KORELASI ANTARA DATA CURAH HUJAN  PENAKAR MANUAL DAN TRMM (TROPICAL RAINFALL  MEASURING MISSION) GIOVANNI TOVAS.  (STUDI KASUS TEKNOLOGI MODIFIKASI CUACA UNTUK MENANGGULANGI KABUT ASAP KEBAKARAN HUTAN DAN LAHAN DI  RIAU TAHUN 2014)

Intisari Telah dilakukan kajian tentang korelasi antara data curah hujan yang terukur di Pos Meteorologi dan data curah hujan yang terukur pada TRMM (Tropical Rainfall Measuring Mission). Data curah hujan merupakan data curah hujan rata – rata harian dibeberapa titik yang ada di Provinsi Riau. Data yang digunakan dalam kajian ini adalah data hujan dari tanggal 16 Maret sampai dengan 28 April 2014. Pengujian korelasi dilakukan dengan menggunakan teknik korelasi Product Moment Pearson dengan asumsi bahwa data terdistribusi normal. Dari hasil perhitungan dengan korelasi Pearson didapatkan nilai korelasi sebesar 0,52. Korelasi yang terhitung sebesar 0,52 masuk kedalam kategori CUKUP. Selain pengujian korelasi, data curah hujan juga dianalisa dengan uji perbandingan streamline yang terbentuk pada diagram kartesius. Tanpa melihat besarnya nilai curah hujan tetapi dengan melihat pola terbentuknya streamline terlihat tanggal 16 Maret sampai dengan tanggal 21 Maret 2014 pola yang terbentuk cenderung berkebalikan dimana ketika data curah hujan pada Posmet turun curah hujan pada TRMM justru malah naik. Sementara mulai tanggal 22 Maret 2014 sampai akhir tanggal 28 April 2014 terlihat tren stream line yang cenderung berpola mirip walaupun ada beberapa titik yang saling berkebalikan sehingga secara umum terlihat polanya mirip.Abstract Studied correlation between data rainfall in Post Meteorological (Posmet) and rainfall data on TRMM (Tropical Rainfall Measuring Mission) have been done. Precipitacion is average rainfall data at the daily average some point in Province of Riau. Data used in this study is data from 16 March to 28 April, 2014. Correlation testing was done by using Pearson Product Moment correlation with assumption that data were normally distributed. From the calculation of Pearson correlation obtained correlation value is 0.52. Correlations were calculated is 0.52, category ENOUGH. In addition to testing the correlation, data rainfall were also analyzed with a streamlined comparison test were formed on Cartesian diagram. Without seeing the value of rainfall but by looking at the pattern formation of streamlined look dated March 16 until March 21, 2014 established pattern which tends to reverse when the rainfall data Posmet down on TRMM rainfall actually even go up. While the start date of March 22, 2014 until the end date of 28 April 2014 visible trends that tend to stream line pattern is similar, although there are a few points of each other so that in general the pattern looks similiar.

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A Comparison of Gamma and Lognormal Distributions for Characterizing Satellite Rain Rates from the Tropical Rainfall Measuring Mission

Journal of Applied Meteorology ◽

10.1175/jam2165.1 ◽

2004 ◽

Vol 43 (11) ◽

pp. 1586-1597 ◽

Cited By ~ 69

Author(s):

Hye-Kyung Cho ◽

Kenneth P. Bowman ◽

Gerald R. North

Keyword(s):

Gamma Distribution ◽

Lognormal Distribution ◽

Rain Rate ◽

Tropical Rainfall Measuring Mission ◽

Rainfall Data ◽

Retrieval Algorithm ◽

Sample Mean ◽

Tropical Rainfall ◽

Lognormal Distributions ◽

Rain Rates

Abstract This study investigates the spatial characteristics of nonzero rain rates to develop a probability density function (PDF) model of precipitation using rainfall data from the Tropical Rainfall Measuring Mission (TRMM) satellite. The minimum χ2 method is used to find a good estimator for the rain-rate distribution between the gamma and lognormal distributions, which are popularly used in the simulation of the rain-rate PDF. Results are sensitive to the choice of dynamic range, but both the gamma and lognormal distributions match well with the PDF of rainfall data. Comparison with sample means shows that the parametric mean from the lognormal distribution overestimates the sample mean, whereas the gamma distribution underestimates it. These differences are caused by the inflated tail in the lognormal distribution and the small shape parameter in the gamma distribution. If shape constraint is given, the difference between the sample mean and the parametric mean from the fitted gamma distribution decreases significantly, although the resulting χ2 values slightly increase. Of interest is that a consistent regional preference between two test functions is found. The gamma fits outperform the lognormal fits in wet regions, whereas the lognormal fits are better than the gamma fits for dry regions. Results can be improved with a specific model assumption depending on mean rain rates, but the results presented in this study can be easily applied to develop the rainfall retrieval algorithm and to find the proper statistics in the rainfall data.

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Evaluasi Kesesuaian Data Tropical Rainfall Measuring Mission (TRMM) dengan Data Pos Hujan Pada Das Temef di Kabupaten Timor Tengah Selatan

JURNAL SUMBER DAYA AIR ◽

10.32679/jsda.v16i1.646 ◽

2020 ◽

Vol 16 (1) ◽

pp. 51-62

Author(s):

Denik Sri Krisnayanti ◽

Davianto Frangky B. Welkis ◽

Fery Moun Hepy ◽

Djoko Legono

Keyword(s):

Correlation Coefficient ◽

Correction Factor ◽

Daily Rainfall ◽

Tropical Rainfall Measuring Mission ◽

Rainfall Data ◽

Annual Maximum ◽

Monthly Basis ◽

Discharge Data ◽

Tropical Rainfall ◽

South Central

The construction of the Temef Dam in Oenino Village, Oenino District, and Konbaki Village, Polen District, South Central Timor Regency requires long and reliable rainfall data. To overcome the minimum data or the unavailability of automatic rainfall (ARR) and discharge data in the past decades, the use of Tropical Rainfall Measuring Mission (TRMM) satellite data is foreseen. The accuracy of TRMM data is obtained when the parameters of suitability and compatibility of TRMM are in a good agreement with the ARR. For the Temef watershed, there are six rainfall stations that were reviewed, namely Fatumnasi, Oeoh, Noelnoni, Polen, Nifukani, and Batinifukoko rainfall stations. Direct comparisons of rainfall data were conducted for 20 years (1998-2018) with temporal resolution on a monthly and daily basis. The results of the study show that the rainfall patterns in the TRMM data product (version 3B42V7) tend to be consistent with 3 rainfall stations in the Temef watershed namely Noelnoni, Fatumnasi, and Batinifukoko. A correlation coefficient of 0.505 – 0.813 was obtained from TRMM data calibration at monthly basis while a correction factor level of 0.0056 - 0.0129 was obtained for daily. The calibration on the annual maximum daily rainfall data resulted in a correction factor of 0.0298 - 0.2516. Monthly and daily TRMM data fit well with the data of 3 rainfall stations. However, the Noelnoni rainfall station showed poor results on the annual maximum daily rainfall.Keywords: TRMM data, ARR data, correction factor, correlation coefficient

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KONDISI CURAH HUJAN PADA KEJADIAN BANJIR JAKARTA DAN ANALISIS KONDISI UDARA ATAS WILAYAH JAKARTA BULAN JANUARI – FEBRUARI 2013

Jurnal Sains & Teknologi Modifikasi Cuaca ◽

10.29122/jstmc.v14i1.2678 ◽

2013 ◽

Vol 14 (1) ◽

pp. 19

Author(s):

M. Djazim Syaifullah

Keyword(s):

High Intensity ◽

Rainy Season ◽

Tropical Rainfall Measuring Mission ◽

Rainfall Data ◽

Atmospheric Conditions ◽

Wet Season ◽

Tropical Rainfall ◽

Local Factors ◽

Precipitation Area

IntisariKondisi curah hujan di wilayah Jakarta pada kejadian banjir besar tanggal 17 Januari 2013 telah dianalisis yang dihubungkan dengan kondisi atmosfer pada selang waktu tersebut. Data curah hujan menggunakan data TRMM sedangkan analisis kondisi atmosfer menggunakan data rawinsonde. Hasil analisis menunjukkan bahwa puncak kejadian banjir Jakarta musim hujan tahun 2013 terjadi pada tanggal 17 Januari 2013 disebabkan oleh faktor lokal yang sangat kuat ditambah dengan faktor global yang mendukung, sementara pada kejadian banjir tanggal 6 Februari 2013 faktor lokalnya tidak begitu kuat sehingga diduga faktor globalnya lebih dominan. Untuk wilayah Jakarta terdapat indikasi bahwa pada musim hujan, intensitas curah hujan wilayah Jakarta yang melebihi 40 mm/hari selama lebih dari empat hari berturut-turut mempunyai potensi besar menimbulkan genangan (banjir). Perlunya kewaspadaan yang lebih tinggi lagi dengan meningkatkan antisipasi pada saat terjadi curah hujan dengan intensitas tinggi selama empat hari berturut-turut.AbstractRainfall condition in the Jakarta area on great flood January 17, 2013 has been analyzed that is associated with the atmospheric conditions. Rainfall Data using Tropical Rainfall Measuring Mission TRMM data and analysis of the atmospheric conditions using rawindsonde data. Results of analysis showed that the peak of the flooding incident, Jakarta's wet season 2013 occurred on January 17, 2013 is caused by a very strong local factors coupled with the global factors, while the flood February 6, 2013 global factors are thought to be more dominant than local factors. For the Jakarta area there are indications that in the rainy season, the intensity of the precipitation area of Jakarta that exceeds 40 mm/day for more than four consecutive days have great potential cause inundation (flooding). The need for vigilance is higher with increasing anticipation when the rainfall with high intensity for four consecutive days.

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CORRELATION BETWEEN RAINFALL PATTERN AND OIL PALM PERFORMANCE IN SUMATRA AND BORNEO ISLAND DURING EL NIÑO 2015

Jurnal Penelitian Kelapa Sawit ◽

10.22302/10.22302/iopri.jur.jpks.v24i2.11 ◽

2018 ◽

Vol 24 (2) ◽

pp. 87-96

Author(s):

Iput Pradiko ◽

Eko Novandy Ginting ◽

Nuzul Hijri Darlan ◽

Winarna Winarna ◽

Hasril Hasan Siregar

Keyword(s):

Oil Palm ◽

El Niño ◽

El Nino ◽

Southern Oscillation ◽

Pearson Correlation ◽

Rainfall Data ◽

Rainfall Pattern ◽

Dry Spell ◽

Male Flowers ◽

Central South

El Niño 2015 is one of the strongest El Niño. Drought stress due to El Niño could affect oil palm performances. This study was conducted to determine rainfall pattern and oil palm performance in Sumatra and Borneo Island during El Niño 2015. Data employed in this study is monthly rainfall data, Southern Oscillation Index (SOI) January-December 2015, andoil palm performances. Pearson correlation between SOI and rainfall data was used to analyze rainfall pattern, while oil palm performances were observed based on morphological conditions. Result shows that southern part of Sumatra and mostly part of Borneo suffer from more dry spell, dry month, and water deficit such as 37-133 days, 3-5 months, and 349-524 mm respectively. Analysis of rainfall pattern shows that Jambi, South Sumatra, Lampung, Central, South, and East Borneo are significantly (r ≥ +0,60) affected by El Niño 2015. Oil palms in southern part of Sumatra and mostly part of Borneo are suffer from drought stressmarked by the emergence of more than two spear fronds, appearing of many male flowers, malformations on bunches, fronds tend to hanging down, and lower fronds tend to dry.

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