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 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 PERBAIKAN ESTIMASI CURAH HUJAN BERBASIS DATA SATELIT DENGAN MEMPERHITUNGKAN FAKTOR PERTUMBUHAN AWAN

2020 ◽  
Vol 20 (2) ◽  
pp. 67-78
Author(s):  
Adi Mulsandi ◽  
Mamenun Mamenun ◽  
Lutfi Fitriano ◽  
Rahmat Hidayat
Keyword(s):  
Growth Factor ◽  
Satellite Data ◽  
Point Cloud ◽  
Heavy Rainfall ◽  
Convective Cloud ◽  
Cloud System ◽  
Slope Parameter ◽  
Rainfall Estimation ◽  
Coupled Method ◽  
Stratiform Clouds

Intisari Permasalahan utama dalam mengestimasi curah hujan menggunakan data satelit adalah kegagalan membedakan antara awan cumuliform dengan awan stratiform dimana dapat menyebabkan nilai estimasi hujan under/overestimate. Dalam penelitian ini teknik estimasi curah hujan berbasis satelit yang digunakan adalah modifikasi Convective Stratiform Technique (CSTm). CSTm memiliki kelemahan ketika harus menghitung sistem awan konveksi dengan inti konveksi yang sangat luas karena akan memiliki nilai slope parameter kecil, sehingga menghasilkan estimasi curah hujan yang underestimate. Dengan melibatkan perhitungan faktor pertumbuhan awan di algoritma CSTm permasalahan tersebut dapat diatasi. Penelitian ini menerapkan algoritma CSTm dan faktor pertumbuhan awan (CSTm+Growth Factor) untuk mengestimasi kejadian hujan lebat yang menyebabkan banjir di Jakarta pada tanggal 24 Januari 2016 yang digunakan juga sebagai studi kasus di proyek pengembangan model NWP di BMKG. Hasil penelitian menunjukan bahwa perlibatan faktor pertumbuhan awan sangat efektif memperbaiki kelemahan teknik CSTm, diperlihatkan dengan peningkatan nilai korelasi dari 0.6 menjadi 0.8 untuk wilayah Kemayoran dan -0.1 menjadi 0.83 untuk wilayah Cengkareng. Secara umum gabungan teknik CSTm dan faktor pertumbuhan awan dapat memperbaiki estimasi nilai intensitas dan fase hujan. Abstract  The main problem in estimating rainfall using satellite data is a failure to distinguish between cumuliform and stratiform clouds, which can cause under/overestimate of rains. In this research, the Modified Convective Stratiform Technique (CSTm) has been used to estimate rainfall based on satellite data. The weakness of the CSTm technique is defined when calculating the convective cloud system within a widely convective point. Cloud convective will have a low value of parameter slope and produce an underestimate of rainfall. This issue can be resolved by calculating the cloud growth factor on CSTm. CSTm algorithm and cloud growth factor (CSTm+Growth Factor) has been applied to this research to estimate heavy rainfall for floods event in Jakarta area on January 24th, 2016. The result showed that the cloud growth factor is very effective in improving the weakness of rainfall estimation using the CSTm technique. Correlation between estimation and observation rainfall has increased from 0,6 to 0,8 on Kemayoran and from -0,1 to 0,83 on Cengkareng. The coupled method of CSTm and cloud growth factor significantly improve in estimating phase and intensity of rainfall.

Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part II: Supercell and QLCS Tornado Environments

2012 ◽  
Vol 27 (5) ◽  
pp. 1136-1154 ◽  
Author(s):  
Richard L. Thompson ◽  
Bryan T. Smith ◽  
Jeremy S. Grams ◽  
Andrew R. Dean ◽  
Chris Broyles
Keyword(s):  
United States ◽  
Radar Data ◽  
Convective System ◽  
Severe Thunderstorm ◽  
Severe Thunderstorms ◽  
Real Time Identification ◽  
Environmental Archive ◽  
Tornado Damage ◽  
Effective Layer ◽  
Convective Mode

Abstract A sample of 22 901 tornado and significant severe thunderstorm events, filtered on an hourly 40-km grid, was collected for the period 2003–11 across the contiguous United States (CONUS). Convective mode was assigned to each case via manual examination of full volumetric radar data (Part I of this study), and environmental information accompanied each grid-hour event from the hourly objective analyses calculated and archived at the Storm Prediction Center (SPC). Sounding-derived parameters related to supercells and tornadoes formed the basis of this investigation owing to the dominance of right-moving supercells in tornado production and the availability of supercell-related convective parameters in the SPC environmental archive. The tornado and significant severe thunderstorm events were stratified by convective mode and season. Measures of buoyancy discriminated most strongly between supercell and quasi-linear convective system (QLCS) tornado events during the winter, while bulk wind differences and storm-relative helicity were similar for both supercell and QLCS tornado environments within in each season. The larger values of the effective-layer supercell composite parameter (SCP) and the effective-layer significant tornado parameter (STP) favored right-moving supercells that produced significant tornadoes, as opposed to weak tornadoes or supercells that produced only significant hail or damaging winds. Additionally, mesocyclone strength tended to increase with increasing SCP for supercells, and STP tended to increase as tornado damage class ratings increased. The findings underscore the importance of convective mode (discrete or cluster supercells), mesocyclone strength, and near-storm environment (as represented by large values of STP) in consistent, real-time identification of intense tornadoes.

scholarly journals Impact of Atmospheric Stability Indices on Convective Systems Over India and Srilanka

2019 ◽  
Vol 8 (4) ◽  
pp. 3142-3146
Keyword(s):  
Real Time ◽  
Satellite Data ◽  
Large Scale ◽  
Human Life ◽  
Atmospheric Stability ◽  
Thunderstorm Activity ◽  
Convective System ◽  
Convective Systems ◽  
Severe Thunderstorms ◽  
Stability Indices

Thunderstorms are real-time global phenomena, as their occurrence can take place at anytime at any place. Though their duration is less when compared to large scale processes, their damage is devastating to human life. Thunderstorms are linked with damage factors such as lightning, damaging wind, hails and rain. Real-time satellite data provide atmospheric data which is useful for prediction of thunderstorms. In this paper, an attempt is made to analyze the statistical based stability indices from INSAT-3D, MODIS and ECMWF satellites for the now casting of thunderstorms. The occurrences of severe thunderstorms over India and Srilanka during the month of October 2013, 2014 and 2015 have been analyzed. In these three years, five severe thunderstorm cases were identified using Insat-3D cloud images and thunderstorm reports. Atmospheric stability indices such as K Index (KI), Lifted Index (LI), Total Totals Index (TTI), Total Precipitable water (TPW), Humidity Index (HI) related with severe convection system over India and Srilanka during October month were identified to provide guidance for the study of convection and thunderstorm activity. These indices give us a clear indication of development of convective system before 3 to 4 hours. Results of this study indicate the importance of satellite data for studying the development and decay of convective systems

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 How do changes in warm-phase microphysics affect deep convective clouds?

2017 ◽  
Vol 17 (15) ◽  
pp. 9585-9598 ◽  
Author(s):  
Qian Chen ◽  
Ilan Koren ◽  
Orit Altaratz ◽  
Reuven H. Heiblum ◽  
Guy Dagan ◽  
...  
Keyword(s):  
Rain Rate ◽  
Convective Cloud ◽  
Cloud Fraction ◽  
Marshall Islands ◽  
Cloud System ◽  
Main Question ◽  
Convective Clouds ◽  
Deep Convective Clouds ◽  
Aerosol Effects ◽  
Deep Convective Cloud

Abstract. Understanding aerosol effects on deep convective clouds and the derived effects on the radiation budget and rain patterns can largely contribute to estimations of climate uncertainties. The challenge is difficult in part because key microphysical processes in the mixed and cold phases are still not well understood. For deep convective clouds with a warm base, understanding aerosol effects on the warm processes is extremely important as they set the initial and boundary conditions for the cold processes. Therefore, the focus of this study is the warm phase, which can be better resolved. The main question is: How do aerosol-derived changes in the warm phase affect the properties of deep convective cloud systems? To explore this question, we used a weather research and forecasting (WRF) model with spectral bin microphysics to simulate a deep convective cloud system over the Marshall Islands during the Kwajalein Experiment (KWAJEX). The model results were validated against observations, showing similarities in the vertical profile of radar reflectivity and the surface rain rate. Simulations with larger aerosol loading resulted in a larger total cloud mass, a larger cloud fraction in the upper levels, and a larger frequency of strong updrafts and rain rates. Enlarged mass both below and above the zero temperature level (ZTL) contributed to the increase in cloud total mass (water and ice) in the polluted runs. Increased condensation efficiency of cloud droplets governed the gain in mass below the ZTL, while both enhanced condensational and depositional growth led to increased mass above it. The enhanced mass loading above the ZTL acted to reduce the cloud buoyancy, while the thermal buoyancy (driven by the enhanced latent heat release) increased in the polluted runs. The overall effect showed an increased upward transport (across the ZTL) of liquid water driven by both larger updrafts and larger droplet mobility. These aerosol effects were reflected in the larger ratio between the masses located above and below the ZTL in the polluted runs. When comparing the net mass flux crossing the ZTL in the clean and polluted runs, the difference was small. However, when comparing the upward and downward fluxes separately, the increase in aerosol concentration was seen to dramatically increase the fluxes in both directions, indicating the aerosol amplification effect of the convection and the affected cloud system properties, such as cloud fraction and rain rate.

scholarly journals Synergy between satellite observations and model simulations during extreme events

2018 ◽  
Author(s):  
Anne Wiese ◽  
Joanna Staneva ◽  
Johannes Schultz-Stellenfleth ◽  
Arno Behrens ◽  
Luciana Fenoglio-Marc ◽  
...  
Keyword(s):  
Satellite Data ◽  
Extreme Events ◽  
Wave Model ◽  
Coastal Areas ◽  
In Situ Measurements ◽  
Model Simulations ◽  
Significant Wave ◽  
Operational Analysis

Abstract. In this study, the quality of wind and wave data provided by the new Sentinel-3A satellite is evaluated. We focus on coastal areas, where altimeter data are of lower quality than those for the open ocean. The satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in a comparison with in situ measurements and spectral wave model (WAM) simulations. The sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, ECMWF operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations -coastDat. Numerical simulations show that both the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7 cm to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.

scholarly journals PEMANFAATAN DATA SATELIT HIMAWARI-8 SERTA DATA CURAH HUJAN DAN HARI HUJAN BULANAN DALAM ANALISIS KEJADIAN BANJIR KOTA PADANG, 9 SEPTEMBER 2017 DAN 26 SEPTEMBER 2018

2019 ◽  
Vol 3 ◽  
pp. 264
Author(s):  
Vinca Amalia Rizkiafama ◽  
Tesla Kadar Dzikiro ◽  
Agus Safril
Keyword(s):  
Satellite Data ◽  
Atmospheric Stability ◽  
Convective Cloud ◽  
Atmospheric Conditions ◽  
Flood Events ◽  
Growth Activity ◽  
One Year ◽  
Almost All ◽  
The City ◽  
Rainy Days

<p class="AbstractEnglish"><strong>Abstract:</strong> Flood events on Wednesday, September 26, 2018, in several sub-districts in the city of Padang showed different conditions with the Indonesian region in general which were in normal to drier conditions. One year earlier, precisely on September 9, 2017, there were floods in almost all areas of the city of Padang. This study aims to determine the atmospheric conditions during flood events from the climatological and meteorological side. The data used are monthly rainfall and a monthly number of Rainy Days (HH) from 1981-2018 from the Minangkabau Meteorological Station, as well as Himawari-8 Weather Satellite data. Satellite data is processed using Satellite Animation and Interactive Diagnosis (SATAID) software to obtain cloud cover analysis, cloud growth activities, and atmospheric lability levels. September 2017 and September 2018 are in the nature of normal rain with a percentage of 101% and 88%. The increase in the amount of rainfall in August 2017 to September 2017 is not significant at 27 mm compared to August 2018 to September 2018 which is significant at 148 mm. The number of rainy days in September 2017 and 2018 were 24 and 23 respectively, which showed that almost every day there was rain in those months. The meteorological analysis shows that there is convective cloud growth activity in the Padang area which is characterized by an unstable level of atmospheric stability which has the potential for moderate to heavy rainfall.</p><p class="KeywordsEngish"><strong>Abstrak:</strong> Kejadian banjir pada Rabu, 26 September 2018 di beberapa kecamatan di Kota Padang menunjukkan kondisi yang berlainan dengan wilayah Indonesia pada umumnya yang berada dalam kondisi normal hingga lebih kering. Satu tahun sebelumnya, tepatnya pada 9 September 2017 juga terjadi banjir hampir di seluruh wilayah Kota Padang. Penelitian ini bertujuan untuk mengetahui kondisi atmosfer pada saat kejadian banjir dari sisi klimatologis dan meteorologisnya. Data yang digunakan adalah curah hujan bulanan dan jumlah Hari Hujan (HH) bulanan dari tahun 1981-2018 dari Stasiun Meteorologi Minangkabau, serta data Satelit Cuaca Himawari-8. Data satelit diolah menggunakan piranti lunak Satellite Animation and Interactive Diagnosis (SATAID) untuk mendapatkan analisis tutupan awan, aktivitas pertumbuhan awannya, dan tingkat labilitas atmosfer. September 2017 dan September 2018 berada pada sifat hujan normal dengan presentase 101% dan 88%. Peningkatan jumlah curah hujan bulan Agustus 2017 ke September 2017 tidak signifikan yaitu sebesar 27 mm dibandingkan Agustus 2018 ke September 2018 yang signifikan yaitu sebesar 148 mm. Jumlah hari hujan di bulan September 2017 dan 2018 berturut-turut sebesar 24 dan 23 yang menunjukkan bahwa hampir setiap hari terjadi hujan di bulan-bulan tersebut. Analisis secara meteorologis menunjukkan bahwa terdapat aktivitas pertumbuhan awan konvektif di daerah Padang yang ditandai dengan tingkat stabilitas atmosfer yang labil sehingga berpotensi terjadinya hujan sedang hingga lebat.</p>

scholarly journals Improvement in WRF model prediction for heavy rain events over North Sumatra region using satellite data assimilation

2021 ◽  
Vol 893 (1) ◽  
pp. 012040
Author(s):  
Immanuel Jhonson Arizona Saragih ◽  
Huda Abshor Mukhsinin ◽  
Kerista Tarigan ◽  
Marzuki Sinambela ◽  
Marhaposan Situmorang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Initial Data ◽  
Satellite Data ◽  
Wrf Model ◽  
Heavy Rain ◽  
Convective System ◽  
Large Area ◽  
Weather Forecasts ◽  
Rain Events ◽  
North Sumatra

Abstract Located adjacent to the Indian Ocean and the Malacca Strait as a source of water vapour, and traversed by the Barisan Mountains which raise the air orographically causing high diurnal convective activity over the North Sumatra region. The convective system that was formed can cause heavy rainfall over a large area. Weather Research and Forecasting (WRF) was a numerical weather model used to make objective weather forecasts. To improve the weather forecasts accuracy, especially for predict heavy rain events, needed to improve the output of the WRF model by the assimilation technique to correct the initial data. This research was conducted to compare the output of the WRF model with- and without assimilation on 17 June 2020 and 14 September 2020. Assimilation was carried out using the 3D-Var technique and warm starts mode on three assimilation schemes, i.e. DA-AMSU which used AMSU-A satellite data, DA-MHS which used MHS satellite data, and DA-BOTH which used both AMSU-A and MHS satellite data. Model output verification was carried out using the observational data (AWS, AAWS, and ARG) and GPM-IMERG data. The results showed that the satellite data assimilation corrects the WRF model initial data, so as increasing the accuracy of rainfall predictions. The DA-BOTH scheme provided the best improvement with a final weighted performance score of 0.64.

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