Rainfall Estimation with Convective Stratiform Technique (CST) Model

Andi Ihwan; Muliadi Muliadi; Muh. Ishak Jumarang

Authors

Andi Ihwan Department of Physics, Faculty of Mathematics and Natural Sciences, Tanjungpura University
Muliadi Muliadi Department of Physics, Faculty of Mathematics and Natural Sciences, Tanjungpura University
Muh. Ishak Jumarang Department of Physics, Faculty of Mathematics and Natural Sciences, Tanjungpura University

Keywords:

Convective, Stratiform, Satellite Imagery, Rainfall

Abstract

Pontianak City is geographically located on the equator. Based on its location, the atmospheric dynamics in this region fluctuate greatly, the equatorial region throughout the year is exposed to solar radiation so that the potential for convective clouds is very high. This research aims to estimate rainfall based on the characteristics of convective and stratiform rain during extreme weather that causes flooding in Pontianak City. The data used is HIMAWARI 8 satellite image data with a duration of December 22-23, 2023. The method used is Convective Stratiform Technique (CST). The results showed that the atmospheric dynamics on December 22 and 23, 2023 were very high, this was characterized by the formation of high clouds with very low cloud top temperatures below -70°C around Pontianak City. Then the estimation of rainfall based on the CST model can be done during heavy rains that cause flooding in Pontianak City. The model rainfall value overestimates the observation data, on December 22 the difference is very large, while on December 23 the model rainfall is able to approach the obeservation rainfall with a very small difference of 1.2 mm.

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References

S. Steinke, M. Mohtadi, M. Prange, V. Varma, D. Pittauerova, and H. W. Fischer, “Mid-to late-Holocene Australian–Indonesian summer monsoon variability,” Quat. Sci. Rev., vol. 93, pp. 142–154, 2014.

P. Abadi, S. Ekawati, and D. Marlia, “Analisis distribusi spasial dan temporal sintilasi ionosfer kuat di atas indonesia selama ekuinoks 2013” J. Sains Dirgant., vol. 12, no. 2, 2015.

B. Konecky, J. Russell, and S. Bijaksana, “Glacial aridity in central Indonesia coeval with intensified monsoon circulation,” Earth Planet. Sci. Lett., vol. 437, pp. 15–24, 2016.

Supari, F. Tangang, E. Salimun, E. Aldrian, A. Sopaheluwakan, and L. Juneng, “ENSO modulation of seasonal rainfall and extremes in Indonesia,” Clim. Dyn., vol. 51, pp. 2559–2580, 2018.

A. Kurniadi, E. Weller, S. Min, and M. Seong, “Independent ENSO and IOD impacts on rainfall extremes over Indonesia,” Int. J. Climatol., vol. 41, no. 6, pp. 3640–3656, 2021.

K. Handayani, T. Filatova, and Y. Krozer, “The vulnerability of the power sector to climate variability and change: Evidence from Indonesia,” Energies, vol. 12, no. 19, p. 3640, 2019.

L. R. E. Malau and A. T. Darhyati, “The impact of climate change and natural disasters on food security in Indonesia: lessons learned on preserving forests sustainability,” in IOP Conference Series: Earth and Environmental Science, IOP Publishing, p. 12090, 2021.

L. Brocca et al., “Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data,” J. Geophys. Res. Atmos., vol. 119, no. 9, pp. 5128–5141, 2014.

Q. Sun, C. Miao, Q. Duan, H. Ashouri, S. Sorooshian, and K. Hsu, “A review of global precipitation data sets: Data sources, estimation, and intercomparisons,” Rev. Geophys., vol. 56, no. 1, pp. 79–107, 2018.

A. V. Wulandari, K. R. Pratama, and P. Ismail, “Using Convective Stratiform Technique (CST) method to estimate rainfall (case study in Bali, December 14th 2016),” in Journal of Physics: Conference Series, IOP Publishing, p. 12039, 2018.

A. Mulsandi, M. Mamenun, L. Fitriano, and R. Hidayat, “Perbaikan Estimasi Curah Hujan Berbasis Data Satelit Dengan Memperhitungkan Faktor Pertumbuhan Awan,” J. Sains Teknol. Modif. Cuaca, vol. 20, no. 2, pp. 67–78, 2019.

J. Ren et al., “Evaluation and Improvement of FY-4A AGRI Quantitative Precipitation Estimation for Summer Precipitation over Complex Topography of Western China,” Remote Sens., vol. 13, no. 21, p. 4366, 2021.

M. N. Islam, A. Islam, T. Hayashi, T. Terao, and H. Uyeda, “Application of a method to estimate rainfall in Bangladesh using GMS-5 data,” J. Nat. Disaster Sci., vol. 24, no. 2, pp. 83–89, 2002.

A. J. P. Andani and F. N. U. Endarwin, “Kajian penerapan estimasi curah hujan per jam memanfaatkan metode convective stratiform technique (CST) dan modified convective stratiform technique (mCST) di pontianak,” J. Meteorol. Klimatologi dan Geofis., vol. 3, no. 3, pp. 9–20, 2016.

S. E. Giangrande et al., “Convective cloud vertical velocity and mass‐flux characteristics from radar wind profiler observations during GoAmazon2014/5,” J. Geophys. Res. Atmos., vol. 121, no. 21, pp. 12–891, 2016.

M. Lazri, F. Ouallouche, S. Ameur, J. M. Brucker, and Y. Mohia, “Identifying convective and stratiform rain by confronting SEVERI sensor multispectral infrared to radar sensor data using neural network,” Sensors & Transducers, vol. 145, no. 10, p. 19, 2012.

W. Xu, R. F. Adler, and N.-Y. Wang, “Combining Satellite Infrared and Lightning Information to Estimate Warm‐Season Convective and Stratiform Rainfall,” J. Appl. Meteorol. Climatol., vol. 53, no. 1, pp. 180–199, 2014.

I. A. Ramadhan and A. Mulya, “Estimasi Curah Hujan Menggunakan Metode Convective Stratiform Technique (CST) Dan Modified Convective Stratiform Terchnique (mCST) (studi kasus: Jombang, 2 Januari 2021),” Pros. Konf. Nas. Mat. Dan IPA Univ. PGRI Banyuwangi, vol. 2, no. 1, pp. 265–274, 2022.