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J-L. Redelsperger, D. B. Parsons, and F. Guichard

Abstract

This study investigates the recovery of the tropical atmosphere to moist conditions following the arrival of a dry intrusion observed during the Tropical Ocean and Global Atmosphere Program Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). A cloud-resolving model was used to quantify the processes leading to the moistening of the lower and middle troposphere. The model replicates the general recovery of the tropical atmosphere. The moisture field in the lower and middle troposphere recovered in large part from clouds repeatedly penetrating into the dry air mass. The moistening of the dry air mass in the simulation was due to lateral mixing on the edges of cloudy regions rather than mixing at cloud top. While the large-scale advection of moisture played a role in controlling the general evolution of moisture field, the large-scale thermal advection and radiation tend to directly control the evolution of the temperature field. The diurnal variations in these two terms were largely responsible for temperature variations above the boundary layer. Thermal inversions aloft were often found at the base of dry layers.

The study also investigates which factors control cloud-top height for convective clouds. In both the observations and simulation, the most common mode of convection was clouds extending to ∼4–6 km in height (often termed cumulus congestus clouds), although the period also exhibited a relatively wide range of cloud tops. The study found that cloud-top height often corresponded to the height of the thermal inversions. An examination of the buoyancy in the simulation suggested that entrainment of dry air decreased the parcel buoyancy making these inversions more efficient at controlling cloud top. Water loading effects in the simulation were generally secondary. Thus, there is a strong coupling between the dry air and thermal inversions as clear-air radiative processes associated with the vertical gradient of water vapor produce these inversions, while inversions and entrainment together limit the vertical extent of convection. One positive impact of dry air on convection occurred early in the simulation when clouds first penetrate the extremely dry air mass just above the boundary layer. At this time in the simulation, water vapor excesses within the rising parcels strongly contributed to the positive buoyancy of the clouds. In general, however, the impacts of dry air are to limit the vertical extent of convection and weaken the vertical updrafts.

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S. B. Trier, W. C. Skamarock, M. A. LeMone, D. B. Parsons, and D. P. Jorgensen

Abstract

In this study a numerical cloud model is used to simulate the three-dimensional evolution of an oceanic tropical squall line observed during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment and investigate the impact of small-scale physical processes including surface fluxes and ice microphysics on its structure and evolution. The observed squall line was oriented perpendicular to a moderately strong low-level jet. Salient features that are replicated by the model include an upshear-tilted leading convective region with multiple updraft maxima during its linear stage and the development of a 30-km scale midlevel vortex and associated transition of the line to a pronounced bow-shaped structure.

In this modeling approach, only surface flukes and stresses that differ from those of the undisturbed environment are included. This precludes an unrealistically large modification to the idealized quasi-steady base state and thus allows us to more easily isolate effects of internally generated surface fluxes and stresses on squall line evolution. Neither surface fluxes and stresses nor ice microphysics are necessary to simulate the salient features of the squall line. Their inclusion, however, results in differences in the timing of squall line evolution and greater realism of certain structural characteristics. Significant differences in the convectively induced cold pool strength occur between the early stages of simulations that included ice microphysics and a simulation that contained only warm-rain microphysical processes. The more realistic strength and depth of the cold pool in the simulations that contained ice processes is consistent with an updraft tilt that more closely resembles observations. The squall-line-induced surface fluxes also influence the strength but, more dramatically, the areal extent of the surface cold pool. For the majority of the 6-h simulation, this influence on the cold pool strength is felt only within several hundred meters of the surface. Significant impact of squall-line-induced surface, fluxes on the evolving deep convection at the leading edge of the cold pool is restricted to the later stages (t ≥ 4 h) of simulations and is most substantial in regions where the ground-relative winds are strong and the convectively induced cold pool is initially weak and shallow.

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J. O. Pinto, D. B. Parsons, W. O. J. Brown, S. Cohn, N. Chamberlain, and B. Morley

Abstract

An enhanced National Center for Atmospheric Research (NCAR) integrated sounding system (ISS) was deployed as part of the Vertical Transport and Mixing (VTMX) field experiment, which took place in October of 2000. The enhanced ISS was set up at the southern terminus of the Great Salt Lake Valley just north of a gap in the Traverse Range (TR), which separates the Great Salt Lake and Utah Lake basins. This location was chosen to sample the dynamic and thermodynamic properties of the flow as it passes over the TR separating the two basins. The enhanced ISS allowed for near-continuous sampling of the nocturnal boundary layer (NBL) and low-level winds associated with drainage flow through the gap in the TR. Diurnally varying winds were observed at the NCAR site on days characterized by weak synoptic forcing and limited cloud cover. A down-valley jet (DVJ) was observed on about 50% of the nights during VTMX, with the maximum winds usually occurring within 150 m of the surface. The DVJ was associated with abrupt warming at low levels as a result of downward mixing and vertical transport of warm air from the inversion layer above. Several processes were observed to contribute to vertical transport and mixing at the NCAR site. Pulses in the strength of the DVJ contributed to vertical transport by creating localized areas of low-level convergence. Gravity waves and Kelvin–Helmholtz waves, which facilitated vertical mixing near the surface and atop the DVJ, were observed with a sodar and an aerosol backscatter lidar that were deployed as part of the enhanced ISS. The nonlocal nature of the processes responsible for generating turbulence in strongly stratified surface layers in complex terrain confounds surface flux parameterizations typically used in mesoscale models that rely on Monin–Obukhov similarity theory. This finding has major implications for modeling NBL structure and drainage flows in regions of complex terrain.

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M. J. Rodwell, D. S. Richardson, D. B. Parsons, and H. Wernli

Abstract

While chaos ensures that probabilistic weather forecasts cannot always be “sharp,” it is important for users and developers that they are reliable. For example, they should not be overconfident or underconfident. The “spread–error” relationship is often used as a first-order assessment of the reliability of ensemble weather forecasts. This states that the ensemble standard deviation (a measure of forecast uncertainty) should match the root-mean-square error on the ensemble mean (when averaged over a sufficient number of forecast start dates). It is shown here that this relationship is now largely satisfied at the European Centre for Medium-Range Weather Forecasts (ECMWF) for ensemble forecasts of the midlatitude, midtropospheric flow out to lead times of at least 10 days when averaged over all flow situations throughout the year. This study proposes a practical framework for continued improvement in the reliability (and skill) of such forecasts. This involves the diagnosis of flow-dependent deficiencies in short-range (∼12 h) reliability for a range of synoptic-scale flow types and the prioritization of modeling research to address these deficiencies. The approach is demonstrated for a previously identified flow type, a trough over the Rockies with warm, moist air ahead. The mesoscale convective systems that can ensue are difficult to predict and, by perturbing the jet stream, are thought to lead to deterministic forecast “busts” for Europe several days later. The results here suggest that jet stream spread is insufficient during this flow type, and thus unreliable. This is likely to mean that the uncertain forecasts for Europe may, nevertheless, still be overconfident.

Open access
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.

Open access
D. B. Parsons, M. Beland, D. Burridge, P. Bougeault, G. Brunet, J. Caughey, S. M. Cavallo, M. Charron, H. C. Davies, A. Diongue Niang, V. Ducrocq, P. Gauthier, T. M. Hamill, P. A. Harr, S. C. Jones, R. H. Langland, S. J. Majumdar, B. N. Mills, M. Moncrieff, T. Nakazawa, T. Paccagnella, F. Rabier, J.-L. Redelsperger, C. Riedel, R. W. Saunders, M. A. Shapiro, R. Swinbank, I. Szunyogh, C. Thorncroft, A. J. Thorpe, X. Wang, D. Waliser, H. Wernli, and Z. Toth

Abstract

The Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.

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Bart Geerts, David Parsons, Conrad L. Ziegler, Tammy M. Weckwerth, Michael I. Biggerstaff, Richard D. Clark, Michael C. Coniglio, Belay B. Demoz, Richard A. Ferrare, William A. Gallus Jr., Kevin Haghi, John M. Hanesiak, Petra M. Klein, Kevin R. Knupp, Karen Kosiba, Greg M. McFarquhar, James A. Moore, Amin R. Nehrir, Matthew D. Parker, James O. Pinto, Robert M. Rauber, Russ S. Schumacher, David D. Turner, Qing Wang, Xuguang Wang, Zhien Wang, and Joshua Wurman

Abstract

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night.

To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

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