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Evaluation of WRF simulation of deep convection in the US Southern Great Plains
The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Here, seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection permitting resolution with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from ASOS stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both RR and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr –1 over the domain. Detailed analyses of the ten days with highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr –1 ) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.
What Makes Boundary Layer Convergence Lines So Effective at Deep-Convection Initiation?
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Advancing Understanding of Deep Convective Anvil Clouds
In this project we use ground-based DOE ARM observations, satellite observations, and Weather Research and Forecasting (WRF) model simulations to arrive at a more complete understanding (or, new theory) of how atmospheric heating profiles in thunderstorm cores drives how quickly air rises in the storms. The rate at which air motion increases or decreases with altitude directly relates to how much cloud mass is ejected laterally into the adjacent atmosphere, which then influences the development and maintenance of “stratiform raining cloud anvils”. Our work has led to new equations connecting the heating in these thunderstorms to these stratiform clouds, with the connection modulated by the stability structure of the atmosphere (i.e., if more stable, then a more rapid change in thunderstorm heating with altitude results in more stratiform cloud, independent of whether over land or ocean, or how organized the thunderstorms are). Improving knowledge of stratiform clouds is important, since they contribute to substantial accumulated rainfall (important to agriculture and local hydrology) as well as radiation, given their large areal extents and lifetime. The radiation impacts likely impact simulated cloud feedback in all Earth System models (ESMs).
Investigating the Impact of the QBO on Tropical Deep Convection and the MJO in Free-Running and Nudged E3SM Simulations
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Updraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol–deep convection interactions
One fundamental question about atmospheric moist convection processes that remains debated is whether, or under which conditions, a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using the following two different reference frames: static cloudy updraft grid cells versus tracked cumulus thermals. In both frameworks, we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.
BIRDIE beryllium-10 and -7 measurements from 2022 summer deep convection rain at ARM SGP
Water samples were manually collected from 11 SGP ARM sites in the early summer of 2022 to measure cosmogenic isotopes of beryllium. The water samples were brought back to the Center for Accelerator Mass Spectrometry (CAMS) at LLNL and analysed for beryllium-10 and beryllium-7 as well as for chlorine-37, chlorine-36, and tritium. A total of six storm events were measured over three weeks. At least five of those storms included overshooting cloud events. Available data include precipitation amount, beryllium-10 concentration, beryllium-7 concentration, and 10/7Be ratio. Spatial and temporal variability in the cosmogenic isotopes was relatively high but could not directly be linked to precipitation amount. Analysis is on-going to explain the measured variability and to see if it can be linked to cloud top height and overshooting depth.
Urban Effect on Precipitation and Deep Convective Systems Over Dallas‐Fort Worth
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Lightning NO x in the 29–30 May 2012 Deep Convective Clouds and Chemistry (DC3) Severe Storm and Its Downwind Chemical Consequences
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The Effects of Deep Convection on Regional Temperature Structure in the Tropical Upper Troposphere and Lower Stratosphere
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A CloudSat cloud object partitioning technique and assessment and integration of deep convective anvil sensitivities to sea surface temperature
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Spatiotemporal characteristics of deep convection initiation in the Central United States
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The roles of deep convection and extratropical mixing in the tropical tropopause layer: An in situ measurement perspective
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Deep Convective Cloud Top Altitudes at High Temporal and Spatial Resolution
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A dynamical basis for the parameterization of organized deep convection in large-scale numerical models
A hierarchy of steady, nonlinear, semianalytic models of different types of convection were produced. These provide a theoretical framework for determining cloud outflow fluxes of both dynamic and thermodynamic quantities, which can be used to formulate dynamical transports in parameterization schemes. This was achieved by exploiting certain Lagrangian conservation properties of steady flow, from which an equation for the vertical displacement of particles can be obtained and the outflow entropy, energy and momentum fluxes and the infow/outflow mass fluxes can be determined from solution to the equation. These fluxes are determined in terms of grid scale parameters such as convective available potential energy (CAPE), cloud layer shear, and horizontal pressure gradients. Five main types of system models are identified, respectively representing archtypes of convection in zero shear, large shear, midlatitude squall lines, tropical squall lines and cellular convection. The downdraught is an important aspect in the first four of these and the cloud scale transport of momentum is very distinctive.
Observations of deep convection from an airborne high-frequency (92 and 183 GHz) passive microwave radiometer
Spencer et al. (1983) have reported that very low Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures at 37 GHz over land coincide with heavy thunderstorm rainfall, while Wilheit et al. (1982) used an aircraft-mounted radiometer operating at 92 and 183 GHz to observe convective precipitation associated with a tropical storm over the ocean. A scanning version of the instrument employed by Wilheit et al. is the Advanced Microwave Moisture Sounder (AMMS). The present paper has the objective to summarize the preliminary results of AMMS observations of convective raining clouds and to determine whether empirical relationships between rain rate and microwave brightness temperature, such as those developed for 37 GHz satellite data by Spencer et al., can be extended to higher microwave frequencies.
A model-based investigation of the role of boundary layer fluxes and deep convective processes in the precipitation distribution of East Coast cyclones
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Aircraft microwave observations and simulations of deep convection at 18-183 GHz
A radiative transfer model is used to simulate the aircraft multichannel microwave observations and to study a storm system observed on June 29, 1986 during the Cohmex program. The model, which is a revision of the model used by Wilheit et al. (1982), is described. The microwave upwelling brightness temperatures at the top of the atmosphere are calculated from hydrometeor profiles derived from ground-based radar data. The model is used to study various vertical hydrometeor phase profiles and particle size distributions. The results are compared with aircraft data from the Multispectral Cloud Radiometer and the Microwave Precipitation Radiometer. The results show that the brightness temperatures are directly influenced by the complex nature of hydrometeors, including size distribution and the mixture of ice and water phases.