| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21d.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34T/45SHU4S | |||
| Repository | sid.inpe.br/mtc-m21d/2021/11.29.13.16 (restricted access) | |||
| Last Update | 2021:11.29.13.16.10 (UTC) simone | |||
| Metadata Repository | sid.inpe.br/mtc-m21d/2021/11.29.13.16.10 | |||
| Metadata Last Update | 2022:04.03.22.27.43 (UTC) administrator | |||
| DOI | 10.1016/j.rsase.2021.100618 | |||
| ISSN | 2352-9385 | |||
| Citation Key | LealGuiDalPalKam:2021:CaStUs | |||
| Title | A new approach to detect extreme events: a case study using remotely-sensed precipitation time-series data  | |||
| Year | 2021 | |||
| Month | Nov. | |||
| Access Date | 2024, May 19 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 7061 KiB | |||
| 2. Context | ||||
| Author | 1 Leal, Philipe Riskalla 2 Guimarães, Ricardo José de Paula Souza e 3 Dall Cortivo, Fábio 4 Palharini, Rayana Santos de Araújo 5 Kampel, Milton | |||
| Resume Identifier | 1 2 3 4 5 8JMKD3MGP5W/3C9JHTG | |||
| Group | 1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 2 3 YYY-CGCT-INPE-MCTI-GOV-BR 4 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 5 DIOTG-CGCT-INPE-MCTI-GOV-BR | |||
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Evandro Chagas (IEC) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 leal.philipe@gmail.com 2 ricardojpsg@gmail.com 3 fdcortivo@gmail.com 4 rayana.palharini@gmail.com 5 milton.kampel@inpe.br | |||
| Journal | Remote Sensing Applications: Society and Environment | |||
| Volume | 24 | |||
| Pages | e100618 | |||
| History (UTC) | 2021-11-29 13:16:38 :: simone -> administrator :: 2021 2022-04-03 22:27:43 :: administrator -> simone :: 2021 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Version Type | publisher | |||
| Keywords | Extreme event detection Precipitation time-series analysis Brazilian Amazon region Climate change | |||
| Abstract | Detecting and predicting extreme events are of major importance for socioeconomic, healthcare and ecological purposes. This study proposes an alternative model to detect extreme events based on analyses of probability distribution functionffns s (f((X))), called Optimum Probability Distribution Function Searcher Model (Opt.PDF-model). The Opt.PDFmodel involves the optimization of a fitness function between an histogram and a set of theoretical f((X)), and the subsequent evaluation of the Probability Point Function (PPF) of the fittest theoretical (f((X))) to assess threshold values for the classification of extreme events. Any occurrence in the dataset with a PPF value equal to or greater than 90% was considered an extreme event candidate. A satellite-derived precipitation time-series (Climate Hazards Group InfraRed Precipitation with Station data) was used to calibrate and validate the proposed model, with data on accumulated precipitation from more than 30 years (Jan.1981 to Dec.2018) of the Brazilian Amazon region. The proposed method was pairwise cross-validated with two other extreme event models based on Gamma and Gaussian distributions, as applied by the European Drought Observatory of the European Environment Agency. Aditionally, all three extreme event classification models were cross-validated relative to the El Nino Southern Oscillation (ENSO). By means of the Opt.PDF-model, it was possible to evidence two positive temporal trends for the area of study: one for more intense precipitation events, and another for less intense events. The pairwise cross-validation analysis returned specific Kappa's similarity indices, and the highest similarity was observed between the Gamma and the Opt.PDF models (48% for PPF(97.7%)). This analysis indicated that extreme event detection models are highly sensitive to distribution family priors and to threshold definitions. The proposed approach and the results obtained here are potentially useful for climate change warnings, and can be extended to other scientific areas that involve time-series analyses. | |||
| Area | SRE | |||
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > A new approach... | |||
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > A new approach... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
| |||
| 4. Conditions of access and use | ||||
| Language | en | |||
| Target File | leal_new.pdf | |||
| User Group | simone | |||
| Reader Group | administrator simone | |||
| Visibility | shown | |||
| Read Permission | deny from all and allow from 150.163 | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3F3NU5S 8JMKD3MGPCW/46KUATE | |||
| Citing Item List | sid.inpe.br/bibdigital/2013/10.18.22.34 2 sid.inpe.br/mtc-m21/2012/07.13.14.56.38 1 | |||
| Dissemination | PORTALCAPES; SCOPUS. | |||
| Host Collection | urlib.net/www/2021/06.04.03.40 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||