Influence of Large-Scale Flow Regimes on Cool-Season Precipitation in the Northeastern United States

2008 ◽  
Vol 136 (8) ◽  
pp. 2945-2963 ◽  
Author(s):  
Heather M. Archambault ◽  
Lance F. Bosart ◽  
Daniel Keyser ◽  
Anantha R. Aiyyer
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Large Scale ◽  
Flow Regimes ◽  
Average Frequency ◽  
Composite Analysis ◽  
Cool Season ◽  
Eastern Canada ◽  
Large Scale Flow ◽  
Precipitation Events

Abstract The influence of large-scale flow regimes on cool-season (November–April) northeastern U.S. (Northeast) precipitation is investigated for the period 1948–2003 from statistical and synoptic perspectives. These perspectives are addressed through (i) a statistical analysis of cool-season Northeast precipitation associated with the North Atlantic Oscillation (NAO) and Pacific–North American (PNA) regimes (one standard deviation or greater NAO or PNA daily index anomalies persisting several days), and (ii) a composite analysis of the synoptic signatures of major (two standard deviation) 24-h cool-season Northeast precipitation events occurring during NAO and PNA regimes. The statistical analysis reveals that negative PNA regimes are associated with above-average cool-season Northeast precipitation and an above-average frequency of light and moderate precipitation events, whereas the opposite associations are true for positive PNA regimes. In comparison with PNA regimes, NAO regimes are found to have relatively little influence on the amount and frequency of cool-season Northeast precipitation. The composite analysis indicates that a surface cyclone flanked by an upstream trough over the Ohio Valley and downstream ridge over eastern Canada and upper- and lower-level jets in the vicinity of the Northeast are characteristic signatures of major cool-season Northeast precipitation events occurring during NAO and PNA regimes. Negative NAO and positive PNA precipitation events, however, are associated with a more amplified trough–ridge pattern and greater implied Atlantic moisture transport by a low-level jet into the Northeast than positive NAO and negative PNA precipitation events. Furthermore, a signature of lateral upper-level jet coupling is noted only during positive and negative PNA precipitation events.

Relationships between Large-Scale Regime Transitions and Major Cool-Season Precipitation Events in the Northeastern United States

2010 ◽  
Vol 138 (9) ◽  
pp. 3454-3473 ◽  
Author(s):  
Heather M. Archambault ◽  
Daniel Keyser ◽  
Lance F. Bosart
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
North Atlantic ◽  
Large Scale ◽  
Precipitation Event ◽  
Composite Analysis ◽  
Cool Season ◽  
Regime Transitions ◽  
Precipitation Events

Abstract This observational study investigates statistical and synoptic–dynamic relationships between regime transitions, defined as a North Atlantic Oscillation (NAO) or Pacific–North American pattern (PNA) index change from at least a 1 standard deviation anomaly to at least a 1 standard deviation anomaly of opposite sign within 7 days, and cool-season (November–April) northeastern U.S. (NE) precipitation. A statistical analysis is performed of daily cool-season NE precipitation during all NAO and PNA transitions for 1948–2003, and a composite analysis and case study of a major cool-season NE precipitation event occurring during a positive-to-negative NAO transition are conducted. Datasets used are the 0.25° NCEP Unified Precipitation Dataset, the 2.5° NCEP–NCAR reanalysis, and the 1.125° 40-yr ECMWF Re-Analysis (ERA-40). Results of the statistical analysis suggest that cool-season NE precipitation tends to be enhanced during positive-to-negative NAO and negative-to-positive PNA transitions, and suppressed during negative-to-positive NAO and positive-to-negative PNA transitions. Of the four types of regime transitions, only the positive-to-negative NAO transition is associated with substantially more frequent major cool-season NE precipitation events compared to climatology. Results of the composite analysis and case study indicate that a surface cyclone and cyclonic wave breaking associated with the major NE precipitation event can help produce a high-latitude blocking pattern over the North Atlantic characteristic of a negative NAO pattern via thermal advection, potential vorticity transport, and diabatic processes.

Mechanoreceptor and Photoreceptor Tonic Integration in the Crayfish

1973 ◽  
Vol 51 (12) ◽  
pp. 949-958 ◽  
Author(s):  
C. Galeano ◽  
S. Beliveau
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Average Frequency ◽  
Ipsilateral Side ◽  
Average Interval ◽  
Caudal Photoreceptor ◽  
Deviation Coefficient ◽  
Variation Interval ◽  
Density Results

The activity of the caudal photoreceptor of crayfish was studied in: (1) intact tail ganglion, (2) partially isolated, and (3) totally isolated ganglion preparations. Statistical analysis of the photoreceptor activity included average frequency, average interval, variance, standard deviation, coefficient of variation, interval histograms, auto-expectation density, and cross-expectation density. Results showed that the average influence of the mechanoreceptor synapses on the photoreceptors during a period of several seconds was inhibitory, strong on the contralateral and weak on the ipsilateral side.

A multi-wave model for the Quasi-Biennial Oscillation: Plumb’s model extended

2020 ◽  
Author(s):  
Pierre Léard ◽  
Daniel Lecoanet ◽  
Michael Le Bars
Keyword(s):  
Standard Deviation ◽  
Gravity Waves ◽  
Large Scale ◽  
Internal Gravity Waves ◽  
Quasi Biennial Oscillation ◽  
Periodic Oscillations ◽  
Atmospheric Sciences ◽  
Large Scale Flow ◽  
S Model ◽  
Biennial Oscillation

<p>In the Earth’s stratosphere, equatorial zonal winds reverse from easterlies to westerlies with a period of roughly 28 months. This phenomenon, known as Quasi-Biennial Oscillation (QBO), is driven by internal gravity waves (IGWs) propagating in the stratosphere and interacting with the ambient large-scale flow. Those waves are generated by the turbulent motions of the troposphere. In 1977, an idealised model describing the generation of a reversing large-scale flow by two counter-propagating monochromatic internal gravity waves was developed by Plumb [1]. In 1978, the famous Plumb & McEwan’s experiment [2] validated this model using oscillating membranes to force a standing wave pattern at the boundary of a linearly stratified salty-water layer in a cylindrical shell container.</p><p>Recently, the effects of the wave dissipation and wave energy were studied by Renaud et al. [3] using the Plumb model in order to explain the QBO disruption observed in 2016. It was found that as the Reynolds number increases, bifurcations from periodic to non-periodic regimes are seen for the large-scale flow oscillations.</p><p>Here, we present the results obtained from an extended version of the Plumb’s model, taking into account the stochastic generation of IGWs in Nature. Our new model includes a wide spectrum of waves as forcing for the large-scale flow. A gaussian distribution of energy is used in order to compare monochromatic forcing results (characterised by a gaussian energy spectrum with a small standard deviation) with multi-wave forcing results (large standard deviation). Unexpectedly, we find that in a large parameter domain, gathering the energy of the forcing into one frequency results in non-periodic oscillations for the QBO while spreading the same amount of energy among many frequencies results in periodic oscillations. We also investigate more realistic distribution of energy for the forcing including classical convective spectra, with or without rotation. We find that different forcings result in very similar reversals. This result is quite relevant for Global Circulation Models (GCMs) where internal gravity waves are parameterised in order to drive a realistic QBO. However, our study suggests that driving a QBO with realistic characteristics (amplitude, period) does not involve that the input forcing (i.e. the wave spectrum characteristics) is realistic as well.</p><p><strong>References:</strong></p><p>[1] R. A. Plumb, « The interaction of two internal waves with the mean flow: Implications for the theory of the quasi-biennial oscillation », Journal of the Atmospheric Sciences, 1977.</p><p>[2] R. A. Plumb and A. D. McEwan, « The instability of a forced standing wave in a viscous stratified fluid: a laboratory analogue of the quasi biennial oscillation », Journal of the Atmospheric Sciences, 1978.</p><p>[3] A. Renaud, L.-P. Nadeau, and A. Venaille, « Periodicity Disruption of a Model Quasibiennial Oscillation of Equatorial Winds », Phys. Rev. Lett., vol. 122, n<sup>o</sup> 21, p. 214504, 2019.</p>

Precipitation variability in the Meuse basin in relation to atmospheric circulation

2005 ◽  
Vol 51 (5) ◽  
pp. 5-14 ◽  
Author(s):  
M. Tu ◽  
P.J.M. de Laat ◽  
M.J. Hall ◽  
M.J.M. de Wit
Keyword(s):  
Statistical Analysis ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Precipitation Variability ◽  
Past Century ◽  
The Past ◽  
Winter Half ◽  
Summer Half ◽  
Large Scale Atmospheric Circulation ◽  
Precipitation Events

The distribution of precipitation events in the Meuse basin during the past century has been found to reflect the large-scale atmospheric circulation, as characterised by the Grosswetterlagen system. Statistical analysis of the long observation records (1911–2002) for the basin showed that although the annual (November to October) and winter half-year (November to April) frequencies of wet days (≥1 mm/day) were nearly stable, the associated precipitation amounts have significantly increased since 1980. From 1980 onwards, the very wet days (≥10 mm/day) in the winter half-year have become more frequent. No obvious change was identified for the summer half-year (May to October) very wet days. Both the precipitation amounts of wet and very wet days in the winter half-year and the occurrence of associated atmospheric circulation of the types/sub-types west cyclone, southwest cyclone and northwest cyclone showed a significant increase around 1980.

scholarly journals Distribution of Single-Banded Snowfall in Central U.S. Cyclones

2017 ◽  
Vol 32 (2) ◽  
pp. 533-554 ◽  
Author(s):  
Martin A. Baxter ◽  
Philip N. Schumacher
Keyword(s):  
United States ◽  
Life Span ◽  
Large Scale ◽  
Situational Awareness ◽  
Weather Prediction ◽  
Composite Analysis ◽  
Synoptic Scale ◽  
Surface Cyclone ◽  
Central United States ◽  
Large Scale Flow

Abstract A climatology of single-banded snowfall in the central United States and the variability of processes at work in its formation are presented. Ninety-eight snowbands are identified in association with 66 cyclones over 5 yr spanning the winters from 2006/07 through 2010/11. An additional 38 cyclones featured nonbanded snowfall exceeding 4 in. (10.2 cm). Nearly twice as many bands were observed to the northeast of the surface low than to the northwest. Over each snowband’s life cycle, the median (mean) snowband lasted 4.0 (5.2) h, was 42 (45) km wide, 388 (428) km long, and had an aspect ratio of 10.2 (10.8). A common appearance exists for snowbands in different large-scale flow regimes and locations relative to the surface cyclone. The median snowband elongates during the first half of its life span, with its width remaining constant. During the second half of the median snowband’s life span, the length and width contract. Composite analysis of the synoptic and broad mesoscale environments that snowbands form in illustrates that the juxtaposition of the ingredients necessary for snowbands are similar no matter which quadrant of the surface low the band is located in, indicating that the synoptic-scale flow determines where these ingredients are organized with respect to the cyclone. The frequency of banded snowfall within each northern quadrant of the surface low, the typical snowband characteristics and their evolution, and the patterns that give rise to snowbands documented by this work can all prove useful to forecasters tasked with maintaining situational awareness in the presence of many solutions provided by ensemble numerical weather prediction.

Large-scale flow field visualization for aneurysm treatment

2001 ◽  
Vol 9 (1) ◽  
pp. 3-7
Author(s):  
Damon Liu ◽  
Mark Burgin ◽  
Walter Karplus ◽  
Daniel Valentino
Keyword(s):  
Flow Field ◽  
Large Scale ◽  
Aneurysm Treatment ◽  
Large Scale Flow

Effects of Squish Flow on Tangential Flow and Turbulence in a Diesel Engine

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Yanzhe Sun ◽  
Kai Sun ◽  
Tianyou Wang ◽  
Yufeng Li ◽  
Zhen Lu
Keyword(s):  
Diesel Engine ◽  
Turbulent Flows ◽  
Large Scale ◽  
Radial Flow ◽  
Tangential Component ◽  
Tangential Flow ◽  
Image Velocimetry ◽  
Turbulence Production ◽  
Large Scale Flow ◽  
Main Effects

Emission and fuel consumption in swirl-supported diesel engines strongly depend on the in-cylinder turbulent flows. But the physical effects of squish flow on the tangential flow and turbulence production are still far from well understood. To identify the effects of squish flow, Particle image velocimetry (PIV) experiments are performed in a motored optical diesel engine equipped with different bowls. By comparing and associating the large-scale flow and turbulent kinetic energy (k), the main effects of the squish flow are clarified. The effect of squish flow on the turbulence production in the r−θ plane lies in the axial-asymmetry of the annular distribution of radial flow and the deviation between the ensemble-averaged swirl field and rigid body swirl field. Larger squish flow could promote the swirl center to move to the cylinder axis and reduce the deformation of swirl center, which could decrease the axial-asymmetry of annular distribution of radial flow, further, that results in a lower turbulence production of the shear stress. Moreover, larger squish flow increases the radial fluctuation velocity which makes a similar contribution to k with the tangential component. The understanding of the squish flow and its correlations with tangential flow and turbulence obtained in this study is beneficial to design and optimize the in-cylinder turbulent flow.

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