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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