scholarly journals Characteristics of Low-level Jets in Shanghai during the 2008-2009 Warm Seasons as Inferred from Wind Profiler Radar Data

2012 ◽  
Vol 90 (6) ◽  
pp. 891-903 ◽  
Author(s):  
Yu DU ◽  
Qinghong ZHANG ◽  
Yue YING ◽  
Yinming YANG
2001 ◽  
Vol 19 (8) ◽  
pp. 825-836 ◽  
Author(s):  
V. Lehmann ◽  
G. Teschke

Abstract. In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes) from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques) – Radio science (remote sensing; signal processing)


2008 ◽  
Vol 86 (5) ◽  
pp. 699-717 ◽  
Author(s):  
Nga T. PHAM ◽  
Kenji NAKAMURA ◽  
Fumie A. FURUZAWA ◽  
Shinsuke SATOH

2009 ◽  
Vol 48 (8) ◽  
pp. 1627-1642 ◽  
Author(s):  
P. Baas ◽  
F. C. Bosveld ◽  
H. Klein Baltink ◽  
A. A. M. Holtslag

Abstract A climatology of nocturnal low-level jets (LLJs) is presented for the topographically flat measurement site at Cabauw, the Netherlands. LLJ characteristics are derived from a 7-yr half-hourly database of wind speed profiles, obtained from the 200-m mast and a wind profiler. Many LLJs at Cabauw originate from an inertial oscillation, which develops after sunset in a layer decoupled from the surface by stable stratification. The data are classified to different types of stable boundary layers by using the geostrophic wind speed and the isothermal net radiative cooling as classification parameters. For each of these classes, LLJ characteristics like frequency of occurrence, height above ground level, and the turning of the wind vector across the boundary layer are determined. It is found that LLJs occur in about 20% of the nights, are typically situated at 140–260 m above ground level, and have a speed of 6–10 m s−1. Development of a substantial LLJ is most likely to occur for moderate geostrophic forcing and a high radiative cooling. A comparison with the 40-yr ECMWF Re-Analysis (ERA-40) is added to illustrate how the results can be used to evaluate the performance of atmospheric models.


2005 ◽  
Vol 135 (1-4) ◽  
pp. 35-43 ◽  
Author(s):  
N. Mathieu ◽  
I.B. Strachan ◽  
M.Y. Leclerc ◽  
A. Karipot ◽  
E. Pattey

Author(s):  
Evan S. Bentley ◽  
Richard L. Thompson ◽  
Barry R. Bowers ◽  
Justin G. Gibbs ◽  
Steven E. Nelson

AbstractPrevious work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–2018) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance.Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1nm) circulations in a poor (STP=0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.


2014 ◽  
Vol 7 (1) ◽  
pp. 135-148 ◽  
Author(s):  
M. Maruri ◽  
J. A. Romo ◽  
L. Gomez

Abstract. It is well known in the scientific community that some remote sensing instruments assume that sample volumes present homogeneous conditions within a defined meteorological profile. At complex topographic sites and under extreme meteorological conditions, this assumption may be fallible depending on the site, and it is more likely to fail in the lower layers of the atmosphere. This piece of work tests the homogeneity of the wind field over a boundary layer wind profiler radar located in complex terrain on the coast under different meteorological conditions. The results reveal the qualitative importance of being aware of deviations in this homogeneity assumption and evaluate its effect on the final product. Patterns of behavior in data have been identified in order to simplify the analysis of the complex signal registered. The quality information obtained from the homogeneity study under different meteorological conditions provides useful indicators for the best alternatives the system can offer to build wind profiles. Finally, the results are also to be considered in order to integrate them in a quality algorithm implemented at the product level.


2012 ◽  
Vol 140 (12) ◽  
pp. 3972-3991 ◽  
Author(s):  
Corey K. Potvin ◽  
Louis J. Wicker

Abstract Kinematical analyses of mobile radar observations are critical to advancing the understanding of supercell thunderstorms. Maximizing the accuracy of these and subsequent dynamical analyses, and appropriately characterizing the uncertainty in ensuing conclusions about storm structure and processes, requires thorough knowledge of the typical errors obtained using different retrieval techniques. This study adopts an observing system simulation experiment (OSSE) framework to explore the errors obtained from ensemble Kalman filter (EnKF) assimilation versus dual-Doppler analysis (DDA) of storm-scale mobile radar data. The radar characteristics and EnKF model errors are varied to explore a range of plausible scenarios. When dual-radar data are assimilated, the EnKF produces substantially better wind retrievals at higher altitudes, where DDAs are more sensitive to unaccounted flow evolution, and in data-sparse regions such as the storm inflow sector. Near the ground, however, the EnKF analyses are comparable to the DDAs when the radar cross-beam angles (CBAs) are poor, and slightly worse than the DDAs when the CBAs are optimal. In the single-radar case, the wind analyses benefit substantially from using finer grid spacing than in the dual-radar case for the objective analysis of radar observations. The analyses generally degrade when only single-radar data are assimilated, particularly when microphysical parameterization or low-level environmental wind errors are introduced. In some instances, this leads to large errors in low-level vorticity stretching and Lagrangian circulation calculations. Nevertheless, the results show that while multiradar observations of supercells are always preferable, judicious use of single-radar EnKF assimilation can yield useful analyses.


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