Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica
Rainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/4/700 |
| _version_ | 1797617693968302080 |
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| author | Rachel MacKay Altman Ofir Harari Nadya Moisseeva Douw Steyn |
| author_facet | Rachel MacKay Altman Ofir Harari Nadya Moisseeva Douw Steyn |
| author_sort | Rachel MacKay Altman |
| collection | DOAJ |
| description | Rainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwater recharge and hydroelectricity production. We propose a novel model of rainfall in this region, the double-Gaussian model, which uses monthly total rainfall data collected from 1980 to 2020 from two meteorological observation stations. Our model provides an intuitive way of describing the seasonality of rainfall, the inter-annual variability of the cycle, and variability due to the monthly Oceanic Niño Index, ONI. We also consider two alternative models, a regression model with ARMA errors and a Tweedie model, as a means of assessing the robustness of our conclusions to violations of the assumptions of the double-Gaussian model. We found that the data provide strong evidence of an increase/decrease in rainfall in both temporal maxima during La Niña/El Niño (negative/positive ONI) conditions but no evidence of a decade-scale trend after accounting for ONI effects. Finally, we investigated the problem of forecasting future rainfall based on our three models. We found that when ONI is incorporated as a predictor variable, our models can produce substantial gains in prediction accuracy of spring, summer, and annual totals over naive methods based on monthly sample means or medians. |
| first_indexed | 2024-03-11T07:59:26Z |
| format | Article |
| id | doaj.art-1de605278a4544f5af48a2305eb3d8a5 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T07:59:26Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-1de605278a4544f5af48a2305eb3d8a52023-11-16T23:52:18ZengMDPI AGWater2073-44412023-02-0115470010.3390/w15040700Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa RicaRachel MacKay Altman0Ofir Harari1Nadya Moisseeva2Douw Steyn3Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC V5A 1S6, CanadaDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC V5A 1S6, CanadaDepartment of Earth, Ocean and Atmospheric Sciences, The University of British Columbia, Vancouver, BC V6T 1Z4, CanadaDepartment of Earth, Ocean and Atmospheric Sciences, The University of British Columbia, Vancouver, BC V6T 1Z4, CanadaRainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwater recharge and hydroelectricity production. We propose a novel model of rainfall in this region, the double-Gaussian model, which uses monthly total rainfall data collected from 1980 to 2020 from two meteorological observation stations. Our model provides an intuitive way of describing the seasonality of rainfall, the inter-annual variability of the cycle, and variability due to the monthly Oceanic Niño Index, ONI. We also consider two alternative models, a regression model with ARMA errors and a Tweedie model, as a means of assessing the robustness of our conclusions to violations of the assumptions of the double-Gaussian model. We found that the data provide strong evidence of an increase/decrease in rainfall in both temporal maxima during La Niña/El Niño (negative/positive ONI) conditions but no evidence of a decade-scale trend after accounting for ONI effects. Finally, we investigated the problem of forecasting future rainfall based on our three models. We found that when ONI is incorporated as a predictor variable, our models can produce substantial gains in prediction accuracy of spring, summer, and annual totals over naive methods based on monthly sample means or medians.https://www.mdpi.com/2073-4441/15/4/700precipitationCosta Ricastatistical modellingOceanic Niño Indextime trends |
| spellingShingle | Rachel MacKay Altman Ofir Harari Nadya Moisseeva Douw Steyn Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica Water precipitation Costa Rica statistical modelling Oceanic Niño Index time trends |
| title | Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica |
| title_full | Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica |
| title_fullStr | Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica |
| title_full_unstemmed | Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica |
| title_short | Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica |
| title_sort | statistical modelling of the annual rainfall pattern in guanacaste costa rica |
| topic | precipitation Costa Rica statistical modelling Oceanic Niño Index time trends |
| url | https://www.mdpi.com/2073-4441/15/4/700 |
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