scholarly journals KAJIAN BANJIR BANDANG MASAMBA JULI 2020, TINJAUAN METEOROLOGIS

2020 ◽  
Vol 21 (2) ◽  
pp. 73-83
Author(s):  
Muhamad Djazim Syaifullah
Keyword(s):  
Cumulus Congestus

Banjir bandang dan tanah longsor telah melanda kawasan Masamba, Kabupaten Luwu Utara Sulawesi Selatan, pada Senin 13 Juli 2010. Sedikitnya puluhan warga meninggal dunia dan ratusan orang luka serta belasan ribu orang mengungsi dan kehilangan harta benda. Data satelit menunjukkan adanya titik-titik longsor yang cukup banyak di wilayah hulu Sungai Sabbang, Sungai Radda, dan Sungai Masamba. Pemerintah menyebutkan bahwa bencana banjir bandang dan tanah longsor di Masamba adalah akibat curah hujan yang tinggi yang dipicu oleh adanya pertumbuhan awan Cumulonimbus (Cb). Analisis lebih detail menunjukkan bahwa beberapa hari sebelumnya daerah Sulawesi Selatan bagian tengah (termasuk juga wilayah Masamba dan sekitarnya) hampir selalu tertutupi oleh tutupan awan jenis Cumulus Congestus. Namun demikian dari analisis TRMM, wilayah Masamba bukan merupakan pusat curah hujan tertinggi. Curah hujan tertinggi berada di wilayah pantai timur Sulawesi Tengah. Adanya kejadiah hujan selama beberapa hari dan struktur tanah yang tidak mendukung memungkinkan permukaan tanah menjadi cepat jenuh, sehingga diduga menyebabkan terjadinya tanah longsor.

scholarly journals Entrainment and Detrainment in Numerically Simulated Cumulus Congestus Clouds. Part I: General Results

1998 ◽  
Vol 55 (23) ◽  
pp. 3417-3432 ◽  
Author(s):  
Richard L. Carpenter ◽  
Kelvin K. Droegemeier ◽  
Alan M. Blyth
Keyword(s):  
Cumulus Congestus

Observations of Moist Adiabatic Ascent in Northeast Colorado Cumulus Congestus Clouds

1978 ◽  
Vol 35 (9) ◽  
pp. 1689-1703 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Peter N. Johnson ◽  
James E. Dye
Keyword(s):  
Cumulus Congestus

scholarly journals Measurement of Convective Entrainment Using Lagrangian Particles

2013 ◽  
Vol 70 (1) ◽  
pp. 266-277 ◽  
Author(s):  
Kyongmin Yeo ◽  
David M. Romps
Keyword(s):  
Direct Measurement ◽  
Cloud Base ◽  
Entrainment Rate ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Environmental Air ◽  
Cumulus Congestus ◽  
Entrained Air ◽  
Eulerian Methods ◽  
Good Agreement

Abstract Lagrangian particle tracking is used in a large-eddy simulation to study an individual cumulus congestus. This allows for the direct measurement of the convective entrainment rate and of the residence times of entrained parcels within the cloud. The entrainment rate obtained by Lagrangian direct measurement is found to be higher than that obtained using the recently introduced method of Eulerian direct measurement. This discrepancy is explained by the fast recirculation of air in and out of cloudy updrafts, which Eulerian direct measurement is unable to resolve. By filtering these fast recirculations, the Lagrangian calculation produces a result in very good agreement with the Eulerian calculation. The Lagrangian method can also quantify some aspects of entrainment that cannot be probed with Eulerian methods. For instance, it is found that more than half of the air that is entrained by the cloud during its lifetime is air that was previously detrained by the cloud. Nevertheless, the cloud is highly diluted by entrained air: for cloudy air above 2 km, its mean height of origin is well above the cloud base. This paints a picture of a cloud that rapidly entrains both environmental air and its own detritus.

scholarly journals Lagrangian Investigation of the Precipitation Efficiency of Convective Clouds

2015 ◽  
Vol 72 (3) ◽  
pp. 1045-1062 ◽  
Author(s):  
Wolfgang Langhans ◽  
Kyongmin Yeo ◽  
David M. Romps
Keyword(s):  
Large Eddy Simulations ◽  
Cloud Base ◽  
Water Molecules ◽  
Lagrangian Particle ◽  
Surface Precipitation ◽  
Convective Clouds ◽  
Precipitation Efficiency ◽  
Surface Rainfall ◽  
Large Eddy ◽  
Cumulus Congestus

Abstract The precipitation efficiency of cumulus congestus clouds is investigated with a new Lagrangian particle framework for large-eddy simulations. The framework is designed to track particles representative of individual water molecules. A Monte Carlo approach facilitates the transition of particles between the different water classes (e.g., vapor, rain, or graupel). With this framework, it is possible to reconstruct the pathways of water as it moves from vapor at a particular altitude to rain at the surface. By tracking water molecules through both physical and microphysical space, the precipitation efficiency can be studied in detail as a function of height. Large-eddy simulations of individual cumulus congestus clouds show that the clouds convert entrained vapor to surface precipitation with an efficiency of around 10%. About two-thirds of all vapor that enters the cloud does so by entrainment in the free troposphere, but free-tropospheric vapor accounts for only one-third to one-half of the surface rainfall, with the remaining surface rainfall originating as vapor entrained through the cloud base. The smaller efficiency with which that laterally entrained water is converted into surface precipitation results from the smaller efficiencies with which it condenses, forms precipitating hydrometeors, and reaches the surface.

Entrainment and Detrainment in Numerically Simulated Cumulus Congestus Clouds. Part II: Cloud Budgets

1998 ◽  
Vol 55 (23) ◽  
pp. 3433-3439 ◽  
Author(s):  
Richard L. Carpenter ◽  
Kelvin K. Droegemeier ◽  
Alan M. Blyth
Keyword(s):  
Cumulus Congestus

scholarly journals A PDF-Based Formulation of Microphysical Variability in Cumulus Congestus Clouds*

2015 ◽  
Vol 73 (1) ◽  
pp. 167-184 ◽  
Author(s):  
Yefim L. Kogan ◽  
David B. Mechem
Keyword(s):  
Mesoscale Model ◽  
Distribution Functions ◽  
Cumulus Clouds ◽  
Atmospheric Sciences ◽  
Microphysical Process ◽  
Eddy Simulation ◽  
Shallow Cumulus ◽  
Toga Coare ◽  
Accretion Rates ◽  
Cumulus Congestus

Abstract Calculating unbiased microphysical process rates over mesoscale model grid volumes necessitates knowledge of the subgrid-scale (SGS) distribution of variables, typically represented as probability distribution functions (PDFs) of the prognostic variables. In the 2014 Journal of the Atmospheric Sciences paper by Kogan and Mechem, they employed large-eddy simulation of Rain in Cumulus over the Ocean (RICO) trade cumulus to develop PDFs and joint PDFs of cloud water, rainwater, and droplet concentration. In this paper, the approach of Kogan and Mechem is extended to deeper, precipitating cumulus congestus clouds as represented by a simulation based on conditions from the TOGA COARE field campaign. The fidelity of various PDF approximations was assessed by evaluating errors in estimating autoconversion and accretion rates. The dependence of the PDF shape on grid-mean variables is much stronger in congestus clouds than in shallow cumulus. The PDFs obtained from the TOGA COARE simulations for the calculation of accretion rates may be applied to both shallow and congestus cumulus clouds. However, applying the TOGA COARE PDFs to calculate autoconversion rates introduces unacceptably large errors in shallow cumulus clouds, thus precluding the use of a “universal” PDF formulation for both cloud types.

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