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Alexey Pankine
,
Zhanqing Li
,
David Parsons
,
Michael Purucker
,
Elliot Weinstock
,
Warren Wiscombe
, and
Kerry Nock

Advanced, robust, yet inexpensive observational platforms and networks of platforms will make revolutionary Earth science observations possible in the next 30 years. One new platform concept that is needed is a long-duration stratospheric balloon flying in a near-space environment and capable of remaining aloft for a year carrying a half ton of payload. We dub these platforms StratoSats for stratospheric satellites because they usually orbit the Earth in the stratosphere with an orbit period of 10–20 days. StratoSats can complement space satellites or play a completely independent role in Earth observation. Constellations of these platforms could steer themselves to desired locations and perform coordinated in situ and remote sensing observations of the Earth and its atmosphere. In principle, such constellations could easily surpass the capabilities of a single satellite for far less cost. NASA has defined stratospheric science measurement requirements and platform capabilities for several Earth science disciplines, including atmospheric chemistry, Earth radiation budget, geomagnetism, and weather. StratoSats can satisfy these measurement requirements and platform capabilities. Key enabling technologies for StratoSats include very long-life, sealed super-pressure balloons and techniques for balloon guidance. These key technologies are relatively mature, having achieved successful prototype and model tests in relevant environments, although a final push in engineering development is needed with a focus on meeting Earth science platform needs.

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David B. Parsons
,
Kevin R. Haghi
,
Kelton T. Halbert
,
Blake Elmer
, and
Junhong Wang

Abstract

This investigation explores the relationship among bores, gravity waves, and convection within the nocturnal environment through the utilization of measurements taken during the International H2O Project (IHOP_2002) over the Southern Great Plains. The most favorable conditions for deep convection were found to occur within the boundary layer during the late afternoon and early evening hours in association with the diurnal cycle of solar insolation. At night, the layers most favorable for deep convection occur at and above the height of the nocturnal southerly low-level jet in association with distinct maxima in both the southerly and westerly components of the wind. Observations taken during the passage of 13 nocturnal wave disturbances over a comprehensive profiling site show the average maximum and net upward displacements with these waves were estimated to be ~900 and ~660 m, respectively. The lifting was not limited to the stable boundary layer, but reached into the conditionally unstable layers aloft. Since the net upward displacements persisted for many hours as the disturbances propagated away from the convection, areas well in excess of 10 000 km2 are likely impacted by this ascent. This lifting can directly maintain existing convection and aid in the initiation of new convection by reducing the convective inhibition in the vicinity of the active convection. In agreement with past studies, strong ascent in the lowest ~1.5 km was generally consistent with the passage of a bore. However, separate wave responses also occurred well above the bores, and low-frequency gravity waves may explain such disturbances.

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Samuel P. Lillo
,
Steven M. Cavallo
,
David B. Parsons
, and
Christopher Riedel

Abstract

An extreme Arctic cold air outbreak took place across the Midwest, Great Lakes, and Northeast during 29 January to 1 February 2019. The event broke numerous long-standing records with wide-reaching and detrimental societal impacts. This study found that this rare and dangerous cold air outbreak (CAO) was a direct consequence of a tropopause polar vortex (TPV) originating at high latitudes and subsequently tracking southward into the United States. The tropopause depression at the center of this TPV extended nearly to the surface. Simulations using the atmospheric component of the Model for Prediction Across Scales (MPAS) were conducted, revealing excellent predictability at 6–7-day lead times with the strength, timing, and location of the CAO linked to the earlier characteristics of the TPV over the Arctic. Within the middle latitudes, the TPV subsequently developed a tilt with height. Warming and the destruction of potential vorticity also took place as the TPV passed over the Great Lakes initiating a lake-effect snow storm. The climatological investigation of CAOs suggests that TPVs frequently play a role in CAOs over North America with a TPV located within 1000 km of a CAO 85% of the time. These TPVs tended to originate in the northern Canadian Arctic and are ejected equatorward into the Great Lakes/Upper Midwest and then to the Northeast over Labrador. This study also provides insight into how the impact of Arctic circulations on middle latitudes may vary within the framework of a rapidly changing Arctic.

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Pierre-Emmanuel Kirstetter
,
Tian-You Yu
,
Robert Palmer
,
David Parsons
,
Hirohiko Ishikawa
, and
Jessica M. Erlingis
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Hristo G. Chipilski
,
Xuguang Wang
,
David B. Parsons
,
Aaron Johnson
, and
Samuel K. Degelia

Abstract

There is a growing interest in the use of ground-based remote sensors for numerical weather prediction, which is sparked by their potential to address the currently existing observation gap within the planetary boundary layer. Nevertheless, open questions still exist regarding the relative importance of and synergy among various instruments. To shed light on these important questions, the present study examines the forecast benefits associated with several different ground-based profiling networks using 10 diverse cases from the Plains Elevated Convection at Night (PECAN) field campaign. Aggregated verification statistics reveal that a combination of in situ and remote sensing profilers leads to the largest increase in forecast skill, in terms of both the parent mesoscale convective system and the explicitly resolved bore. These statistics also indicate that it is often advantageous to collocate thermodynamic and kinematic remote sensors. By contrast, the impacts of networks consisting of single profilers appear to be flow-dependent, with thermodynamic (kinematic) remote sensors being most useful in cases with relatively low (high) convective predictability. Deficiencies in the data assimilation method as well as inherent complexities in the governing moisture dynamics are two factors that can further limit the forecast value extracted from such networks.

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Benjamin T. Blake
,
David B. Parsons
,
Kevin R. Haghi
, and
Stephen G. Castleberry

Abstract

Previous studies have documented a nocturnal maximum in thunderstorm frequency during the summer across the central United States. Forecast skill for these systems remains relatively low and the explanation for this nocturnal maximum is still an area of active debate. This study utilized the WRF-ARW Model to simulate a nocturnal mesoscale convective system that occurred over the southern Great Plains on 3–4 June 2013. A low-level jet transported a narrow corridor of air above the nocturnal boundary layer with convective instability that exceeded what was observed in the daytime boundary layer. The storm was elevated and associated with bores that assisted in the maintenance of the system. Three-dimensional variations in the system’s structure were found along the cold pool, which were examined using convective system dynamics and wave theory. Shallow lifting occurred on the southern flank of the storm. Conversely, the southeastern flank had deep lifting, with favorable integrated vertical shear over the layer of maximum CAPE. The bore assisted in transporting high-CAPE air toward its LFC, and the additional lifting by the density current allowed for deep convection to occur. The bore was not coupled to the convective system and it slowly pulled away, while the convection remained in phase with the density current. These results provide a possible explanation for how convection is maintained at night in the presence of a low-level jet and a stable boundary layer, and emphasize the importance of the three-dimensionality of these systems.

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Bore-ing into Nocturnal Convection

Kevin R. Haghi
,
Bart Geerts
,
Hristo G. Chipilski
,
Aaron Johnson
,
Samuel Degelia
,
David Imy
,
David B. Parsons
,
Rebecca D. Adams-Selin
,
David D. Turner
, and
Xuguang Wang

Abstract

There has been a recent wave of attention given to atmospheric bores in order to understand how they evolve and initiate and maintain convection during the night. This surge is attributable to data collected during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. A salient aspect of the PECAN project is its focus on using multiple observational platforms to better understand convective outflow boundaries that intrude into the stable boundary layer and induce the development of atmospheric bores. The intent of this article is threefold: 1) to educate the reader on current and future foci of bore research, 2) to present how PECAN observations will facilitate aforementioned research, and 3) to stimulate multidisciplinary collaborative efforts across other closely related fields in an effort to push the limitations of prediction of nocturnal convection.

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David Parsons
,
Walter Dabberdt
,
Harold Cole
,
Terrence Hock
,
Charles Martin
,
Anne-Leslie Barrett
,
Erik Miller
,
Michael Spowart
,
Michael Howard
,
Warner Ecklund
,
David Carters
,
Kenneth Gage
, and
John Wilson

An Integrated Sounding System (ISS) that combines state-of-the-art remote and in situ sensors into a single transportable facility has been developed jointly by the National Center for Atmospheric Research (NCAR) and the Aeronomy Laboratory of the National Oceanic and Atmospheric Administration (NOAA/AL). The instrumentation for each ISS includes a 915-MHz wind profiler, a Radio Acoustic Sounding System (RASS), an Omega-based NAVAID sounding system, and an enhanced surface meteorological station. The general philosophy behind the ISS is that the integration of various measurement systems overcomes each system's respective limitations while taking advantage of its positive attributes. The individual observing systems within the ISS provide high-level data products to a central workstation that manages and integrates these measurements. The ISS software package performs a wide range of functions: real-time data acquisition, database support, and graphical displays; data archival and communications; and operational and posttime analysis. The first deployment of the ISS consists of six sites in the western tropical Pacific—four land-based deployments and two ship-based deployments. The sites serve the Coupled Ocean-Atmosphere Response Experiment (COARE) of the Tropical Ocean and Global Atmosphere (TOGA) program and TOGA's enhanced atmospheric monitoring effort. Examples of ISS data taken during this deployment are shown in order to demonstrate the capabilities of this new sounding system and to demonstrate the performance of these in situ and remote sensing instruments in a moist tropical environment. In particular, a strong convective outflow with a pronounced impact of the atmospheric boundary layer and heat fluxes from the ocean surface was examined with a shipboard ISS. If these strong outflows commonly occur, they may prove to be an important component of the surface energy budget of the western tropical Pacific.

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Junho Ho
,
Guifu Zhang
,
Petar Bukovcic
,
David B. Parsons
,
Feng Xu
,
Jidong Gao
,
Jacob T. Carlin
, and
Jeffrey C. Snyder

Abstract

Raindrop size distributions (DSD) and rain rate have been estimated from polarimetric radar data using different approaches with the accuracy depending on the errors both in the radar measurements and the estimation methods. Herein, a deep neural network (DNN) technique was utilized to improve the estimation of the DSD and rain rate by mitigating these errors. The performance of this approach was evaluated using measurements from a two-dimensional video disdrometer (2DVD) at the Kessler Atmospheric and Ecological Field Station in Oklahoma as ground truth with the results compared against conventional estimation methods for the period 2006–17. Physical parameters (mass-/volume-weighted diameter and liquid water content), rain rate, and polarimetric radar variables (including radar reflectivity and differential reflectivity) were obtained from the DSD data. Three methods—physics-based inversion, empirical formula, and DNN—were applied to two different temporal domains (instantaneous and rain-event average) with three diverse error assumptions (fitting, measurement, and model errors). The DSD retrievals and rain estimates from 18 cases were evaluated by calculating the bias and root-mean-squared error (RMSE). DNN produced the best performance for most cases, with up to a 5% reduction in RMSE when model errors existed. DSD and rain estimated from a nearby polarimetric radar using the empirical and DNN methods were well correlated with the disdrometer observations; the rain-rate estimate bias of the DNN was significantly reduced (3.3% in DNN vs 50.1% in empirical). These results suggest that DNN has advantages over the physics-based and empirical methods in retrieving rain microphysics from radar observations.

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Philippe Drobinski
,
Fatima Karbou
,
Peter Bauer
,
Philippe Cocquerez
,
Christophe Lavaysse
,
Terry Hock
,
David Parsons
,
Florence Rabier
,
Jean-Luc Redelsperger
, and
Stéphanie Vénel

Abstract

During the international African Monsoon Multidisciplinary Analysis (AMMA) project, stratospheric balloons carrying gondolas called driftsondes capable of dropping meteorological sondes were deployed over West Africa and the tropical Atlantic Ocean. The goals of the deployment were to test the technology and to study the African easterly waves, which are often the forerunners of hurricanes. Between 29 August and 22 September 2006, 124 sondes were dropped over the seven easterly waves that moved across Africa into the Atlantic between about 10° and 20°N, where almost no in situ vertical information exists. Conditions included waves that developed into Tropical Storm Florence and Hurricanes Gordon and Helene. In this study, a selection of numerical weather prediction model outputs has been compared with the dropsondes to assess the effect of some developments in data assimilation on the quality of analyses and forecasts. By comparing two different versions of the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model of Météo-France with the dropsondes, first the benefits of the last data assimilation updates are quantified. Then comparisons are carried out using the ARPEGE model and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts. It is shown that the two models represent very well the vertical structure of temperature and humidity over both land and sea, and particularly within the Saharan air layer, which displays humidity below 5%–10%. Conversely, the models are less able to represent the vertical structure of the meridional wind. This problem seems to be common to ARPEGE and IFS, and its understanding still requires further investigations.

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