Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis
High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds – the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2013-04-01
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| Series: | Advances in Geosciences |
| Online Access: | http://www.adv-geosci.net/33/41/2013/adgeo-33-41-2013.pdf |
| _version_ | 1818546479501934592 |
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| author | T. Maldonado E. Alfaro B. Fallas-López L. Alvarado |
| author_facet | T. Maldonado E. Alfaro B. Fallas-López L. Alvarado |
| author_sort | T. Maldonado |
| collection | DOAJ |
| description | High mountains divide Costa Rica, Central America, into two main climate
regions, the Pacific and Caribbean slopes, which are lee and windward,
respectively, according to the North Atlantic trade winds – the
dominant wind regime. The rain over the Pacific slope has a bimodal annual
cycle, having two maxima, one in May–June and the other in
August-September-October (ASO), separated by the mid-summer drought in July.
A first maximum of deep convection activity, and hence a first maximum of
precipitation, is reached when sea surface temperature (SST) exceeds
29 °C (around May). Then, the SST decreases to around
1 °C due to diminished downwelling solar radiation and
stronger easterly winds (during July and August), resulting in a decrease in
deep convection activity. Such a reduction in deep convection activity
allows an increase in down welling solar radiation and a slight increase in
SST (about 28.5 °C) by the end of August and early
September, resulting once again in an enhanced deep convection activity, and,
consequently, in a second maximum of precipitation. Most of the extreme events
are found during ASO. Central American National Meteorological and
Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora
(RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with
different socioeconomic stakeholders took place to translate the probable
climate impacts from predictions. From the feedback processes of these
meetings has emerged that extreme event and rainy days seasonal predictions
are necessary for different sectors. As is shown in this work, these
predictions can be tailored using Canonical Correlation Analysis for rain
during ASO, showing that extreme events and rainy days in Central America
are influenced by interannual variability related to El Niño-Southern
Oscillation and decadal variability associated mainly with Atlantic
Multidecadal Oscillation. Analyzing the geographical distribution of the
ASO-2010 disaster reports, we noticed that they did not necessarily agree
with the geographical extreme precipitation event distribution, meaning
that social variables, like population vulnerability, should be included in
the extreme events impact analysis. |
| first_indexed | 2024-12-12T07:53:46Z |
| format | Article |
| id | doaj.art-fc051402863c4c6f9e1fa83f1a35de80 |
| institution | Directory Open Access Journal |
| issn | 1680-7340 1680-7359 |
| language | English |
| last_indexed | 2024-12-12T07:53:46Z |
| publishDate | 2013-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Advances in Geosciences |
| spelling | doaj.art-fc051402863c4c6f9e1fa83f1a35de802022-12-22T00:32:22ZengCopernicus PublicationsAdvances in Geosciences1680-73401680-73592013-04-0133415210.5194/adgeo-33-41-2013Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation AnalysisT. Maldonado0E. Alfaro1B. Fallas-López2L. Alvarado3Center for Geophysical Research, San Jose, Costa RicaCenter for Geophysical Research, San Jose, Costa RicaCosta Rican Electricity Institute, San Jose, Costa RicaNational Meteorological Institute, San Jose, Costa RicaHigh mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds – the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May–June and the other in August-September-October (ASO), separated by the mid-summer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 °C (around May). Then, the SST decreases to around 1 °C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 °C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.http://www.adv-geosci.net/33/41/2013/adgeo-33-41-2013.pdf |
| spellingShingle | T. Maldonado E. Alfaro B. Fallas-López L. Alvarado Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis Advances in Geosciences |
| title | Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis |
| title_full | Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis |
| title_fullStr | Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis |
| title_full_unstemmed | Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis |
| title_short | Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis |
| title_sort | seasonal prediction of extreme precipitation events and frequency of rainy days over costa rica central america using canonical correlation analysis |
| url | http://www.adv-geosci.net/33/41/2013/adgeo-33-41-2013.pdf |
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