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INDONESIA
Agromet
Published by Institut Pertanian Bogor
ISSN : 01263633     EISSN : 2655660X     DOI : -
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Agromet publishes original research articles or reviews that have not been published elsewhere. The scope of publication includes agricultural meteorology/climatology (the relationships between a wide range of agriculture and meteorology/climatology aspects). Articles related to meteorology/climatology and environment (pollution and atmospheric conditions) may be selectively accepted for publication. This journal is published twice a year by Indonesian Association of Agricultural Meteorology (PERHIMPI) in collaboration with Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, IPB University.
Arjuna Subject : -
Articles 287 Documents
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MODEL DINAMIK PENILAIAN KESESUAIAN AGROKLIMAT TANAMAN KEDELAI(DYNAMIC MODEL OF AGROCLIMATIC SUITABILITY OF SOYBEAN) H. Supriyadi; Y. Koesmaryono; L.H. Sibuea
Agromet Vol. 21 No. 1 (2007): June 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (137.468 KB) | DOI: 10.29244/j.agromet.21.1.55-64

Abstract

The experiment aims to arrange of data-based of agroclimatic suitability for soybean, to arrange dynamic models for evaluation of suitability for soybean, and to evaluate agroclimatic suitability for soybean on computer. Secondary data of soybean yield and climate were collected from four locations of West Java as specific site targets, those were: Pusakanagara Subang, Cimanggu Bogor, Karangpawitan Garut, and Pasirsarongge Cianjur. Dynamic model has been developed as a tool to assess agroclimatic suitability of soybean which comprises the class, sub class, and sub-sub class level. The model provides information on land productivity, climatic constraint, stages of plant development that related to climate condition. Agroclimatic suitability is classified to five classes, i.e. S1 (very suitable), S2 (suitable), S3 (moderately suitable), S4 (not suitable), and S5 (very not suitable). Base on climate data of 2002, the models indicated that class of S1 were not found. While Cimanggu Bogor is classified as S2; Pusakanagara Subang and Karangpawitan Garut are classified as S3; and Pasirsarongge Cianjur is classified as S4.
THE USE OF AGRICULTURE SYSTEM MODELING FOR CROP MANAGEMENT: CASE STUDY IN PUSAKA NEGARA(PENGGUNAAN MODEL SISTIM PERTANIAN UNTUK PENGELOLAAN TANAMAN :STUDI KASUS PUSAKANEGARA) R. Boer; M.K. Rahadiyan; P. Perdinan
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (324.24 KB) | DOI: 10.29244/j.agromet.21.2.1-11

Abstract

Agriculture system modeling is an effective tool in assisting agriculture practitioners to make crop calendar and to set up crop management strategies. Integration of the toll with climate forecast modeling will provide greater help for decision makers and farmers to set up better drought coping strategies. However the adoption of this tool is constrained by limited availability of long historical daily climatic data. This study indicates that the use of climatic data generator can solve this problem. Application of this approach at Pusaka Negara was assessed. It is suggested that when April SOI phase is rapidly falling or constantly negative (indicating EL-Nino years), keeping planting rice in the dry season is not recommended. Farmers may need to change their crops to non-rice crops requiring less water. The latest planting time for these crops in the El-Nino years should be first week of May. If the harvesting of first rice crops occur after 1st week of May, it is suggested that the land should be fallowed.---------------------------------------------------------------------Pemodelan sistim pertanian merupakan salah salat alat yang efektif untuk membantu pelaksana lapang dalam menyusun kalender tanam atau mengatur strategi pengelolaan tanaman. Penggabungan model tanaman dengan model prakiraan iklim akan sangat membantu pengambil kebijakan dan petani dalam menyusun strategi antisipasi kekeringan. Namun penggunaan model ini seringkali mengalami hambatan karena terbatasnya ketersediaan data iklim harian jangka panjang. Penelitian ini menunjukkan bahwa penggunakan pembangkit data iklim dapat memecahkan masalah tersebut. Aplikasi pendekatan ini di Pusakanegara telah dilakukan. Hasil penelitian merekimendaiskan ika kondisi SOI pada bulan April turun secara cepat atau konstan negatif (mengindikasikan El Nino), penanaman padi pada musim kemarau tidak direkomendasikan. Petani disarankan untuk mengganti tanamannya dengan tanaman selain padi yang memerlukan lebih sedikit air. Waktu penanaman paling terakhir pada tahun El Nino adalah minggu pertama bulan Mei. Jika panen padi pertama dilakukan setelah 1 Mei sangat disarankan untuk memberakan lahan.
ANTHROPOGENIC CHANGES ON LAND COVER AND ITS IMPACT ON ACTUAL EVAPOTRANSPIRATION E. Runtunuwu
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.21.2.12-26

Abstract

 Tulisan ini memaparkan perubahan distribusi vegetasi akibat kegiatan manusia serta dampaknya terhadap perubahan evapotranspirasi aktual di Monsoon Asia. Perbandingan antara vegetasi aktual dan potensial menjadi indikator dari dampak perubahan akibat kegiatan manusia. Kondisi vegetasi akual diidentifikasi dengan menggunakan citra satelit, sedangkan vegetasi potensial diekstrak dengan menggunakan data iklim. Dengan membandingkan distribusi vegetasi antara potensial dan aktual, ternyata bahwa perubahan banyak terjadi di India, China, Indonesia dan Malaysia. Selanjutnya, dengan menggunakan analisis neraca air dilakukan perhitungan evapotransipirasi aktual untuk kedua kondisi tersebut dengan menggunakan data iklim yang sama, tetapi dengan nilai albedo yang berbeda sebagai penciri perbedaan antara kondisi vegetasi potensial dan actual. Perubahan a E berkisar antara 0-12% per tahun. Nilai 0 untuk mencirikan daerah yang tidak mengalami perubahan akibat kegiatan manusia. Penurunan a E sebesar kurang dari 5% teridentifikasi di daerah yang mengalami perubahan dari evergreen broadleaf forest (seasonal) ke padi sawahataupun dari hutan subtropikal menjadi lahan pertanian, seperti yang terjadi di Shandong (China), Uttar Pradesh (India). Penurunan a E mencapai 9% teridentifikasi pada saat hutan sub tropis berubah menjadi padi sawah, seperti yang terjadi di Assam (India), serta Guangdong dan Guangxi (China). Penurunan sebesar 12% terjadi pada saat hutan tropis berubah menajdi lahan pertanian seperti yang terjadi di Kalimantan Selatan (Indonesia) and Pahang (Malaysia).
METODE NERACA ENERGI UNTUK PERHITUNGAN INDEKS LUAS DAUN MENGGUNAKAN DATA CITRA SATELIT MULTI SPEKTRAL(ENERGY BALANCE METHOD FOR DETERMINING LEAF AREA INDEX LAND USING MULTI SPECTRAL SATELLITE IMAGINARY) I. Risdiyanto; R. Setiawan
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.205 KB) | DOI: 10.29244/j.agromet.21.2.27-38

Abstract

Leaf area index (LAI) is a variable showing relation between leaf area leaf and area closed over it. The conventionally technique to determine LAI value conducted by measure and accumulate wide of amount of leaf in one selected area and divided broadly area. The other technique, LAI also can be measured by using measuring instrument of solar radiation like attached tube solarimeter parallelly above and below/under plant canopy. Both of the approaches have limitation of spatial which developed new method with remote sensing technique. Determination of LAI with remote sensing technique exploits the nature of spectral of surface both from short wave (sun radiation) and long wave (surface radiation). One of the method able to be developed is surface energy balance approach with Beer-Lambert law. Result of this research indicate that value of LAI for the vegetation area by surface energy balance method and equation of Beer-Lambert law got value of mean LAI for natural forest equal to 3.05 with the range value 2.85 - 3.50 and R2 is 0.91, for the rubber agroforest equal to 3.01 with range value 2.79 - 3.40 and R2 is 0.69, while value of mean LAI for the plantation of monoculture of rubber equal to 2.96 with range value 2.74 - 3.28 and and R2 is 0.82. This method can be used for vegetation area especially for homogeneously like natural forest and monoculture.---------------------------------------------------------------------Indeks luas daun (ILD) merupakan suatu peubah yang menunjukkan hubungan antara luas daun dan luas bidang yang tertutupi. Secara konvensional penentuan nilai LAI dilakukan dengan mengukur dan mengakumulasikan jumlah luas daun dalam satu bidang tertentu dan dibagi dengan luas bidang tersebut. ILD juga dapat diukur menggunakan alat ukur radiasi surya seperti tube solari meter yang dipasang paralel di atas dan di bawah tajuk tumbuhan. Kedua pendekatan tersebut mempunyai keterbatasan spasial, sehingga dicoba mengembangkan metode baru dengan teknik penginderaan jauh. Pendugaan ILD dengan teknik ini memanfaatkan sifat spektral dari permukaan baik yang bersumber dari radiasi gelombang pendek dari matahari maupun radiasi gelombang panjang dari permukaan. Salah satu metode yang dapat dikembangkan adalah pendekatan neraca energi untuk menghasilkan peubah-peubah penduga ILD menggunakan hukum Beer-Lambert. Hasil penelitian ini menunjukkan bahwa nilai rata-rata ILD untuk lahan bervegetasi menggunakan metode neraca energi dan persamaan hukum Beer-Lambert untuk hutan alam sebesar 3.05 dengan nilai kisaran selang 2.85- 3.50 dan R2 validasi dengan ILD lapangan sebesar 0.91. Nilai rata-rata LAI pendugaan untuk agroforest karet sebesar 3.01 dengan selang 2.79–3.40 dan nilai R2 validasi sebesar 0.69, sedangkan nilai rata-rata ILD untuk perkebunan karet monokultur sebesar 2.96 dengan selang 2.74–3.28 dan nilai R2 validasi sebesar 0.82. Metode pendugaan ILD ini dapat digunakan untuk lahan bervegetasi terutama untuk pertanaman homogen seperti hutan alam dan monokultur.
ANALISA POTENSI CURAH HUJAN BERDASARKAN DATA DISTRIBUSI AWAN DAN DATA TEMPERATURE BLACKBODY DI KOTOTABANG SUMATERA BARAT( ANALYSIS OF RAINFALL POTENCY BASED ON CLOUD DISTRIBUTION AND TEMPERATURE BLACKBODY DATA IN KOTOTABANG) A. Turyanti; I. Sunarsih; E. Hermawan
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (365.381 KB) | DOI: 10.29244/j.agromet.21.2.39-45

Abstract

Precipitation in West Sumatera was influenced by monsoon circulation and its position in equator, and also the topography of Bukit Barisan. This study is designed to learn more about characteristics of precipitation in West Sumatera (case study in Kototabang) using cloud distribution data from XDR and Temperature Black Body (TBB). The result shows the precipitation increase on the end of February, and XDR data represents the clouds are convective, and also TBB data increasing at the same time. This is the early of rainy season in West Sumatera. On the other season, in the middle of July, the intensity of precipitation decreased, and XDR data shows much clouds are formed, but the rainfall wasvery rare until August. The TBB data also represents decreasing of top clouds temperature, so dry season in West Sumatera begin in the middle of July.--------------------------------------------------------------------Curah hujan Sumatera Barat selain dipengaruhi oleh sirkulasi monsoon, juga dipengaruhi oleh posisinya yang dilalui garis khatulistiwa serta kondisi topografi lokal yang berpegunungan. Penelitian ini mengkaji tentang karakteristik curah hujan wilayah Sumatera Barat khususnya Kototabang berdasar distribusi awan dan Temperature Black Body (TBB). Data curah hujan yang dianalisa adalah data curah hujan bulan Januari dan Februari 2004 (menjelang musim hujan), serta bulan Juli dan Agustus 2004 (musim kemarau). Hasil kajian menunjukkan bahwa intensitas curah hujan mulai meningkat pada akhir bulan Februari, dan didukung oleh data kondisi awan dari XDR yang menunjukkan pada waktu tersebut awan yang tumbuh adalah awan-awan konvektif yang berpotensi menjadi hujan, serta grafik suhu puncak awan (TBB) yang meningkat tajam. Pada musim kemarau, curah hujan yang rendah terjadi mulai pertengahan Juli. Pada periode 3 Agustus sampai 12 Agustus tidak terjadi hujan. Jumlah awan yang terbentuk pada saat musim kemarau lebih banyak dibandingkan musim hujan tetapi tidak potensial untuk terjadi hujan lebat. Data TBB pada periode ini menurun drastis yang menunjukkan suhu puncak awan yang rendah, tidak berpotensi untuk terjadi hujan.
ANALISIS KORELASI CURAH HUJAN DAN SUHU PERMUKAAN LAUT WILAYAH INDONESIA, SERTA IMPLIKASINYA UNTUK PRAKIRAAN CURAH HUJAN (STUDI KASUS KABUPATEN CILACAP) (CORRELATION ANALYSIS OF RAINFALL AND INDONESIA SEA SURFACE TEMPERATURE, AND ITS ... W. Estiningtyas; F. Ramadhani; E. Aldrian
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1046.496 KB) | DOI: 10.29244/j.agromet.21.2.46-60

Abstract

Significant decrease in rainfall caused extreme climate has significant impact on agriculture sector, especialy food crops production. It is one of reason and push developing of rainfall prediction models as anticipate from extreme climate events. Rainfall prediction models develop base on time series data, and then it has been included anomaly aspect, like rainfall prediction model with Kalman filtering method. One of global parameter that has been used as climate anomaly indicator is sea surface temperature. Some of research indicate, there are relationship between sea surface temperature and rainfall. Relationship between Indonesian rainfall and global sea surface temperature has been known, but its relationship with Indonesian’s sea surface temperature not know yet, especialy for rainfall in smaller area like district. So, therefore the research about relationship between rainfall in distric area and Indonesian’s sea surface temperature and it application for rainfall prediction is needed. Based on Indonesian’s sea surface temperature time series data Januari 1982 until Mei 2006 show there are zona of Indonesian’s sea surface temperature (with temperature more than 27,6 0C) dominan in Januari-Mei and moved with specific pattern. Highest value of spasial correlation beetwen Cilacap’s rainfall and Indonesian’s sea surface temperature is 0,30 until 0,50 with different zona of Indonesian’s sea surface temperature. Highest positive correlation happened in March and July. Negative correlation is -0,30 until -0,70 with highest negative correlation in May and June. Model validation resulted correlation coeffcient 85,73%, fits model 20,74%, r2 73,49%, RMSE 20,5% and standart deviation 37,96. Rainfall prediction Januari-Desember 2007 period indicated rainfall pattern is near same with average rainfall pattern, rainfall less than 100/month. The result of this research indicate Indonesian’s sea surface temperature can be used as indicator rainfall condition in distric area, that means rainfall in district area can be predicted based on Indonesian’s sea surface temperature in zona with highest correlation in every month.------------------------------------------------------------------Penurunan curah hujan yang cukup signifikan akibat iklim ekstrim telah membawa dampak yang cukup signifikan pula pada sektor pertanian, terutama produksi tanaman pangan. Hal ini menjadi salah satu alasan yang mendorong semakin berkembangnya model-model prakiraan hujan sebagai upaya antipasi terhadap kejadian iklim ekstrim. Model prakiraan hujan yang pada awalnya hanya berbasis pada data time series, kini telah berkembang dengan memperhitungkan aspek anomali iklim, seperti model prakiraan hujan dengan metode filter Kalman. Salah satu indikator global yang dapat digunakan sebagai indikator anomali iklim adalah suhu permukaan laut. Dari berbagai hasil penelitian diketahui bahwa suhu permukaan laut ini memiliki keterkaitan dengan kejadian curah hujan. Hubungan curah hujan Indonesia dengan suhu permukaan laut global sudah banyak diketahui, tetapi keterkaitannya dengan suhu permukaan laut wilayah Indonesia belum banyak mendapat perhatian, terutama untuk curah hujan pada cakupan yang lebih sempit seperti kabupaten. Oleh karena itu perlu dilakukan penelitian yang mengkaji hubungan kedua parameter tersebut serta mengaplikasikannya untuk prakiraan curah hujan pada wilayah Kabupaten. Hasil penelitian berdasarkan data suhu permukaan laut wilayah Indonesia rata-rata Januari 1982 hingga Mei 2006 menunjukkan zona dengan suhu lebih dari 27,6 0C yang dominan pada bulan Januari-Mei dan bergerak dengan pola yang cukup jelas. Korelasi spasial antara curah hujan kabupaten Cilacap dengan SPL wilayah Indonesia rata-rata bulan Januari-Desember menunjukkan korelasi positip tertinggi antara 0,30 hingga 0,50 dengan zona SPL yang beragam. Korelasi tertinggi terjadi pada bulan Maret dan Juli. Sedangkan korelasi negatip berkisar antara -0,30 hingga -0,70 dengan korelasi negatip tertinggi pada bulan Mei dan Juni. Validasi model prakiraan hujan menghasilkan nilai koefisien korelasi 85,73%, fits model 20,74%, r2 sebesar 73,49%, RMSE 20,5% dan standar deviasi 37,96. Hasil prakiraan hujan bulanan periode Januari-Desember 2007 mengindikasikan pola curah hujan yang tidak jauh berbeda dengan rata-rata selama 19 tahun (1988-2006) dengan jeluk hujan kurang dari 100 mm/bulan. Hasil penelitian mengindikasikan bahwa SPL wilayah Indonesia dapat digunakan sebagai indikator untuk menunjukkan kondisi curah hujan di suatu wilayah (kabupaten), artinya curah hujan dapat diprediksi berdasarkan perubahan SPL pada zona-zona dengan korelasi yang tertinggi pada setiap bulannya.
KARAKTERISTIK BADAI TROPIS DAN DAMPAKNYA TERHADAP ANOMALI HUJAN DI INDONESIA(TROPICAL CYCLONE CHARACTERISTIC AND ITS IMPACT ON RAINFALL ANOMALY IN INDONESIA) N. Dyahwathi; S. Effendy; E.S. Adiningsih
Agromet Vol. 21 No. 2 (2007): December 2007
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.622 KB) | DOI: 10.29244/j.agromet.21.2.61-72

Abstract

Tropical cyclone never reached Indonesia area but its impact able to cause disaster to this country. Some research indicated effect of tropical cyclone due to high intensity the rain in short duration in some location but drought in another. Tropical cyclone often followed by small scale tornado callled ’puting beliung’ that cause local or regional damage. This research purpose to analyze physical characteristics of tropical cyclone at period January-March 2004 in south Hindia Sea. The Fay is a strong tropical cyclone has increase rainfall until 32 ms-1 and rainfaal on 47% Java station rainfall. On the other hand, The Ken is a weak tropical cyclone only cause higher wind speed and rainfall are 8 ms-1 and 18% Java station rainfall, respectively.------------------------------------------------------------------------Meskipun siklon tropis tidak pernah terjadi di Indonesia namun dampaknya sering berpengaruh terhadap Indonesia. Hasil berbagai penelitian menunjukkan bahwa siklon tropis menyebabkan hujan intensitas yang tinggi dalam waktu singkat pada suatu wilayah, dan juga menyebabkan kekeringan di daerah lain. Siklon tropis sering diikuti terjadinya puting beliung dengan daya rusak bersifat lokal hingga regional. Penelitian ini bertujuan untuk menganalisis karakteristik fisik siklon tropis di Samudera Hindia bagian selatan pada periode puncak terjadinya siklon yakni, Januari-Maret 2004. Analisis dilakukan terhadap dua siklon yang terjadi pada periode pengamatan yaitu siklon Fay (siklon kuat) dan siklon Ken (siklon lemah). Dampak siklon Fay terhadap peningkatan kecepatan angin menjadi 32 ms-1 dan peningkatan hujan yang signifikan padak 47% stasiun hujan di Jawa. Sedangkan siklon Ken hanya menyebabkan kecepatan angin meningkat sebesar 8 ms-1 dan peningkatan hujan pada 8% stasiun hujan di pulau Jawa.
IDENTIFIKASI KEKUATAN DAN KELEMAHAN KOMPONEN SISTEM INFORMASI IKLIM(STRENGTH AND WEAKNESS IDENTIFICATION OF CLIMATE INFORMATION COMPONENT) Urip Haryoko
Agromet Vol. 22 No. 2 (2008): December 2008
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.612 KB) | DOI: 10.29244/j.agromet.22.2.132-143

Abstract

Based on the survey of climate information application in many sectors showed that climate informations are inaccurate, lately received, abstrused and not meet to the user activities. There is a big gaps between climate information producer and user, it needs a bridging to handle a problem in interpreting information. These conditions caused to not optimally climate risk anticipation, so that there were still a lot of failures in some sectors, i.e. crops failure, urban floods, food and water shortage, health crisis, forest fire, etc. There are many activities have been done to increase skill to intepret and react to climate information. Providing climate information is one of the methods to minimize the climate risk. By understanding the climate information, climate risk could be managed optimally and it can minimize negative impact of climate extreme and get benefit from good climate conditions. Boer, 2009, said that there are five primary components as a key to climate information application in manage a risk, 1) climate data observation and data analysis, 2) climate forecast/prediction system, 3) climate information production and evaluation system, 4) communication and dissemination system, and 5) climate information system. Valuation of strength and weakness of five components above relatively depends on which angel be used. It needs an objective indicator to evaluate those components. In this paper, strength and weakness of climate information components will be identified. Data was collected from Meteorological, Climatological and Geophysical Agency’s stations and some institutions in Banten Province as climate information users by distributing questionaire. Furthermore, based on the components identification it could be created a strategy how to increase the capacity of climate information applications.
PENGEMBANGAN MODEL PREDIKSI MADDEN JULIAN OSCILLATION (MJO) BERBASIS PADA HASIL ANALISIS DATA REAL TIME MULTIVARIATE MJO (RMM1 DAN RMM2) (PREDICTION MODEL DEVELOPMENT MADDEN JULIAN OSCILLATION (MJO) BASED ON THE RESULTS OF DATA ANALYSIS ... Lisa Evana; Sobri Effendy; Eddy Hermawan
Agromet Vol. 22 No. 2 (2008): December 2008
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (829.212 KB) | DOI: 10.29244/j.agromet.22.2.144-159

Abstract

Background of this research is the importance of study on the Madden Julian Oscillation, the dominant oscillation in the equator area. MJO cycle showed by cloud cluster growing in the Indian Ocean then moved to the east and form a cycle with a range of 40-50 days and the coverage area from 10N-10S. Method that used to predict RMM is Box-Jenkins based on ARIMA (Autoregressive Integrated Moving Average) statistical analysis. The data used RMM daily data period 1 Maret 1979–1 Maret 2009 (30 years). RMM1 and RMM2 is an index for monitoring MJO. This is based on two empirical orthogonal functions (EOFs) from the combined average zonal 850hPa wind, 200hPa zonal wind, and satellite-observed Outgoing Longwave Radiation (OLR) data. The results in form of the Power Spectral Density (PSD) graph Real Time Multivariate MJO (RMM) and long wave radiation (OLR = Outgoing Longwave Radiation) at the position 100° BT, 120° BT, and 140°BT that show the wave pattern (spectrum pattern) and clearly shows the oscillation periods. There is a close relation between RMM1 with OLR at the position 100oBT that characterized the PSD value about 45 day. Through Box-Jenkins method, the prediction model that close to time series data of RMM1 and RMM2 is ARIMA (2,1,2), that mean the forecasts of RMM data for the future depending on one time previously and the error one time before. Prediction model for Zt = Zt = 1,681 Zt-1 – 0,722 Zt-2 - 0,02 at-1 - 0,05 at-2.. Prediction model for RMM2 is Zt = 1,714 Zt-1 – 0,764 Zt-2 - 0,109 at-1 - 0,05 at-2.. The flood case in Jakarta January-February 1996 and 2002 are one of real evidence that made the MJO prediction important. MJO with active phase dominant cover almost the entire Indonesia west area at that moment.
PEMANFATAAN DATA EQUATORIAL ATMOSPHERE RADAR (EAR) DALAM MENGKAJI TERJADINYA MONSUN DI KAWASAN BARAT INDONESIA(THE VALUABLE OF EQUATORIAL ATMOSPHERE RADAR (EAR) DATA TO STUDY MONSOON IN THE WEST AREA INDONESIA) Veza Azteria; Sobri Effendy; Eddy Hermawan
Agromet Vol. 22 No. 2 (2008): December 2008
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (992.783 KB) | DOI: 10.29244/j.agromet.22.2.160-173

Abstract

Kototabang, Padang Panjang and Sicincin city are area in the West part of Indonesia and they are relative in the equator line. Otherwise, three of these cities have difference of behaviors of rainfall for Monsoon. In this study, we were used EAR Data, which were including the rainfall Kototabang, Padangpanjang, and Sicincin. Base on this data (i.e EAR data) in Kototabang, there is monsoon in 8-18 km layer and the higher monsoon is in 14 km layer during the April 2002-April 2006 period. Analisis Power Spectral Density (PSD) and Transformasi wavelet were shown that Monsoon oscillation around 12 months. While vertical profile was presented that the stronger monsoon will be in the wet weather on January. The domination of wind in Kototabang city is South Wind, it is because the wind took water vapor mass from South to North. According to analysis of rainfall in Kototabang, Padangpanjang and Sicincin City, meridional wind in the the Sicincin has rainfall pattern the same as with monsoon. Its was indicated that there were local indicator which can cause the monsoon. From the cross correlation between meridionial wind speed with rainfall in Kototabang, Pontianak and Sicincin, they were shown that three of these cities have significant correlation.

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