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<![CDATA[AN INDICATION OF SEA-AIR INTERACTION THAT AFFECTS THE CLIMATE PATTERN OVER THE MOLUCCAN SEA ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 3, No 2 (2002): December 2002 ]]>
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DOI: 10.29122/jstmc.v3i2.2170
<![CDATA[Starting with the regional annual cycle of rainfall over Molucca, which follow the sun eclipse movement instead of the common Inter Tropical Convergence Zone (ITCZ) movement, a suspicion of the sea-air interaction driven climate pattern comes up. The empirical study on rainfall â sea surface temperature (SST) relationship clarifies a function of rainfall accumulation to SST. A strong evident on the interaction comes from the result of Ocean General Circulation Model (OGCM). The model shows a surface water intrusion that comes from west Pacific into the north Molucca Sea before it enter the mainstream of the Indonesian throughflow in the north end of the Makasar strait. Most of the throughflow, as shown by the model, come from north Pacific, enter the Makasar strait southward and go into the Indian ocean through the Lombok strait (mostly) and a strait between Flores and Timor island. The intrusion of surface water in north Molucca conserves the warm sea surface temperature and keep a high convective area.Diawali dengan pembagian region berdasarkan pola hujan tahunan di Maluku, yangmengikuti pergerakan tahunan matahari dan bukannya yang biasa yaitu Inter TropicalConvergence Zone (ITCZ), kecurigaan akan adanya interaksi laut udara yang mendorong pola iklim timbul. Studi empiris mengenai hubungan hujan dan suhu permukaan laut menjelaskan fungsi akumulasi hujan terhadap suhu laut. Indikasi kuat adanya interaksi berasal dari keluaran model global sirkulasi laut. Model menunjukkan adanya intrusi arus permukaan dari pasifik barat ke Maluku utara sebelum masuk ke alur utama dari arus lintas Indonesia di ujung utara selat makasar. Sebagian besar arus lintas, sebagaimana dituntukkan oleh model, berasal dari utara, memasuki selat Makasar ke selatan dan menuju ke samudra Indonesia kebanyakan melalui selat Lombok dan sebagian kecil melalui selat antara pulau Flores dan Timor. Intrusi arus permukaan di utara Maluku menjaga kehangatan suhu muka laut dan menjaga daerah konvektif aktif.]]>
<![CDATA[PEMBAGIAN IKLIM INDONESIA BERDASARKAN POLA CURAH HUJAN DENGAN METODA âDOUBLE CORRELATIONâ ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 2, No 1 (2001): June 2001 ]]>
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DOI: 10.29122/jstmc.v2i1.2142
<![CDATA[Pembagian wilayah atau region iklim Indonesia berdasarkan pola curah hujan tahunandibahas disini. Sebuah metoda yang dinamakan metoda âdouble correlationâ diperkenalkan untuk tujuan di atas. Dengan metoda regionalisasi yang dipakai dihasilkan tiga region iklim berdasarkan pola curah hujan tahunan. Region pertama adalah region A yang terletak di wilayah selatan Indonesia yang disebut region monsun Australia karena region ini lebih banyak dipengaruhi oleh monsun Australia. Region kedua adalah region B di wilayah barat laut Indonesia, yang disebut sebagai region monsun passat tenggara karena dipengaruhi oleh monsun ini. Region terakhir adalah region C atau region arus lintas laut Indonesia (arlindo) karena terletak pada daerah aliran arlindo. Pola hasil dari regionalisasi ini dibandingkan dengan pola pada region yang sama pada keluaran model reanalisa ECMWF dan ECHAM.A regionalization of Indonesian climate based on its annual rainfall patterns has been done. A new method called the âdouble correlation methodâ was introduced and used for such purpose. With this regionalization method there are three climate regions based on their annual rainfall patterns. The first region or region A lies in south Indonesia and is called the Australian monsoon region because it is much affected by the Australian monsoon. The second region or region B lies in northwest Indonesia, which is called as the NE Passat region because it is much affected by that monsoon. The last region or region C lies over the Indonesian Throughflow and is called as the Indonesian Throughflow region. Patterns resulted from this regionalization method are compared to those of their corresponding regions from the output of ECMWF reanalysis and a Global Circulation Model ECHAM.]]>
<![CDATA[THE SIMULATION OF CO- AND CROSS-POLAR CHARACTERS OF RAINFALL DROPLETS AND CHAFF ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 3, No 2 (2002): December 2002 ]]>
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DOI: 10.29122/jstmc.v3i2.2166
<![CDATA[The error analyses and simulations of the co- and cross-polar characters of chaff andrainfall have been done. Error analyses include the ZDR distribution, numbers ofscaterers, the orientation and shape dependence, the system DC bias, the channel gainimbalance and the quantification errors. There is no effect of number of scatterers on the noise. The orientation and shape dependence study indicates wider frequency distribution of ZDR from chaff is because of the chaffs needle shape. The orientation of chaff contributes insignificantly to noises The noises has been reduced considerably after eliminating system DC bias and gaining more channel balance. Further possible source of error is the quantification error in data analyses. LDR is more useful than ZDR when both chaff and rain are present. The result suggests a possibility of using chaffâs LDR in tracing air movement.Analisa error dan simulasi sifat co- dan cross-polar dari chaff dan butir -butir hujan telahdilakukan. Analisa error termasuk penyebaran ZDR, jumlah chaff atau bidang pemantul(scatterers), orientasi dan bentuk dari chaff, factor kesalahan DC, keseimbangan keduakanal pada radar dan factor kesalahan kuantitatif unit. Tidak ada sumbangan kesalahandari jumlah scatterers pada noise. Penelitian orientasi dan bentuk menunjukkan lebarnya penyebaran ZDR pada chaff karena bentuknya. Orientasi dari chaff tidak menyumbang factor kesalahan yang berarti. Noise telah dapat dikurangi hingga minimal setelah menghilangkan factor kesalahan system DC dan menyeimbangkan kedua kanal. Faktor kesalahan lainnya yang mungkin adalah kesalahan kuantitatif unit pada analisis data. LDR lebih berguna dari ZDR ketika kedua duanya yaitu chaff dan butir hujan berada. Hasil tersebut menyarankan kegunaan chaff LDR untuk pemantauan pergerakan udara.]]>
<![CDATA[THE SPECTRUM THRESHOLD FILTER METHOD FOR CHAFF AND RAIN ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 3, No 1 (2002): June 2002 ]]>
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DOI: 10.29122/jstmc.v3i1.2157
<![CDATA[Polarization doppler radar observations of chaff and rain were conducted. At least in thevertical pointing case, the spectrum of chaff is much narrower than that of rain. In dataanalysis a new method of filtering chaff data from noise is used. This filter method, named the spectrum threshold filter method, was also applied for rain data for comparison. Instead of using the average power as in the conventional method this fil ter method utilizes the doppler spectral peak power. Consequently this filter method is able to detect a presence of even a single strong doppler velocity signals. Hence the performance of this filter is better with metallic strips, such as chaff, than raindrops. The variation of the filterâ s threshold will change significantly the filtered rainfall area but not the chaff one. The filter technique is also useful to detect a narrow but strong spectral data.Pengamatan hujan dan chaff dengan memakai radar dengan polarisasi doppler telahdilakukan. Paling tidak pada posisi tegak lurus, spektrum dari chaff lebih sempit daripada pada butir hujan. Dalam melakukan analisa data kita telah mengembangkan sebuah metoda filtering untuk memilah data chaff dari noise sekitarnya. Metoda filter ini, yang disebut metoda filter spectrum threshold, juga diterapkan pada data hujan sebagai perbandingan. Daripada memakai kekuatan rata-rata dengan metoda umumnya, metoda filter ini memakai puncak spektrum. Sehingga metoda filter ini dapat mendeteksi keberadaan dari hanya sebuah puncak kecepatan doppler dalam sinyal. Pada akhirnya kinerja metoda filter ini lebih baik untuk aplikasi pada pita-pita logam seperti chaff daripada butiran hujan. Variasi dari batas ambang (threshold) dari filter ini akan mengubah area hujan yang terfilter secara drastis tetapi tidak pada data chaff. Teknik filter ini juga berguna untuk mendeteksi spektrum doppler yang sempit tetapi kuat.]]>
<![CDATA[POLA HUJAN RATA-RATA BULANAN WILAYAH INDONESIA; TINJAUAN HASIL KONTUR DATA PENAKAR DENGAN RESOLUSI ECHAM T -42 ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 1, No 2 (2000): December 2000 ]]>
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DOI: 10.29122/jstmc.v1i2.2124
<![CDATA[Kajian temporal dari sifat iklim Indonesia berdasarkan pola curah hujan rata-rata bulanan telah dilakukan dengan mengacu pada beberapa parameter ECMWF seperti angin 850 mb, OLR dan suhu permukaan. Parameter ECMWF tersebut dapat menjelaskan hampir semua pola kecuali daerah yang terdapat pola gangguan lokal. Dengan kajian temporal ini, penulis menemukan ITCZ, daerah siklon di utara Australia dan aktivitas monsun yang dominan pada beberapa bulan. Hasil lainnya menunjukkan adanya perioda transisi pada bulan April dan Oktober yang dapat dimengerti dari pola angin 850 mb dan suhu permukaan. Juga dijelaskan bahwa puncak hujan tahunan di Bali ke Timor lebih banyak dipengaruhi oleh siklon tropis di utara Australia daripada monsun Asia.Temporal assesment of Indonesian climate characteristic based on monthly rainfall pattern was done with several ECMWF (European Center for Medium Range Weather Forecast) parameters; i.e. wind field of 850 mb, Outgoing Longwave Radiation (OLR) and surface temperature. Those ECMWF parameters could explain almost all rainfall pattern with some exceptional areas which are due to their local disturbances. With this temporal assesment, the author found Inter Tropical Continental Zone (ITCZ), cyclonic area in north of Australia and monsoon activities which are dominant in some specific months. One results of this research shows transitional period existence in April and October which are fully understood by analysis of 850 mb wind and surface temperature. It is also explained that peak of rainfall pattern in Bali - Timor area are much characterized by tropical cyclones in north of Australia rather than by Asian monsoon.]]>
<![CDATA[SPATIAL PATTERNS OF ENSO IMPACT ON INDONESIAN RAINFALL ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Sains & Teknologi Modifikasi Cuaca Vol 3, No 1 (2002): June 2002 ]]>
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DOI: 10.29122/jstmc.v3i1.2154
<![CDATA[A monthly temporal and spatial assesment on ENSO impact on Indonesian rainfall hasbeen done. The study uses monthly ensemble averages of El Nino and La Nina years from 1961 to 1993. There are 6 El Niño years and 5 La Niña years during that period. Indonesia experiences negative ENSO influences from April on both El Niño (warm phase) and La Niña (cold phase). The influences of ENSO reach their peaks in August and September by both types of events and decay afterward. The influences diminish totally by December. Since the influences occur in the dry season, El Niño contributes a negative impact, while La Niña a positive impact to the Indonesian climate. The maximum spatial extension of ENSO reaches almost all parts of Indonesia except north Sumatera and some parts of Kalimantan. There is an indication of a negative influence of ENSO to the onset of Asian monsoon in the Southeast Asian.Kajian bulanan secara temporal dan geografis tentang pengaruh ENSO terhadap curahhujan Indonesia telah dilakukan. Penelitian ini memakai nilai rata-rata gabungan bulanan dari tahun El Niño dan La Niña dari 1961 hingga 1993. Ada 6 tahun El Niño dan 5 tahun La Niña pada perioda tersebut. Indonesia menerima pengaruh negatif dari ENSO mulai April pada tahun ENSO. Pengaruh ENSO mencapai puncaknya pada bulan Agustus dan September pada keduanya dan menurun setelahnya. Pengaruhnya benar-benar hilang pada bulan Desember. Karena pengaruh ENSO terjadi pada musim kering, El Niño memberikan kontribusi negative terhadap iklim Indonesia, sementara La Niña memberikan kontribusi positive. Luasan daerah pengaruh ENSO yang maksimal terjadi di hampir seluruh wilayah Indonesia kecuali bagian utara Sumatera dan sebagian Kalimantan. Ada indikasi pengaruh negative dari ENSO terhadap kedatangan muson Asia ke wilayah Asia Tenggara.]]>
<![CDATA[PREDICTION OF SOUTHERN OSCILLATION USING THE INDONESIAN THROUGHFLOW VARIABILITY ]]>
<![CDATA[Aldrian, Edvin]]>;
<![CDATA[Arifian, Jon]]>
<![CDATA[ Marine Research in Indonesia Vol 34, No 1 (2009) ]]>
Publisher : <![CDATA[Research Center for Oceanography - Indonesian Institute of Sciences (LIPI) ]]>
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DOI: 10.14203/mri.v34i1.516
<![CDATA[Atmospheric boundary layer derived from NCEP/NCAR reanalyses for the period of 1974 to 2002 has been used as boundary forcings for the global ocean model Max Planck Institute Ocean Model (MPIOM). The ocean model is a curvilinear grid model, whose poles are located over mainland China and over the Australian continent, thus focusing on the maritime continent. The model simulates major Indonesian throughflow passages that focus on six cannels representing three inlets and three outlets (the Makassar, Lifamatola, Halmahera, Lombok, Ombai and Timor Straits). The model results have been validated using the Arlindo observation Project over the Makassar Strait in the period of January 1997 to February 1998, which fortunately was during a strong El Niño episode. The model simulation results were then investigated for their prediction capabilities of any of those channels in foreseeing the incoming southern oscillation events. Temporal correlation analysis with lag and advance time correlation methods were performed against simulated data at all levels on those channels. Variabilities in depth of 74 to 200m (thermocline depth) show the strongest correlation with SOI index (Darwin minus Tahiti mean sea level pressure). The temperature and salinity correlations with SOI are the highest with one-month in advance over Lifamatola Strait (0.77) and two-month in advance over the Makassar Straits (0.74). These significant correlations highlight the important of those two straits in prediction of incoming southern oscillation that usually leads to ENSO episode which brings most of the time devastating impact to economy, agriculture and ecosystem. ]]>
<![CDATA[DOMINANT FACTORS OF JAKARTA’S THREE LARGEST FLOODS ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Hidrosfir Indonesia Vol 3, No 3 (2008) ]]>
Publisher : <![CDATA[Jurnal Hidrosfir Indonesia ]]>
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<![CDATA[In year 2002, 2007 and 2008 Jakarta experienced heaviest flood in early February from rain that precipitate in several days ahead. Those rainfalls take place in early morning for few consecutive days. The extreme early morning rainfall occurs due to three dominant phenomena the Madden Julian oscillation wet phase, the cold surge and a vortex in the southwest of Java. The cold surge from north compressed the air mass over the north of Jakarta Bay, picked up as much as water vapor over it and brings to the bay. Especially at night during intense land breeze, south ward movement of compressed and moist air collided frontally with the land breeze andcaused strong uplifting at the coast. The latter phenomenon created strong convection at the Jakarta metropolitan areas at early morning and caused extreme rainfall events. Those daily rainfall rate are almost and exceed the monthly rainfall values. Analises of data from satellite observation, rain gauge, wind and radar imagery prove the mechanism of extreme weather in early morning that cause heavy flood over Jakarta. The incoming of those three phenomena could be predicted in advance with quite a certainty. The MJO is a feature that has 50 days oscillation so that MJO wet phase could be predicted in advance up to 2 weeks. The cold surge that comes from Siberia has index of sudden drop of pressure in Hongkong before propagate to Southeast Asia, thus could be predicted in advance about one week ahead. Lastly the vortex development in southwest of Java could be predicted up to 1 days in advanced. Those information on the three major or dominant weather feature will be a good early warning for heavy flood of Jakarta especially in early February.]]>
<![CDATA[PEAT CARBON, CIRE AND CLIMATE INTERACTIONS ]]>
<![CDATA[Aldrian, Edvin]]>
<![CDATA[ Jurnal Hidrosfir Indonesia Vol 3, No 1 (2008) ]]>
Publisher : <![CDATA[Jurnal Hidrosfir Indonesia ]]>
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<![CDATA[This study describes the interaction between forest fire and climate, which focuses on the peatland fire contribution and its carbon released. We established the interannual carbon released that refer to some previous result and we extend the results for the last decade(1997 to 2007) of total carbon and PM10 estimations. We found a significant relationship betweenclimate and hotspot number, which indicate the behavior of fires over Sumatera and Kalimantan over the last decade, except for 2006. Improvement in the correlation occurs when we utilized second half of the year in to consideration. Apparently there are two regional climatic systemsthat drive or force the annual variability of hotspots over Sumatera and Kalimantan through trans equatorial cold surge in the first half of year and El Nino in the second half of the year. The cold surge phenomenon is crucial for the hotspot variability for Riau province, while the latter could impacts both Sumatera and Kalimantan. Strong climate forcing indicates, by excluding 2006, that Indonesian peat pool is vulnerable to the regional climatic system or a victim of regional climate perturbation. Recent data (latest four years) shows larger fluctuation from the climatic factor. The 2006 fires and their emission are exceptionally high and divert from the strong correlation between fire and climatic factor. The 2006 fire close to 1997 firein amount and emission (88.4%) and PM10 (87%) and hotspot number (92.8%). Overall, during the last decade, the carbon emission from forest fires in Indonesia fluctuates following climate variability and could not be generalized to emit carbon at persistently high level every year.]]>
<![CDATA[PERSEPSI KERENTANAN BAHAYA BANJIR DAN KEKERINGAN AKIBAT PERUBAHAN IKLIM DI DAS BATANGHARI ]]>
<![CDATA[Handoko, Unggul]]>;
<![CDATA[Boer, Rizaldi]]>;
<![CDATA[Apip, Apip]]>;
<![CDATA[Aldrian, Edvin]]>;
<![CDATA[Dwi Dasanto, Bambang]]>
<![CDATA[ LIMNOTEK - Perairan Darat Tropis di Indonesia Vol 25, No 2 (2018) ]]>
Publisher : <![CDATA[Research Center for Limnology ]]>
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<![CDATA[ABSTRAKPenelitian persepsi tingkat perubahan iklim dan tingkat kerentanan daerah terhadap bahaya banjir dan kekeringan telah dilakukan di DAS Batanghari. Persepsi tersebut kemudian dianalisis konsistensinya dengan kejadian sesungguhnya. Metode penelitian yang digunakan untuk analisis persepsi menggunakan teknik wawancara accidental sampling, uji validitas, uji reliabilitias, penskoran, dan pengkelasan. Sedangkan untuk analisis konsistensi antara persepsi dengan kejadian sesungguhnya menggunakan analisis kecenderungan anomali curah hujan dan suhu udara (untuk tingkat perubahan iklim) dan membandingkan dengan peta rawan banjir dan kekeringan (untuk kerentanan daerah terhadap bahaya banjir dan kekeringan). Hasil penelitian menunjukkan bahwa di DAS Batanghari perubahan iklim telah terjadi hal ini sesuai dengan persepsi sebagian besar masyarakat yang ada di DAS Batanghari serta didukung dengan adanya peningkatan kecenderungan nilai anomali suhu dan curah hujan dari tahun ke tahun. Wilayah yang paling rentan terhadap bahaya banjir dan kekeringan berdasarkan persepsi masyarakat adalah segmen hilir DAS Batanghari, hal ini sesuai dengan peta daerah rawan bencana banjir dan kekeringan. Kata kunci : perubahan iklim, kerentanan, banjir, kekeringan, DAS Batanghari ]]>
