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David A. Matthews

Abstract

This paper presents aircraft, radar, satellite and rawinsonde observations which describe a cloud am formed by moist downdraft outflow from a cumulonimbus cluster in northwest Kansas. Aircraft cross sections are presented of four variables at 160 and 320 m AGL, flown in clear air, which show the detailed structure of the mesoscale cold front in its final dissipating stages 3 h after its initiation. These observations indicate that along the mesoscale cold front, strong vertical velocities of 3–5 m s−1 occur. This lifting was examined in a numerical cloud model to determine its triggering cleat on convective cloud development. Model results, which agree with radar echo observations, indicate that lifting produced by the mesocold front is an important trigger mechanism for the observed cumulus congestus cloud growth. Model analyses also show that the vertical profile of lifting is an important factor in determining its not triggering impact on convective development. Seeding simulations indicate that clouds triggered by the mesoscale cold front had potential for dynamic modification.

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David A. Matthews

Abstract

A statistical summary of the thermodynamic features generally thought to be relevant to convective cloud development and the dynamic seeding hypothesis, as diagnosed by a one-dimensional steady-state model, has been compiled for selected locations on the High Plains. The summary is based primarily on rawinsonde data collected at Miles City, Montana, Goodland, Kansas, and Big Spring, Texas during the summer months from 1975 to 1977, as part of the High Plains Cooperative Program (HIPLEX). Data were stratified according to the occurrence or non-occurrence of convective clouds and, when clouds occurred, according to cloud type as seen in geosynchronous satellite imagery. Geographic comparisons are presented showing significant variations from north to south over the High Plains, the most intense convection occurring in the central and southern plains and the least intense in the north. Large annual variations were noted in mean values of thermodynamic features at each site between the three summers.

Analyses of mesoscale variability of thermodynamic features were made using observations from a mesoscale rawinsonde network. Although large spatial variations in thermodynamic variables on a given day were found, seasonal mean values were similar, suggesting that the variations are related to small-scale dynamics and appear statistically random but that the average values at any one site are representative of a given region.

While no cloud seeding was performed to test the dynamic seeding hypothesis in field experiments, the cloud model indicated that soundings on the High Plains had potential for additional dynamic growth. The dynamic modification potential (DMP) is defined as the post-seeding enhancement of growth that is predicted by the cumulus model to result from heat released by converting supercooled water to ice. This is equivalent to Simpson's (1976) “seedability”, and is similar to model-predicted changes in cloud depth used by other authors. While supercooled water is presumed to exist in sufficient quantity for a long enough time to produce changes in cloud dynamics, no in-cloud measurements of the presence and duration of supercooled water were made in this study. However, the model indicated that DMP was found to exist in about 50% of the soundings analyzed in this study. The maximum frequency of occurrence of DMP was associated with mesoscale convective systems in Montana and Texas; whereas in Kansas, it occurred on days with smaller air mass convective clouds. Large variations in the frequency of modeled DMP occurred as a function of observed cloud types and mesoscale types.

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David A. Matthews
and
Bernard A. Silverman

Abstract

Numerical model simulation of mesoscale lifting of the convective environment indicates that the ability of the environment to develop deep moist convection increases as mesoscale lifting increases. Mesoscale lifting produces increases in modeled cloud development (cloud depth, cloud-top height, number of clouds, etc.) in most of the samples of 232 summer soundings observed in the High Plains as part of HIPLEX (High Plains Cooperative Program). These increases were statistically significant at the P = 0.001 level in most cases. The effect of lifting was found to vary geographically from north to south over the High plains.

On days when convective cloud lines and clusters were observed in satellite imagery, model simulations produced deep convection only when mesoscale released the conditional instability. On days when isolated convective clouds or clear skies prevailed, model simulations produced less intense convective development; however, lifting was often required to supplement surface heating to produce clouds on these days. These results suggest that the model may be used to determine a convective potential index of the effects of lifting on cloud development, provided there is a means for determining the magnitude of mesoscale velocities.

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Jerome D. Fast
,
Larry K. Berg
,
Lizbeth Alexander
,
David Bell
,
Emma D’Ambro
,
John Hubbe
,
Chongai Kuang
,
Jiumeng Liu
,
Chuck Long
,
Alyssa Matthews
,
Fan Mei
,
Rob Newsom
,
Mikhail Pekour
,
Tamara Pinterich
,
Beat Schmid
,
Siegfried Schobesberger
,
John Shilling
,
James N. Smith
,
Stephen Springston
,
Kaitlyn Suski
,
Joel A. Thornton
,
Jason Tomlinson
,
Jian Wang
,
Heng Xiao
, and
Alla Zelenyuk

Abstract

Shallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land–atmosphere interactions and aerosol–radiation–cloud interactions can influence the formation of shallow clouds and their properties. These processes exhibit large spatial and temporal variability and occur at the subgrid scale for all current climate, operational forecast, and cloud-system-resolving models; therefore, they must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface-layer, boundary layer, and aerosol properties. Predictions of the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data are a key factor needed to achieve a more complete understanding of the life cycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation Measurement (ARM) Southern Great Plains site in north-central Oklahoma during the spring and summer of 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data.

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Jian Wang
,
Rob Wood
,
Michael P. Jensen
,
J. Christine Chiu
,
Yangang Liu
,
Katia Lamer
,
Neel Desai
,
Scott E. Giangrande
,
Daniel A. Knopf
,
Pavlos Kollias
,
Alexander Laskin
,
Xiaohong Liu
,
Chunsong Lu
,
David Mechem
,
Fan Mei
,
Mariusz Starzec
,
Jason Tomlinson
,
Yang Wang
,
Seong Soo Yum
,
Guangjie Zheng
,
Allison C. Aiken
,
Eduardo B. Azevedo
,
Yann Blanchard
,
Swarup China
,
Xiquan Dong
,
Francesca Gallo
,
Sinan Gao
,
Virendra P. Ghate
,
Susanne Glienke
,
Lexie Goldberger
,
Joseph C. Hardin
,
Chongai Kuang
,
Edward P. Luke
,
Alyssa A. Matthews
,
Mark A. Miller
,
Ryan Moffet
,
Mikhail Pekour
,
Beat Schmid
,
Arthur J. Sedlacek
,
Raymond A. Shaw
,
John E. Shilling
,
Amy Sullivan
,
Kaitlyn Suski
,
Daniel P. Veghte
,
Rodney Weber
,
Matt Wyant
,
Jaemin Yeom
,
Maria Zawadowicz
, and
Zhibo Zhang

Abstract

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from 21 June to 20 July 2017 and from 15 January to 18 February 2018 in the Azores. The flights were designed to maximize the synergy between in situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Finally, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

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Adam C. Varble
,
Stephen W. Nesbitt
,
Paola Salio
,
Joseph C. Hardin
,
Nitin Bharadwaj
,
Paloma Borque
,
Paul J. DeMott
,
Zhe Feng
,
Thomas C. J. Hill
,
James N. Marquis
,
Alyssa Matthews
,
Fan Mei
,
Rusen Öktem
,
Vagner Castro
,
Lexie Goldberger
,
Alexis Hunzinger
,
Kevin R. Barry
,
Sonia M. Kreidenweis
,
Greg M. McFarquhar
,
Lynn A. McMurdie
,
Mikhail Pekour
,
Heath Powers
,
David M. Romps
,
Celeste Saulo
,
Beat Schmid
,
Jason M. Tomlinson
,
Susan C. van den Heever
,
Alla Zelenyuk
,
Zhixiao Zhang
, and
Edward J. Zipser

Abstract

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

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