Journal articles 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.

Increasing the accuracy of rainfall forecasts is crucial as an effort to prevent hydrometeorological disasters. Weather changes that can occur suddenly and in a local scope make fast and precise weather forecasts increasingly difficult to inform. Additionally, the results of the numerical weather model used by the Indonesia Agency for Meteorology, Climatology, and Geophysics are only able to predict the rainfall with a temporal resolution of 1–3 h and cannot yet address the need for rainfall information with high spatial and temporal resolution. Therefore, this study aims to provide the rainfall forecast in high spatiotemporal resolution using Himawari-8 and GPM IMERG (Global Precipitation Measurement: The Integrated Multi-satellite Retrievals) data. The multivariate LSTM (long short-term memory) forecasting is employed to predict the cloud brightness temperature by using the selected Himawari-8 bands as the input and training data. For the rain rate regression, we used the random forest technique to identify the rainfall and non-rainfall pixels from GPM IMERG data as the input in advance. The results of the rainfall forecast showed low values of mean error and root mean square error of 0.71 and 1.54 mm/3 h, respectively, compared to the observation data, indicating that the proposed study may help meteorological stations provide the weather information for aviation purposes.

Abstract. Much research and speculation exists about the meteorological and climatological impacts of biomass burning in the Maritime Continent (MC) of Indonesia and Malaysia, particularly during El Niño events. However, the MC hosts some of the world's most complicated meteorology, and we wish to understand how tropical phenomena at a range of scales influence observed burning activity. Using Moderate Resolution Imaging Spectroradiometer (MODIS) derived active fire hotspot patterns coupled with aerosol data assimilation products, satellite based precipitation, and meteorological indices, the meteorological context of observed fire prevalence and smoke optical depth in the MC are examined. Relationships of burning and smoke transport to such meteorological and climatic factors as the interannual El Niño-Southern Oscillation (ENSO), El Niño Modoki, Indian Ocean Dipole (IOP), the seasonal migration of the Intertropical Convergence Zone, the 30–90 day Madden Julian Oscillation (MJO), tropical waves, tropical cyclone activity, and diurnal convection were investigated. A conceptual model of how all of the differing meteorological scales affect fire activity is presented. Each island and its internal geography have different sensitivities to these factors which are likely relatable to precipitation patterns and land use practices. At the broadest scales as previously reported, we confirm ENSO is indeed the largest factor. However, burning is also enhanced by periods of El Niño Modoki. Conversely IOD influences are unclear. While interannual phenomena correlate to total seasonal burning, the MJO largely controls when visible burning occurs. High frequency phenomena which are poorly constrained in models such as diurnal convection and tropical cyclone activity also have an impact which cannot be ignored. Finally, we emphasize that these phenomena not only influence burning, but also the observability of burning, further complicating our ability to assign reasonable emissions.

Abstract. Much research and speculation exists about the meteorological and climatological impacts of biomass burning in the Maritime Continent (MC) of Indonesia and Malaysia, particularly during El Nino events. However, the MC hosts some of the world's most complicated meteorology, and we wish to understand how tropical phenomena at a range of scales influence observed burning activity. Using Moderate Resolution Imaging Spectroradiometer (MODIS) derived active fire hotspot patterns coupled with aerosol data assimilation products, satellite based precipitation, and meteorological indices, the meteorological context of observed fire prevalence and smoke optical depth in the MC are examined. Relationships of burning and smoke transport to such meteorological and climatic factors as the interannual El Nino-Southern Oscillation (ENSO), El Nino Modoki, Indian Ocean Dipole (IOD), the seasonal migration of the Intertropical Convergence Zone, the 30–90 day Madden Julian Oscillation (MJO), tropical waves, tropical cyclone activity, and diurnal convection were investigated. A conceptual model of how all of the differing meteorological scales affect fire activity is presented. Each island and its internal geography have different sensitivities to these factors which are likely relatable to precipitation patterns and land use practices. At the broadest scales as previously reported, we corroborate ENSO is indeed the largest factor. However, burning is also enhanced by periods of El Nino Modoki. Conversely, IOD influences are unclear. While interannual phenomena correlate to total seasonal burning, the MJO largely controls when visible burning occurs. High frequency phenomena which are poorly constrained in models such as diurnal convection and tropical cyclone activity also have an impact which cannot be ignored. Finally, we emphasize that these phenomena not only influence burning, but also the observability of burning, further complicating our ability to assign reasonable emissions.

Riau is one of the most vulnerable provinces to forest and land fires in Indonesia. The potency for forest and land fires is inseparable from the presence of peatlands and exacerbated by drought. The purpose of this research is to know the characteristics of meteorological drought using SPI (Standardized Precipitation Index) method and its relation with forest and peatland fire as one of disaster management effort in Riau Province. The data used in this research are monthly rainfall data from meteorology station and rainfall posts of BMKG, hotspot data from NOAA satellite, map of Forest Use Agreement (TGHK), peat land map and land use map. Analysis of drought characteristics was done by calculating monthly SPI-1 then determining the maximum duration, intensity, severity and drought exposure. Determination of the severity of the drought by weighting and suspension method was based on duration and intensity while drought exposure was done by overlaying the map of the severity of the drought with the land use map. Meanwhile, to know the potential of forest and land fires began with the selection of hotspots on peatlands and forest areas every month then created a graph of the relationship of meteorological drought with the number of hotspots. Then, to see the relationship of drought distribution to the distribution of hotspots in dry season (MK) and wet season (MH) of 2015 was done by overlaying cover the drought distribution with hotspot distribution. The result shows that drought characteristic in the most of Riau province has maximum duration around 4-6 months, dry category of intensity, high category of severity with exposure area in paddy field, field, habitation, and plantation. Then, negative SPI Index (dry condition) has potential to increase the number of hotspots otherwise positive SPI index (wet condition) leads to low occurrence of hotspot. The drought distribution in the dry season (July, August, September) of 2015 triggers the number of hotspots during drought conditions, while in wet season (April, November, December) of 2015 are dominated by normal conditions, some areas are dry and wet, resulting in lower hotspots distribution compared to the dry season.

Abstract A weather radar is an active system remote sensing tool that observes precipitation indirectly. Weather radar has an advantage in estimating precipitation because it has a high spatial resolution (up to 0.5 km). Reflectivity generated by weather radar still has signal interference caused by attenuation factors. Attenuation causes the Quantitative Precipitation Estimation (QPE) by the C-band weather radar to underestimate. Therefore attenuation correction on C-band weather radar is needed to eliminate precipitation estimation errors. This study aims to apply attenuation correction to determine Quantitative Precipitation Estimation (QPE) on the c-band weather radar in Bengkulu in December 2018. Gate-by-gate method attenuation correction with Kraemer approach has applied to c-band weather radar data from the Indonesian Agency for Meteorology and Geophysics (BMKG) weather radar network Bengkulu. This method uses reflectivity as the only input. Quantitative Precipitation Estimation (QPE) has obtained by comparing weather radar-based rain estimates to 10 observation rain gauges over a month with the Z-R relation equation. Root Mean Square Error (RMSE) is used to calculate the estimation error. Weather radar data are processed using Python-based libraries Wradlib and ArcGIS 10.5. As a result, the calculation between the weather radar estimate precipitation and the observed rainfall obtained equation Z=2,65R1,3. The attenuation correction process with Kreamer's approach on the c-band weather radar has reduced error in the Qualitative Precipitation Estimation (QPE). Corrected precipitation has a smaller error value (r = 0.88; RMSE = 8.38) than the uncorrected precipitation (r = 0.83; RMSE = 11.70).

Daerah aliran sungai (DAS) Kapuas, walaupun berada di wilayah benua maritim Indonesia dengan curah hujan yang tinggi sepanjang tahun, namun sering mengalami kebakaran lahan dan hutan. Bencana kebakaran lahan dan hutan tersebut merupakan dampak dari kekeringan yang berkepanjangan. Informasi tentang karakteristik kekeringan di wilayah DAS Kapuas masih kurang diungkap terutama terkait dengan penggunaan data iklim global. Penelitian ini bertujuan untuk menganalisis karakteristik kekeringan meteorologis dan kekeringan hidrologis DAS Kapuas. Analisis kekeringan meteorologis digunakan pendekatan Standardize Precipitation Index (SPI) dan kekeringan hidrologis digunakan Standarized Runoff Index (SRI). Data curah hujan dan runoff dari Global Climate Model (GCM) yang telah di-downscaling menjadi 20 km x 20 km digunakan sebagai input data. Berdasarkan indeks kekeringan skala satu bulanan selama 30 tahun (1981-2010), diperoleh bahwa DAS Kapuas telah mengalami kekeringan meteorologis sebanyak 45 kali dan 48 kali kekeringan hidrologis dengan kategori moderat kering sampai dengan ekstrim kering. Luas wilayah yang mengalami kekeringan meteorologis maksimum terjadi pada tahun 1986 yakni 11,01% dari total wilayah DAS, kekeringan hidrologis maksimum terjadi pada tahun 1991 yakni 13,9% dari total wilayah DAS. Durasi kejadian kedua jenis kekeringan tersebut dominan berdurasi satu bulan. Luas wilayah kekeringan, tingkat keparahan, frekuensi, dan durasi kekeringan cenderung meningkat saat kejadian El-Niño. Hasil analisis karakteristik kekeringan menunjukkan bahwa data GCM dapat digunakan untuk analisis kekeringan di DAS Kapuas.

Kekeringan dapat didefinisikan pengurangan persediaan air yang bersifat sementara secara signifikan di bawah normal. Bencana kekeringan yang terjadi di Indonesia saat ini mengakibatkan daerah kekurangan suplai air untuk kebutuhan hidup, pertanian, dan kegiatan ekonomi dalam masa yang berkepanjangan. Meninjau dampak yang ditimbulkan, maka diperlukan analisis untuk daerah-daerah yang memiliki potensi terjadinya bencana kekeringan. Terdapat beberapa metode yang dikembangkan untuk menganalisis kekeringan, seperti SPI (Standardized Precipitation Index) dan RDI (Reconnaissance Drought Index), sehingga mengetahui tingkat dan karakteristik kekeringan suatu daerah. Setelah melakukan analisis dengan kedua indeks tersebut dilakukan pengambaran peta sebaran kekeringan menggunakan Sistem Informasi Geografi sehingga mempermudah menginterpretasikan daerah yang mengalami potensi kekeringan pada DAS Lekso , serta dapat melakukan upaya-upaya pencegahan dan penanggulangan bahaya bencana kekeringan. hasil penelitian menunjukkan puncak kekeringan metode SPI periode defisit 1 bulan terjadi Mei tahun 2005 dengan wilayah desa yaitu Desa Slumbung, Balerejo, Semen, Tulungrejo dan Soso. Sedangkan pada metode RDI , puncak kekeringan terjadi pada bulan Mei tahun 2005 dengan wilayah desa yang mengalami kekeringan yaitu Desa Slumbung, Balerejo, Semen, Tulungrejo dan Soso. Berdasarkan analisis kesesuaian antara indeks kekeringan dengan data Southern Oscillation Indeks, disimpulkan bahwa perhitungan indeks kekeringan metode RDI memiliki prosentase tingkat kesesuaian lebih tinggi dibandingkan dengan metode indeks kekeringan SPI.

Sub DAS Kadalpang, Kabupaten Pasuruan merupakan salah satu daerah rawan bencana kekeringan di Indonesia. Analisis kekeringan serta pemetaan sebarannya diperlukan sebagai upaya meminimalisir dampak kekeringan. Studi ini bertujuan untuk mengetahui hasil kesesuaian metode Standardized Precipitation Index (SPI) dan China Z Index (CZI) dengan Southern Oscillation Index (SOI) sehingga didapatkan metode yang lebih sesuai diterapkan pada Sub DAS Kadalpang. Pemetaan sebaran kekeringan menggunakan metode Inversed Distance Weight (IDW) dengan bantuan Sistem Informasi Geografi bertujuan untuk mengetahui daerah terdampak secara lebih akurat agar penanganan dapat dilakukan dengan optimal. Hasil indeks kekeringan terparah metode SPI sebesar (-3,711) pada periode 1 bulan, pada bulan Mei 2018. Hasil indeks kekeringan terparah metode CZI sebesar (-6,701) pada periode 1 bulan, pada bulan Mei 2018. Analisis korelasi CZI dan SPI dengan SOI menunjukkan hubungan linier yang lemah. Dipilih opsi perbandingan dengan pola curah hujan untuk menunjukkan kesesuaian dengan lokasi studi dan metode CZI lebih sesuai. Penggambaran peta sebaran kekeringan menggunakan metode yang lebih sesuai yaitu CZI. Hasil peta sebaran kekeringan dengan jumlah kejadian kekeringan terparah tahun 2007 dengan bulan kering terparah bulan Mei, dan terdapat 17 desa di Sub DAS Kadalpang berpotensi terdampak kekeringan sehingga perlu diprioritaskan dalam upaya mitigasi bencana kekeringan di masa mendatang.

Drought happen when the rainfall decreases in the extreme condition for long period of time (above normal). Drought hazard mapping can be analyzed by various approaches, like environmental approach, ecological approach, hydrological approach, meteorological approach, geological approach, agricultural approach, and many other. Meteorological, Climatological, and Geophysical Agency (in Indonesia a.k.a BMKG) measures the drought hazard by utilizing Standardized Precipitation Index (SPI)The comparison of rainfall rate through SPI has positive correlation with drought type, for example SPI 3 indicates agricultural drought; while SPI 6, SPI 9 and SPI 12 indicate hydrological drought. The analysis of drought hazard level also can be done using soil moisture level measurement. Soil moisture is the result of water shortages in the hydroclimatological concept. Soil moisture analysis utilizes several influenced variables, such as soil water, precipitation, evapotranspiration, and percolation. Each of variables was analyzed using GIS as a method of soil moisture modeling. Drought index level analysis is using soil moisture deficit index, which indicates that drought occurs if the index score less than (-0.5). Some assumptions used in this modeling are both SMDI modeling using WHC (Water Holding Capacity) and without using WHC. This modeling used medium term analysis during 2007-2012 to prove the occurrence of extreme drought on 2009 and 2012 for measurement of drought level in agriculture area. Based on SMDI, it is known that the dangers of SMDI drought have positive correlation to SPI 3, SPI 6, SPI 9, and SPI 12, where SPI is in accordance with the interpretation of meteorolgy, agriculture, and hydrological drought indices.

Abstract Rainfall in Parapat as a part of Lake Toba, North Sumatera and a super-priority tourist destination in Indonesia on May, 13 2021 causes flood, it exceeds Meteorologi, Climatologi and Geophysics Agency’s threshold about intensity of extreme condition. It is related to dynamic of weather’s parameter, especially with convection process and clouds. The landslide material was very closed the road so that the SiantarParapat access was temporarily closed down. Heavy rains that have occurred since noon are said to be the cause of the floods and landslides that occurred at night. This study aims to describe the distribution of rain in Parapat and surrounding areas during floods and landslides. The data used are measured rainfall at the nearest AWS (Automatic Weather Station), and rainfall estimation data from GPM IMERG (Global Precipitation Measurement – The Integrated Multi-SatellitE Retrievals). The results of the study show that convective cloud classification model can be identify the reconstruction of heavy rain that trigger the flood and landslide in parapet. There has been rain with moderate to heavy intensity since 12 May 2021. Heavy rains that have occurred in the last few days have caused soil conditions to become saturated, resulting in landslides. Cloud classification shows the presence of Cumulonimbus cloud clusters that grow and develop around the Lake Toba area before and during heavy rains.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. 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The seasonal atmospheric condition over the Maritime Continent is mainly driven by the Asian-Australian Monsoon. Precipitation over the Maritime Continent is highly influenced by the intra-seasonal Madden-Julian Oscillation (MJO), also highly affected by the El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole Mode (IOD). At an interannual time scale the Maritime Continent is also crossed by Indonesia Through Flow (ITF), as the artery connecting Tropical Pacific and Indian Oceans, and acting as a crucial link of the ocean general circulation that affects not only properties of these two oceans but also global climate. This complex mixture of land and sea interaction, with various atmospheric and oceanic phenomena within, makes the Maritime Continent as a unique, enigmatic and challenging area for scientific endeavor on tropical meteorology and atmospheric sciences. Various observations and research have been coordinated, campaigned, and conducted to better understand the atmospheric and oceanic condition over the tropics, especially the Maritime Continent. Many scientific discoveries have been found to enrich the knowledge of atmospheric science on the tropics, from the International Winter Monsoon Experiment in 1978, TOGA COARE in 1993, HARIMAU that ended in 2010, to CINDY/DYNAMO in 2011. The recent Year of Maritime Continent (YMC) during 2017 - 2020 aimed to improve understanding and prediction local multi-scale variability of the Maritime Continent weather-climate system and its global impact through observations and modelling exercises, was the state-of-art for such coordinated research on the tropics. As a part of YMC program, BMKG will also be involved in Measurements and Modelling of the Indonesian Throughflow International Experiment (MINTIE) which is collaborative research among countries including Indonesia BMKG and being led by Columbia University during 2019 – 2024. LIST OF Committee, Steering Committee, Organizing Committee Leader, Leader, Secretariat & Public Relations, Treasure, Event are available in this pdf.

Kekeringan merupakan salah satu bencana alam di Indonesia. Badan Nasional Penanggulangan Bencana (BNPB) melaporkan bahwa Provinsi Papua Barat memiliki ancaman kekeringan yang sedang hingga tinggi. Penelitian ini bertujuan untuk menganalisis tingkat kekeringan di Provinsi Papua Barat menggunakan data Global Precipitation Measurement (GPM) dan metode Standardized Precipitation Index (SPI). Hasil penelitian menunjukkan bahwa sepanjang tahun 2019 di Papua Barat tidak terjadi kekeringan meteorologis, hanya beberapa wilayah di Kabupaten Kaimana yang agak kering pada SPI bulan Januari – Maret 2019. Secara umum data GPM dan metode SPI memiliki akurasi yang cukup baik dalam menggambarkan tingkat kekeringan meteorologis di Provinsi Papua Barat dibandingkan dengan analisis data hujan dan peta tingkat kekeringan yang dirilis oleh Badan Meteorologi, Klimatologi, dan Geofisika (BMKG), sehingga data GPM dan metode SPI dapat digunakan untuk memantau tingkat kekeringan di Provinsi Papua Barat khususnya pada kawasan pertanian.

AbstractFlooding represents around 32% of total disasters in Indonesia and disproportionately affects the poorest of communities. The objective of this study was to determine significant statistical differences, in terms of river catchment characteristics, between regions in West Java that reported suffering from flood disasters and those that did not. Catchment characteristics considered included various statistical measures of topography, land-use, soil-type, meteorology and river flow rates. West Java comprises 154 level 9 HydroSHEDS sub-basin regions. We split these regions into those where flood disasters were reported and those where they were not, for the period of 2009 to 2013. Rainfall statistics were derived using the CHIRPS gridded precipitation data package. Statistical estimates of river flow rates, applicable to ungauged catchments, were derived from regionalisation relationships obtained by stepwise linear regression with river flow data from 70 West Javanese gauging stations. We used Kolmogorov–Smirnov tests to identify catchment characteristics that exhibit significant statistical differences between the two sets of regions. Median annual maximum river flow rate (AMRFR) was found to be positively correlated with plantation cover. Reducing plantation land cover from 20 to 10% was found to lead to a modelled 38% reduction in median AMRFR. AMRFR with return periods greater than 10 years were found to be negatively correlated with wetland farming land cover, suggesting that rice paddies play an important role in attenuating extreme river flow events. Nevertheless, the Kolmogorov–Smirnov tests revealed that built land cover is the most important factor defining whether or not an area is likely to report flood disasters in West Java. This is presumably because the more built land cover, the more people available to experience and report flood disasters. Our findings also suggest that more research is needed to understand the important role of plantation cover in aggravating median annual maximum river flow rates and wetland farming cover in mitigating extreme river flow events.