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

Abstract: 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.Abstrak: 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.

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

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-4-4867-2011 ◽

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.

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Estimating cereal evapotranspiration using a simple model driven by satellite data

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477) ◽

10.1109/igarss.2003.1294577 ◽

2004 ◽

Cited By ~ 1

Author(s):

B. Duchemin ◽

S. Er-Raki ◽

P. Gentine ◽

P. Maisongrande ◽

L. Coret ◽

...

Keyword(s):

Simple Model ◽

Satellite Data ◽

Model Driven

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

Jurnal Sains & Teknologi Modifikasi Cuaca ◽

10.29122/jstmc.v20i2.3810 ◽

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.

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

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d8595.118419 ◽

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

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A simple model for the calculation of global solar radiation using geostationary satellite data

Atmospheric Research ◽

10.1016/0169-8095(94)00058-l ◽

1995 ◽

Vol 39 (1-3) ◽

pp. 79-90 ◽

Cited By ~ 9

Author(s):

P. Illera ◽

A. Fernández ◽

A. Pérez

Keyword(s):

Simple Model ◽

Solar Radiation ◽

Satellite Data ◽

Global Solar Radiation ◽

Geostationary Satellite

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

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d8594.118419 ◽

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.

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