Analisis Curah Hujan di Indonesia untuk Memetakan Daerah Potensi Banjir dan Tanah Longsor dengan Metode Cluster Fuzzy C-Means dan  Singular Value Decompotition (SVD)

One of the climate changes impact is extreme rainfall. Extreme rainfall can cause some hydrometeorological disasters, especially floods and landslides. In 2016, BNPB recorded that there were 2,342 disaster events in Indonesia, 92% of which were disasters dominated by floods, landslides, and cyclones. There were 766 floods, 612 landslides, and 74 combinations of both. In this case, clustering is one of the important method to identify groups of areas with similar characteristics of high or low rainfall. Another analysis that can be applied is the identification of the extreme rainfall and the determination of dominant rainfall pattern using Singular Value Decomposition (SVD) for each region in Indonesia. The data was taken from Indonesia’s rainfall data in January 1998 - March 2017, obtained from the Tropical Rainfall Measuring Mission (TRMM) meteorological satellite, with 12,834 observation units. The highest average rainfall in Indonesia in December is 290,26 mm/month. Rainy season is predicted from November to April because they have the highest average rainfall. The SVD analysis formed four dominant rainfall patterns in Indonesia with a variance of 25.59%, where Papua and West Papua are the regions with the highest rainfall. The area around the Indian Ocean is the area with the most extreme rainfall events compared to other regions. Using Fuzzy C-means, three clusters can be formed, with criteria for areas of high, medium, and low rainfall. Based on the results of the analysis, the area has the potential for flooding and landslides due to high rainfall, so that preventive and mitigation efforts against the risk of flooding and landslides can be treated better.

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06/00652 Determination of PSS location based on singular value decomposition

Fuel and Energy Abstracts ◽

10.1016/s0140-6701(06)80654-5 ◽

2006 ◽

Vol 47 (2) ◽

pp. 99

Keyword(s):

Singular Value Decomposition ◽

Singular Value ◽

Value Decomposition

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Determination of Broadening Functions using the Singular Value Decomposition (SVD) Technique

International Astronomical Union Colloquium ◽

10.1017/s0252921100048405 ◽

1999 ◽

Vol 170 ◽

pp. 82-90 ◽

Cited By ~ 2

Author(s):

Slavek Rucinski

Keyword(s):

Correlation Function ◽

Singular Value Decomposition ◽

Cross Correlation ◽

Singular Value ◽

Spectral Lines ◽

Linear Inversion ◽

Standard Tool ◽

Contact Binaries ◽

Value Decomposition

AbstractThe cross-correlation function (CCF) has become the standard tool for extraction of radial-velocity and broadening information from high resolution spectra. It permits integration of information which is common to many spectral lines into one function which is easy to calculate, visualize and interpret. However, the CCF is not the best tool for many applications where it should be replaced by the proper broadening function (BF). Typical applications requiring use of BFs rather than CCFs involve finding locations of star spots, studies of projected shapes of highly distorted stars such as contact binaries (as no assumptions can be made about BF symmetry or even continuity) and [Fe/H] metallicity determinations (good baselines and avoidance of negative lobes are essential). It is stressed that the CCFs are not broadening functions. This note concentrates on the advantages of determining BFs through the process of linear inversion, preferably accomplished using the singular value decomposition (SVD). Some basic examples of numerical operations are given in the IDL programming language.

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TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-369-163-2015 ◽

2015 ◽

Vol 369 ◽

pp. 163-168 ◽

Cited By ~ 4

Author(s):

E. Schiavo Bernardi ◽

D. Allasia ◽

R. Basso ◽

P. Freitas Ferreira ◽

R. Tassi

Keyword(s):

Temporal Distribution ◽

Daily Rainfall ◽

Tropical Rainfall Measuring Mission ◽

Extreme Rainfall ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Remote Sensors ◽

Indirect Measures ◽

Equation Error ◽

Convective Cells

Abstract. The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998–2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5–10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10–35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

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A case of apodization function using singular-value decomposition: Determination of beamforming parameters by optimization

Acoustical Science and Technology ◽

10.1250/ast.29.185 ◽

2008 ◽

Vol 29 (2) ◽

pp. 185-187 ◽

Cited By ~ 8

Author(s):

Chikayoshi Sumi

Keyword(s):

Singular Value Decomposition ◽

Singular Value ◽

Value Decomposition ◽

Apodization Function

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Extreme rainfall events during and following heatwaves

10.5194/egusphere-egu21-8851 ◽

2021 ◽

Author(s):

Christoph Sauter ◽

Christopher White ◽

Hayley Fowler ◽

Seth Westra

Keyword(s):

Natural Hazards ◽

Rainfall Intensity ◽

Daily Rainfall ◽

Extreme Rainfall ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Rainfall Extremes ◽

Average Rainfall ◽

Time Of Year ◽

The Impact

Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.

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Regional Characteristics of Extreme Rainfall Extracted from TRMM PR Measurements

Journal of Climate ◽

10.1175/jcli-d-14-00107.1 ◽

2014 ◽

Vol 27 (21) ◽

pp. 8151-8169 ◽

Cited By ~ 31

Author(s):

Atsushi Hamada ◽

Yuki Murayama ◽

Yukari N. Takayabu

Keyword(s):

Regional Differences ◽

Tropical Rainfall Measuring Mission ◽

Extreme Rainfall ◽

Horizontal Resolution ◽

Mesoscale Convective Systems ◽

Extreme Rainfall Events ◽

Near Surface ◽

Rainfall Events ◽

Convective Systems ◽

Mesoscale Convective

Abstract Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000–1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of “intense and extensive” extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of “intense but less extensive” extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of “extensive but less intense” extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones.

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