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.

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.

ASSESSMENT AND MONITORING OF NATURAL ATMOSPHERIC HAZARDS (HEAVY RAINFALL) IN THE CITIES OF NORTHWESTERN IRAN USING SATELLITE DATA

2021 ◽  
Vol 16 (2) ◽  
pp. 423-436
Author(s):  
Leila ABDOLALIZADEH ◽  
◽  
Ahmad FATAHI ◽  
Mostafa DASTORANI ◽  
Vahid SAFARIAN ◽  
...  
Keyword(s):  
Satellite Data ◽  
Heavy Rainfall ◽  
Assessment And Monitoring ◽  
Northwestern Iran

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 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 Global and long-term comparison of SCIAMACHY limb ozone profiles with correlative satellite data (2002–2008)

2011 ◽  
Vol 4 (4) ◽  
pp. 4867-4910
Author(s):  
S. Mieruch ◽  
M. Weber ◽  
C. von Savigny ◽  
A. Rozanov ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Satellite Data ◽  
Convective Cloud ◽  
Residual Effects ◽  
Statistical Hypothesis ◽  
Systematic Bias ◽  
Statistical Hypothesis Testing ◽  
Trend Model ◽  
The Tropics ◽  
Linear Trends

Abstract. SCIAMACHY limb scatter ozone profiles from 2002 to 2008 have been compared with MLS (2005–2008), SABER (2002–2008), SAGE II (2002–2005), HALOE (2002–2005) and ACE-FTS (2004–2008) measurements. The comparison is performed for global zonal averages and heights from 10 to 50 km in one km steps. The validation was performed by comparing monthly mean zonal means and by comparing averages over collocated profiles within a zonal band and month. Both approaches yield similar results. For most of the stratosphere SCIAMACHY agrees to within 10 % or better with other correlative data. A systematic bias of SCIAMACHY ozone of up to 100 % between 10 and 20 km in the tropics points to some remaining issues with regard to convective cloud interference. Statistical hypothesis testing reveals at which altitudes and in which region differences between SCIAMACHY and other satellite data are statistically significant. We also estimated linear trends from monthly mean data for different periods where SCIAMACHY has common observations with other satellite data using a classical trend model with QBO and seasonal terms in order to draw conclusions on potential instrumental drifts as a function of latitude and altitude. SCIAMACHY exhibits a statistically significant negative trend in the range of of about 1–3 % per year depending on latitude during the period 2002–2005 (overlapping with HALOE and SAGE II) and somewhat less during 2002–2008 (overlapping with SABER) in the altitude range of 30–40 km, while in the period 2004–2008 (overlapping with MLS and ACE-FTS) no significant trends are observed. The statistically significant negative trends only observed with SCIAMACHY data point at some residual effects from errors in the tangent height registration.

A Simple Model for Tropical Convective Cloud Shield Area Time Tendencies Informed by Geostationary IR, GPM, and Aqua/AIRS Satellite Data

2021 ◽  
Author(s):  
Gregory Elsaesser ◽  
Remy Roca ◽  
thomas fiolleau ◽  
Anthony D. Del Genio ◽  
Jingbo Wu
Keyword(s):  
Simple Model ◽  
Satellite Data ◽  
Convective Cloud

scholarly journals Simulation of Severe Local Storm by Mesoscale Model MM5 and Validation Using Data from Different Platforms

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Prosenjit Chatterjee ◽  
Utpal Kumar De ◽  
Devendra Pradhan
Keyword(s):  
Heavy Rainfall ◽  
West Bengal ◽  
Mesoscale Model ◽  
Temperature Drop ◽  
Pressure Rise ◽  
Convective Cloud ◽  
Rainfall Simulation ◽  
Temporal Shift ◽  
Rainfall Occurrence ◽  
Using Data

During premonsoon season (March to May) convective developments in various forms are common phenomena over the Gangetic West Bengal, India. In the present work, simulation of wind squall on three different dates has been attempted with the help of mesoscale model MM5. The combination of various physical schemes in MM5 is taken as that found in a previous work done to simulate severe local storms over the Gangetic West Bengal. In the present study the model successfully simulates wind squall showing pressure rise, wind shift, wind surge, temperature drop, and heavy rainfall, in all cases. Convective cloud development and rainfall simulation by the model has been validated by the corresponding product from Doppler Weather Radar located at Kolkata and TRMM satellite product 3B42 (V6), respectively. It is found that the model is capable of capturing heavy rainfall pattern with up to three-hour time gap existing between simulation and observation of peak rainfall occurrence. In all simulations there is spatial as well as temporal shift from observation.

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