Detailed flow, hydrometeor and lightning characteristics of an isolated thunderstorm during COPS

Abstract. The three-hour life-cycle of the isolated thunderstorm on 15 July 2007 during the Convective and Orographically-induced Precipitation Study (COPS) is documented in detail, with a special emphasis on the rapid development and mature phases. Remote sensing techniques as 5-min rapid scans from geostationary satellites, combined velocity retrievals from up to four Doppler-radars, the polarimetric determination of hydrometeors and spatio-temporal occurrences of lightning strokes are employed to arrive at a quantification of the physical parameters of this, during the COPS period, singular event. Inner cloud flow fields are available from radar multiple Doppler analyses at four consecutive times separated by 15 min-intervals. They contain horizontal winds of around 15 m s−1 and updrafts exceeding 5 m s−1, the latter collocated with lightning strokes. Reflectivity and polarimetric data indicate the existence of hail at the 2 km level around 14:40. Furthermore, polarimetric and Doppler radar variables indicate intense hydrometeor variability and turbulence corresponding to an enhanced variance of the retrieved 3-D wind fields. Profiles of flow and hydrometeor statistics over the entire cloud volume provide reference data for high-resolution numerical weather prediction runs in research mode. The study embarks from two movie-loops of geostationary satellite imagery (as Supplement), which provide an intuitive distinction of six phases making up the entire life-cycle of the thunderstorm. It concludes with a triple-image loop, juxtaposing a close-up of the cloud motion as seen by Meteosat, simulated brightness temperature (as a proxy for clouds seen by the infrared satellite channel), and a perspective view on the model generated system of cloud cells. The simulation suggests that several updrafts fed from a low level convergence line eventually removed the convective inhibition and set deep convection in motion. A shear line in the radial velocity relative to the Feldberg radar site shows good agreement beween observation and simulation, whereas the onset location of deep convection exhibits a horizontal discrepancy of 15 km. A quantitative schematic of the isolated thunderstorm synthesizes all retrieved characteristics.

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Detailed flow, hydrometeor and lightning characteristics of an isolated thunderstorm during COPS

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-9717-2012 ◽

2012 ◽

Vol 12 (4) ◽

pp. 9717-9769 ◽

Cited By ~ 1

Author(s):

K. Schmidt ◽

M. Hagen ◽

H. Höller ◽

E. Richard ◽

H. Volkert

Keyword(s):

Life Cycle ◽

Doppler Radar ◽

Rapid Development ◽

Weather Prediction ◽

Rare Event ◽

Time Lapse ◽

Physical Parameters ◽

Wind Fields ◽

Perspective View ◽

Spatio Temporal

Abstract. The three-hour life-cycle of the isolated thunderstorm on 15 July 2007 during the Convective and Orographically-induced Precipitation Study (COPS) is documented in detail, with a special emphasis on the rapid development and mature phases. Remote sensing techniques as 5-min rapid scans from geostationary satellites, combined velocity retrievals from up to four Doppler-radars, the polarimetric determination of hydrometeors and spatio-temporal occurrences of lightning strokes are employed to arrive at a synoptic quantification of the physical parameters of this, during the COPS period, rare event. Inner cloud flow fields are available from radar multiple Doppler analyses, gridded on a 500 m-mesh, at four consecutive times separated by 15 min-intervals (14:35, 14:50, 15:05, 15:20; all times are in UTC). They contain horizontal winds of around 15 m s−1 and updrafts exceeding 5 m s−1, the latter collocated with lightning strokes. Reflectivity and polarimetric data indicate the existence of hail at the 2 km level around 14:40. Furthermore, polarimetric and Doppler radar variables indicate intense hydrometeor variability and cloud dynamics corresponding to an enhanced variance of the retrieved 3-D wind fields. Profiles of flow and hydrometeor statistics over the entire cloud volume provide reference data for high-resolution, episode-type numerical weather prediction runs in research mode. The study embarks from two multi-channel time-lapse movie-loops from geostationary satellite imagery (as Supplement), which provide an intuitive distinction of six phases making up the entire life-cycle of the thunderstorm. It concludes with a triple image-loop, juxtaposing a close-up of the cloud motion as seen by Meteosat, simulated brightness temperature (as a proxy for clouds seen by the infrared satellite channel), and a perspective view on the model generated system of cloud cells. By employing the motion-geared human visual system, such multiple image loops provide a high, and as yet hardly utilised potential for a well-grounded specification of further sensitivity experiments in the modelling community.

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Reducing Errors in Velocity–Azimuth Display (VAD) Wind and Deformation Retrievals from Airborne Doppler Radars in Convective Environments

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-20-0034.1 ◽

2020 ◽

Vol 37 (12) ◽

pp. 2251-2266

Author(s):

Charles N. Helms ◽

Matthew L. Walker McLinden ◽

Gerald M. Heymsfield ◽

Stephen R. Guimond

Keyword(s):

Wind Field ◽

Doppler Radar ◽

Weighting Function ◽

Deep Convection ◽

Absolute Error ◽

Doppler Velocity ◽

Wind Fields ◽

Time Data ◽

Single Antenna ◽

Median Absolute Error

AbstractThe present study describes methods to reduce the uncertainty of velocity–azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion. While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the second hurricane nature run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track and for the across-track wind is reduced from 0.36 to 0.08 m s−1 and from 0.35 to 0.24 m s−1, respectively. Although the study focuses on Doppler radars, the results are equally applicable to conically scanning Doppler lidars as well.

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Impact of Flow-Dependent Horizontal Diffusion on Resolved Convection in AROME

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-032.1 ◽

2012 ◽

Vol 51 (1) ◽

pp. 54-67 ◽

Cited By ~ 9

Author(s):

Lisa Bengtsson ◽

Sander Tijm ◽

Filip Váňa ◽

Gunilla Svensson

Keyword(s):

Prediction Models ◽

Mesoscale Model ◽

Deep Convection ◽

Weather Prediction ◽

Nonlinear Flow ◽

Dynamical Model ◽

Convective Precipitation ◽

Physical Parameters ◽

Rain Intensity ◽

Horizontal Diffusion

AbstractHorizontal diffusion in numerical weather prediction models is, in general, applied to reduce numerical noise at the smallest atmospheric scales. In convection-permitting models, with horizontal grid spacing on the order of 1–3 km, horizontal diffusion can improve the model skill of physical parameters such as convective precipitation. For instance, studies using the convection-permitting Applications of Research to Operations at Mesoscale model (AROME) have shown an improvement in forecasts of large precipitation amounts when horizontal diffusion is applied to falling hydrometeors. The nonphysical nature of such a procedure is undesirable, however. Within the current AROME, horizontal diffusion is imposed using linear spectral horizontal diffusion on dynamical model fields. This spectral diffusion is complemented by nonlinear, flow-dependent, horizontal diffusion applied on turbulent kinetic energy, cloud water, cloud ice, rain, snow, and graupel. In this study, nonlinear flow-dependent diffusion is applied to the dynamical model fields rather than diffusing the already predicted falling hydrometeors. In particular, the characteristics of deep convection are investigated. Results indicate that, for the same amount of diffusive damping, the maximum convective updrafts remain strong for both the current and proposed methods of horizontal diffusion. Diffusing the falling hydrometeors is necessary to see a reduction in rain intensity, but a more physically justified solution can be obtained by increasing the amount of damping on the smallest atmospheric scales using the nonlinear, flow-dependent, diffusion scheme. In doing so, a reduction in vertical velocity was found, resulting in a reduction in maximum rain intensity.

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Unusually Long Duration, Multiple-Doppler Radar Observations of a Front in a Convective Boundary Layer

Monthly Weather Review ◽

10.1175/mwr3261.1 ◽

2007 ◽

Vol 135 (1) ◽

pp. 93-117 ◽

Cited By ~ 12

Author(s):

John R. Stonitsch ◽

Paul M. Markowski

Keyword(s):

Boundary Layer ◽

Density Gradient ◽

Doppler Radar ◽

Deep Convection ◽

Three Dimensional ◽

Horizontal Wind ◽

Normal Density ◽

Wind Fields ◽

Convective Boundary ◽

Convection Initiation

Abstract Dual-Doppler observations acquired by a network of mobile radars deployed in the Oklahoma panhandle on 3 June 2002 are used to document the kinematic structure and evolution of a front. The data were collected during the International H2O Project on a mission to study the initiation of deep convection. Synchronized scanning allowed for the synthesis of three-dimensional wind fields for nearly 5.5 h of the 1557–0000 UTC period. The front initially moved southward as a cold front, stalled, and later retreated northward as a warm front. Deep convection failed to be initiated along the front. In situ thermodynamic measurements obtained by a mobile mesonet were used to document changes in the density gradient at the surface. This paper examines the relationships among the changes in baroclinity, the thermally direct frontal circulation, updraft intensity, alongfront updraft variability, and the intensity of vortices along the front. Increases in the front-normal density gradient tended to be associated with increases in the thermally direct frontal circulation, as expected. Increases in the front-normal density gradient were also associated with an increase in the tilt of the frontal updraft as well as an increase in the contiguity of the updraft along the front, termed the “slabularity.” During periods when the front-normal density gradient and associated thermally direct frontal circulation were weak, the kinematic fields were dominated by boundary layer convection and the slabularity of the front was reduced. Intensification of the front-normal density gradient was accompanied by an increase in the horizontal wind shear and the intensity of vortices that were observed along the front. The vortices modulated the vertical velocity field along the front and therefore the slabularity, too. Thus, although the slabularity was a strong function of the strength of the thermally direct frontal circulation, the slabularity appeared to be modified by vortices in complex ways. Possible implications of the observations for convection initiation are also discussed, particularly with respect to updraft tilt and slabularity.

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Life Cycle of a Mesoscale Circular Gust Front Observed by a C-Band Doppler Radar in West Africa

Monthly Weather Review ◽

10.1175/2010mwr3480.1 ◽

2011 ◽

Vol 139 (5) ◽

pp. 1370-1388 ◽

Cited By ~ 32

Author(s):

Marie Lothon ◽

Bernard Campistron ◽

Michel Chong ◽

Fleur Couvreux ◽

Françoise Guichard ◽

...

Keyword(s):

Boundary Layer ◽

Life Cycle ◽

Doppler Radar ◽

Deep Convection ◽

Convective System ◽

Massachusetts Institute Of Technology ◽

Shallow Convection ◽

Multidisciplinary Analysis ◽

Institute Of Technology ◽

Gust Front

On 10 July 2006, during the Special Observation Period (SOP) of the African Monsoon Multidisciplinary Analysis (AMMA) campaign, a small convective system initiated over Niamey and propagated westward in the vicinity of several instruments activated in the area, including the Massachusetts Institute of Technology (MIT) C-band Doppler radar and the Atmospheric Radiation Measurement (ARM) mobile facility. The system started after a typical convective development of the planetary boundary layer. It grew and propagated within the scope of the radar range, so that its entire life cycle is documented, from the precluding shallow convection to its traveling gust front. The analysis of the observations during the transitions from organized dry convection to shallow convection and from shallow convection to deep convection lends support to the significant role played by surface temperature heterogeneities and boundary layer processes in the initiation of deep convection in semiarid conditions. The analysis of the system later in the day, of its growth and propagation, and of its associated density current allows the authors to estimate the wake available potential energy and demonstrate its capability to trigger deep convection itself. Given the quality and density of observations related to this case, and its typical and quasi-textbook characteristics, this is considered a prime case for the study of initiation and evolution of deep convection, and for testing their parameterizations in single-column models.

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An Enhanced Optical Flow Technique for Radar Nowcasting of Precipitation and Winds

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0110.1 ◽

2017 ◽

Vol 34 (12) ◽

pp. 2637-2658 ◽

Cited By ~ 7

Author(s):

Renzo Bechini ◽

V. Chandrasekar

Keyword(s):

Optical Flow ◽

Doppler Radar ◽

Weather Prediction ◽

Three Dimensional ◽

Wind Fields ◽

Radar Images ◽

A New Technique ◽

Potential Improvement ◽

Analysis System ◽

Precipitation Modeling

AbstractThe atmospheric state evolution is an inherently highly complex three-dimensional problem that numerical weather prediction (NWP) models attempt to solve. Although NWP models are being successfully employed for medium- and long-range forecast, their short-duration forecast (or nowcast) capabilities are still limited because of model initialization challenges. On the lower end of the complexity scale, nowcasting by extrapolation of two-dimensional weather radar images has long been the most effective tool for nowcasting precipitation. Attempts are being made to take advantage of both approaches by blending extrapolation and numerical model forecasts. In this work a different approach is presented, relying on the additional Doppler radar wind information and a simplified modeling of basic physical processes. Instead of mixing the outputs of different forecasts as in blended approaches, the idea behind this study is to combine extrapolation and precipitation modeling in a new technique with a higher level of complexity with respect to conventional nowcasting methods, although still much simpler than NWP models. As a preliminary step, the Variational Doppler Radar Analysis System (VDRAS) is used to provide an initial analysis exploiting all the available dual-polarization and Doppler radar observations. The rainwater and wind fields are then advected using an optical flow technique that is subject to simplified physical interactions. As a result precipitation and wind nowcasting are obtained and are successively validated up to a 1-h lead time, showing potential improvement upon standard extrapolation.

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A Scheme to Assimilate “No Rain” Observations from Doppler Radar

Weather and Forecasting ◽

10.1175/waf-d-17-0108.1 ◽

2018 ◽

Vol 33 (1) ◽

pp. 71-88 ◽

Cited By ~ 9

Author(s):

Shibo Gao ◽

Juanzhen Sun ◽

Jinzhong Min ◽

Ying Zhang ◽

Zhuming Ying

Keyword(s):

Water Vapor ◽

Data Assimilation ◽

Prediction Models ◽

Doppler Radar ◽

Weather Prediction ◽

Grid Point ◽

Three Dimensional ◽

Radar Data ◽

Wind Fields ◽

Radar Data Assimilation

Abstract Radar reflectivity observations contain valuable information on precipitation and have been assimilated into numerical weather prediction models for improved microphysics initialization. However, low-reflectivity (or so-called no rain) echoes have often been ignored or not effectively used in radar data assimilation schemes. In this paper, a scheme to assimilate no-rain radar observations is described within the framework of the Weather Research and Forecasting Model’s three-dimensional variational data assimilation (3DVar) system, and its impact on precipitation forecasts is demonstrated. The key feature of the scheme is a neighborhood-based approach to adjusting water vapor when a grid point is deemed as no rain. The performance of the scheme is first examined using a severe convective case in the Front Range of the Colorado Rocky Mountains and then verified by running the 3DVar system in the same region, with and without the no-rain assimilation scheme for 68 days and 3-hourly rapid update cycles. It is shown that the no-rain data assimilation method reduces the bias and false alarm ratio of precipitation over its counterpart without that assimilation. The no-rain assimilation also improved humidity, temperature, and wind fields, with the largest error reduction in the water vapor field, both near the surface and at upper levels. It is also shown that the advantage of the scheme is in its ability to conserve total water content in cycled radar data assimilation, which cannot be achieved by assimilating only precipitation echoes.

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Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

International Journal of Micro Air Vehicles ◽

10.1177/17568293211004846 ◽

2021 ◽

Vol 13 ◽

pp. 175682932110048

Author(s):

Huajun Song ◽

Yanqi Wu ◽

Guangbing Zhou

Keyword(s):

Detection System ◽

Rapid Development ◽

Reference Value ◽

Scale Transformation ◽

Hardware System ◽

Time Requirements ◽

Aerial Vehicle ◽

Spatio Temporal ◽

Small Targets ◽

Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

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Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment

Atmosphere ◽

10.3390/atmos12020238 ◽

2021 ◽

Vol 12 (2) ◽

pp. 238

Author(s):

Pablo Contreras ◽

Johanna Orellana-Alvear ◽

Paul Muñoz ◽

Jörg Bendix ◽

Rolando Célleri

Keyword(s):

Random Forest ◽

Model Performance ◽

Early Warning Systems ◽

Point Of View ◽

Lead Times ◽

Physical Parameters ◽

Runoff Forecasting ◽

Spatio Temporal ◽

Improved Model ◽

Search Approach

The Random Forest (RF) algorithm, a decision-tree-based technique, has become a promising approach for applications addressing runoff forecasting in remote areas. This machine learning approach can overcome the limitations of scarce spatio-temporal data and physical parameters needed for process-based hydrological models. However, the influence of RF hyperparameters is still uncertain and needs to be explored. Therefore, the aim of this study is to analyze the sensitivity of RF runoff forecasting models of varying lead time to the hyperparameters of the algorithm. For this, models were trained by using (a) default and (b) extensive hyperparameter combinations through a grid-search approach that allow reaching the optimal set. Model performances were assessed based on the R2, %Bias, and RMSE metrics. We found that: (i) The most influencing hyperparameter is the number of trees in the forest, however the combination of the depth of the tree and the number of features hyperparameters produced the highest variability-instability on the models. (ii) Hyperparameter optimization significantly improved model performance for higher lead times (12- and 24-h). For instance, the performance of the 12-h forecasting model under default RF hyperparameters improved to R2 = 0.41 after optimization (gain of 0.17). However, for short lead times (4-h) there was no significant model improvement (0.69 < R2 < 0.70). (iii) There is a range of values for each hyperparameter in which the performance of the model is not significantly affected but remains close to the optimal. Thus, a compromise between hyperparameter interactions (i.e., their values) can produce similar high model performances. Model improvements after optimization can be explained from a hydrological point of view, the generalization ability for lead times larger than the concentration time of the catchment tend to rely more on hyperparameterization than in what they can learn from the input data. This insight can help in the development of operational early warning systems.

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Raindrop Size Distribution and Rain Characteristics during the 2013 Great Colorado Flood

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0184.1 ◽

2015 ◽

Vol 17 (1) ◽

pp. 53-72 ◽

Cited By ~ 21

Author(s):

Katja Friedrich ◽

Evan A. Kalina ◽

Joshua Aikins ◽

Matthias Steiner ◽

David Gochis ◽

...

Keyword(s):

Drop Size ◽

Doppler Radar ◽

Liquid Water Content ◽

Size Distributions ◽

Intense Rainfall ◽

Wind Fields ◽

Raindrop Size Distribution ◽

Median Volume ◽

Drop Size Distributions ◽

Analysis System

Abstract Drop size distributions observed by four Particle Size Velocity (PARSIVEL) disdrometers during the 2013 Great Colorado Flood are used to diagnose rain characteristics during intensive rainfall episodes. The analysis focuses on 30 h of intense rainfall in the vicinity of Boulder, Colorado, from 2200 UTC 11 September to 0400 UTC 13 September 2013. Rainfall rates R, median volume diameters D0, reflectivity Z, drop size distributions (DSDs), and gamma DSD parameters were derived and compared between the foothills and adjacent plains locations. Rainfall throughout the entire event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) resulting in small values of Z (<40 dBZ), differential reflectivity Zdr (<1.3 dB), specific differential phase Kdp (<1° km−1), and D0 (<1 mm). In addition, high liquid water content was present throughout the entire event. Raindrops observed in the plains were generally larger than those in the foothills. DSDs observed in the foothills were characterized by a large concentration of small-sized drops (d < 1 mm). Heavy rainfall rates with slightly larger drops were observed during the first intense rainfall episode (0000–0800 UTC 12 September) and were associated with areas of enhanced low-level convergence and vertical velocity according to the wind fields derived from the Variational Doppler Radar Analysis System. The disdrometer-derived Z–R relationships reflect how unusual the DSDs were during the 2013 Great Colorado Flood. As a result, Z–R relations commonly used by the operational NEXRAD strongly underestimated rainfall rates by up to 43%.

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