scholarly journals ANN and ARMA based thunderstorm prediction over Andhra Pradesh using INSAT 3D Satellite

2019 ◽  
Vol 8 (4) ◽  
pp. 4723-4726
Keyword(s):  
Satellite Data ◽  
Extreme Events ◽  
Heat Waves ◽  
Convective Cloud ◽  
Rainfall Events ◽  
Severe Thunderstorm ◽  
Severe Thunderstorms ◽  
Time Period ◽  
Faster Development ◽  
Heavy Rainfall Events

Extreme events such as severe thunderstorms, heat waves, cyclones, heavy rainfall events are increasing day by day in recent years over India. Out of all extreme events, thunderstorms are causing more damage and deaths when compared to others. Thunderstorms are tougher to be predicted in advance due to their faster development. In this paper, we tried to analyse two severe thunderstorm cases in premonsoon season for the time period 2017 and 2018 by using INSAT-3D satellite data. This satellite data helps us to monitor the convective cloud system every 30 minutes. Using this satellite data we are able to calculate the atmospheric indices like LI, KI, TTI and HI for every 30 minutes. After being analyzed by INSAT-3D satellite data, we tried to predict the peak stage of thunderstorms using ANN and ARMA techniques. The atmospheric based stability indices have been used as inputs for ANN & ARMA models inorder to achieve prediction. ANN prediction was better than ARMA prediction when compared to INSAT-3D satellite data

scholarly journals Thunderstorms over A.P using INSAT- 3D Satellite Data

2019 ◽  
Vol 8 (4) ◽  
pp. 4591-4594
Keyword(s):  
Satellite Data ◽  
Extreme Events ◽  
Convective Cloud ◽  
Cloud System ◽  
Convective System ◽  
Clear Indication ◽  
Severe Thunderstorm ◽  
Severe Thunderstorms ◽  
Day By Day

Extreme events related to severe thunderstorms have been increasing day by day in recent years over India. Due to the shorter span of occurrence, these events are tough to be predicted. To achieve this, we took the help of the satellite data. In this paper, we analysed the two severe thunderstorm cases in May 2019 by INSAT-3D satellite data. This satellite data helps us to monitor the convective cloud system every 30 minutes. Using this satellite data we are able to calculate the atmospheric indices like LI, KI, TTI and HI for every 30 minutes. These satellite derived atmospheric indices gives us a clear indication of development of Convective system before 3 -4 hours.

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

Runoff regime after heavy rainfall events in view of changing climate in a beech stand at the LTER-CWN site “Klausenleopoldsdorf”

2021 ◽  
Author(s):  
Gollobich Günther ◽  
Gartner Karl ◽  
Riedel Sebastian
Keyword(s):  
Electrical Conductivity ◽  
Water Level ◽  
Time Resolution ◽  
Extreme Events ◽  
Heavy Rainfall ◽  
Research Infrastructure ◽  
Precipitation Event ◽  
Rainfall Events ◽  
Runoff Regime ◽  
Heavy Rainfall Events

<p>The Austrian Research Infrastructure LTER-CWN (Long-Term Ecosystem Research Infrastructure for Carbon, Water and Nitrogen) aims for measuring extreme events in high temporal resolution. Within the framework of this project a measuring weir was installed near Klausen-Leopoldsdorf (Lower Austria) in order to collect high-resolution data of stream-water quantity and quality. The measuring weir is located in the western part of the „Wienerwald“, the north-eastern edge of the Alps, at about 475m a.s.l. Especially in the year 2020 this area showed humid weather conditions with an annual precipitation of 904mm. The observed catchment has an area of about 46 hectares. The dominating soil types in the catchment are Planosoils and Stagnosols. The observations at the weir with a time resolution of 5 minutes started in February 2019. The plot was set up for recordings of carbon (C), nitrogen (N) and water fluxes theparameters TOC-N, DOC-N, NO<sub>3,</sub> water level, water temperature, electrical conductivity, turbidity and organic matter values being measured. To answer one of the main research issues - the impact of heavy rainfall events on the runoff regime of a catchment within a dense beech forest in relation to the soil, specific time, the influence of interception and corresponding water level in the observed river - a water level sensor (OTT) and a multifunction spectrolyzer (S:CAN) were installed at the weir. During the measuring period 2019/2020 11 heavy rainfall events (corresponding to more than 20mm daily precipitation sum) were recorded. Due to the small catchment area the average time interval between heavy rainfall events and the corresponding increase of the water level at the measuring weir is about 2 hours. The time and intensity of the rainfall event together with the level of soil moisture before the precipitation event are the key factors for the amount of runoff. Additionally, other measured parameters like the turbidity or the electrical conductivity of the water correspond very well with the amount of runoff. Data with such a high time resolution will help to get a better understanding of extreme events and the consequences of these events in respect to climate change.</p>

Investigation of the vertical structure of the lower atmosphere during heat wave conditions

2021 ◽  
Author(s):  
Till Fohrmann ◽  
Andreas Hense ◽  
Petra Friederichs
Keyword(s):  
Boundary Layer ◽  
Heat Wave ◽  
Extreme Events ◽  
Vertical Structure ◽  
Heat Waves ◽  
Lower Atmosphere ◽  
Vertical Profiles ◽  
Interesting Phenomenon ◽  
Time Period ◽  
Severity Levels

<p>The research on heat waves is strongly motivated by their impacts on human<br />life and the economy. Consequently, less research has been done on the<br />state of the lower atmosphere as a whole during these extreme events,<br />although it may play a role in the formation and persistence of heat<br />waves. Miralles et al. (2014) show that different factors must come<br />together to produce extremes such as the pronounced heat waves<br />in the year 2003 in France and 2010 in Russia. One interesting phenomenon<br />in this context is the emergence of an unusually deep boundary layer. The aim<br />of this work is to analyse whether this feature is a common trait of European<br />heat waves in general. To this end, we systematically investigate the vertical<br />structure and evolution of the lower atmosphere during heat waves in the<br />time period from 2014 to 2018. COSMO-REA6 data is used to find heatwaves<br />and provides vertical profiles of the atmosphere which we also compare<br />to radio sonde measurements. The results of our work could possibly be<br />used to improve the discriminability of different severity levels of heat waves or to<br />formulate a heat wave measure that is not based solely on surface variables.</p>

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

scholarly journals Mesoscale Analysis of Heavy Rainfall Episodes from SoWMEX/TiMREX

2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee
Keyword(s):  
Heavy Rainfall ◽  
Southwest Monsoon ◽  
Rainfall Events ◽  
Mesoscale Analysis ◽  
Mesoscale Structure ◽  
Profound Influence ◽  
Moist Condition ◽  
Virtual Temperature ◽  
Convection Initiation ◽  
Heavy Rainfall Events

Abstract The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5–6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°–3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes.

scholarly journals A Total Lightning Trending Algorithm to Identify Severe Thunderstorms

2010 ◽  
Vol 27 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Patrick N. Gatlin ◽  
Steven J. Goodman
Keyword(s):  
Severe Weather ◽  
Lightning Flash ◽  
Severe Thunderstorm ◽  
Critical Success ◽  
Severe Thunderstorms ◽  
Weather Events ◽  
Total Lightning ◽  
Jump Algorithm ◽  
Early Indication ◽  
Critical Success Index

Abstract An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

scholarly journals An Improved Weighting Method of Time-Lag-Ensemble Averaging for Hourly Precipitation Forecasts and Its Application in a Typhoon-Induced Heavy Rainfall Event

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen
Keyword(s):  
Heavy Rainfall ◽  
Time Lag ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Ensemble Averaging ◽  
Weighting Method ◽  
Prediction Ability ◽  
Rainfall Events ◽  
Hourly Precipitation ◽  
Heavy Rainfall Events

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall.

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