TREND ANALYSIS OF EXTREAM RAINFALL FROM 1982 - 2013 AND PROJECTION FROM 2014 - 2050 IN BANDA ACEH AND MEULABOH
Bibliographic record
Abstract
Abstract. Climate change is a global phenomenon that currently and seriously impacts the environment. Increasing concentrations of greenhouse gases have caused changes in extreme climate events. We have studied index rainfall extream trend at two meteorological stations of Sultan Iskandar Muda in Banda Aceh and Cut Nyak Dien in Meulaboh from 1982-2013. Daily rainfall data were processed using software of RClimDex to obtain the extreme rainfall index. Such indexes are extreme climate index set by the expert team for Climate Change Detection Monitoring and Indices (ETCCDMI) including of maximum 1-day and 5-days precipitation amount (RX1day and RX5day), total annual precipitation (PRCPTOT), consecutive dry days (CDD), consecutive wet days (CWD), very wet days (R95p), extremely wet days (R99p) and heavy precipitation days (R20mm). Based on our study, we found that the PRCPTOT tend to decrease, whereas occurances of RX1day and RX5day increase. The Banda Aceh station which has a monsoonal pattern is charaterized by increasing in R95p and R99p as well as but decreasing in R20mm. The CWD and CDD tend to accumulate at once. The Meulaboh station that has the type of equatorial rain show decreasing trend in R95p and R99p, but increasing trend in R20mm. The CWD and CDD occur within some days. The projection Representative Concentration Pathways (RCP) 4.5 and 8.5 from 2014-2050 showed an increasing pattern frequency of rain in Banda Aceh and a decreasing pattern in Meulaboh. Keywords: Trend, Extream Climate Index, ProjectionREFERENCE Lutgens. F.K. and Tarbuck. E.J. 2004. The Atmosphere: An Introduction to Meteorology. Pearson Prentice Hall. New Jersey.Ratag, M.A., Halimurrahman, Juaeni, I., Siswanto, B., dan N., Adikusumah. 2002. Perubahan Iklim : Basis Alamiah dan Dampaknya. Bandung, Lembaga Penerbangan dan Antariksa Nasional.IPCC, 2013. Climate Change. World Meteororogical Organization. Switzerland.Nuraini, Ida Sartika. 2014. Analisis dan Proyeksi Trend Temperatur dan Curah Hujan untuk Mendeteksi Perubahan Iklim (Studi Kasus Provinsi Kalimantan Barat). STMKG, Tangerang Selatan.Sulistya, W., Swarinoto, T.S., Zakir, A.,Riyanto, H., dan B., Ridwan.1998. The Impact of El Nino 1997/98 over Indonesia Region. Jakarta: Jurnal Meteorologi dan Geofisika, No 4, Desember.Zhang, X., and Feng Yang, 2004. RClimDex User Manual. Climate Research Branch, Environment Canada, Downsview, Ontario, Canada.Aldrian, E., 2007 Perubahan iklim global dan dampak terhadap iklim benua mantim di laut dan di daratan Prosiding Jumal Club Tahun 2007.Badan Meteorologi dan Geofisika. ISBN:978-979-1241-11-3
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".