scholarly journals Karakteristik Ketinggian Melting Layer di Indonesia Berdasarkan Radar Hujan Yang Terpasang Di Satelit TRMM

2018 ◽  
Vol 10 (2) ◽  
pp. 73-82
Author(s):  
Rany Audia Dwianda ◽  
Marzuki Marzuki

Ketinggian melting layer atau freezing level height (FH) di Indonesia telah diteliti melalui data radar hujan yang terpasang di satelit Tropical Rainfall Measuring Mission (TRMM). Data yang digunakan adalah data TRMM 2A25 versi 7 selama 2011-2013. Nilai FH dari TRMM dibandingkan dengan nilai yang direkomendasikan oleh model ITU-R P.839. FH di Indonesia memiliki variasi musiman dan diurnal yang signifikan. Rata-rata bulanan FH menunjukkan pola bimodal dengan dua puncak dan dua lembah, mirip dengan pola curah hujan dan temperatur permukaan air laut di Indonesia. Puncak FH teramati pada bulan-bulan basah (musim hujan) ketika temperatur permukaan air laut tinggi. Nilai FH mencapai puncaknya pada sore hari yaitu sekitar jam 18-19 waktu setempat. Adanya perbedaan pola FH antara darat dan laut yang menandakan adanya pengaruh sirkulasi darat-laut (land-sea breezes). Pada dini dan pagi hari, hujan dengan FH > 5 km tidak teramati di daratan tetapi pada siang dan sore hari jumlahnya meningkat, terutama di Sumatera, Kalimantan dan Papua. Nilai FH tertinggi yang teramati dalam penelitian ini adalah 5,55 km yang teramati pada 2013, dan nilai terendah adalah 4,40 km, yang teramati pada 2012. Sebagian besar hujan yaitu sekitar 82% dari total data, memiliki FH lebih rendah dari yang direkomendasikan oleh ITU-R P.839 (5 km). Dengan demikian, model ITU-R menakar FH lebih tinggi dari semestinya. Selain itu, asumsi nilai FH yang konstan (5 km) dalam model ITU-R juga tidak tepat karena nilai FH di Indonesia menunjukkan variasi diurnal dan musiman yang signifikan.Kata kunci : melting layer, Indonesia, TRMM-PR, ITU-R P.839, variasi diurnal, variasi musiman 

2007 ◽  
Vol 46 (5) ◽  
pp. 667-672 ◽  
Author(s):  
Yunfei Fu ◽  
Guosheng Liu

Abstract Rain-type statistics derived from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) standard product show that some 70% of raining pixels in the central Tibetan Plateau summer are stratiform—a clear contradiction to the common knowledge that rain events during summer in this region are mostly convective, as a result of the strong atmospheric convective instability resulting from surface heating. In examining the vertical distribution of the stratiform rain-rate profiles, it is suspected that the TRMM PR algorithm misidentifies weak convective rain events as stratiform rain events. The possible cause for this misidentification is believed to be that the freezing level is close to the surface over the plateau, so that the ground echo may be mistakenly identified as the melting level in the PR rain classification algorithm.


2013 ◽  
Vol 52 (9) ◽  
pp. 2001-2008 ◽  
Author(s):  
K. Saikranthi ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
S. Vijaya Bhaskara Rao

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.


INCREaSE 2019 ◽  
2019 ◽  
pp. 97-110
Author(s):  
Géri Eduardo Meneghello ◽  
Letícia Burkert Méllo ◽  
Ritâ De Cassia Fraga Damé ◽  
Francisco Amaral Villela ◽  
Maria Clotilde Carré Chagas Neta ◽  
...  

Author(s):  
Kenneth S. Gage ◽  
Christopher R. Williams ◽  
Wallace L. Clark ◽  
Paul E. Johnston ◽  
David A. Carter

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