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At least 109 records · Page 6

A Baseline for Global Weather and Climate Simulations at 1 km Resolution

In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four-month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forecasting System (IFS) at an average grid spacing of 1.4 km. The impact of explicitly simulating deep convection on the atmospheric circulation and its variability is assessed by comparing the 1.4 km simulation to the equivalent well-tested and calibrated global simulations at 9 km grid spacing with and without parametrized deep convection. The explicit simulation of deep convection at 1.4 km results in a realistic large-scale circulation, better representation of convective storm activity, and stronger convective gravity wave activity when compared to the 9 km simulation with parametrized deep convection. Comparison of the 1.4 km simulation to the 9 km simulation without parametrized deep convection shows that switching off deep convection parametrization at a too coarse resolution (i.e., 9 km) generates too strong convective gravity waves. Based on the limited statistics available, improvements to the Madden-Julian Oscillation or tropical precipitation are not observed at 1.4 km, suggesting that other Earth system model components and/or their interaction are important for an accurate representation of these processes and may well need adjusting at deep convection resolving resolutions. Overall, the good agreement of the 1.4 km simulation with the 9 km simulation with parametrized deep convection is remarkable, despite one of the most fundamental parametrizations being turned off at 1.4 km resolution and despite no adjustments being made to the remaining parametrizations.

54 ENVIRONMENTAL SCIENCES↗

Characteristics of Thunderstorms and Lightning Flashes Which Produce Mesospheric Transient Luminous Events

A six year record of optical observations of lightning-induced mesospheric transient luminous events (TLEs) is available from the Yucca Ridge Field Station (YRFS) near Ft. Collins, CO. Climatological analyses reveal sprites and elves occur in a variety of convective storm types, but principally mesoscale convective systems (MCSs) and squall lines. Severe supercell storms rarely produce TLEs, except during their dissipating stage. Few TLEs are observed during storms with radar echo areas <7,500 sq km. Above this size there is a modest correlation with radar areal coverage. A typical High Plains storm produces 45 TLEs over a 143 interval. Sprites and most elves are associated with +CGs. The probability of a TLE increases with peak current. In six storms, 5.1% of +CGs produced TLEs, the number increasing to 32% of +CGs with >75 kA and 52% of +CGs with >100 kA peak current.

Lyons, W. A.↗

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

McCaul, Eugene W., Jr.↗

Report of convective phenomena team

A group meeting was assembled to focus on the planning of specific experiments, to establish some priorities, identify interested scientists who would like to participate, establish any special requirements, make recommendations on data processing, and to prepare flight plan outlines. Since the number of convective storms in the CCOPE (Cooperative Convective Precipitation Experiment) field experiment area are limited to only a few days during the operational time period the flight plans must be designed with a hierarchy of abort experiments so that the easily identified and lowest probability events should take priority until their quota is filled.

Orville, H.↗

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗

Notable impact of wildfires in the western United States on weather hazards in the central United States

Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.

54 ENVIRONMENTAL SCIENCES↗

Large Eddy Simulations of Severe Convection Induced Turbulence

Convective storms can pose a serious risk to aviation operations since they are often accompanied by turbulence, heavy rain, hail, icing, lightning, strong winds, and poor visibility. They can cause major delays in air traffic due to the re-routing of flights, and by disrupting operations at the airports in the vicinity of the storm system. In this study, the Terminal Area Simulation System is used to simulate five different convective events ranging from a mesoscale convective complex to isolated storms. The occurrence of convection induced turbulence is analyzed from these simulations. The validation of model results with the radar data and other observations is reported and an aircraft-centric turbulence hazard metric calculated for each case is discussed. The turbulence analysis showed that large pockets of significant turbulence hazard can be found in regions of low radar reflectivity. Moderate and severe turbulence was often found in building cumulus turrets and overshooting tops.

Ahmad, Nash'at↗

On CCN Effects upon Convective Cold Pool Timing and Features

Abstract Cold pools produced by deep convection can initiate new convection, and their representation in larger-scale weather and climate models could improve prediction of the extent and timing of upscale growth. Cold pools originate from latent cooling from precipitation changing phase, but little attention has been paid to microphysical influences on cold pool characteristics, particularly CCN effects. Datasets obtained from the CACTI and RELAMPAGO field campaigns, along with idealized numerical modeling, are utilized to investigate the hypothesis that convective storms forming in higher-CCN environments generate their first surface rainfall later, delaying cold pool initiation. Aircraft observations of CCN and shallow convection on 9 days do suggest a CCN effect. Those ingesting more CCN contained fewer drizzle drops, although a decreased cloud depth with increasing CCN was also likely a limiting factor. In three of those cases that later developed into deep convection, the timing of cold pool onset was not ubiquitously delayed in environments with more CCN. Idealized numerical simulations suggest that an ordinary thunderstorm can experience small delays in cold pool onset with increasing CCN due to changes in graupel production, but CCN effects on the cold pool from a supercell thunderstorm can be easily overpowered by its unique dynamics. A strong inverse relationship between cold pool strength, expansion rate, and depth with increasing CCN is suggested by the results of the ordinary thunderstorm simulation. Further consideration of CCN appears warranted for future cold pool parameterization development, but other environmental factors affecting storm morphology and precipitation cannot be ignored.

Meteorology & Atmospheric Sciences↗

The Impact on Simulated Storm Structure and Intensity of Variations in the Lifted Condensation Level and the Level of Free Convection

The sensitivities of convective storm structure and intensity to changes in the altitudes of the prestorm environmental lifted condensation level and level of free convection axe studied using a full-physics three-dimensional cloud model. Matrices of simulations are conducted for a range of LCL=LFC altitudes, using a single moderately-sheared curved hodograph trace in conjunction with 1 convective available potential energy values of either 800 or 2000 J/kg, with the matrices consisting of all four combinations of two distinct choices of buoyancy and shear profile shape. For each value of CAPE, the LCL=LFC altitudes are also allowed to vary in a series of simulations based on the most highly compressed buoyancy and shear profiles for that CAPE, with the environmental buoyancy profile shape, subcloud equivalent potential temperature, subcloud lapse rates of temperature and moisture, and wind profile held fixed. For each CAPE, one final simulation is conducted using a near optimal LFC, but a lowered LCL, with a neutrally buoyant environmental thermal profile specified in between. Results show that, for the buoyancy-starved small-CAPE environments, the simulated storms are supercells and are generally largest and most intense when LCL=LFC altitudes lie in the approximate range 1.5-2.5 km above the surface. The simulations show similar trends for the shear-starved large-CAPE environments, except that conversion from supercell to multicell morphology frequently occurs when the LCL is high. For choices of LCL=LFC height within the optimal 1.5-2.5 km range, peak storm updraft overturning efficiency may approaches unity relative to parcel theory, while for lower LCL=LFC heights, overturning efficiency is reduced significantly. The enhancements of overturning efficiency and updraft diameter with increasing LFC height are shown to be the result of systematic increases in the mean equivalent potential temperature of the updraft at cloud base. For the shear-starved environments, the tendency for outflow dominance is eliminated, but a large overturning efficiency maintained, when a low LCL is used in conjunction with a high LFC. The result regarding outflow dominance at high LCL is consistent with expectations, but the beneficial effect of a high LFC on convective overturning efficiency has not previously been widely recognized. The simulation findings here also appear to be consistent with statistics from previous severe storm environment climatologies, but provide a new framework for interpreting those statistics.

McCaul, Eugene W., Jr.↗

The promise of remote sensing in the atmospheric sciences

The applications and advances in remote sensing technology for weather prediction, mesoscale meteorology, severe storms, and climate studies are discussed. Doppler radar permits tracking of the three-dimensional field of motion within storms, thereby increasing the accuracy of convective storm modeling. Single Doppler units are also employed for detecting mesoscale storm vortices and tornado vortex signatures with lead times of 30 min. Clear air radar in pulsed and high resolution FM-CW forms reveals boundary layer convection, Kelvin-Helmoltz waves, shear layer turbulence, and wave motions. Lidar is successfully employed for stratospheric aerosol measurements, while Doppler lidar provides data on winds from the ground and can be based in space. Sodar is useful for determining the structure of the PBL. Details and techniques of satellite-based remote sensing are presented, and results from the GWE and FGGE experiments are discussed.

Atlas, D.↗

Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires, including wildfires, harm air quality and essential public services like transportation, communication, and utilities. These fires can also influence atmospheric conditions, including temperature and aerosols, potentially affecting severe convective storms. Here, we investigate the remote impacts of fires in the western United States (WUS) on the occurrence of large hail (size: $\geqslant$ 2.54 cm) in the central US (CUS) over the 20-year period of 2001–20 using the machine learning (ML), Random Forest (RF), and Extreme Gradient Boosting (XGB) methods. The developed RF and XGB models demonstrate high accuracy (> 90%) and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide, particularly in four states (Wyoming, South Dakota, Nebraska, and Kansas). The key contributing variables identified from both ML models include the meteorological variables in the fire region (temperature and moisture), the westerly wind over the plume transport path, and the fire features (i.e., the maximum fire power and burned area). Importantly, the results confirm a linkage between WUS fires and severe weather in the CUS, corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

54 ENVIRONMENTAL SCIENCES↗

Development of a severe local storm prediction system: A 60-day test of a mesoscale primitive equation model

The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.

Paine, D. A.↗

The role of near surface outflow in maintaining convective activity

Continuous measurements of horizontal velocity, temperature and humidity at the surface over a dense network of stations were used to examine the behavior, at the surface, of a large number of convective storms. Feedback between storm outflow at the surface and the generation of convective cells is demonstrated. The outflow is shown in the surface divergence fields once rain begins, with characteristics common to storms in distinctly different meteorological environments, such as summertime Florida and Illinois. This commencement precedes the occurence of rainfall and radar echo in the location of the cell by some tens of minutes up to more than 100 mins. Given surface measurements with a spacing of no more than 10 km, the direction of propagation, timing of the future occurence of rainfall and the intensity of the rainfall generated in the cell can be determined.

Garstang, M.↗

A Complex Storm System in Saturn's North Polar Atmosphere in 2018

Saturn’s convective storms usually fall in two categories. One consists of mid-sized storms ~ 2,000 km wide, appearing as irregular bright cloud systems that evolve rapidly, on scales of a few days. The other includes the exceptional Great White Spots (GWS), planetary-scale giant storms that disturb a full latitude band, and which have been observed only seven times. Here we report a new intermediate type, observed in 2018 in the North Polar Region. Four large storms (the first one lasting longer than 200 days) formed sequentially in close latitudes, experiencing mutual encounters, and leading to zonal disturbances affecting a full latitude band ~ 8,000 km wide, during at least 8 months. Dynamical simulations indicate that each storm required energies ~ 100 times smaller than those necessary for a GWS. This event occurred at about the same latitude and season as the GWS in 1960, in close correspondence with the cycle of approximately 60 years hypothesized for equatorial GWSs.

A Sánchez-Lavega↗

Assimilating Scanning Radar Data into Cloud-Scale Models

The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.

54 ENVIRONMENTAL SCIENCES↗

Spaceborne Passive-Microwave and Visible/IR Observations of Severe Weather: Leveraging Multiple Perspectives for Detection, Validation, and Climatologies

Severe weather phenomena not only are responsible for damages to property, infrastructure, and agriculture, they are also difficult to measure in-situ and have been associated with large errors and uncertainties in precipitation estimation that pose challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Severe convection exhibits distinct signatures in remote-sensing datasets, where it is manifested as textured or overshooting cloud tops in visible/IR imagery, or resulting a prominent brightness temperature depression in passive-microwave imagery. These distinct deep convective signatures in spaceborne datasets have been leveraged to analyze severe thunderstorms, create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data may be inconsistent or unavailable. Visible/IR and passive-microwave instruments are powerful tools for detecting severe thunderstorms, however, these datasets exhibit key limitations when examined individually: passive-microwave channels have large footprint and exhibit non-uniform beam filling. The visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. We investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair passive microwave, IR, and visible signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis to characterize potentially severe convective storms observed by Aqua MODIS and AMSR-E. We will discuss how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically.

Sarah D. Bang↗

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗