Comparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Peru

Simple item page
dc.contributor.authorAliaga-Nestares, Vannia
dc.contributor.authorDe La Cruz, Gustavo
dc.contributor.authorTakahashi, Ken
dc.coverage.spatialPerú
dc.date.accessioned2023-09-08T20:06:47Z
dc.date.available2023-09-08T20:06:47Z
dc.date.issued2023-04-06
dc.description.abstractMultiple linear regression models were developed for 1–3-day lead forecasts of maximum and minimum temperature for two locations in the city of Lima, on the central coast of Peru (12°S), and contrasted with the operational forecasts issued by the National Meteorological and Hydrological Service—SENAMHI and the output of a regional numerical atmospheric model. We developed empirical models, fitted to data from the 2000–13 period, and verified their skill for the 2014–19 period. Since El Niño produces a strong low-frequency signal, the models focus on the high-frequency weather and subseasonal variability (60-day cutoff). The empirical models outperformed the operational forecasts and the numerical model. For instance, the high-frequency annual correlation coefficient and root-mean-square error (RMSE) for the 1-day lead forecasts were 0.37°–0.53° and 0.74°–1.76°C for the empirical model, respectively, but from around −0.05° to 0.24° and 0.88°–4.21°C in the operational case. Only three predictors were considered for the models, including persistence and large-scale atmospheric indices. Contrary to our belief, the model skill was lowest for the austral winter (June–August), when the extratropical influence is largest, suggesting an enhanced role of local effects. Including local specific humidity as a predictor for minimum temperature at the inland location substantially increased the skill and reduced its seasonality. There were cases in which both the operational and empirical forecast had similar strong errors and we suggest mesoscale circulations, such as the low-level cyclonic vortex over the ocean, as the culprit. Incorporating such information could be valuable for improving the forecasts.es_ES
dc.description.peer-reviewPor pareses_ES
dc.formatapplication/pdfes_ES
dc.identifier.citationAliaga-Nestares, V., De La Cruz, G., & Takahashi, K. (2023). Comparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Peru.==$Weather and Forecasting, 38$==(4), 555-570. https://doi.org/10.1175/WAF-D-21-0094.1es_ES
dc.identifier.doihttps://doi.org/10.1175/WAF-D-21-0094.1es_ES
dc.identifier.govdocindex-oti2018
dc.identifier.journalWeather and Forecastinges_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12816/5452
dc.language.isoenges_ES
dc.publisherAMSes_ES
dc.relation.ispartofurn:issn:1520-0434
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_ES
dc.subjectSynoptic climatologyes_ES
dc.subjectSynoptic-scale processeses_ES
dc.subjectRegression analysises_ES
dc.subjectForecast verification/skilles_ES
dc.subjectNumerical weather prediction/forecastinges_ES
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.05.09es_ES
dc.titleComparison between the Operational and Statistical Daily Maximum and Minimum Temperature Forecasts on the Central Coast of Perues_ES
dc.typeinfo:eu-repo/semantics/articlees_ES

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Aliaga-Nestares_et_al_2023_Weather_and_Forecasting.pdf
Size:
4.16 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Arbitrados