iklim dan flash flood
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IKLIM SEBAGAI PEMICU BANJIR BANDAN
Halmar HalideJurusan Fisika FMIPA UNHAS
Presentasi pada kegiatan Workshop dan FGD UNHAS- BNPB PenanggulanganBanjir Bandang , tgl 26 September 2013, Hotel Makassar Golden, Makassar
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Parodi et al. Predictability and predictive abilityof severe rainfall processes http://www.cimafoundation.org
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http://www.popsugar.com/Flash-Flood-Boulder-Colorado-2013-Pictures-31755647
1 inch = 2,54 cm
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http://www.nyc.gov/html/oem/html/hazards/weather_flashflood.shtml
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The tribals assess the probability of early warning of flood extent by observing color ofclouds, their location, intensity and frequency of rainfall. The unusual sounds and changesin water flow, colour of water, direction of wind and the unusual behavior of wildlife likeants, birds, rats and Snakes also helps in the assessment of climatic variations.
In the prediction that a particular year is likely to be a drought year, the nature of clouds isdescribed as follows: There would neither be prosperity nor rain in the land should theclouds be rough and small, tossed about by the wind have the shape of camels, corms,dead bodies, monkeys or other inauspicious creatures, and be silent
The tribals of Rajasthan also have faith in the sayings of elders about the prediction ofweather, for e.g Pawan baje Suryo,to hali halav kim puryo if winds flow in the North west direction then farmer should not plough his field because it indicates heavy rains.
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Indigenous knowledge in seasonal rainfall prediction in Tanzania: A case of theSouth-western Highland of TanzaniaLadislaus B. Changa , Pius Z. Yanda and James NganaJournal of Geography and Regional Planning Vol. 3(4), pp. 66-72, April 2010
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Indigenous knowledge in seasonal rainfall prediction in Tanzania: A case of theSouth-western Highland of TanzaniaLadislaus B. Changa , Pius Z. Yanda and James NganaJournal of Geography and Regional Planning Vol. 3(4), pp. 66-72, April 2010
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Indigenous knowledge in seasonal rainfall prediction in Tanzania: A case of theSouth-western Highland of TanzaniaLadislaus B. Changa , Pius Z. Yanda and James NganaJournal of Geography and Regional Planning Vol. 3(4), pp. 66-72, April 2010
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http://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.html
http://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.htmlhttp://bpkp-sidrap.blogspot.com/2011/05/petunjuk-lontara-allaorumang-adat-bugis.html -
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DESCRIPTION: Warm (red) and cold (blue) episodes based on a threshold of +/- 0.5 oC for theOceanic Nio Index (ONI) [3 month running mean of ERSST.v3b SST anomalies in the Nio 3.4region (5 oN-5oS, 120 o-170 oW)], based on centered 30-year base periods updated every 5 years .
For historical purposes cold and warm episodes (blue and red colored numbers) are definedwhen the threshold is met for a minimum of 5 consecutive over-lapping seasons.
http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtmlhttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtmlhttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtmlhttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtmlhttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtmlhttp://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_change.shtml -
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2011
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2011
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2011
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http://weather.unisys.com/upper_air/skew/details.php
http://weather unisys com/upper air/skew/details php
http://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.php -
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http://weather.unisys.com/upper_air/skew/details.php
http://weather unisys com/upper air/skew/details php
http://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.php -
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http://weather.unisys.com/upper_air/skew/details.php
http://weather.unisys.com/upper_air/skew/details.phphttp://weather.unisys.com/upper_air/skew/details.php -
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G i O i l E i l S lli
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Geostationary Operational Environmental Satellitehttp://www.oso.noaa.gov/goes/http://www.goes.noaa.gov/
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MCC as the mean correlation coefficient
MCE is the mean coefficient of efficiency
MAE is the mean absolute error MAPE is the mean absolute percentage error
RMSE is the root mean square error
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El Nino
LaNina
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Halide and Ridd, 2008
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Bersama ..Kita bisa!
dan tentu sajalebih cepat!
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