Teleconnections between ENSO and rainfall ... - Wiley Online Library

INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. (2018) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/joc.5444

Teleconnections between ENSO and rainfall and drought in Puerto Rico Angel R. Torres-Valcárcela,b* a

b

COSUAM de Puerto Rico, San Juan, Puerto Rico Department of Environmental Sciences, Natural Sciences Faculty, University of Puerto Rico, Río Piedras, Puerto Rico

ABSTRACT: An analytical study was conducted to assess the long-term influence, role, and impacts of El Niño-Southern Oscillation (ENSO) on Puerto Rico’s precipitation patterns and significant moisture deficits (droughts). Detection and attribution was addressed by evaluating local rainfall measures and ENSO-related data to (1) detect ENSO signals and patterns, (2) quantify the magnitude of any impacts, and (3) determine if ENSO may be an important factor for local prediction of future droughts. Data were evaluated at different time periods and two spatial scales (island-wide and internal climate regions of Puerto Rico). Although a signal was detected, it was weak, in both directions, varied regionally, and has inconsequential impacts. No evidence was found for a major control by ENSO over local monthly, seasonal, and yearly rainfall for any climate regions on the island. These results indicate that ENSO is not a main factor causing droughts in Puerto Rico for the study period and thus should not be a factor in predicting the potential for local dry periods or large precipitation deficits in the future. Any presumed teleconnections between Puerto Rico’s dry periods and ENSO are not based on current climatological evidence. Thus, local drought prediction efforts should be focused on finding major causes of local rainfall variation other than ENSO. KEY WORDS

ENSO; teleconnections; local rainfall

Received 10 June 2017; Revised 3 November 2017; Accepted 4 January 2018

1. Introduction The threats of climate change continue to be an increasing concern around the world because of the many potential impacts for humans and ecosystems alike, and also for the level of uncertainty that some impacts may have locally. Although the global climate may change, changes are not necessarily linear or symmetrical and may not uniformly impact every place on Earth in the same direction and magnitude. Although climate studies at small scales can help understand climate phenomena at larger scales, climatological studies of tropical islands remain limited (Torres-Valcárcel et al., 2015). Most assessments of climate change focus on regional and global impacts and thus may lack enough detail to help local efforts in policy and decision making. Small jurisdictions, including small tropical islands, are constantly facing the uncertainty of regional and global low-resolution climate assessments that overlook their particular conditions and physical reality (Torres-Valcárcel et al., 2014). In places where data are lacking for local assessments, it is reasonable to rely on generalized, low-resolution assessments and projections of regional impacts for local policy and decision making. However, in places where accurate, high-density, long-term data are * Correspondence to: A. R. Torres-Valcárcel, COSUAM de Puerto Rico, San Juan, José R. Acosta #380, Roosevelt, Hato Rey Puerto Rico 00918. E-mail: [email protected]

© 2018 Royal Meteorological Society

available to conduct such assessments, failing to conduct local-scale analyses is a wasted opportunity and could lead to development and implementation of pointless contingency plans. The three main climate change threats for small-scale tropical islands are sea level rise, precipitation changes, and increased temperatures (Nurse et al., 2014). Sea level rise and temperature increases are extensively covered in the literature while precipitation has a higher level of uncertainty for impact assessment and future predictions (Bindoff et al., 2013). One of the biggest challenges in climate science is assessing local and regional phenomena that can mask the effects of climate change, because this requires detecting and isolating the impacts of climate change and local/regional phenomena. Detecting local, regional, and global climate signals is a complicated task because long-term variation must be accounted for at each spatiotemporal scale. Major atmospheric events capable of causing a detectable effect over large distances are said to have a ‘teleconnection’ with the places where their effects are detected. One of the most important regional climate signals on Earth is the ‘El Niño-Southern Oscillation’ (ENSO), a regional phenomenon capable of causing intensive atmospheric events impacting large areas of the world. ENSO characterization has changed over time, leading to confusion due to the lack of an operational definition (Trenberth, 1997). However, in any study of climate change, it is reasonable to include the possibility

A. R. TORRES-VALCÁRCEL

of an ENSO-related impact. Yet, assuming the same level of teleconnection at each and every place on Earth would also be misleading, because the ENSO signal varies in magnitude and direction at different spatial and temporal scales. In an area with a strong ENSO teleconnection, Gill et al. (2015) found notable teleconnection asymmetries implying important variations in signal strength and direction by region and sub-seasons. In other words, detecting a strong ENSO warm episode does not imply that its opposite phase (ENSO cool episode) will occur with the same intensity, at the same region or in the same season. The standard way of assessing ENSO’s impacts around the world is through investigating for interdependence relationships between ENSO and local phenomena. Detection and attribution are two key elements in climate science, requiring the statistical identification of a signal (detection) and establishing corresponding causal effects (attribution) (Bindoff et al., 2013). Detecting an ENSO signal may not necessarily imply that it has a controlling or major impact over a particular place in the world. Several studies have previously explored teleconnections between ENSO and Caribbean climate; however, very few have attempted to assess impacts on Puerto Rico’s climate. Torres-Valcárcel et al. (2014) summarized the main findings of published work on Puerto Rico’s precipitation, including those related to ENSO. Although a temperature relationship has been clearly confirmed (Malmgren et al., 1998), precipitation relationships are ambiguous, perhaps because of the combination of the fragmented nature of precipitation, conflicting interpretations of published articles, low-resolution studies, and reliance on generalized assessments about Caribbean teleconnections. During the 2013–2015 drought, local Puerto Rican authorities developed their first ever ‘drought management protocol’. Local preparedness and response were guided by a presumed strong relationship and teleconnection between ENSO and local rainfall, and season forecasts were based in ENSO episodes. However, a key underlying question is whether this local moisture deficit is actually attributable to any ENSO teleconnections. Attribution requires that (1) observations are consistent with expectations based on an underlying causal explanation and (2) observations are inconsistent with alternative explanations (Zwiers, 2014). Unfortunately, existing publications about ENSO’s relationship with Puerto Rico’s rainfall lack enough clarity to attribute drought in Puerto Rico to ENSO, and communicate an ambiguous message to the general audience. Inaccurately assuming a teleconnection when there could be none is misleading can lead to inaccurate decision making, waste of resources and hinders efforts to identify sources of variation that may play a bigger role or be the real cause of significant moisture deficits. Future drought prediction requires assessing different sources of moisture variation and other factors that meet attribution criteria. 1.1.

Study area

Puerto Rico, one of the world’s biodiversity hotspots (Helmer et al., 2002), is located at 18∘ N latitude and 66∘ W © 2018 Royal Meteorological Society

longitude in the eastern part of the Caribbean basin. It is the smallest of the Greater Antilles with a territorial extent of about 180 km wide from east to west, and 60 km from north to south. The island terrain is 53% mountainous, with an east to west Central Mountain Range, and 25% of the land area is plains and 20% hills (Gould et al., 2007). Puerto Rico’s climate is tropical and maritime and is similar to other Caribbean islands with small seasonal temperature variations that decrease with elevation while warmer temperatures and high humidity occur along the coastline (Daly et al., 2003). Puerto Rico’s yearly precipitation cycle has two maxima (bimodal distribution) (Jury et al., 2007) consistent with Caribbean basin and Central America patterns (Curtis and Gamble, 2007; Gamble et al., 2008) with a first peak in May at the beginning of the wet season followed by the ‘mid-summer drought’ (Magaña et al., 1999) and then a second and biggest peak in October–November. Locally, trade winds generally blow from the east to northeast Atlantic and are controlled by topography and local land surface characteristics on synoptically calm days (Velazquez-Lozada et al., 2006; Comarazamy et al., 2013). Orographic effects dominate the island with wetter regions on the northern side of mountains creating orographic precipitation (Malmgren et al., 1998; Comarazamy et al., 2013), keeping the humidity north while shielding the driest south from Atlantic moisture. In addition, other mesoscale phenomena such as sea breezes contribute to local rainfall variation (Carter and Elsner, 1997). 1.1.1. Sources of moisture Puerto Rico has local and synoptic sources of atmospheric moisture for rainfall. The different sources are associated with seasonal and some to regional variations. Locally induced rainfall is related to the combination of daytime wind direction, heat, and moisture. The western part of the island is influenced by local landscape and land cover features and mesoscale processes, while the eastern third is influenced more by synoptic moisture advection (Torres-Valcarcel, 2013). Typical synoptic moisture sources occur in the form of cold fronts from the North American continent during the subtropical winter or dry season (December–April), easterly waves dominate during the subtropical summer or wet season (May–November) while mid- and upper-level troughs are likely to be more frequent during the wet season (summer). As ENSO is a strong climatic variation signal known to cause or be directly associated with extreme weather events around the world (Trenberth, 1997), it is often evaluated as a possible indirect driver or control on weather elsewhere. ENSO is known to limit cyclonic activity in the Atlantic basin and, because many tropical storms and hurricanes form from easterly waves, this leads to the idea that ENSO events may be related to rainfall shortages and droughts. For ENSO to be a driving cause for moisture deficits in Puerto Rico it must cause a detectable and notable reduction in any of the main moisture sources affecting monthly, season, or yearly totals, Int. J. Climatol. (2018)

PR VERSUS ENSO

Table 1. Previous studies of rainfall–ENSO relationships for Puerto Rico. Reference

Period

Data

Method

Malmgren et al. (1998) Gianni et al. (2001)

1901–1995 1951–1980

Surface stations Surface stations

Burnaby test Multivariate analysis, PCA, covariance

Angeles et al. (2007)

1996–2098

Reanalysis grids

Parallel climate model

Jury et al. (2007) Blanco et al. (2007)

1951–1981 1931–2004

Angeles et al. (2010)

1983–2004

Surface stations Regional surface stations (3) Reanalysis grids

Factor analysis Pearson/Mann–Whitney U-test Pearson/RAMS

Climate Prediction Center (2010)

1948–2010

Reanalysis grids

Pearson

April–June 1955–1959; April–June 2000–2004 Vélez-Rodríguez and Votaw (2012) 1972–2012 Stephenson et al. (2014) 1961–2010

Reanalysis grids and surface stations (5)

RAMS

Reanalysis grids Regional surface stations (51)

Pearson Statistics/indexes

Comarazamy and González (2011)

Van Beusekom et al. (2015)

2001–2013

Surface stations (20)

Statistics

This study

1950–2014, 1900–2014

Surface stations

Pearson, Spearman, Kendall, EOF/PCA, odds ratio, multivariate analysis, Fourier analysis

beyond the usual variation. To date, there are no published studies that unambiguously link ENSO to Puerto Rico’s rainfall. 1.2. Previous Puerto Rico: ENSO teleconnection studies Most studies examining links between ENSO and Puerto Rico’s rainfall have found either no relationship or a weak and almost negligible relationship. However, it seems that the identification of a weak link in some work has been misinterpreted, leading to a general belief that ENSO in fact drives local precipitation and is the main cause of local droughts. This section illustrates how published articles and official government information may have led to confusion. Malmgren et al. (1998) was the first long-term local teleconnection study directly examining the relationship between Puerto Rico’s temperature and rainfall and ENSO, using data from surface stations. The study evaluated © 2018 Royal Meteorological Society

Findings No relationship (annual) No relationship strength computed for Puerto Rico (annual) Associated ENSO with vertical wind shear impacting rainfall in the Caribbean Positive relationship Non-significant relationship (annual) Excluded ENSO as factor for Caribbean summer rainfall bimodal behaviour No relationship (10 months) Moderate precipitation relationship (2 months) Positive and negative relationship maps Discussed ENSO’s positive effects around the Caribbean −1.1% (annual) Excluded ENSO as driving factor for the Caribbean Includes ENSO as factor for Caribbean summer rainfall bimodal behaviour/excluded ENSO driving local rainfall trends Non-significant/weak See results and conclusions sections

annual timescales for the entire island from 1901 to 1995 and although it did find evidence of a significant statistical relationship between ENSO and temperature, it found ‘no evidence’ of a relationship between ENSO and total annual rainfall (Table 1). The spatial and temporal scale of this study left questions unanswered about seasonal and monthly dynamics and relationships in subregions of Puerto Rico. Further studies explored ENSO impacts at larger scales in the Caribbean using reanalysis grids or combining them with surface station data detecting a little influence over Puerto Rico’s rainfall, although some others were interpreted as if they effectively attributed ENSO a major role. While some of the studies deducted conclusions form Caribbean basin analysis, others focused on internal regions of the island without drawing categorical conclusions about ENSO’s teleconnection in Puerto Rico. Int. J. Climatol. (2018)


Figure 1. CPC ENSO warm episode worldwide teleconnection map for June–August (http://www.cpc.noaa.gov/products/analysis_monitoring/ impacts/cold.gif, accessed 13 February 2016). [Colour figure can be viewed at wileyonlinelibrary.com].

Jury et al. (2007) was the second long-term study including data from Puerto Rico using regional surface stations in the Caribbean basin from 1951 to 1981 evaluating annual and monthly scales. They found mostly a positive rainfall relationship with ENSO (warmer temperatures associated with higher rainfall) except in the southeast during September, October, and November. They also found a strong positive significant relationship with warm ENSO in Puerto Rico for two out of the seven evaluated stations but no seasonal or internal regions of the island were assessed. Giannini et al. (2000) is a frequently cited publication in the Caribbean that studied stations around the whole Caribbean basin and reported a mixture of positive and negative relationships between ENSO and rainfall in Puerto Rico. However, this work used the Oceanic Niño Index (ONI) 3.0, assessed annual timescales, did not specify which stations or the number of stations used from Puerto Rico, and did not report any values, probabilities, or quantities specifically for Puerto Rico. However, Giannini et al. (2000) remains highly cited in local studies as supporting a negative teleconnection between ENSO and rainfall in Puerto Rico (e.g. Comarazamy and González, 2011) while discussing ENSO’s positive effects around the Caribbean just as Enfield and Alfaro, 1999; Giannini et al., 2001; Taylor et al., 2002; Chen and Taylor, 2002. Giannini et al. (2001) followed up with another Caribbean basin analysis from 1951 to 1980 using monthly data and ONI 3.0; however, they did not specify the number of stations used or evaluate any internal © 2018 Royal Meteorological Society

regions in Puerto Rico. This study reported opposite effects in only one station on the island with positive ENSO effects during the dry season (March–April) and just another station with negative ENSO effects during the wet season (September–October). Taylor et al. (2002) is also frequently cited for their work using the hybrid data set (Magaña) for the Caribbean basin from 1958–1998 and ONI 3.0. However, this study explicitly acknowledged that the data they used was only representative of large-scales patterns and not of smaller scales were orography is important, such as the case of Puerto Rico. This study found gridded rainfall anomalies around the Caribbean including Puerto Rico for the early rainfall season (ERS) months (May, June, and July) but no actual rainfall estimates were generated directly for the island or its internal regions. Van Beusekom et al. (2015) cited Giannini et al. (2000) in their work examining ENSO controls over Caribbean rainfall bimodal behaviour, despite the fact that Angeles et al. (2010) had already excluded ENSO as a potential factor controlling Caribbean summer bimodal behaviour. Van Beusekom et al. (2015) also ruled out ENSO as a driving factor in their short-term study in northeastern Puerto Rico, just as Blanco et al. (2007) had concluded in their regional study of a small watershed in the southwest corner of the island. More recently, Hosannah et al. (2017) suggested a relationship between ENSO and precipitable water for reanalysis grid data over Puerto Rico for the 2015 drought. In summary, while Caribbean basin and grid-based studies have been used or cited as if they Int. J. Climatol. (2018)

PR VERSUS ENSO

Figure 2. CPC ENSO reanalysis grids worldwide teleconnection map for June–August (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/ ENSO/regressions/diag.prec.regr.JJA.png, accessed 22 February 2016). [Colour figure can be viewed at wileyonlinelibrary.com].

have established ENSO teleconnection with Puerto Rico’s rainfall, two subregional studies (Blanco et al., 2007; Van Beusekom et al., 2015) found no relationship. Finally, conflicting information from the Climate Prediction Center (CPC) regarding Puerto Rico’s teleconnection with ENSO have not clarified the issue. Two official CPC maps show contradicting information regarding ENSO’s teleconnection with local rainfall for the same monthly period from June to August during ENSO warm episodes. A worldwide ENSO teleconnection map shows increased temperature and decreased precipitation relationship in Puerto Rico from June to August during ENSO warm episodes (Figure 1) while a 2010 map shows no rainfall relationship in Puerto Rico for the same period (June–August) during an ENSO warm episode (Figure 2). In addition, a National Weather Service technical study by Vélez-Rodríguez and Votaw (2012) reported a weak negative annual rainfall ENSO relationship in Puerto Rico and also a stronger positive relationship with © 2018 Royal Meteorological Society

precipitable water. Lastly, Stephenson et al. (2014) did not consider ENSO as a variable in their study for the Caribbean basin. The weak relationship detected between ENSO and Puerto Rico’s rainfall in some studies, combined with Caribbean generalized assessments and the fact that warm ENSO events have been associated with low hurricane activity in the Atlantic due to increased vertical wind shear (Angeles et al., 2007), seems to have led many to believe that hurricanes and tropical storms are main sources of rainfall in Puerto Rico, and thus an ENSO control on hurricanes and tropical storms drives drought in Puerto Rico. This requires an implicit assumption that extreme events are the main source of atmospheric moisture, ignoring additional sources of variation such as the abundant local rainfall generated by the local mountains and other boundary layer phenomena. The ‘ENSO controls local rainfall’ dogma, which is based on conflicting information, misleads local officials who are Int. J. Climatol. (2018)


Figure 3. San Juan NWS climate zones. NC = Northern Coasts; NS = Northern Slopes; WI = Western Interior; EI = Eastern Interior; SS = Southern Slopes; SC = Southern Coasts. http://www.srh.noaa.gov/images/sju/climo/ClimateZones.jpg (accessed July 28 2016).

Table 2. Rainfall statistics for Puerto Rico’s Climate Regions, 1950–2014. Region

Puerto Rico (total) Northern Coasts Northern Slopes Western Interior Eastern Interior Southern Slopes Southern Coasts

No. of Annual stations total rainfallb (inches) 141a 19 10 36 23 30 15

67.26 64.15 67.13 81.54 75.55 64.95 37.08

Seasonal total rainfallb (inches) Dry

Wet

17.87 20.95 19.59 21.56 24.11 14.28 7.01

48.99 43.56 46.38 60.92 58.91 48.07 28.86

Monthly average rainfallc (inches)

5.36 5.01 5.29 6.52 5.72 5.13 2.69

a Registered

NOAA stations, 133 used in regional computations, 8 minor island stations excluded. b Values are trimmed means (Tmean). c Averaged monthly Tmean.

responsible for preparedness and responses to dry and wet periods. The purpose of the work reported in this article is to clarify and evaluate the role of ENSO as a potential controlling factor for Puerto Rico’s rainfall, in particular the potential role of ENSO in significant moisture deficits in Puerto Rico leading to local droughts. This study analyses data with several methods at relevant spatial and timescales in order to answer specific questions about the possible existence and potential impacts of a teleconnection and also suggests an analytical framework for evaluating teleconnections leading to local decision making based on quantified impacts, if any. Study questions are (1) Is there an attributable teleconnection between ENSO and Puerto Rico’s rainfall? (2) What is the magnitude of any teleconnection? (3) What are ENSO’s impacts on Puerto Rico’s rainfall, if any? (4) Can significant dry periods and moisture deficits leading to local droughts in Puerto Rico be attributable to ENSO’s occurrence? Study null hypotheses are (1) ENSO controls rainfall patterns in Puerto Rico and (2) ENSO causes significant moisture deficits in Puerto Rico leading to local © 2018 Royal Meteorological Society

droughts. Study objectives are to (1) detect and measure ENSO’s signal in Puerto Rico’s rainfall record, (2) assess ENSO’s level of control over Puerto Rico’s rainfall, (3) determine if ENSO is an important factor causing significant moisture deficits leading to droughts in Puerto Rico, and (4) evaluate if ENSO can be a predictor of future significant moisture deficits leading to droughts in Puerto Rico.

2. Materials and methods Climate science seeks to (1) uncover atmospheric patterns in the historical record, (2) detect signals and changes, (3) assess magnitude of signals and changes, and (4) attribute cause and effect. The objectives of this study are to (1) detect ENSO signals in Puerto Rico’s rainfall record, (2) measure the magnitude of any detected signal, and (3) draw conclusions about ENSO’s role in the island’s rainfall and in moisture deficits leading to droughts. Teleconnections were tested using common climate methods at different timescales (annually, seasonally, and monthly), time periods (1950–2014 and 1900–2014), and spatial scales (island total and internal regions). Most previous studies have relied on using a limited number of stations with the most complete long-term records, to ensure data continuity avoiding data gaps. In this work, the data were not adjusted or transformed. Torres-Valcárcel et al. (2014, 2015) used a similar methodology in previous climate studies in Puerto Rico. However, in this study, regional and seasonal data were aggregated by averaging monthly totals of all existing stations and data points from the same region and same season at a given time, ignoring missing values. Ignoring missing values produces a dryer climatology, but this must be balanced against the fact that only using a limited number of stations with complete data also produces unrepresentative rainfall data for a given region and a given time. Here, long-term monthly rainfall data from Puerto Rico surface rain-gage stations from the National Oceanic and Atmospheric Administration (NOAA) Int. J. Climatol. (2018)

PR VERSUS ENSO

Figure 5. 1950–2014 Puerto Rico internal regions seasonal rainfall scatter plots. (a) Wet season. (b) Dry season. Figure 4. 1950–2014 Puerto Rico internal regions seasonal rainfall Wishker plots. (a) Wet season. (b) Dry season. [Colour figure can be viewed at wileyonlinelibrary.com].

surface stations from 1900 to 2014 were aggregated for total annual rainfall and sub divided between dry season or winter (December–April) and wet season or summer (May–November). Regional data were summarized into NOAA’s local National Weather Service climate regions (Figures 3–5) by aggregating and averaging monthly totals (Table 2). CPC monthly oceanic Niño index from region 3.4 (ONI 3.4) from 1950 to 2014 was used for the study along with precipitation totals at different timescales (monthly, seasonal, and annual). For longer-term analysis, the Southern Oscillation index (SOI) from 1876 to 2016 from the Australian Bureau of Meteorology (ABM) and Atlantic sea surface temperatures (SST) and Pacific (SST) data from 1870 to 2016 from NOAA were used. SOI is a barometric index developed from pressure differences between Tahiti and Darwin, known to be an indicator of ENSO intensity (ABM), its negative relationship with ENSO was used for the longer-term evaluation (Figure 6). Monthly temperature indexes (ONI and SOI) were averaged to get annual values. To maximize ENSO and local rainfall signal detection, several valid and traditional interdependence testing methods [Pearson, Spearman, and Kendall] were applied at © 2018 Royal Meteorological Society

different time and spatial scales. Pearson (rxy ) is a parametric test widely used in science, including Earth Sciences and Atmospheric Sciences, and by the Intergovernmental Panel for Climate Change (IPCC) and government agencies such NOAA and the United States Geological Survey (USGS). Spearman (rrank ) and Kendall t (rt ) are less popular, but are nonetheless robust and resistant nonparametric tests. Empirical orthogonal function analysis (EOF)/principal components analysis (PCA) (Bjornsson and Venegas, 1997) another widely used method was also conducted to further test any teleconnection hypothesis. Discrete operational intervals of ENSO (≤−0.5; neutral; ≥0.5) as defined by CPC and SOI (7) as defined by the ABM were analysed using Chi square (McHugh, 2013). Rainfall estimation was performed only for significant values detected by any test at the 0.05 significance level (95% confidence interval). Wilks (2006) provides detailed description and explanations of the methods and the corresponding functions and equations.

3. 3.1.

Results Island-wide results

For the spatial and temporal scales included in this study, there was no evidence of ENSO as a major control over rainfall in Puerto Rico (Table 3). Interdependence tests for Int. J. Climatol. (2018)


Figure 6. 1900–2014 Puerto Rico seasonal rainfall standardized anomalies versus SOI standardized anomalies. (a) Wet season. (b) Dry season. Table 4 shows correlation results.

annual rainfall and ONI 3.4 from 1950 to 2014 for the entire island did not yield any statistically significant relationships (Figure 7). The dry and wet season island-wide tests also yielded no significant relationships 1950–2014. In a longer-term analysis, with data from 1900 to 2014, local rainfall showed a stronger relationship with Atlantic SST than with Pacific SST and SOI. SOI interdependence tests from 1900 to 2014 were also not significant for annual and dry season rainfall. A weak statistically significant signal was detected for the wet season, representing quantities under an inch (Table 4). Long-term EOF/PCA analysis from 1900 to 2014 show that Puerto Rico’s annual rainfall and Atlantic SST mostly contributed to the first mode while SOI was heavily represented in the second mode (Table 5). This high level of orthogonality represents a high degree of independence thus no relationship between local rainfall and the Pacific © 2018 Royal Meteorological Society

variables of SOI/ENSO and SST. Seasonally, the Atlantic SST again dominated the first mode and SOI the second mode, Puerto Rico’s dry season rainfall dominated the third mode contributing with 89% of the variation (Figure 8). The Atlantic SST annual cycle has been identified as a major source of regional variation capable of driving inter-tropical convergence zone (ITCZ) dynamics and even modifying the North Atlantic Oscillation (NAO) (Xie and Carton, 2004). Annual and seasonal analysis shows that although Pacific influences have been detected over the Caribbean basin as a whole (Malmgren et al., 1998; Giannini et al. (2000); Giannini et al. (2001); Taylor et al., 2002; Chen and Taylor, 2002; Wu et al., 2007), Puerto Rico’s rainfall responds more to the dominant Atlantic Ocean conditions driven by SST and the Atlantic Multidecadal Oscillation (AMO) (Stephenson et al., 2014) and Int. J. Climatol. (2018)

PR VERSUS ENSO

Table 3. Puerto Rico seasonal and monthly rainfall ENSO detection test results, 1950–2014. Test

Annual

Seasonal Dry

rp

rp %

−0.124

(−) 1.5

p

0.327

rs

−0.154

rs %

(−) 2.4

p

0.221

rk

−0.099

rk %

p

Monthly

Remarks

Wet

0.069 −0.220 May 0.275 Sep −0.275 Oct −0.249

0.48 (−) 4.84 May (+) 7.5 Sep (−) 7.6 Oct (−) 6.2 0.585 0.078 May 0.027 Sep 0.027 Oct 0.045 0.034 −0.192 May 0.286 Aug −0.336 Sep −0.248 Oct −0.291

0.11 (−) 3.69 May (+) 8.2 Aug (−) 11.3 Sep (−) 6.2 Oct (−) 8.5 0.789 0.125 May 0.021 Aug 0.007 Sep 0.047 Oct 0.019 0.023 −0.125 May 0.201 Aug −0.230 Sep −0.171 Oct −0.197

Positive May Negative September and October

Positive May Negative August, September, and October

Positive May Negative August, September, and October

(−) 1.0 0.05 (−) 1.57 May 4.1 Aug (−) 5.3 Sep (−) 2.9 Oct (−) 3.9 0.246 0.790 0.143 May 0.021 Aug 0.008 Sep 0.048 Oct 0.023

rp = Pearson; rs = Spearman; rK = Kendall.

to atmospheric pressure driven by the NAO (Malmgren et al., 1998; Jury et al., 2007). The analysis of a shorter-term record, with monthly rainfall data from 1950 to 2014, yielded statistically significant positive and negative relationships with ENSO (Table 6). May, the very beginning of the wet season (ERS), had a significant positive relationship (rainfall increase) with ENSO for the whole island and all internal regions. August, September, and October or late rainfall season (LRS) had a significant negative relationship (rainfall decrease) with ENSO for the entire island. This opposite seasonal response was also detected slightly in the results for the only two weather stations given in Giannini et al. (2001) (figure 4). September was the month with the largest rainfall reductions (around 1 in. less) coincident with ENSO. The contrasting response to ENSO in ERS © 2018 Royal Meteorological Society

and LRS may be related to different dynamics for each sub-season (Gouirand et al., 2012). ERS seems dominated by two major moisture sources, the end of westerly cold fronts season and the beginning of the easterly waves season, while LRS is dominated by the intensification of easterly waves and the potential peak of upper-level troughs. 3.2.

Regional analysis

In general, the north of the island is more sensitive to ENSO than the south, in terms of the number of months with ENSO relationship detections. Most climate regions did not have significant results for the seasonal interdependence tests (Table 7). Only the Kendall t-test detected a significant negative signal: this was in the Western Interior and had a correlation percentage of only 2.9% representing a reduction in rainfall of −0.53 in./season. The seasonal and regional EOF/PCA 1950–2014 rainfall analysis also had results that indicated no significant ENSO effect by climate regions. The regional differences were dominated by the first mode (61% dry season; 68% wet season), with an average contribution of 16% for each season, while ENSO contributed under 0.1 and 1% for each season, respectively. The second mode was dominated by ENSO, with over 94% contribution in each season, and a seasonal analysis resulted in near perfect orthogonality of regional rainfall with ENSO (Figure 9). The effects of ENSO that were detected are slightly negative island-wide (−2.4 in. year−1 ) (Table 6). Meanwhile significant negative relationships varied by region and averaged less than 1 in. month−1 per region. Regional impacts represented a net decrease of −1.73 in. year−1 (Figure 10). The biggest regional deficit was detected in the Northern Coasts with −1.45 in. year−1 , while the deficit in the rest of the regions was under 1 in. (Table 7). For context, the average annual rainfall in Puerto Rico is 67.26 in. year−1 (Table 2). Most internal regions responded negatively to ENSO during August but the highest impact was detected during September, the only month that averaged reductions of 1 in. per region. In general, regional negative impacts progressively decrease from August to September and October. December impacts were only detected in the Northern Coasts. Net positive increases with ENSO were detected in the Eastern Interior and Southern Coasts (Table 8). The Northern Coasts region was the most sensitive to ENSO, with rainfall reductions during four different months (August, September, October, and December) while the Southern Coasts and Eastern Interior only had reductions during August. However, the reductions were minimal (1 in. month−1 or less) and these magnitudes are in no way sufficient to cause droughts in Puerto Rico, especially if a strong positive increase has already occurred in May.

4.

Discussion and conclusions

The results of the analyses presented in this study clearly show that an ENSO signal is not detected in annual rainfall Int. J. Climatol. (2018)


Figure 7. 1950–2014 island-wide ENSO monthly rainfall impacts. [Colour figure can be viewed at wileyonlinelibrary.com].

Table 4. Annual and seasonal rainfall attribution results, Puerto Rico 1900–2014. Region

Annual rainfall

Dry season rainfall (r%/p)

Wet season rainfall (r%/p)

Rainfall impacts (in.)

Atlantic SST

Not significant

Not significant

N/A

Pacific SST

Not significant

Not significant

SOI

Not significant

Not significant

13.7%/0.000 (P) 15.0%/0.000 (S) 6.7%/0.000 (K) 5.3%/0.014 (P) 5.0%/0.016 (S) 2.3%/0.017 (K) 5.1%/0.015 (P) 5.4%/0.012 (S) 2.3%/0.016 (K) 6.8%/0.005 (C)

N/A

(−) 0.25/season (l) (−) 0.25/season (nl) (−) 0.26/season (np)

P = Pearson; S = Spearman; K = Kendall, C = Chi square; l = linear regression, nl = nonlinear regression, np = nonparametric regression. (−) = Because SOI index is opposite of ENSO the positive interdependence between Puerto Rico’s rainfall and SOI truly represents a negative relationship with ENSO.

Table 5. Annual and seasonal rainfall EOF/PCA results, Puerto Rico 1900–2014. Time period

First mode EOF 1900–2014

Second mode EOF 1900–2014

Comments/remarks

PR

Atl

SOI

PR

Atl

SOI

Annual

51.46%

44.39%

4.15%

0.58%

13.36%

86.07%

SOI dominates second mode overwhelmingly

Seasonal Dry

2.06%

38.83%

0.70%

3.11%

0.77%

43.15%

Atlantic SST dominated the first mode; SOI dominated the second mode, PR dry dominated the third mode

Wet

20.40%

36.90%

1.11%

2.94%

1.20%

48.83%

PR = Puerto Rico’s rainfall; Atl. = Atlantic SST


Int. J. Climatol. (2018)

PR VERSUS ENSO

(b)

Pac AVE

1

0.75 At AVE

0.25 PR Total 0 –0.25

F2 (34.33 %)

F2 (33.20 %)

0.5

(c)

SOI AVE

1

1

0.75

0.75

0.5

0.5

0.25

PR Total

0 –0.25

F2 (24.81 %)

(a)

–0.25

At AVE

–0.5

–0.75

–0.75

–0.75

–1 –0.5

–0.25

0

0.25

0.5

F1 (47.18 %)

0.75

1

At Dry Ave At Wet Ave

0

–0.5

–1 –0.75

PR Dry Total PR Wet Total

0.25

–0.5

–1

SOI Wet Ave SOI Dry Ave

–1 –1 –0.75

–0.5

–0.25

0

0.25

F1 (46.80 %)

0.5

0.75

1

–1 –0.75

–0.5

–0.25

0

0.25

0.5

0.75

1

F1 (37.41 %)

Figure 8. 1900–2014 annual and seasonal EOF/PCA results. (a) Puerto Rico annual rainfall, Atlantic average SST, and Pacific SST. (b) Puerto Rico annual rainfall, Atlantic average SST, and SOI. (c) Puerto Rico seasonal rainfall, Atlantic seasonal SST, and seasonal SOI. Seasons were based on Puerto Rico’s annual cycle. [Colour figure can be viewed at wileyonlinelibrary.com].

Table 6. Summary of ENSO-related rainfall impacts and timescales, Puerto Rico 1950–2014. Time frame analysis Annual

Seasonal

Monthly

Findings/comments/impacts None island-wide/not significant None regionally/not significant None island-wide/not significant Mostly none regionally Significant in wet season at Western Interior (3%)/−0.53 in./season May +1.68 in. month−1 August −0.77 in. month−1 September −1.1 in. month−1 October −0.93 in. month−1

around the island, is weakly detected seasonally, and minimally detected monthly in Puerto Rico’s climate regions. ENSO is slightly related to an island-wide rainfall increase during May and to varying small regional decreases during August, September, October, and December (Figure 11). The rainfall impacts that occur in association with ENSO are not large enough on their own to cause a major moisture deficit or drought in Puerto Rico. The top ten driest years in Puerto Rico’s record from 1950 to 2014 (Table 9) average 51.7 in. year−1 , representing a 24% reduction in total rainfall, while the driest year (1967) had a 34% reduction compared to average annual totals. In a worst-case scenario, where no positive increases occurred during May related to ENSO, and negative impacts occur in August, September, and October, the island-wide rainfall related to ENSO represents a 4.1% reduction from annual totals and a reduction of 5.7% on seasonal rainfall. Regionally ENSO’s most negative impacts occur on the Northern Coasts, representing a 4.5% reduction in annual rainfall and 6.7% reduction in seasonal rainfall. However, water reservoirs are located on the slopes and in interior regions of the island, so coastal © 2018 Royal Meteorological Society

rainfall contributions and deficits represent minor inconveniences in terms of water availability. The evidence provided here suggests little to no control of ENSO over Puerto Rico’s sources of rainfall moisture. First, mesoscale sources are dominated by daytime wind direction controlled by the North Atlantic subtropical jet, local topography, landcover types, and daytime heat and moisture. Second, during summer or wet season (May–November) easterly waves transit closer to the island when the ITCZ migrates north from the equator. Easterly waves are originated from boundary layer interactions in the Saharan Desert separately from Atlantic conditions (http://www.aoml.noaa.gov/hrd/tcfaq/A4.html) and their quantity has little annual variation (around 60 year−1 ) and although intensity may vary this source of moisture is independent from ENSO. Furthermore, Saharan dust comprises the second most prevalent air mass in the Caribbean with 20%, following tropical humid with 66% while mid-level dry air incursions from the US mainland account for the remaining 14% and dominate even during ENSO phases (Dunion, 2011). Third, the main dry season or winter (December–April) synoptic source are North American cold fronts regulated by the NAO and Rossby wave breaking (RWB) events. A strong NAO positive phase drives North America’s continental moisture away from the subtropics while during a NAO negative phase, extratropical moisture travels further south and closer to the Caribbean. Fourth, RWB events bring moisture from the equatorial tropics to the subtropics (Homeyer and Bowman, 2013) and are so dominant that they limit tropical cyclone activity in the Atlantic more than ENSO (Zhang et al., 2017). RWB events are also a source for upper-level potential vorticity streamers (upper-level troughs) (Leroux et al., 2013) and cut-offs (Wernli and Sprenger, 2007). Upper-level troughs can induce mesoscale convective systems (Fischer et al., 2017) and produce rainfall. Other Atlantic moisture sources are more closely related to Puerto Rico’s rainfall than ENSO (Gouirand et al., 2012). Tropical plumes have been related to atmospheric rivers (Fröhlich et al., 2013) and can also bring synoptic Int. J. Climatol. (2018)


Table 7. ENSO analyses by region, Puerto Rico 1950–2014. Region

Annual rainfall

Seasonal rainfall (r%/p)

Monthly rainfall

Detection test


Not significant Not significant Not significant Not significant Not significant Not significant Not significant

Not significant Not significant Not significant 2.9%/0.044 wet season (K) Not significant Not significant Not significant

May + Aug −, Sep −, Oct − May + Aug −, Sep −, Oct −, Dec − May + Aug −, Sep −, Oct − May +, Sep −, Oct − May +, Aug − May + Aug −, Sept −, Oct − May + Aug −

P,S,K Aug (S,K) P,S,K Dec (S,K) P,S,K Sep (S,K) P,S,K P,S,K P,S,K Sep (P) P,S,K S,K

P = Pearson; S = Spearman; K = Kendall.

(b)

Variables (axes F1 and F2: 75.60 %)

Variables (axes F1 and F2: 82.37 %)

1

1

0.75

0.75

0.5

0.5

NC

0.25

F2 (13.91 %)

F2 (14.52 %)

(a)

NS EI WI 0

SC

SS

EI

0.25

NSSS NC SC WI

0

–0.25

–0.25

–0.5

–0.5

–0.75

ONI

–0.75 ONI

–1

–1 –1

–0.75

–0.5

–0.25

0

0.25

0.5

0.75

1

–1

–0.75

–0.5

F1 (61.08 %)

–0.25

0

0.25

0.5

0.75

1

F1 (68.46 %)

Figure 9. EOF/PCA results. (a) Dry season climate regions first versus second mode. (b) Wet season climate regions first versus second mode. [Colour figure can be viewed at wileyonlinelibrary.com].

2

1.5

1

Inches

0.5

0

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

–0.5

–1

–1.5 Northern Coasts

Northern Slopes

Western Interior

Eastern Interior

Southern Slopes Southern Coasts

2

Figure 10. ENSO 1950–2014 monthly rainfall impacts on Puerto Rico climate regions. [Colour figure can be viewed at wileyonlinelibrary.com].



PR VERSUS ENSO

Table 8. Net impacts of ENSO on monthly rainfall by climate region, Puerto Rico 1950–2014. Region

Total positive impacts (in. year−1 )

Total negative impacts (in. year−1 )

Net impacts (in. year−1 )

1.68 (May) 1.46 (May) 1.58 (May) 1.99 (May) 1.92 (May) 1.77 (May) 1.15 (May)

−2.79 (Aug, Sep, and Oct) −2.91 (Aug, Sep, Oct, and Dec) −2.20 (Aug, Sep, and Oct) −2.47 (Sep and Oct) −1.32 (Aug) −1.94 (Aug and Sep) −0.78 (Aug)

−1.11 −1.45 −0.62 −0.48 +0.60 −0.16 +0.38


Figure 11. Climate regions monthly rainfall ENSO-detected impacts. Figures to the left show total rainfall for the month, figures to the right show rainfall actual impacts. May (a, b), August (c, d), September (e, f), October (g, h), and December (i, j). Uncoloured regions on the right figure mean no significant statistics at 0.05. [Colour figure can be viewed at wileyonlinelibrary.com].




Table 9. Driest years in Puerto Rico, 1950–2014 (Source: San Juan National Weather Service, 2015). Year

Inches

Average ONI

Dry season

Dry ave ONI

Wet season

Wet ave ONI

1967 1994 1997 1976 1991 2015a 1957 1973 2000 1953

44.31 46.79 49.52 49.91 50.50 51.64 53.49 54.93 58.03 58.34

−0.250 0.475 1.125 −0.031 0.650 1.26 0.908 −0.567 −0.892 −0.016

10.30 13.39 13.41 14.82 15.18 – 12.45 15.65 12.85 13.51

−0.40 0.38 0.30 −0.60 0.48 0.88 0.54 0.30 −1.22 0.64

33.99 32.93 36.49 35.06 36.17 – 40.94 39.10 44.67 47.08

−0.14 0.54 1.71 0.33 0.77 1.53 1.17 −1.19 −0.66 0.74

ONI 3.4 > 0.5 values in bold. – = not available at time of the study. a Year out of this study.

moisture. Atmospheric rivers have been linked to 40% of heavy precipitation events in the southeast region of the United States (Mahoney et al., 2016), representing an important source of moisture. The annual cycle of tropical plumes in the Northern Hemisphere closely resemble Puerto Rico’s rainfall annual cycle, with a similar peak during May and a second maxima during October–November (Fröhlich et al., 2013, figure 6). Moreover, eastern North Atlantic RWB events peak in August–November, reaching a maximum in September (Galarneau et al., 2015) similar to the island annual cycle. In addition, the annual cycle of tropospheric streamers and cut-offs also resemble Puerto Rico’s summer minimum rainfall and May peaks and October maximums (Wernli and Sprenger, 2007). These examples highlight the existence of Atlantic basin synoptic phenomena that respond more closely to Atlantic Ocean conditions than to Pacific Ocean phenomena such as ENSO. The results of this study suggest that moisture sources for Puerto Rico’s rainfall are likely present and occurring regardless of ENSO phases, and so the key to discerning the island’s potential for predicting the next moisture deficit or drought will depend on breaking down the rainfall fraction or contribution, seasonality and variability from these other moistures sources. The results of the analyses presented here lead to the following conclusions: (1) The magnitude of the ENSO signal in Puerto Rico’s rainfall record is slightly negative and weak. (2) ENSO has not played a major role in controlling Puerto Rico’s precipitation at any timescale or in any region for the past 114 years. (3) ENSO by itself was not the cause of major moisture deficits leading to local droughts. Negative rainfall anomalies are minimal and represent negligible reductions from seasonal and monthly totals. (4) Any conjectures about ENSO controlling Puerto Rico’s precipitation and causing local droughts are not supported by current scientific evidence and more likely reflect popular perception or lack of awareness. Given that the hypothesized teleconnection between ENSO and rainfall in Puerto Rico showed such variation in time and at such small spatial scales, important theoretical questions remain about what actually constitutes a teleconnection: Is it just the detection of a signal? Is it the © 2018 Royal Meteorological Society

magnitude of the signal? or Is it the tangible impacts of the signal? At what temporal and spatial scales can we assert valid teleconnection attributions? How large should impacts be to be considered a teleconnection? In this particular case of local rainfall on Puerto Rico, detection, magnitude, and impacts of the hypothesized teleconnection are all minimal.

Acknowledgements Thanks to Mr Sigfredo Torres – Gonzalez, hydrologist from the USGS Caribbean Water Science Center for helping with data access and manuscript feedback, and to Cesar Gonzalez-Avilés and Ana L. Torres-Valcárcel from COSUAM de Puerto Rico for their statistical analysis advice. Also thanks to Dr Jorge Ortiz-Zayas from the University of Puerto Rico for providing manuscript feedback, and to Dr José Nieves also from the University of Puerto Rico for his technical advice. Special thanks to my former mentor Dr Jon Harbor from Purdue University for English refinement. I am fortunate to count on all of you, this work certainly would have been much more difficult without your help. All data can be downloaded from NOAA, CPC, and ABM websites. This was unfunded and personally motivated research; the author has no conflicts of interests to declare.

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