scholarly journals A study of the relationship between cloud-to-ground lightning and precipitation in the convective weather system in China

2002 ◽  
Vol 20 (1) ◽  
pp. 107-113 ◽  
Author(s):  
Y. Zhou ◽  
X. Qie ◽  
S. Soula
Keyword(s):  
Atmospheric Electricity ◽  
Estimation Method ◽  
Gansu Province ◽  
Lightning Flash ◽  
Weather System ◽  
Convective Systems ◽  
Observation Area ◽  
Precipitation Estimation ◽  
Convective Weather ◽  
Cg Lightning

Abstract. In this paper, the correlation between cloud-to-ground (CG) lightning and precipitation has been studied by making use of the data from weather radar, meteorological soundings, and a lightning location system that includes three direction finders about 40 km apart from each other in the Pingliang area of east Gansu province in P. R. China. We have studied the convective systems that developed during two cold front processes passing over the observation area, and found that the CG lightning can be an important factor in the precipitation estimation. The regression equation between the average precipitation intensity (R) and the number of CG lightning flashes (L) in the main precipitation period is R = 1.69 ln (L) - 0.27, and the correlation coefficient r is 0.86. The CG lightning flash rate can be used as an indicator of the formation and development of the convective weather system. Another more exhaustive precipitation estimation method has been developed by analyzing the temporal and spatial distributions of the precipitation relative to the location of the CG lightning flashes. Precipitation calculated from the CG lightning flashes is very useful, especially in regions with inadequate radar cover.Key words. Meteorology and atmospheric dynamics (atmospheric electricity; lightning; precipitation)

scholarly journals Lightning and precipitation produced by severe weather systems over Belém, Brazil

2014 ◽  
Vol 29 (spe) ◽  
pp. 41-59 ◽  
Author(s):  
Wanda Maria do Nascimento Ribeiro ◽  
José Ricardo Santos Souza ◽  
Márcio Nirlando Gomes Lopes ◽  
Renata Kelen Cardoso Câmara ◽  
Edson José Paulino Rocha ◽  
...  
Keyword(s):  
Large Scale ◽  
Electric Activity ◽  
Weather Conditions ◽  
Rain Gauge ◽  
Mesoscale Convective Systems ◽  
Major Influence ◽  
Rainfall Events ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Cg Lightning

CG Lightning flashes events monitored by a LDN of the Amazon Protection System, which included 12 LPATS IV VAISALA sensors distributed over eastern Amazonia, were analyzed during four severe rainstorm occurrences in Belem-PA-Brazil, in the 2006-2007 period. These selected case studies referred to rainfall events, which produced more than 25 mm/hour, or more than 40 mm/ 2 hours of precipitation rate totals, registered by a tipping bucket automatic high-resolution rain gauge, located at 1º 47' 53" S and 48º 30' 16" W. Centered at this location, a 30 ,10 and 5 km radius circles were drawn by means of a geographic information system, and the data from lightning occurrences within this larger area, were set apart for analysis. During these severe storms the CG lightning events, occurred almost randomly over the surrounding defined circle, previously covered by mesoscale convective systems, for all cases studied. This work also showed that the interaction between large-scale and mesoscale weather conditions have a major influence on the intensity of the storms studied cases. In addition to the enhancement of the lightning and precipitation rates, the electric activity within the larger circles can precede the rainfall at central point of the areas

scholarly journals Analysis and Estimation of Geographical and Topographic Influencing Factors for Precipitation Distribution over Complex Terrains: A Case of the Northeast Slope of the Qinghai–Tibet Plateau

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 349 ◽  
Author(s):  
Weicheng Liu ◽  
Qiang Zhang ◽  
Zhao Fu ◽  
Xiaoyan Chen ◽  
Hong Li
Keyword(s):  
Complex Terrain ◽  
Multivariate Regression ◽  
Estimation Method ◽  
Precipitation Forecast ◽  
Tibet Plateau ◽  
Mean Annual Precipitation ◽  
Observation Data ◽  
Precipitation Distribution ◽  
Precipitation Estimation ◽  
Qinghai Tibet Plateau

Due to the complex terrain, sparse precipitation observation sites, and uneven distribution of precipitation in the northeastern slope of the Qinghai–Tibet Plateau, it is necessary to establish a precipitation estimation method with strong applicability. In this study, the precipitation observation data from meteorological stations in the northeast slope of the Qinghai–Tibet Plateau and 11 geographical and topographic factors related to precipitation distribution were used to analyze the main factors affecting precipitation distribution. Based on the above, a multivariate linear regression precipitation estimation model was established. The results revealed that precipitation is negatively related to latitude and elevation, but positively related to longitude and slope for stations with an elevation below 1700 m. Meanwhile, precipitation shows positive correlations with both latitude and longitude, and negative correlations with elevation for stations with elevations above 1700 m. The established multivariate regression precipitation estimating model performs better at estimating the mean annual precipitation in autumn, summer, and spring, and is less accurate in winter. In contrast, the multivariate regression mode combined with the residual error correction method can effectively improve the precipitation forecast ability. The model is applicable to the unique natural geographical features of the northeast slope of the Qinghai–Tibet Plateau. The research results are of great significance for analyzing the temporal and spatial distribution pattern of precipitation in complex terrain areas.

Nowcasting lightning during RELAMPAGO

2020 ◽  
Author(s):  
Evan Ruzanski ◽  
Venkatachalam Chandrasekar ◽  
Ivan Arias
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
The United States ◽  
Extreme Weather Events ◽  
Optimization Approach ◽  
Lightning Flash ◽  
Convective Systems ◽  
Physical Mechanisms ◽  
Weather Events ◽  
Future Loss

<p>The Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) international field campaign occurred June 1, 2018, to April 30, 2019. This campaign was comprised of more than 150 scientists from 10 organizations. Data was collected to investigate different phases of the life cycle of thunderstorms that occur in Argentina to better understand the physical mechanisms that cause the initiation and growth of organized convective systems in some of the most intense storms on the planet. The main focus of the project was to develop new conceptual models for forecasting extreme weather events that will hopefully lead to reductions in future loss of life and property.</p><p>This presentation shows the performance of a recently developed model for estimating ice mass aloft, a key component in the atmospheric electrification process, and a method for nowcasting lightning activity using C-band weather radar and Global Lightning Dataset (GLD360) data from RELAMPAGO. This nowcasting method uses a grid-based approach to make specific forecasts of lightning in space and time. The method estimates ice mass aloft in the region where electrification occurs using a numerical optimization approach to essentially reframe a simplified bulk microphysical model into a completely data-driven model. Previous results using WSR-88D S-band radar data in the United States showed that using this model significantly improved nowcasts of first-flash lightning occurrence versus the traditional weather radar-based ice mass estimator as well as using lightning flash-rate density directly.</p>

scholarly journals PERSIANN-MSA: A Precipitation Estimation Method from Satellite-Based Multispectral Analysis

2009 ◽  
Vol 10 (6) ◽  
pp. 1414-1429 ◽  
Author(s):  
Ali Behrangi ◽  
Kuo-lin Hsu ◽  
Bisher Imam ◽  
Soroosh Sorooshian ◽  
George J. Huffman ◽  
...  
Keyword(s):  
Estimation Method ◽  
Principal Component ◽  
Input Information ◽  
Multispectral Data ◽  
Spectral Bands ◽  
Infrared Imager ◽  
Precipitation Estimation ◽  
Multispectral Analysis ◽  
Near Future ◽  
Infrared Data

Abstract Visible and infrared data obtained from instruments onboard geostationary satellites have been extensively used for monitoring clouds and their evolution. The Advanced Baseline Imager (ABI) that will be launched onboard the Geostationary Operational Environmental Satellite-R (GOES-R) series in the near future will offer a larger range of spectral bands; hence, it will provide observations of cloud and rain systems at even finer spatial, temporal, and spectral resolutions than are possible with the current GOES. In this paper, a new method called Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks–Multispectral Analysis (PERSIANN-MSA) is proposed to evaluate the effect of using multispectral imagery on precipitation estimation. The proposed approach uses a self-organizing feature map (SOFM) to classify multidimensional input information, extracted from each grid box and corresponding textural features of multispectral bands. In addition, principal component analysis (PCA) is used to reduce the dimensionality to a few independent input features while preserving most of the variations of all input information. The above method is applied to estimate rainfall using multiple channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellite. In comparison to the use of a single thermal infrared channel, the analysis shows that using multispectral data has the potential to improve rain detection and estimation skills with an average of more than 50% gain in equitable threat score for rain/no-rain detection, and more than 20% gain in correlation coefficient associated with rain-rate estimation.

scholarly journals A 10-Year Survey of Extreme Rainfall Events in the Central and Eastern United States Using Gridded Multisensor Precipitation Analyses

2014 ◽  
Vol 142 (9) ◽  
pp. 3147-3162 ◽  
Author(s):  
Stephanie N. Stevenson ◽  
Russ S. Schumacher
Keyword(s):  
United States ◽  
Tropical Cyclones ◽  
Stage Iv ◽  
Extreme Rainfall ◽  
Eastern United States ◽  
Weather System ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Convective Systems ◽  
Maximum Minimum

Extreme rainfall events in the central and eastern United States during 2002–11 were identified using NCEP stage-IV precipitation analyses. Precipitation amounts were compared against established 50- and 100-yr recurrence interval thresholds for 1-, 6-, and 24-h durations. The authors identified points where analyzed precipitation exceeded the threshold, and combined points associated with the same weather system into events. At shorter durations, points exceeding the thresholds were most common in the Southeast, whereas points were more uniformly distributed for the 24-h duration. Most 24-h events have more points than the other durations, reflecting the importance of organized precipitation systems on longer temporal scales. Though monthly peaks varied by region, the maximum (minimum) usually occurred during the summer (winter); however, the 24-h point maximum occurred in September owing to tropical cyclones. The maximum (minimum) in hourly extreme rainfall points occurred at 2300 (1100) LST, though there were regional differences in the timing of the diurnal maxima and minima. Over half of 100-yr, 24-h events were a result of mesoscale convective systems (MCS), with synoptic and tropical systems responsible for nearly one-third and one-tenth, respectively. Of the 10 events with the most points exceeding this threshold, 5 were associated with tropical cyclones, 3 were synoptic events, and 2 were MCSs. Among the MCS events, 7 of the top 10 were training line/adjoining stratiform (TL/AS). While the 49 TL/AS events investigated further had similar moisture availability, the more widespread events had stronger low-level winds, stronger warm air advection, and stronger and more expansive frontogenesis in the inflow.

scholarly journals The Effect of Storm Life Cycle on Satellite Rainfall Estimation Error

2009 ◽  
Vol 26 (4) ◽  
pp. 769-777 ◽  
Author(s):  
Alemu Tadesse ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Life Cycle ◽  
Estimation Error ◽  
Rain Gauge ◽  
Life Cycles ◽  
Error Statistics ◽  
Radar Rainfall ◽  
Convective Systems ◽  
Satellite Retrieval ◽  
Maturity Stages ◽  
Precipitation Estimation

Abstract The study uses storm tracking information to evaluate error statistics of satellite rain estimation at different maturity stages of storm life cycles. Two satellite rain retrieval products are used for this purpose: (i) NASA’s Multisatellite Precipitation Analysis–Real Time product available at 25-km/hourly resolution (3B41-RT) and (ii) the University of California (Irvine) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product available at 4-km–hourly resolution. Both algorithms use geostationary satellite infrared (IR) observations calibrated to an array of passive microwave (PM) earth-orbiting satellite sensor rain retrievals. The techniques differ in terms of algorithmic structure and in the way they use the PM rainfall to calibrate the IR rain algorithms. The satellite retrievals are evaluated against rain gauge–calibrated radar rainfall estimates over the continental United States. Error statistics of hourly rain volumes are determined separately for thunderstorm and shower-type convective systems and for different storm life durations and stages of maturity. The authors show distinct differences between the two satellite retrieval error characteristics. The most notable difference is the strong storm life cycle dependence of 3B41-RT relative to the nearly independent PERSIANN behavior. Another is in the algorithm performance between thunderstorms and showers; 3B41-RT exhibits significant bias increase at longer storm life durations. PERSIANN exhibits consistently improved correlations relative to the 3B41-RT for all storm life durations and maturity stages. The findings of this study support the hypothesis that incorporating cloud type information into the retrieval (done by the PERSIANN algorithm) can help improve the satellite retrieval accuracy.

scholarly journals Thunderstorms in Corsica Island measured during the EXAEDRE aircraft campaign

2021 ◽  
Author(s):  
Keunok Lee ◽  
Eric Defer ◽  
Pauline Combarnous ◽  
Jean-Pierre Pinty ◽  
Magalie Buguet ◽  
...  
Keyword(s):  
Atmospheric Electricity ◽  
Convective Cloud ◽  
Cloud Microphysics ◽  
Convective Systems ◽  
Cloud Radar ◽  
Weather Radars ◽  
Cloud Resolving Model ◽  
Mapping Array ◽  
Locating System ◽  
Horizontal Grid

<p>The aim of this study is to enhance our understanding about the microphysical structure of convective cloud systems and its relationships to the ambient electrical field, and to assess the capability of a model to capture the cloud electrical properties. This study relies on the EXAEDRE (EXploiting new Atmospheric Electricity Data for Research and the Environment) aircraft campaign that took place from 13 September to 8 October 2018 in Corsica Island. Eight electrified convective systems were successfully sampled during the campaign by the French Falcon 20 aircraft (e.g. RASTA Doppler cloud radar, microphysics probes, electric field mills) and ground-based platforms (Lightning Mapping Array network, Météorage operational lightning locating system and Météo-France weather radars). In this study, a multi-cell thunderstorm which developed over the complex topography of Corsica Island on 17 September 2018 was selected to investigate and to understand the physical processes linking lightning occurrence, electrification efficiency, cloud microphysics and dynamics. The detailed analysis results using the unprecedented airborne and ground-based dataset and their comparison to the numerical simulation results with a horizontal grid spacing of 1 km comprising the explicit electrical scheme CELLS (Cloud Electrification and Lightning Scheme) implemented in the cloud resolving model Meso-NH has been conducted. The key results will be presented at the conference.</p>

scholarly journals Backward Adaptive Brightness Temperature Threshold Technique (BAB3T): A Methodology to Determine Extreme Convective Initiation Regions Using Satellite Infrared Imagery

2020 ◽  
Vol 12 (2) ◽  
pp. 337
Author(s):  
Maite Cancelada ◽  
Paola Salio ◽  
Daniel Vila ◽  
Stephen W. Nesbitt ◽  
Luciano Vidal
Keyword(s):  
Brightness Temperature ◽  
Deep Convection ◽  
Convective System ◽  
Temperature Threshold ◽  
Lightning Flash ◽  
Convective Initiation ◽  
Convective Storms ◽  
Convective Systems ◽  
Diurnal Cycles ◽  
Backward Tracking

Thunderstorms in southeastern South America (SESA) stand out in satellite observations as being among the strongest on Earth in terms of satellite-based convective proxies, such as lightning flash rate per storm, the prevalence for extremely tall, wide convective cores and broad stratiform regions. Accurately quantifying when and where strong convection is initiated presents great interest in operational forecasting and convective system process studies due to the relationship between convective storms and severe weather phenomena. This paper generates a novel methodology to determine convective initiation (CI) signatures associated with extreme convective systems, including extreme events. Based on the well-established area-overlapping technique, an adaptive brightness temperature threshold for identification and backward tracking with infrared data is introduced in order to better identify areas of deep convection associated with and embedded within larger cloud clusters. This is particularly important over SESA because ground-based weather radar observations are currently limited to particular areas. Extreme rain precipitation features (ERPFs) from Tropical Rainfall Measurement Mission are examined to quantify the full satellite-observed life cycle of extreme convective events, although this technique allows examination of other intense convection proxies such as the identification of overshooting tops. CI annual and diurnal cycles are analyzed and distinctive behaviors are observed for different regions over SESA. It is found that near principal mountain barriers, a bimodal diurnal CI distribution is observed denoting the existence of multiple CI triggers, while convective initiation over flat terrain has a maximum frequency in the afternoon.

scholarly journals An Analysis on Perturbation Features of Convection-Allowing Ensemble Prediction Based on the Local Breeding Growth Mode

2019 ◽  
Vol 34 (2) ◽  
pp. 289-304 ◽  
Author(s):  
Shenjia Ma ◽  
Chaohui Chen ◽  
Hongrang He ◽  
Jie Xiang ◽  
Shengjie Chen ◽  
...  
Keyword(s):  
Initial Perturbation ◽  
Growth Mode ◽  
Ensemble Prediction ◽  
Weather System ◽  
Ensemble Prediction System ◽  
System A ◽  
Convective Scale ◽  
Local Breeding ◽  
Prediction Systems ◽  
Convective Weather

Abstract In this study, a convection-allowing ensemble prediction experiment was conducted on a strong convective weather process, based on the local breeding growth mode (LBGM) method proposed according to the strongly local nature of the convective-scale weather system. A comparative analysis of the evolution characteristics of the initial perturbation was also performed, considering the results from the traditional breeding growth mode (BGM) method, to enhance understanding and application of this new initial perturbation generation method. The experimental results showed that LBGM results in the perturbation distribution exhibiting characteristics more evident of flow dependence, and an initial perturbation with greater definite kinetic significance was derived. Information entropy theory could well measure the amount of information contained in the perturbation distribution, indicating that the innovative initial perturbation generation method can increase the amount of local information associated with the initial perturbation. With regard to the physical perturbation quantities, the LBGM method can improve the dispersion of the ensemble prediction system, thereby solving the problem of insufficient ensemble spread of prediction systems obtained by the traditional BGM method. Simultaneously, the root-mean-square error of the prediction can be further reduced, and the predicted precipitation distribution is closer to the observed precipitation, thereby improving the prediction effect of the convection-allowing ensemble prediction. The LBGM method has advantages compared to the traditional method and provides a new theoretical basis for further development of initial perturbation technologies for convection-allowing ensemble prediction.

scholarly journals Synoptic Control of Convective Rainfall Rates and Cloud-to-Ground Lightning Frequencies in Warm-Season Mesoscale Convective Systems over North China

2018 ◽  
Vol 146 (3) ◽  
pp. 813-831 ◽  
Author(s):  
Rudi Xia ◽  
Da-Lin Zhang ◽  
Cuihong Zhang ◽  
Yongqing Wang
Keyword(s):  
Environmental Conditions ◽  
North China ◽  
Convective Available Potential Energy ◽  
Cloud Microphysics ◽  
Small Sample ◽  
Mesoscale Convective Systems ◽  
Convective Rainfall ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Cg Lightning

Abstract This study examines whether environmental conditions can control convective rainfall rates and cloud-to-ground (CG) lightning frequencies in mesoscale convective systems (MCSs) over north China (NC). A total of 60 identified MCSs over NC during June–August of 2008–13 were classified into 4 categories based on their high/low convective rainfall rates (HR/LR) and high/low CG lightning frequencies (HL/LL) (i.e., HRHL, HRLL, LRHL, and LRLL MCSs). MCSs with HR (HL) occurred most frequently in July (August), while those with LR or LL occurred most frequently in June; they followed closely seasonal changes. All MCSs were apt to form during afternoon hours. HRLL MCSs also formed during evening hours while HRHL MCSs could occur at any time of a day. A composite analysis of environmental conditions shows obvious differences and similarities among the HRHL, HRLL, and LRLL categories, while the LRHL MCSs exhibited little differences from the climatological mean because of its small sample size. Both the HRHL and HRLL MCSs occurred in the presence of upper-level anomalous divergence, a midlevel trough, and the lower-tropospheric southwesterly transport of tropical moist air. In contrast, LRLL MCSs took place as a result of daytime heating over mountainous regions, with little midlevel forcing over NC. The HRHL, HRLL, LRHL, and LRLL categories exhibited orders of the highest-to-smallest convective available potential energy and precipitable water but the smallest-to-largest convective inhibition and lifted indices. It is concluded that environmental conditions determine to some extent convective rainfall rates and CG lightning activity, although some other processes (e.g., cloud microphysics) also play certain roles, especially in CG lightning production.

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