The Himawari-8 satellite can be used to derive precipitation data for rainfall estimation. This study aims to test several methods for suchestimation employing the Himawari-8 satellite. The methods are compared in three regions with different topographies, namely Bukittinggi, Pontianak and Ambon. The rainfall estimation methods that are tested are auto estimator, IMSRA, non-linear relation and non-linear inversion approaches. Based on the determination of the statistical verification(RMSE, standard deviation and correlation coefficient) of the amount of rainfall, the best method in Bukittinggi and Pontianak was shown to be IMSRA, while for the Ambon region was the non-linear relations. The best methods from each research area were mapped using the Google Maps Application Programming Interface (API).

On 12 May 2021, 12 August 2021, 6 September 2021 and 27 June 2022, extreme rain occured with an intensity of 58.85 mm/day, 101.3 mm/day, 124.4 mm/day and 176.8 mm/day respectively in East Kotawaringin. These phenomena occurred during the dry season and caused flooding, which is a rare condition during the dry season in East Kotawaringin. This study aims to evaluate extreme rainfall using GSMaP (Global Satellite Mapping of Precipitation) data, where analysis using GSMaP has never been done before in East Kotawaringin. These GSMaP data were processed and compared with the observation data from the Meteorological Station of H. Asan, East Kotawaringin. After that, the GSMaP rainfall results are verified using statistical methods, namely RMSE, correlation coefficient and bias. The verification results show that the bias gives underestimate results for all dates. In addition, the RMSE values on 12 May 2021, 12 August 2021, 6 September 2021 and 27 June 2022 are 10.83, 17.32, 12.41 and 34.03, respectively. These high RMSE values indicate that the GSMaP rainfall value is quite far from the observed rainfall value. The correlation value between GSMaP rainfall and observations has a high correlation with values of 0.84, 0.90, 0.96 and 0.98 for each date. These results show that the GSMaP data has a good correlation value and can be used for extreme rainfall analysis at the Meteorological Station of H. Asan, East Kotawaringin.

On November 11, 2017, extreme weather in the form of very heavy rain has occurred in Pontianak. Based on surface observations data from Supadio Meteorological Station, the amount of rainfall reached 187.4 mm / day and caused flooding in several areas in Pontianak. As a result, a number of flights were cancelled on November 12, 2017 due to flooding in the airport runway. This study aims to examine the causes of very heavy rain using the WRF-ARW model and the results of Himawari-8 satellite images which are processed using Python Programming. Based on the output of the WRF-ARW model with the resolution 3 km, it shows some weather parameters that have potential for bad weather in Pontianak, namely the existence of shear line in West Kalimantan and the eddy circulation in this region which can trigger convective cloud accumulation in Pontianak, the wet RH in the 850-500 mb layer ranges from 70-90%, the CAPE ranges from 1000-2000 J/kg, and the air pressure decreases between 03.00 UTC until 06.00 UTC with a 1.7 mb tendency. In addition, the results of the Himawari-8 Satellite Image show that the cloud peak temperature is very low at -75.8°C at 08.33 UTC. Therefore, based on the WRF-ARW and Himawari-8 Satellite results, those support the occurrence of very heavy rain in Pontianak.

Hujan es terjadi di Sukabumi, Sekadau dan Bogor, yang terjadi masing–masing pada tanggal 23 Agustus 2020, 22 Agustus 2020 dan 23 September 2020. Fenomena cuaca ekstrem di tiga tempat ini terjadi di musim kemarau. Penelitian ini memanfaatkan data model reanalysis ERA5 untuk menganalisa kondisi vertical velocity saat terjadi hujan es dan kaitannya dengan parameter cuaca lain seperti kelembapan udara dan pola angin. Selain itu, data satelit produk HCAI (High resolution Cloud Analysis Information) digunakan sebagai data pendukung untuk analisis perkembangan awan konvektif. Berdasarkan hasil model ERA5, nilai vertical velocity di lapisan 925 mb s/d 300 mb untuk wilayah Sukabumi, Sekadau dan Bogor masing–masing berkisar antara –1.2–(–0.2), –1.5–(–0.2), –1–0 Pa/s. Nilai negatif sebelum kejadian hujan es mengindikasikan terdapat upward motion dari massa udara yang memicu pertumbuhan awan konvektif yang memproduksi hujan es. Selain itu, kelembapan udara di lapisan 850–700 mb terdeteksi basah dan berkisar antara 80–90%. Sementara itu, pola angin di ketiga wilayah tersebut menunjukan adanya konvergensi dengan perlambatan kecepatan angin berkisar antara 2–4 knots. Hasil tersebut menunjukan bahwa upward motion dari vertical velocity cukup untuk membentuk kelembapan udara yang basah di atmosfer dan konvergensi untuk pertumbuhan awan konvektif yang menghasilkan hujan es di musim kemarau.

<p><em>On April 27, 2018 heavy rain was occurred in Palangkaraya. Based on surface data observations at Tjilik Riwut Meteorological Station, the peak of rain occurred between 18-21 UTC, which 54 mm within 3 hours. As a result, the flood inundated on the following day. This research purposed to discover the cause of heavy rain used the WRF model of 3DVar technique that assimilated with AMSU-A satellite which used the tropical physic suite parameterization scheme and Himawari-8 Satellite (IR-1 data), processed by Python Programming. Based on the results, the WRF of the 3DVar model is not representative enough in total rainfall results. However, several weather disturbances show the potency for severe weather occurrence from WRF 3DVar modeling. These are indicated by the shear line and eddy circulation at 18 and 21 UTC, and the time series of air pressure decreases with a 0.5 Mb tendency between 15 to 18 UTC. Moreover, the cloud top temperature graph from Himawari-8 Satellite data shows a drastic reduction in temperature to -61.4323 at 18.20 UTC, which supports the heavy rain process. The weather analysis above show that WRF 3DVar is not representative enough for total rainfall result, but appropriate for other weather aspects (shear line, eddy, and air pressure). Therefore, the heavy rain is caused by shear line and eddy condition, air pressure and low temperature of the cloud top.</em><em></em></p>