variables of interest, revealing robust relationships such as those among the lifting condensation level (LCL), level of free convection (LFC), and convective inhibition (CIN), aligning with prior knowledge. Relative humidity is shown to directly influence LMD; however, this relationship exhibits strong nonlinearity and becomes difficult to detect when the contrast between oceanic and continental environments is excluded from the analysis. This study highlights the importance of establishing causal relationships before performing statistical inference.

54 ENVIRONMENTAL SCIENCES↗

The daytime course of total ozone content caused by cloud convection

Presented are the experimental data on the daytime course of the total O3 and SO2 content obtained by Brewer 044 spectrophotometer in the tropics (Thumba, India, 8.53 N, 76.87 W, March-May 1990) and at middle latitudes (Obninsk, Russia, 55.12 N, 36.6 W, May-October 1991) of the Northern Hemisphere. The analysis showed that under fine warm weather conditions without precipitation (air mass change and frontal passage were not observed during several days) in days with well-developed convective clouds (cloudless morning, convective clouds in the daytime, no clouds in the evening) there is a typical nearly symmetric (with respect to local noon) course of the total O3 (with the minimum at about local noon) and SO2 (with the maximum at about local noon) content. The minimum depth is about 2-5 percent of the average daytime values of the total ozone content. The synchronous measurements of pressure pulsations with microbarograph (they are the indicator of convective and turbulent motion development in the lower subcloud atmospheric layer) showed that during these days there is a nearly symmetric course of pressure pulsations with the maximum at about local noon.

Ishov, Alexander G.↗

Investigating Aerosol and Meteorological Influences on Convective Clouds in Houston, Texas, during the TRACER/ESCAPE Field Campaigns

Aerosols serve as cloud condensation nuclei, shaping the microphysical properties of cloud droplets. Aerosol effects on convective clouds are complex and remain controversial. The debate centers around the process of aerosol-induced invigoration of deep convection, a phenomenon that could significantly affect convective cloud properties but lacks robust evidence due to methodological limitations in observational approaches and questions about the robustness of modeling studies. Resolving these discrepancies is crucial for understanding how aerosols affect the atmosphere. Here, this study examines the effects of meteorological and aerosol parameters in a weakly synoptic-driven convective environment, where the influence of aerosols may be more pronounced and observable. Daily atmospheric soundings and aerosol concentrations from several ground instruments collected during the summer of 2022 in Houston, Texas, as part of the Tracking Aerosol Convection interactions Experiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) field campaigns are analyzed. Statistical learning methods are applied to uncover the complex relationships between aerosols, meteorology, and convective cloud characteristics, such as cell area and echo-top height. The findings reveal that higher aerosol concentrations are associated with narrower convective cells, which we argue contradicts the idea of stronger convection with increased aerosol loading. However, once the data are clustered by the synoptic environment, the relationship between aerosol loading and convective cell area diminishes, indicating that the covariablity between synoptic-scale weather patterns, local thermodynamics, and aerosol loading makes it challenging to draw definitive conclusions about the specific impacts of aerosols on convective cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Description and Evaluation of a New Deep Convective Cloud Model Considering In-cloud Inhomogeneity

Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in-cloud inhomogeneities, a new convective cloud model explicitly considering in-cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub-plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single-column tests show a stronger mass flux profile and low-level detrainment with the new model. In global simulations, the long-lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is slightly over-enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Varying Concentrations of Cloud Condensation Nuclei On Deep Convective Cloud Updrafts – A Multimodel Assessment

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations amongst seven, state-of-the-art, cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced, updraft changes. The models show several consistent trends. In general, the changes between the High- CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5-15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~-5-0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

deep convective cloud updrafts↗

Generating a stratocumulus-like cloud top in a convection-cloud chamber

Stratocumulus-topped boundary layers play a crucial role in influencing daily weather and earth energy balance. Entrainment at the stratocumulus cloud top affects the cloud’s lifetime, precipitation, and radiative properties, but our understanding remains limited due to the lack of resolution in both field observations and numerical simulations. A recently proposed convection-cloud chamber with detailed control of sidewall temperatures can provide a unique opportunity to explore this mechanism in a laboratory setting. In this work, we use numerical simulations to demonstrate that this design can produce a cloud top that mimics the entrainment interfacial layer in a stratocumulus cloud. Our results show that a steady-state cloud can be formed by cooling the lower portions of the sidewalls and warming the bottom surface, while a temperature inversion at the cloud top can be generated by keeping the upper sidewalls and top surface warmer than the bottom. The turbulent kinetic energy profile and budget are similar to those found in a convective boundary layer, and inhomogeneous mixing near the cloud top can be observed. These findings significantly enhance the scientific value of constructing the tall convection-cloud chamber.

54 ENVIRONMENTAL SCIENCES↗

Potential impact of aerosols on convective clouds revealed by Himawari-8 observations over different terrain types in eastern China

Convective clouds are common and play a major role in Earth's water cycle and energy balance; they may even develop into storms and cause severe rainfall events. To understand the convective cloud development process, this study investigates the impact of aerosols on convective clouds by considering the influence of both topography and diurnal variation in radiation. By combining texture analysis, clustering, and thresholding methods, we identify all convective clouds in two warm seasons (May–September, 2016/17) in eastern China based on Himawari-8 Level 1 data. Having large diurnally resolved cloud data together with surface meteorological and environmental measurements, we investigate convective cloud properties and their variation, stratified by elevation and diurnal change. We then analyze the potential impact of aerosol on convective clouds under different meteorological conditions and topographies. In general, convective clouds tend to occur preferentially under polluted conditions in the morning, which reverses in the afternoon. Convective cloud fraction first increases then decreases with aerosol loading, which may contribute to this phenomenon. Topography and diurnal meteorological variations may affect the strength of aerosol microphysical and radiative effects. Updraft is always stronger along the windward slopes of mountains and plateaus, especially in northern China. The prevailing southerly wind near the foothills of mountains and plateaus is likely to contribute to this windward strengthening of updraft and to bring more pollutant into the mountains, thereby strengthening the microphysical effect, invigorating convective clouds. By comparison, over plain, aerosols decrease surface heating and suppress convection by blocking solar radiation reaching the surface.

clouds↗

Potential impact of aerosols on convective clouds revealed by Himawari-8 observations over different terrain types in Eastern China

Convective clouds are common and play a major role in Earth’s water cycle and energy balance; they may even develop into storms and cause severe rainfall events. To understand the convective cloud development process, this study investigates the impact of aerosols on convective clouds by considering the influence of both topography and diurnal variation of radiation. By combining texture analysis, clustering and thresholding methods, we identify all convective clouds in two warm seasons (May-September, 2016-2017) in eastern China based on Himawari-8 Level 1 data. Having a large diurnally resolved cloud data together with surface meteorological and environmental measurements, we investigate convective cloud properties and their variation, stratified by elevation and diurnal change. We then analyze the potential impact of aerosol on convective clouds under different meteorological conditions and topographies. In general, convective clouds tend to occur preferentially under polluted conditions in the morning, which reverses in the afternoon. Convective cloud fraction first increases then decreases with aerosol loading, which may contribute to this phenomenon. Topography and diurnal meteorological variations may affect the strength of aerosol microphysical and radiative effects. Updraft is always stronger along the windward slopes of mountains and plateaus, especially in northern China. The prevailing southerly wind near the foothills of mountains and plateaus is likely to contribute to this windward strengthening of updraft and to bring more pollutant into the mountains, thereby strengthening the microphysical effect, invigorating convective clouds. By comparison, over plain, aerosols decrease surface heating and suppresses convection by blocking solar radiation reaching the surface.

Tianmeng Chen↗

Statistical Analyses of Satellite Cloud Object Data from CERES: Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds - Part III

The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud top height while it overestimates the differences in the observed outgoing longwave radiation and cloud top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and in space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

Luo, Yali↗

Statistical Analyses of Satellite Cloud Object Data from CERES: Tropical Convective Cloud Objects During 1998 El Nino and Validation of the Fixed Anvil Temperature Hypothesis - Part II

Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January-August 1998 are examined using the Tropical Rainfall Measuring Mission/ Clouds and the Earth s Radiant Energy System single scanner footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud-object size, sea surface temperature (SST), and satellite precessing cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the Earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100 - 150 km (small), 150 - 300 km (medium), and > 300 km (large), respectively, except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towards high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precessing cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This result suggests that the fixed anvil temperature hypothesis of Hartmann and Larson may be valid for the large-size category. Combining with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SSTs where large-scale dynamics plays important roles, statistical characteristics of cloud microphysical properties, optical depth and albedo are not sensitive to the SST, but those of cloud macrophysical properties are strongly dependent upon the SST. Frequency distributions of vertical velocity from the European Center for Medium-range Weather Forecasts model that is matched to each cloud object are used to interpret some of the findings in this study.

Xu, Kuan-Man↗

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

54 ENVIRONMENTAL SCIENCES↗

Alabama Ground Operations during the Deep Convective Clouds and Chemistry Experiment

The Deep Convective Clouds and Chemistry (DC3) field campaign investigates the impact of deep, midlatitude convective clouds, including their dynamical, physical and lighting processes, on upper tropospheric composition and chemistry. DC3 science operations took place from 14 May to 30 June 2012. The DC3 field campaign utilized instrumented aircraft and ground ]based observations. The NCAR Gulfstream ]V (GV) observed a variety of gas ]phase species, radiation and cloud particle characteristics in the high ]altitude outflow of storms while the NASA DC ]8 characterized the convective inflow. Groundbased radar networks were used to document the kinematic and microphysical characteristics of storms. In order to study the impact of lightning on convective outflow composition, VHF ]based lightning mapping arrays (LMAs) provided detailed three ]dimensional measurements of flashes. Mobile soundings were utilized to characterize the meteorological environment of the convection. Radar, sounding and lightning observations were also used in real ]time to provide forecasting and mission guidance to the aircraft operations. Combined aircraft and ground ]based observations were conducted at three locations, 1) northeastern Colorado, 2) Oklahoma/Texas and 3) northern Alabama, to study different modes of deep convection in a variety of meteorological and chemical environments. The objective of this paper is to summarize the Alabama ground operations and provide a preliminary assessment of the ground ]based observations collected over northern Alabama during DC3. The multi ] Doppler, dual ]polarization radar network consisted of the UAHuntsville Advanced Radar for Meteorological and Operational Research (ARMOR), the UAHuntsville Mobile Alabama X ]band (MAX) radar and the Hytop (KHTX) Weather Surveillance Radar 88 Doppler (WSR ]88D). Lightning frequency and structure were observed in near real ]time by the NASA MSFC Northern Alabama LMA (NALMA). Pre ]storm and inflow proximity soundings were obtained with the UAHuntsville mobile sounding unit and the Redstone Arsenal (QAG) morning sounding.

Carey, Lawrence↗

Properties of deep convective clouds in the ISCCP Pilot Data Set

Statistics on tropical deep convective clouds in the International Satellite Cloud Climatology Project Pilot Data Set are compiled by binning daytime data over areas of 2 X 2.5, 4 X 5, and 8 X 10 degrees. To isolate the convective clouds, only pixels with minimum visible optical thickness of 32 and maximum cloud top pressure of 550 mb are considered. Maps of convective cloud cover and frequency of convective events and frequency histograms of deep convective cloud pixels and cloud top pressures are presented.

Del Genio, Anthony D.↗

Simulation of Shallow Cumuli and Their Transition to Deep Convective Clouds by Cloud-resolving Models with Different Third-order Turbulence Closures

The abilities of cloud-resolving models (CRMs) with the double-Gaussian based and the single-Gaussian based third-order closures (TOCs) to simulate the shallow cumuli and their transition to deep convective clouds are compared in this study. The single-Gaussian based TOC is fully prognostic (FP), while the double-Gaussian based TOC is partially prognostic (PP). The latter only predicts three important third-order moments while the former predicts all the thirdorder moments. A shallow cumulus case is simulated by single-column versions of the FP and PP TOC models. The PP TOC improves the simulation of shallow cumulus greatly over the FP TOC by producing more realistic cloud structures. Large differences between the FP and PP TOC simulations appear in the cloud layer of the second- and third-order moments, which are related mainly to the underestimate of the cloud height in the FP TOC simulation. Sensitivity experiments and analysis of probability density functions (PDFs) used in the TOCs show that both the turbulence-scale condensation and higher-order moments are important to realistic simulations of the boundary-layer shallow cumuli. A shallow to deep convective cloud transition case is also simulated by the 2-D versions of the FP and PP TOC models. Both CRMs can capture the transition from the shallow cumuli to deep convective clouds. The PP simulations produce more and deeper shallow cumuli than the FP simulations, but the FP simulations produce larger and wider convective clouds than the PP simulations. The temporal evolutions of cloud and precipitation are closely related to the turbulent transport, the cold pool and the cloud-scale circulation. The large amount of turbulent mixing associated with the shallow cumuli slows down the increase of the convective available potential energy and inhibits the early transition to deep convective clouds in the PP simulation. When the deep convective clouds fully develop and the precipitation is produced, the cold pools produced by the evaporation of the precipitation are not favorable to the formation of shallow cumuli.

Cheng, Anning↗

Climate Impacts of Convective Cloud Microphysics in NCAR CAM5

Here we improved the treatments of convective cloud microphysics in the NCAR Community Atmosphere Model version 5.3 (CAM5.3) by 1) implementing new terminal velocity parameterizations for convective ice and snow particles, 2) adding graupel microphysics, 3) considering convective snow detrainment, and 4) enhancing rain initiation and generation rate in warm clouds. Furthermore, we evaluated the impacts of improved microphysics on simulated global climate, focusing on simulated cloud radiative forcing, graupel microphysics, convective cloud ice amount, and tropical precipitation. Compared to CAM5.3 with the default convective microphysics, the too-strong cloud shortwave radiative forcing due primarily to excessive convective cloud liquid is largely alleviated over the tropics and midlatitudes after rain initiation and generation rate is enhanced, in better agreement with the CERES-EBAF estimates. Geographic distributions of graupel occurrence are reasonably simulated over continents; whereas the graupel occurrence remains highly uncertain over the oceanic storm-track regions. When evaluated against the CloudSat–CALIPSO estimates, the overestimation of convective ice mass is alleviated with the improved convective ice microphysics, among which adding graupel microphysics and the accompanying increase in hydrometeor fall speed play the most important role. The probability distribution function (PDF) of rainfall intensity is sensitive to warm rain processes in convective clouds, and enhancement in warm rain production shifts the PDF toward heavier precipitation, which agrees better with the TRMM observations. Common biases of overestimating the light rain frequency and underestimating the heavy rain frequency in GCMs are mitigated.

54 ENVIRONMENTAL SCIENCES↗

Updraft Width Modulates Ambient Atmospheric Controls on Convective Cloud Depth

Abstract The depth of convective clouds affects vertical transport of atmospheric constituents, influencing downstream weather and climate. Atmospheric controls on the maximum depth reached by moist convection are investigated with radar‐tracked convective cells tagged with sounding‐derived atmospheric parameters from a field campaign in central Argentina. Regression analyses show that narrow (<12‐km diameter) and wide (>16‐km diameter) cell depths respond to disparate factors, where cell areas are defined using composite reflectivity signatures. Undiluted lifted parcel indices including convective available potential energy (CAPE) and level of neutral buoyancy (LNB) are top predictors of wide cell maximum depth while mid‐tropospheric relative humidity is the top predictor of narrow cell maximum depth. Because narrow cells are more numerous than wide cells, the overall outcome of the full cell population does not strongly correlate with CAPE and LNB conditions. Tracked cells and atmospheric conditions in a simulation with 3‐km grid spacing covering the field campaign produce similar results to those observed. Narrow cells that are relatively deep have a cooler and moister mid‐troposphere with weaker free tropospheric subsidence, while relatively deep wide cells have much warmer and moister lower tropospheric conditions. These atmospheric differences are present 1 hr before cell initiation at both a fixed observing site and variable cell initiation locations. Simulated narrow cell maximum equivalent potential temperature decreases with height at a rate similar to the ambient vertical gradient, causing these cells to fall short of their LNB and supporting the view that entrainment‐driven dilution is a dominant control on their depth.

54 ENVIRONMENTAL SCIENCES↗

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Sea Breezes and Associated Convective Cloud Evolution in the Model Gray Zone

We characterize convective clouds associated with sea‐breeze circulations (SBC) using multi‐agency observations and multi‐case ensemble model simulations. The focus is on assessing convective cloud lifecycle properties and their merging behavior, as well as the environmental conditions they are embedded in, particularly SBC features. In total, 46 SBC days over the Houston‐Galveston region are selected and simulated using the Weather Research and Forecasting (WRF) model at a gray zone scale with a forecast‐like parameterization setup. Advanced techniques, including change‐point detection, a Lagrangian cloud tracking method, and a newly developed cell merging and splitting detection algorithm, are applied and/or developed for this study. Our findings indicate that the WRF model at 1 km grid spacing well represents the thermodynamic conditions over the region, as well as SBC timing and intensity. However, for the associated convective cells, WRF overestimates the 30‐dBZ echo top height, cell area, and maximum radar reflectivity compared to radar observations. This overestimation is potentially due to under‐resolved entrainment processes, an overestimated merging frequency, and the overestimation of updraft intensity. Furthermore, the model exhibits a deficiency in simulating congestus clouds, showing a more rapid transition from shallow to deep convection compared to observed behavior. Moreover, observations indicate stronger, deeper, and wider clouds when merging happens. Conversely, in simulations, the merging process does not necessarily lead to higher or longer‐lived cells, as many cases experience rapid and frequent merging and splitting which may result in more variance in convective updraft velocity during the convection lifetime.

54 ENVIRONMENTAL SCIENCES↗