Academic literature on the topic 'Precipitation (Meteorology) Indonesia'

Abstract. Temporal variations of precipitating clouds in equatorial Indonesia have been studied based on observations with 1357.5 MHz boundary layer radars at Serpong (6.4° S, 106.7° E) near Jakarta and Bukittinggi (0.2° S, 100.3° E) in West Sumatera. We have classified precipitating clouds into four types: stratiform, mixed stratiform-convective, deep convective, and shallow convective clouds, using the Williams et al. (1995) method. Diurnal variations of the occurrence of precipitating clouds at Serpong and Bukittinggi have showed the same characteristics, namely, that the precipitating clouds primarily occur in the afternoon and the peak of the stratiform cloud comes after the peak of the deep convective cloud. The time delay between the peaks of stratiform and deep convective clouds corresponds to the life cycle of the mesoscale convective system. The precipitating clouds which occur in the early morning at Serpong are dominated by stratiform cloud. Concerning seasonal variations of the precipitating clouds, we have found that the occurrence of the stratiform cloud is most frequent in the rainy season, while the occurrence of the deep convective cloud is predominant in the dry season.Key words. Meteorology and atmospheric dynamics (convective processes; precipitation; tropical meteorology)

This research’s aim is to analyze weather elements that affect marine transportation activities at Tanjung Perak Port. The data used in this study is secondary data obtained from Meteorology, Climatology and Geophysics Agency of the Republic of Indonesia. The data used is weather element record from the meteorological station in Perak II Surabaya for the 2017-2021 period which includes variables of sunlight exposure, precipitation, humidity, wind direction, air pressure, wind speed, and air temperature. The method used is the Principal Component Analysis method. Based on the test, it is found that all weather variables can be analyzed using the Principal Component Analysis Method. The weather element variables formed 2 components which have Initial Eigenvalues 1. The first component consists of Air humidity, Precipitation, Sunlight exposure, and Air Pressure. The second component consists of Air Temperature, Wind Direction, and Wind Speed. Based on the two components formed, the first component is the most dominant component element that affects marine transportation activities at Tanjung Perak Port for the 2017-2021 period with Initial Eigenvalues of 3,681. And air pressure is the most dominant weather element with the loading value based on the Principal Component Analysis method is 0,867.

Abstract. Climate change is a global phenomenon that currently and seriously impacts the environment. Increasing concentrations of greenhouse gases have caused changes in extreme climate events. We have studied index rainfall extream trend at two meteorological stations of Sultan Iskandar Muda in Banda Aceh and Cut Nyak Dien in Meulaboh from 1982-2013. Daily rainfall data were processed using software of RClimDex to obtain the extreme rainfall index. Such indexes are extreme climate index set by the expert team for Climate Change Detection Monitoring and Indices (ETCCDMI) including of maximum 1-day and 5-days precipitation amount (RX1day and RX5day), total annual precipitation (PRCPTOT), consecutive dry days (CDD), consecutive wet days (CWD), very wet days (R95p), extremely wet days (R99p) and heavy precipitation days (R20mm). Based on our study, we found that the PRCPTOT tend to decrease, whereas occurances of RX1day and RX5day increase. The Banda Aceh station which has a monsoonal pattern is charaterized by increasing in R95p and R99p as well as but decreasing in R20mm. The CWD and CDD tend to accumulate at once. The Meulaboh station that has the type of equatorial rain show decreasing trend in R95p and R99p, but increasing trend in R20mm. The CWD and CDD occur within some days. The projection Representative Concentration Pathways (RCP) 4.5 and 8.5 from 2014-2050 showed an increasing pattern frequency of rain in Banda Aceh and a decreasing pattern in Meulaboh. Keywords: Trend, Extream Climate Index, ProjectionREFERENCE Lutgens. F.K. and Tarbuck. E.J. 2004. The Atmosphere: An Introduction to Meteorology. Pearson Prentice Hall. New Jersey.Ratag, M.A., Halimurrahman, Juaeni, I., Siswanto, B., dan N., Adikusumah. 2002. Perubahan Iklim : Basis Alamiah dan Dampaknya. Bandung, Lembaga Penerbangan dan Antariksa Nasional.IPCC, 2013. Climate Change. World Meteororogical Organization. Switzerland.Nuraini, Ida Sartika. 2014. Analisis dan Proyeksi Trend Temperatur dan Curah Hujan untuk Mendeteksi Perubahan Iklim (Studi Kasus Provinsi Kalimantan Barat). STMKG, Tangerang Selatan.Sulistya, W., Swarinoto, T.S., Zakir, A.,Riyanto, H., dan B., Ridwan.1998. The Impact of El Nino 1997/98 over Indonesia Region. Jakarta: Jurnal Meteorologi dan Geofisika, No 4, Desember.Zhang, X., and Feng Yang, 2004. RClimDex User Manual. Climate Research Branch, Environment Canada, Downsview, Ontario, Canada.Aldrian, E., 2007 Perubahan iklim global dan dampak terhadap iklim benua mantim di laut dan di daratan Prosiding Jumal Club Tahun 2007.Badan Meteorologi dan Geofisika. ISBN:978-979-1241-11-3

Abstract Rainfall is one of the critical data for water resources infrastructure planning. In many cases in developing countries such as Indonesia, rainfall stations are not evenly distributed. In many cases, regional development occurs much faster than the improvement of hydrological measurement instruments. The plan to move the capital city of Indonesia to Kalimantan is one example. Satellites rainfall products can be utilized, especially for areas with a limited number of rainfall stations. This study examines the potential use of Global Precipitation Measurement (GPM) satellite products to estimate the spatial distribution of rainfall in the Kalimantan region. Twenty years data of daily maximum rainfall from GPM satellite rainfall products in 2001-2020 were compared to twenty years data of daily maximum rainfall from 16 rainfall stations under the Meteorology, Climatology, and Geophysical Agency (BMKG), with data time spanning from the 1970s to 2020. The analysis results show a significant difference between extreme rainfall analysis computed by using station data and the satellite. The use of the correction function can increase the accuracy of the GPM rainfall product. It can be used as an alternative data source for a region with limited rainfall stations.

Abstract North Sulawesi is one of the Province in northern Indonesia with high spatial annual rainfall variations and influenced by global climate anomaly that can lead to extreme events and disaster occurrence, such as flood, landslide, drought, etc. The purpose of this study is to generate high-resolution meteorological hazard map based on long-term historical consecutive dry days (CDD) over the North Sulawesi region. CDD was calculated based on observed daily precipitation data from Indonesia Agency for Meteorology, Climatology, and Geophysics (BMKG) surface observation station network (CDDobs) and the daily-improved Climate Hazards group Infrared Precipitation with Stations (CHIRPS) version 2.0 (CDDCHIRPS) during 1981 – 2010 period. The Japanese 55-year Reanalysis (JRA-55) data obtained from iTacs (Interactive Tool for Analysis of the Climate System) with the same time scale period also used to explain physical – dynamical atmospheric properties related to drought hazard over this region. The Geostatistical approach using regression kriging method was applied as spatial interpolation technique to generate high resolution gridded (0.05° × 0.05°) drought hazard map. This method combines a regression of CDDobs as dependent variable (target variable) on CDDCHIRPS as predictors with kriging of the prediction residuals. The results show that most of the areas were categorized as medium drought hazard level with CDD values ranging from 80-100 days. Meanwhile, small islands around main Sulawesi island such as Sangihe and Karakelong island are dominated by low drought hazard levels with CDD values ranging from 50-60 days. The highest levels of drought hazard area are located in South Bolaang Mongondow Regency.

Abstract Air pollution transport is entangled with weather and climate factors. As the pollutants tend to move due to the metrological condition. Naturally, pollutants will be deposited to the ground at the end part of the deposition cycle. One of the factors of pollutant deposition in a wet deposition is rain. The soluble pollutants and particulate matter are precipitated to the earth’s surface during precipitation. In order to analyse it, we need a rainfall measuring device/rain gauge, as rainfall is an important parameter to find the correlation between the two. However, there is a limited number of rain-gauge in Indonesia. Thus, we proposed a tipping bucket rain gauge, which consists of a funnel, a bucket, a magnetic switch sensor, and a microcontroller-based processing unit. The prototype is equipped with a GSM module so that the data can be sent in real-time via text message every minute, also an SD Card as the backup storage data. It was calibrated using ISO 17025:2005 standard, the result obtained by a resolution of 0.2 mm/tip with a capacity of 4.2 ml buckets, and U95 uncertainty of ±0,04 - ±0,12 mm/minute. To find the suitable method of rainfall calculation for the prototype, we observe three methods, Natural, Meteorology, and Novel-IAP. From the three we found, Novel-IAP has the best result since the calculation is executed every second. And the other methods are found to have a high error result.

Evaluation of first five years of the Global Precipitation Measurement - Integrated Multi-satellitE Retrievals for GPM (IMERG) final preciptitation product was performed over Bali – Indonesia using surface observation data which derived from The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG) as a reference. This study evaluated IMERG’s performance in describing the temporal characteristics of rainfall variation over various time periods (including daily, monthly, and seasonal). The analysis concentrated on the period of April 2014 to April 2019. The results of statistical measurements consisted Probability of Detection (POD), linear correction coefficient (r), Mean Bias Error (MBE), and Root Mean Square Error (RMSE). In general, the results showed that IMERG rainfall estimation value was lower than rain gauges data. The statistical assesment indicated IMERG data was highly accurate on monthly to seasonal timescales. However, a moderate correlation was shown between the daily data comparison from IMERG to ground references. IMERG Performed better in wet season period (November -April) than in dry season period (May – Oktober). The probability of detection rain events on daily time scale was good. Overall, data from IMERG has the potential to be useful as a complement to rain gauge data in areas where rainfall observations are not available in the field.

Untuk memenuhi kebutuhan cadangan air di tiga danau yang ada di DAS Larona, telah beberapa kali dilakukan penyemaian awan dengan menggunakan Teknologi Hujan Buatan. Teknologi yang selama ini dilakukan adalah penyemaian awan dari udara dengan menggunakan pesawat terbang sebagai sarana penghantar bahan semainya. Namun akhir-akhir ini di Balai Teknologi Modifikasi Cuaca, BPPT telah mulai dikembangkan teknologi penyemaian awan dari darat yang menggunakan menara. Penempatan menara ini perlu mempertimbangkan unsur meteorologi agar bahan semai secara efektif dapat masuk ke dalam awan yang potensial menghasilkan hujan. Dari data satelit dan penakar hujan didapatkan gambaran secara umum sebaran awan hujan. Dengan melakukan analisis reflektifitas radar diperoleh sebaran awan hujan berdasarkan jenis awan hujannya. Dengan metoda ini diketahui bahwa awan-awan hujan yang muncul di Matano, Timampu dan Tokalimbo kebanyakan awan hujan jenis shallow convective. Awan hujan shallow convective dan convective pada bulan Januari-Maret lebih banyak tumbuh di bagian Utara dan Timur DAS. Di bagian tengah DAS, kemunculan awan hujan lebih sedikit.Kata Kunci: radar, awan hujan, sorowako, modifikasi cuacaCloud seeding project has been carried out in Larona watershed to enhanced the rainfall in this area. Until now the cloud seeding technology has been done by delivering the seeding material directly to the cloud by aircraft. But recently, the National Laboratory of Weather Modification Technology of Indonesia is developing a new method of ground based seeding by building some towers for delivering the seeding agent to the cloud. Location of the tower should consider elements of Meteorology in order for the seeding materials can effectively enter into cloud which potentially produce rain. By doing an analysis of the radar reflectivity obtained the distribution of clouds based on the type of precipitation cloud. With this method it is known that rain clouds that appeared in Matano, Timampu and Tokalimbo are mostly shallow convective clouds. In January-March, shallow convective clouds and convective grew more in the North and East of the Larona watershed. In the central part of the watershed, there is less precipitating clouds appear.Keywords: radar, rain cloud, sorowako, weather modification

<p class="AbstractEnglish"><strong>Abstract:</strong>. Madden Julian Oscillation (MJO) is a wave in tropical atmosphere that moving eastward from Indian ocean to Pacific Ocean for a period 30 – 60 days. There are many research that explain when MJO is active in phases 2, 3 and 4 it affects convective activities in the Indonesian Maritime Continent. The purpose of this study is to determine the effect of MJO in phase 3 on temporal rainfall intensity in Sumatra and Java island on 14 – 17 October 2018. This study uses the descriptive analysis method using parameter such as Outgoing Longwave Radiation (OLR) and Phase MJO diagram from Bureau of Meteorology (BOM), Sea Surface Temperature (SST) and vertical velocity data from the National Oceanic and Atmospheric Administration (NOAA) and also raw data of HCAI Himawari-8 satellite to monitor cloud formation on Sumatra and Java island and Global Precipitation Measurement (GPM) data obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) to determine its rainfall distribution on 14 – 17 October 2018. The active MJO in phase 3 causing an increase in convective activity on the Sumatra. The SST value of 29.5⁰ – 30⁰ Celcius supports the occurrence of sufficient evaporation to produce convective clouds with a vertical velocity of less than -0.12 Pa/s (strong updraft) so as to form Cumulonimbus clouds which cause heavy rain intensity which can cause floods. However, in Java Island the influence of MJO was less significant due to the influence of relatively lower sea surface temperatures in the south of Java island so that it is not strong enough to form convective clouds that produce heavy rain.</p><p class="AbstrakIndonesia"><strong>Abstrak:</strong> Madden Julian Oscillation (MJO) merupakan gelombang di kawasan tropis yang menjalar dari Barat (Samudera Hindia) ke timur (Samudera Pasifik) dengan periode 30 – 60 hari. Banyak penelitian menjelaskan bahwa pada saat MJO aktif pada fase 2, 3 dan 4 berpengaruh terhadap giatnya aktivitas konvektif di Benua Maritim Indonesia. Penelitian ini bertujuan untuk mengetahui pengaruh MJO di fase 3 terhadap intensitas curah hujan secara temporal di wilayah Pulau Sumatra dan Pulau Jawa pada 14 – 17 Oktober 2018. Penelitian ini menggunakan metode analisis deskriptif dengan parameter antara lain : <em>Outgoing Longwave Radiation</em> (OLR) dan diagram fase MJO yang diambil dari <em>Bureau of Meteorology</em> (BOM), <em>Sea Surface Temperature </em>(SST)<em> </em>dan<em> </em>kecepatan vertikal yang diambil dari <em>National Oceanic and Atmospheric Administration</em> (NOAA) serta <em>raw</em> data HCAI satelit Himawari-8 untuk memonitoring pembentukan awan di Pulau Sumatera dan Jawa dan data <em>Global Precipitation Measurement</em> (GPM) yang didapatkan dari Badan Meteorologi, Klimatologi dan Geofisika (BMKG) untuk mengetahui distribusi curah hujannya pada 14 – 17 Oktober 2018. Aktifnya MJO pada fase 3 menyebabkan peningkatan aktivitas konvektif di Pulau Sumatera. Nilai SST sebesar 29.5⁰ – 30⁰ Celcius mendukung terjadinya penguapan yang cukup untuk menghasilkan awan konvektif dengan kecepatan vertikal kurang dari -0.12 Pa/s (<em>updraft</em> kuat) sehingga membentuk awan Cumulonimbus yang menyebabkan intensitas hujan lebat yang mampu menimbulkan bencana banjir. Sedangkan di Pulau Jawa pengaruh MJO kurang signifikan akibat pengaruh suhu permukaan laut di selatan Jawa yang relatif lebih rendah sehingga tidak cukup kuat untuk membentuk awan konvektif yang menghasilkan hujan lebat.</p>

Indramayu district experiences frequent droughts that leads to many paddy fields harvest failure. Since the district is one of the national granary, this disaster needs to be addressed urgently. This study aimed to assess the level of dryness in Indramayu using Standard Precipitation Index (SPI) and its relation with the Southern Oscillation Index (SOI). The study used monthly rainfall data from 1996 to 2013 observed by 19 stations and the score of SOI that came from the Bureau of Meteorology of Australia. The method used quantitative approach using SPI and software SPI_sl_6.exe. Drought indices was measured in four different time scale which are 1, 3, and 6 month(s) (for the short term period) and the 12 months time scale (for the long term period). SPI’s assessment was classified in accordance with the classification of WMO (World Meteorological Organization) which consist of seven classes, ranging from wet extreme to dry extreme class. The results showed that the occurence of "very dry" to "dry extreme“ drought was occured mainly from February 1997 to January 1998 at most stations, while for some stations, it lasted until March 1998. The drought period was lasted from nine to ten months. In 2002 to 2003, the droughts that classified as "very dry" on a 3 and 6 months time scale lasted about five months, while the 12 months time scale was lasted about nine months. SPI value that obtained from different time scales has a strong relation with the value of SOI. The negative value of SOI tends to be followed by the negative value of SPI, and vice versa. SOI that has negative value below -7 and occured in a long period (more than three months) indicates a prolonged El Nino which occurred in 1997 and 2002/2003 when the research area was struck by "being dry" to "dry extreme" drought state.