In this paper, we develop an instrumental index based on
historical wind direction observations aimed to quantify the moisture
transport from the tropical Pacific to Central and northern South America at a monthly scale. This transport is mainly driven by the so-called “Chocó
jet”, a low-level westerly jet whose core is located at 5∘ N and 80∘ W. The Chocó jet is profoundly related to the
dynamics of the Intertropical Convergence Zone in the eastern equatorial
Pacific and it is responsible for up to 30 % of the total precipitation in
these areas. We have been able to produce an index for this transport
starting in the 19th century, adding almost a century of data to
previous comparable indices. Our results indicate that the seasonal
distribution of the precipitation in Central America has changed throughout the
20th century as a response to the changes in the Chocó jet, decreasing
(increasing) its strength in July (September). Additionally, we have found
that in general, the relationship between the Chocó jet and the El Niño–Southern Oscillation has been remarkably stable throughout the entire 20th century, a finding particularly significant because the stability of this relation is usually the basis of the hydrologic reconstructions in northern South America.
Introduction
The Northern Hemisphere eastern equatorial Pacific is an interesting area
from a climatological point of view. It is affected by two different low-level jets whose interaction determines the moisture transport towards wide
regions of Central America and northern South America, generating huge
amounts of precipitation and affecting the living of millions of people
(Arias et al., 2015). In the eastern equatorial Pacific, the Intertropical
Convergence Zone (ITCZ) is predominantly located in the Northern Hemisphere
(Wodzicki and Rapp, 2016). In this region, the Southern Hemisphere trade
winds cross the Equator and the change in the sign of the Coriolis term,
facilitated by the coast orientation and the land–sea temperature gradients,
deflects the trades to the east, entering northern South America at
5∘ N as a low-level westerly jet, whose core is located at
the 925 hPa level (Fig. 1a) introducing huge amounts of moisture into the
continent (Poveda and Mesa, 1999, 2000). This jet was first described by
Poveda and Mesa (1999), who named it as the Chocó Jet, the name functioning
both as an acronym for “CHorro del Occidente COlombiano” (Western
Colombian Jet) and as the place name Chocó, one of Colombia's
departments most affected by the moisture advection from the Pacific related
to this jet (Poveda and Mesa, 1999, 2000). In some localities such as
Lloró (5∘30′ N, 76∘32′ W), the large
amounts of moisture transported from the Pacific into the Colombian coast
result in average rainfall ranging from 8000 to 13 000 mm, making this
region one of the rainiest in the world (Murphy, 1939; Trojer, 1958; Arnett
and Steadman, 1970; Meisner and Arkin, 1987; Janowiak et al., 1994; Poveda
and Mesa, 2000; Poveda et al., 2011; Jaramillo et al., 2017; King et al.,
2017). At 80∘ W, the cross section of the zonal wind from
5∘ S to 20∘ N (Fig. 1b) shows the
distinctive characteristics of this system, a jet core located at 925 hPa
and 5∘ N confined to the lower troposphere, with westerlies
restricted to altitudes below 850 hPa. Although the location of the core is
almost constant throughout the year (Poveda and Mesa, 2000; Sakamoto et al.,
2011; Sierra et al., 2018), its intensity has a strong seasonal cycle (Fig. 1c, black line). Minimum velocities at this jet core are found in
February–March (below 1 m s-1), and maximum ones occur in
October–November (6 to 7 m s-1). From May up to
December, the jet is quite active and its relation with the ITCZ seasonal
migration is evidenced by the presence of two relative maxima in June and
October (Fig. 1c).
(a) Average NCEP-NCAR wind vector at 925 hPa for the
period 1981–2010 shading shows the corresponding average GPCCv7
precipitation; (b) 1981–2010 average cross section of the zonal wind from 5∘ S
to 20∘ N at 80∘ W. Positive/negative (westerly/easterly) zonal wind is indicated
by continuous/dashed contours; (c) 1981–2010 average monthly evolution of
the zonal wind at 5∘ N, 80∘ W and 925 hPa (CHOCÓ, black line) and zonal wind
(change of sign) at 15∘ N, 75∘ W and 925 hPa (CLLJ, blue dashed line).
In Fig. 1b a maximum of easterly zonal winds around 10 m s-1 is observed at 15∘ N and 925 hPa. It corresponds to
the Caribbean Low-Level Jet (CLLJ) (Amador, 1998; Poveda and Mesa, 1999;
Poveda et al., 2006; Wang, 2007). This jet also shows a marked seasonal
variation. The absolute value of the zonal wind at 15∘ N,
75∘ W and 925 hPa constitutes a good measure of the
intensity of this jet (Fig. 1c, dashed blue line). At the core of the
CLLJ the absolute value of the wind speed varies between a minimum around 7 m s-1 (October) and a maximum of 14 m s-1 in
July, with a secondary maximum in December and January (12 m s-1).
(a) NCEP-NCAR wind vector at 925 hPa for August 1997. The
black box indicates the area where the index developed in this paper is
defined. (b) Cross section of the zonal wind from 5∘ S to 20∘ N at 80∘ W. (c) Cross section
of the zonal wind from 5∘ S to 20∘ N at 90∘ W. In (b) and (c),
positive/negative (westerly/easterly) zonal wind is indicated by
continuous/dashed contours.
While the location of the core of both jets is rather constant at
inter-annual scales, their relative strength is quite variable and strongly
dependent upon the SST (sea surface temperature) in the tropical Pacific. This dependence is different
in each case. Ultimately, the Chocó jet originates in the Southern
Hemisphere trades; so, the weakening of the trades associated with positive
SST anomalies in the eastern tropical Pacific (El Niño conditions)
results in a weaker Chocó jet (Poveda et al., 2001). On the other hand, the
dependence of the CLLJ with the SST anomalies is season dependent. As
demonstrated by Wang (2007), during the boreal winter, a weak (strong) CLLJ
corresponds to warm (cold) SST anomalies in the tropical Pacific. By contrast, during the boreal summer, a strong (weak) CLLJ is associated with
warm (cold) SST anomalies. In this way, during the boreal winter, warm
(cold) SST anomalies are associated both with weaker (stronger) Chocó jet and the CLLJ. In summer, the modulation of the SST over both jets is the opposite. Warm
(cold) SST anomalies are associated with weak (strong) Chocó jets but strong
(weak) CLLJs. This divergent behaviour results in a major signature on the
distribution of the westerlies or easterlies noticeable at the surface level
and over a large area of the eastern tropical North Pacific. As an example,
Fig. 2 shows the average winds during August 1997, a month with high
positive SST anomalies over the tropical Pacific. The pressure–latitude
cross section of the zonal wind at 80∘ W (Fig. 2b) shows
the consequent weak Chocó jet (although still existing and evidenced by
positive zonal wind at 5∘ N) and an enhanced CLLJ. It is
clearly evidenced that during these episodes, easterlies dominate a large
area in the tropical North Pacific (outlined area in Fig. 2a). Westward of
90∘ W the prevalence of the easterly component is absolute,
even at the surface. By contrast, in August 2010 (Fig. 3), a month of
strong SST negative anomalies in the eastern equatorial Pacific, the
enhanced Chocó jet is quite evident (Fig. 3b) and, most interestingly, in
these cases, the westerlies (predominantly southwesterlies) dominate a wide
area of the tropical Pacific (outlined area in Fig. 3a). Remarkably, the
cross section of the zonal wind at 90∘ W (Fig. 3c) shows
that at the surface the westerlies can reach 14∘ N.
(a) NCEP-NCAR wind vector at 925 hPa for August 2010. The
black box indicates the area where the index developed in this paper is
defined. (b) Cross section of the zonal wind from 5∘ S to 20∘ N at 80∘ W. (c) Cross
section of the zonal wind from 5∘ S to 20∘ N at 90∘ W. In (b) and (c),
positive/negative (westerly/easterly) zonal wind is indicated by
continuous/dashed contours.
From the previous discussion, it is clear that, although the Chocó jet
always blows from the west at its core (925 hPa, 5∘ N and
80∘ W), for the boreal warm season the changes in the
strength of the Chocó jet are concurrent with significant changes in the
distribution of the wind direction over a broad area at the surface. In a
recent review paper, Garcia-Herrera et al. (2018) demonstrated that this
kind of signature in the surface wind field can be exploited to design
indices relying only on wind direction measurements. They also showed that
these indices are highly representative of the moisture advection toward
continental areas. The main advantage of these so-called “directional
indices” is that by design, they only require the knowledge of the wind
direction, a variable that has been routinely measured aboard ships since
the end of the 17th century and avoid the uncertainties associated with the measurement of wind speed for early times (Prieto et al., 2005;
Gallego et al., 2007). As a result of several data recovery projects
(García-Herrera et al., 2005; Allan et al., 2011; Wilkinson et al.,
2011, among others), millions of these early wind observations are today incorporated into the International Comprehensive Ocean-Atmosphere Data Set
(ICOADS) database (Freeman et al., 2017). In its most recent release ICOADS
holds over 456 million individual marine reports, covering the period
1662–2014. The objective of this paper is to develop a new index
representative of the Chocó jet strength by exclusively using the raw wind
direction measurement currently incorporated in ICOADS. As we will show
below, this method provides an extension of almost one century to the current
available indices for this jet.
Number of wind direction observations in a 1×1 grid (May
to November) and the 1800–2014 period available in ICOADS 3.0. Black contour
indicates the area selected to compute the CHOCO-D index (4–15∘ N; 120–80∘ W). The
graph at the bottom-left shows the time evolution of the cumulative number
of wind direction observations inside the selected domain not considering
data taken at moored buoys (note the logarithmic y scale).
The CHOCO-D indexIndex definition
Directional indices are based solely on daily observations of wind direction
and are usually defined as the monthly frequency of wind direction coming
from a given range of angles. For a directional index to be representative,
the climatological feature intended to be quantified must have a noticeable
signature on the wind direction over a wide area at the surface level. We
selected the area 4–15∘ N, 120–84∘ W plus the area 4–9∘ N, 84–77.5∘ W (outlined area in Figs. 2a and 3a) as those
where the change in the distribution of easterlies or westerlies is most
dependent on the relative strength of the two low-level jets active in the
region. Figure 4 shows the selected domain, while shading shows the
1800–2014 cumulative density of ICOADS observations in a 1∘×1∘
grid between May and November. The darkest grid points
noticeable in the equatorial Pacific in Fig. 4 correspond to data taken by
moored buoys, which in this region started operating in June 1986. Some of
these buoys are inside the selected domain, and due to their fixed location,
far from most usual ship's routes, and their high temporal resolution,
they have become the dominant source of data since the 1990s in the selected
domain. In order to maintain the homogeneity in the geographical
distribution of the observed data in the domain, we did not consider data
taken by moored buoys.
(a) Monthly averages (1948–2014) of the NCEP-NCAR zonal
wind at 925 hPa averaged over the 5–7.5∘ N, 90–80∘ W area (blue dashed line) and
monthly averages of the CHOCO-D index for the same period in percentage of days in
a month with prevailing wind flowing from the southwest (black line).
Numbers over the CHOCO-D values indicate the monthly correlation between
both series for the 1948–2014 period. Only correlations statistically
significant (p<0.01) are displayed. Note that the scale of the wind is
expressed as 10 m s-1 to ease comparison. (b) Standardized
temporal series (June to October average) of the CHOCO-D index and the
NCEP-NCAR zonal wind at 925 hPa averaged over 5–7.5∘ N, 90–80∘ W (blue
dashed line).
The graph at the bottom-left corner in Fig. 4 shows the temporal evolution
in the number of the available wind direction observations inside the
selected area between May and November. Unfortunately, for the first half of
the 19th century, ICOADS has a very poor coverage in the Pacific
(typically below 100 observations between May and November). Around 1850
there is an increase in the data coverage, and, for some years, up to around
1000 observations can be found. However, the number of observations
diminishes again to below 100 per year between 1860 and the final decade of the
19th century. From the beginning of the 20th century onwards, the
number of observations is typically well over 1000 per year (with the
exception of the World War II period) rising to more than 10 000 after the
end of the 1950s. It is noteworthy that a large number of observations
correspond to the routes following the coast, with a large contribution from
the route from North America to the Panama Canal since its opening in the
late 1910s. In fact, the latitude of the Panama Canal (around
9∘ N) was the southernmost latitude reached for most of the
ships aiming for the Caribbean Sea.
Expected dispersion (in %) of CHOCO-D as a
function of the number of wind direction observations used to compute it
(x axis) for May to November.
As a calibration series, we selected the NCEP-NCAR monthly zonal wind at 925 hPa
averaged over the area 5–7.5∘ N, 90–80∘ W (Kalnay et al., 1996) as this
database allows performing the calibration since 1948. Although the original
Chocó jet index was defined exclusively at 80∘ W (Poveda and
Mesa, 2000), we chose an extended region from 90 to
80∘ W to calibrate our index series to take into account
the presence of westerlies as far west as 90∘ W in episodes
of enhanced Chocó jet (See Fig. 3c). Inside the area outlined in Fig. 4a,
we computed the so called CHOCO-D index (Chocó – Directional index) as the
percentage of days per month with a prevalent wind blowing from the southwest
(observed wind direction ranging between 180 and 270∘ from the
north). Following the methodology of Barriopedro et al. (2014), we considered
a day as “a day with prevalent wind flowing from the southwest” when at
least 37 % of the wind observations in the selected area for a given day
reported this wind direction. This percentage was set as the one maximizing
the average correlation between June and October for 1948–2014 with the
calibration series. It must be stressed that a sensitivity test (not shown)
proves that variations in this optimal percentage of up to +/-15 %
produce only minor changes in the resulting CHOCO-D. A minimum of 10 days
represented in a month was required to compute the index (Barriopedro et
al., 2014).
GPCC precipitation differences between months with
CHOCO-D over +/-1 standard deviation for the 1901–2013 period (number of
+1/-1 cases are indicated in brackets). Only areas with precipitation
differences statistically significant at p<0.05 are represented.
The seasonal cycle of both the CHOCO-D index (black line) and the
calibration series (dashed blue line) are displayed in Fig. 5a for the
1948–2014 period. The calibration series (dashed blue line) shows that the
region from 90 to 80∘ W is dominated by
weak northeasterly winds between January and March, but this regime has
already changed to a westward one by April and the westward component
characteristic of the Chocó jet is clearly evidenced between May and
November. The two characteristic relative maxima in June and October are
also found. The CHOCO-D index based exclusively on ICOADS wind direction
observations (black line) closely mimics the seasonal march of the
calibration series, with percentages of westerly days close to zero up to
April and higher values between May and November. Two relative maxima are also
found in June and September. A relative minimum is observed in July,
coincident with the well-known midsummer drought in Central America (Small
et al., 2007; Duran-Quesada et al., 2017). Figure 5a also shows the monthly
correlations between the calibration series and the CHOCO-D index for the
concurrent 1948–2014 period. For all the active jet season, correlations are
positive and significant, with a maximum value of +0.69 (p<0.01)
for August and always above +0.50 (p<0.01) from May to October.
With the exception of some years around 1960, the close agreement between
the temporal series of the CHOCO-D index and the 925 hPa zonal wind for the
(June–October average) is shown in Fig. 5b. These values indicate that
CHOCO-D captures a significant part of the variability of the zonal winds at
the latitude of the Chocó jet.
Vertically integrated moisture transport between 1000 and 850 hPa (arrows; scale at the lower-right corner) and moisture convergence (shaded
areas) differences between CHOCO-D +/-0.75 standard deviations, years for
the 1979–2014 period and NCEP-NCAR reanalysis data. Only moisture
convergence differences significant at p<0.05 are represented. The
number of CHOCO-D positive/negative cases used to compute the anomalies is
indicated in brackets.
Assessment of the CHOCO-D index uncertainty
As shown by Gallego et al. (2015), directional indices suffer from a certain
uncertainty derived from the fact that the wind direction in the chosen
sector is represented by a limited number of point observations.
Consequently, it is related to the number of data used to compute the index.
In this case, the region encompasses around 5 000 000 km2. The inherent
spatial variability of the wind inside this huge region and the finite
number of available measurements in a given month is translated as
dispersion in a particular realization of the index based on a finite sample
of data. To estimate the expected uncertainty as a function of the number of
available measurements, we computed 1000 “degraded” CHOCO-D indices
constructed from N randomly selected wind observations inside the selected
area. with N ranging between 10 and 500. For each N, the 1000 degraded
CHOCO-D are expected to be different because they are computed from a
different set of observations. The average standard deviation of these 1000
series as a function of N between May and November is shown in Fig. 6 for
the period 1971–2010. This particular period was selected in order to have a
large-enough pool of wind observation in ICOADS to select a random sample of
at least 500 observations. The results are scarcely dependent on the month
and, as expected, the largest standard deviations are found for N=10
(around 16 %) in all cases. This value rapidly decreases as N increases.
For N=50 observations, the standard deviation is below 10 % and, for
N over 400, the standard deviation is almost stable around 6 % to 7 %. The
fact that the standard deviation does not tend to zero as N increases
reflects the inherent spatial variability of the wind inside the large
region considered. We took the standard deviation shown in Fig. 6 as a
conservative dispersion measure for the final CHOCO-D index. It must be
pointed out that this dispersion measure is purely empirical, depends on the
region and should be only interpreted as the expected standard deviation
of a CHOCO-D value computed from a particular set of wind direction
measurements and not as a confidence interval in a statistical sense.
Standardized CHOCO-D for May to November between 1840 and
2014. Error bars indicate the expected standard deviation based on the
number of observations available each year in ICOADS 3.0 (see text for
details). Shaded smoothed curve is computed as a robust locally weighted
regression with a 31-year window (Cleveland, 1979).
Relation between CHOCO-D and the moisture transport
Traditionally, it has been considered that the Caribbean Sea was the main
moisture supplier for Central America and northern South America through the
CLLJ (Wang et al., 2006). However, the importance of the transport from the
Pacific source by the Chocó jet has been recently highlighted, and it is
estimated that the moisture advected from this ocean can contribute up to
30 % of the total precipitation in areas of the western coast of Central
America (Duran-Quesada et al., 2010, 2017; Hoyos,
2018). The relevance of the Pacific source is captured by CHOCO-D.
Figure 7 shows the difference between precipitation composites for months
with CHOCO-D above and below 1 standard deviation of its average value for
the 1901–2013 period (“positive” and “negative” Chocó jet phases in
succession) covered by the Global Precipitation Climatology Centre (v7)
dataset (Becker et al., 2013). The precipitation changes associated with opposite anomalies of the CHOCO-D index extend over large areas of southern
Mexico and Central America and spread southward into northern Colombia. The
largest positive precipitation anomalies are found between July and
September, when the Chocó jet is fully developed, and they are especially
noticeable in the western coast of Central America from Guatemala to Panama,
where precipitation anomalies exceed 5 mm day-1 during
positive phases of CHOCO-D in relation to the negative ones. The
connection of these rainfall anomalies with the moisture advection has been
assessed by computing the vertically integrated moisture transport through
the 1000–850 hPa levels and the corresponding moisture convergence (Fig. 8).
We limited the latter analysis to the 1979–2014 period because of the large
uncertainties in the vertical distribution of the specific humidity in the
NCEP-NCAR reanalysis over the equatorial Pacific prior to the satellite era.
In order to attain a large enough number of cases for this shorter period,
we relaxed the threshold for including positive/negative phases by
considering the years above/below 0.75 standard deviation of the CHOCO-D
index. Despite the different periods considered and the lower spatial
resolution of the reanalysis, the agreement between Figs. 7 and 8 is
remarkable. As expected, large CHOCO-D values appear related to an enhanced
moisture transport (anomalies of up to 100 kg m-1 s-1) from the Pacific into Central America in a latitude
band extending from around 4 to 15∘ N.
The higher values of moisture convergence related to this enhanced transport
are located over Panama and the pacific coast of Colombia, westward of the
Cordillera Central. It is also interesting to note that the Pacific is a
relevant moisture source for the Caribbean as well. Over this area, large
values of moisture convergence occur, resulting in significant changes in the
precipitation of the Greater Antilles, especially in Jamaica and large areas
of Cuba (see Fig. 7d, for example).
GPCC precipitation differences between the 11-year
period 1965–1975 and 1901–1911 for (a) July and (b) September. Only
differences at p<0.05 are displayed.
Temporal evolution of the CHOCO-D indexInter-annual and decadal variability
The exceptional time coverage of ICOADS allows building an almost continuous
monthly record of the CHOCO-D index starting in the 1880s and for some years
between 1850 and 1860 (Fig. 9). The series indicates that the Chocó jet is
rather variable at an inter-annual scale but the most prominent feature of the
time evolution is a marked interdecadal variability, which is evident for
all months (smoothed coloured curves in Fig. 9). This longer-term
variability is quite dependent on the considered month. In general, the
period 1880–1910 was characterized by stronger-than-average jets from May to
August and also in November, while weaker-than-average jets are found in
September and October. The subsequent three decades (1910–1940) show a
general tendency to lower than average jets (except in November) which is
quite evident in August. After the 1940s, the long-term anomalies even became most dependent on the month. In May, CHOCO-D shows an alternating
behaviour at near-decadal periods, while in June the index oscillates around the
average. In July and August, CHOCO-D was mostly below its long-term average up to the 1990s, while in September and October it was above it up
to the end of the series (2014), with a short period (1981–1990) of weak
jets in October. November shows a long period of quite weak jets from 1960
to the late 1990s followed by a recovery to near-average values since the
first years of the 21st century.
(a) Twenty-one-year running Pearson's correlation coefficient
between CHOCO-D (JJA) and El Niño3.4 in Phase (JJA, red line) and the
following boreal winter (DJF yr +1, blue line); (b) 21 yr running Pearson's
correlation coefficient between CHOCO-D (SON) and El Niño3.4 the
previous boreal summer (JJA, blue) and in phase (SON, red line). Dotted line
indicates statistically significant correlation at p<0.05.
The strong dependence of the CHOCO-D behaviour on the month suggests that
the seasonal distribution of the precipitation associated with the Pacific
moisture source could be modulated by these long-term changes in the Chocó
jet. Accounting for no more that 30 % of the total precipitation in the
area (Duran-Quesada et al., 2010), the changes in the total precipitation
associated with the variability of the Chocó jet are necessarily moderate
but yet discernible in cases of large opposite jet anomalies. For example,
according to Fig. 9, the period 1901–1911 was characterized by a persistent
strong jet in July and a relatively weak one in September. The opposite situation is observed in 1965–1975, with a very weak jet in July and a
strong one in September. When the Global Precipitation Climatology Centre (GPCC) difference in precipitation between
the 11-year periods 1965–1975 and 1911–1911 is computed (Fig. 10), it is
found that in July (September), the period 1965–1975 was significantly drier
(wetter) than 1911–1911 in large parts of Central America and northern
Colombia, with changes in the total precipitation of the order of
+/-2 mm day-1.
Relationship with ENSO
As stated in the introduction, the Chocó jet ultimately originates in the
southerly trade winds, making it strongly dependent on the meridional SST
gradient along the eastern equatorial Pacific (Martinez et al., 2003) and
therefore on ENSO. Typically the ENSO cycle encompasses two calendar
years. A warm event (El Niño) tends to begin during the boreal spring
(year 0), developing increasing SST anomalies peaking the following winter
(year +1), then declining to the subsequent summer (year +1). The
diminished temperature gradient between the Peruvian coast and the Panama
Bight/northern Colombian western coast around 5∘ N during
the course of an El Niño event is accompanied by a weaker Chocó jet
(Poveda et al., 2001). The profound link between this meridional SST
gradient and the precipitation in western Colombia through changes in the
Chocó jet has been documented for the second part of the 20th century
by Poveda and Mesa (2000) and Poveda et al. (2001), and it has been
subsequently assumed as the basis for the reconstruction of the climate in
the area since the last glaciation (Martinez et al., 2003). The long series
of the CHOCO-D index allows us to assess the stability of this relationship
between the Chocó jet and the ENSO at a secular scale for the first time.
Figure 11 shows that as expected, the correlation between the El Niño3.4
index and CHOCO-D has been mostly negative throughout the entire 20th
century for the in-phase (JJA, Fig. 3a red line) and the lagged cases
(CHOCO-D(JJA) leading El Niño3.4; DJF yr +1). This indicates that a
weak jet in JJA tends to be followed by SST increases (El Niño
conditions) the following winter. Some fluctuations in the absolute
magnitude of the correlation are found, but Fig. 11a shows that these
relations have been remarkably stable throughout the 20th century. On the other
hand, Fig. 11b shows that, according to our series, a weak jet during SON
is also typically concurrent with in-phase warmer SSTs (Fig. 11b, red
line), while warm SSTs during JJA tend to be followed by a weaker jet (Fig. 11b, blue line). Interestingly, the intensity of these relations involving
the SON-averaged CHOCO-D has changed throughout the 20th century, being clearly
weaker prior to the 1920s.
Summary and discussion
During the last years, a number of studies have dealt with climate
reconstructions based on historical wind direction measurements (see
Garcia-Herrera et al., 2018, for a recent review). However, due to the low
number of historical meteorological records over the eastern Pacific, most
of these works correspond to reconstructions over the North Atlantic or the
Indian Ocean. The few exceptions considering the Pacific are limited to the
study of the climatic implications in the changes in the duration of a
particular shipping route (Garcia et al., 2001), focus on the westernmost
North Pacific (Vega et al., 2018) or make use of indirect approaches, by
estimating the climate in the tropical Pacific through the use of present-day
teleconnection patterns using data from other oceanic basins (e.g. Barrett et al., 2017a, b). In this work, we have found
that the strength of the Chocó jet can be estimated through an index
starting in the 1850s by using in situ wind direction measurements
contained in ICOADS. To the best of our knowledge, this is the first time
that a quantitative instrumental climate index over the eastern tropical
Pacific has been built for such a long period.
This reconstruction has been possible because the signature of the Chocó jet
variability in the distribution of the wind direction at the surface is
sought in a large area where the aggregated number of observations available
in ICOADS is currently enough for computing a meaningful index. As described graphically by Poveda (2018), in the tropical eastern Pacific, the
wind field configuration is the result of a “tug of war” between two low-level jets blowing from opposite directions: the CLLJ blowing from the
Caribbean into the Pacific and the Chocó jet originating in the Southern
Hemisphere trade winds belt and recurving to the east as it crosses the
Equator (Poveda et al., 2001, 2006 and 2014). While the location of the core
of both jets is almost stationary (Poveda and Mesa, 2000; Sakamoto et al.,
2011; Sierra et al., 2018), their relative strength is quite dependent on
the SST anomalies over the equatorial Pacific. During the Northern
Hemisphere warm season, the modulation of the SST anomalies over both jets
is opposite (Wang, 2007), and this results in a significant change in the
distribution of the westerlies/easterlies in a large oceanic area. In this
way during years of a strong Chocó jet, at the surface the westerlies can
reach the 15∘ N latitude limit even as far west as
120∘ W, while in years of a weak Chocó jet, the westerlies are
restricted to 80∘ W. We found that, the
proportion of days with wind blowing from the southwest in the areas 4–15∘ N, 120–84∘ W plus 4–9∘ N,
84–77.5∘ W is significantly related to
the relative strength of the Chocó jet as measured by the average wind speed
at its core.
It must be pointed out that our index has some caveats. On the one hand, the
strength of the Chocó jet is not exclusively dependent on the relative
strengths of the CLLJ and the Chocó jet, as it is implicitly assumed in our
approach. In fact, the strength of the Chocó jet is partly dependent on the
CLLJ dynamics. From the Caribbean, the CLLJ divides in two branches, one
passes through Central America toward the Pacific (the one entering our
study area), but the other one crosses the Panama Isthmus and then merges
with the Chocó jet (see Fig. 1a), enhancing it (Poveda et al., 2014). On
the other hand, the Chocó jet suffers from positive feedbacks not
necessarily related to the CLLJ, as the Chocó jet core is enhanced by the
latent heat released as it enters the continent generating precipitation
(Velasco and Fritsch, 1987; Poveda and Mesa, 2000). Additionally, while the
Chocó jet is present in the region throughout the whole year, our index can be
only computed between May and November. Between December and April, the
southward migration of the ITCZ allows the northeasterly Northern
Hemisphere trade winds to blow as far south as 4∘ N
(Wodzicki and Rapp, 2016), and during these months easterlies are essentially
dominant in our study area, and the CHOCO-D index is near zero regardless of
the strength of the Chocó jet.
These limitations explain both the absence of estimations of the Chocó jet
strength between December and April and the moderate correlation between
CHOCO-D and the Chocó jet strength for the rest of the year (r=+0.59p<0.01 for the May–October average; see Fig. 5b). However, during
these months, this relation is significant, peaking in May and August, with
correlations above r=+0.68 (p<0.01). Additionally, we have
found that CHOCO-D is strongly representative of the moisture advection
from the Pacific into Central America and northern South America and,
therefore, of a significant part of the precipitation in this area related
to the moisture transported from the Pacific.
According to the CHOCO-D record, the Chocó jet has experienced changes at
decadal scales at least since 1880. They are quite dependent on the month.
Interestingly the July series shows a tendency to be above its long-term
average value from 1840 to 1910 and below it from 1910 to 1990. September
exhibits an opposite behaviour, being below average up to the 1920s and
above it from that decade onwards. As the reversal in the trends for July and
September occurred at the beginning of the 20th century, the evaluation
of the consequent changes in independent precipitation records is rather
uncertain because of the low number of precipitation data in this part of
the world during the first two decades of the 20th century (Becker et
al., 2013). Notwithstanding this, the analysis of the GPCC dataset suggests that
throughout the 20th century, there was a discernible change in the seasonal
distribution of the precipitation related to the intra-annual variability
of the Chocó jet. Finally, it is worth mentioning that Carmona and Poveda
(2014) found an increasing trend in the precipitation of the Pacific coast
of Colombia starting in the last decades of the 20th century. Our
results support this finding, as the strength of the Chocó jet has been
steadily increasing for May, June, July and August since the last years of
the 20th century (Fig. 9).
Since their conception, one of the main applications of directional indices
has been the analysis of the stability of teleconnection patterns
(Gomez-Delgado et al., 2019). For instance, directional indices have been
used to prove that the relation between the strength of the West African
monsoon and the ENSO or the Atlantic Multidecadal Oscillation have been
unstable (Gallego et al., 2015). Similarly, instabilities have been
described in the relation between the ENSO and the strength of the western
North Pacific summer monsoon (Vega et al., 2018). By contrast, we have
found that the relation between the Chocó jet strength during JJA and the El
Niño3.4 index (JJA and DJF yr +1) has been remarkably stable at least
since the 1880s. This is particularly relevant because the stability of this
relation is usually the basis of the hydrologic reconstruction or prediction
in northern South America (Gutiérrez and Dracup, 2001; Prange et al.,
2010; Córdoba-Machado et al., 2015). However, our results suggest that
the intensity of these relations involving the SON-averaged CHOCO-D has
changed throughout the 20th century, being clearly weaker prior to the
1930s. We do not currently have an explanation for this finding, and it must be
considered cautiously as the uncertainty of CHOCO-D during this early
period is the largest (Fig. 9), but it could be related to the shift from
negative to positive anomalies around the 1920s–1930s discussed for the
September and October CHOCO-D series (see Fig. 9). The results are also
found when the ENSO cycle is represented by the Southern Oscillation Index
(Ropelewski and Jones, 1987) based on sea level pressure instrumental
measurements (not shown).
In this paper, we present a new example of how climate indices based
exclusively on wind direction measurements over the ocean have a large
potential to provide a better understanding of the long-term climate
variability, in this case in the eastern equatorial Pacific, a region with
scarce inland observational records. The low-level circulation in this
region is dominated by the Chocó jet, driving a large amount of moisture
toward Central America and northern South America, which as a result is one
of the rainiest areas in the world. With the data currently available on
ICOADS, it has been possible to assess the long-term variability of this jet
since the late 19th century and some years of the 1850s,
revealing a complex but significant variability at multidecadal scales.
However, there are still some important gaps in the data coverage such as
the World War II period and the years between 1860 and 1880, while prior to
the 1920s, the low number of available observations results in uncertainties
of the CHOCO-D index around 15 %. We expect the results of this research
will stimulate future efforts in data rescue aimed at improving the data
coverage in this part of the world for years prior to the 1920s.
Data availability
NCEP reanalysis derived data (Kalnay et al., 1996), CMAP precipitation data (Huffman et
al., 1997) and GPCC precipitation data (Becker et al., 2013) are provided by the
NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at
http://www.esrl.noaa.gov/psd/ (last access: 4 January 2019). ICOADS data (Freeman et al.,
2017) are provided by the NCAR/UCAR Research Data Archive, from their website at
https://rda.ucar.edu/datasets/ds548.0/ (last access: 4 January 2019).
Author contributions
DG, RGH and POP conceived the study and developed the methodology. DG
developed the software, computed the index and prepared the manuscript with
contributions from PR. FdPG calculated the relationship between CHOCO-D and ENSO. All authors discussed the results and took part in the revision of
the original manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “The 8th EGU Leonardo Conference: From evaporation to
precipitation: the atmospheric moisture transport”. It is a result of the 8th EGU
Leonardo Conference, Ourense, Spain, 25–27 October 2016.
Acknowledgements
This research was funded by the Spanish Ministerio de Economía y
Competitividad through the projects CGL2013-44530-P, CGL2014-51721-REDT and
the research group RNM-356 belonging to the “Plan Andaluz de
Investigación Desarrollo e Innovación”.
Review statement
This paper was edited by Sergio Martín Vicente Serrano and reviewed by Germán Poveda and two anonymous referees.
ReferencesAllan, R., Brohan, P., Compo, G. P., Stone, R., Luterbacher, J., and
Brönnimann, S.: The International Atmospheric Circulation
Reconstructions over the Earth (ACRE) Initiative, B. Am. Meteorol. Soc.,
92, 1421–1425, 10.1175/2011BAMS3218.1, 2011.
Amador, J. A.: A climatic feature of the tropical Americas: The trade wind
easterly jet, Top. Meteor. Oceanogr., 5, 91–102, 1998.Arias, P. A., Martínez, J. A., and Vieira, S. C.: Moisture sources to
the 2010–2012 anomalous wet season in northern South America, Clim. Dynam.,
45, 2861–2884, 10.1007/s00382-015-2511-7, 2015.
Arnett, A. B. and Steadman, C. R.: Low-level wind flow over eastern Panama
and northwestern Colombia, ESSA Technical Memorandum ERLTM-ARL 26, U.S. Department of Commerce,
Environmental Science Services, Administration
Research Laboratories, Air Resources Lab., Silver Spring, Maryland, 73 pp.,
1970.Barrett, H. G., Jones, J. M., and Bigg, G. R.: Reconstructing El Niño
Southern Oscillation using data from ships' logbooks, 1815–1854, Part I:
methodology and evaluation, Clim. Dynam., 50, 845–862,
10.1007/s00382-017-3644-7, 2017a.Barrett, H. G., Jones, J. M., and Bigg, G. R.: Reconstructing El Niño
Southern Oscillation using data from ships' logbooks, 1815–1854, Part II:
Comparisons with existing ENSO reconstructions and implications for
reconstructing ENSO diversity, Clim. Dynam., 50, 3131–3152,
10.1007/s00382-017-3797-4, 2017b.Barriopedro, D., Gallego, D., Alvarez-Castro, M. C., Garcia-Herrera, R.,
Wheeler, D., Peña-Ortiz, C., and Barbosa, S. M.: Witnessing North
Atlantic westerlies variability from ship's logbooks (1685–2008), Clim.
Dynam., 43, 939–955, 10.1007/s00382-013-1957-8, 2014.Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K.,
Schneider, U., and Ziese, M.: A description of the global land-surface
precipitation data products of the Global Precipitation Climatology
Centre with sample applications including centennial (trend) analysis from
1901-present, Earth Syst. Sci. Data, 5, 71–99, 10.5194/essd-5-71-2013, 2013.Carmona, A. and Poveda, G.: Detection of long-term trends in monthly
hydro-climatic series of Colombia through Empirical Mode Decomposition,
Climatic Change, 123, 301–313, 10.1007/s10584-013-1046-3, 2014.Cleveland, W. S.: Robust locally weighted regression and smoothing
scatterplots, J. Am. Stat. Assoc., 74, 829–836,
10.1080/01621459.1979.10481038, 1979.Córdoba-Machado, S., Palomino-Lemus, R., Gámiz-Fortis, S. R.,
Castro-Díez, Y., and Esteban-Parra, M. J.: Influence of tropical
Pacific SST on seasonal precipitation in Colombia: prediction using El
Niño and El Niño Modoki, Clim. Dynam., 44, 1293–1310,
10.1007/s00382-014-2232-3, 2015.Durán-Quesada, A. M., Gimeno, L., Amador, J. A., and Nieto, R.: Moisture
sources for Central America: Identification of moisture sources using a
Lagrangian analysis technique, J. Geophys. Res., 115, D05103, 10.1029/2009JD012455, 2010.Durán-Quesada, A. M., Gimeno, L., and Amador, J.: Role of moisture transport for Central
American precipitation, Earth Syst. Dynam., 8, 147–161, 10.5194/esd-8-147-2017, 2017.Freeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C.,
Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W.,
Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G., and Smith, S. R.:
ICOADS Release 3.0: A major update to the historical marine climate record,
Int. J. Climatol., 37, 2211–2237,
10.1002/joc.4775, 2017.Gallego, D., García-Herrera, R., Calvo, N., and Ribera, P.: A new
meteorological record for Cadiz (Spain) 1806–1854, J. Geophys. Res., 112,
D12108, 10.1029/2007JD008517, 2007.Gallego, D., Ordóñez, P., Ribera, P., Peña-Ortiz, C., and
García-Herrera, R.: An instrumental index of the West African Monsoon
back to the 19th century, Q. J. Roy. Meteor. Soc., 141, 3166–3176, 10.1002/qj.2601, 2015.Garcia, R. R., Díaz, H. F., García-Herrera, R., Eischeid, J.,
Prieto, M. R., Hernández, E., Gimeno, L., Durán, F. R., and Bascary,
A. M.: Atmospheric Circulation Changes in the Tropical Pacific Inferred from
the Voyages of the Manila Galleons in the Sixteenth–Eighteenth Centuries,
B. Am. Meteorol. Soc., 82, 2435–2456, 10.1175/1520-0477(2001)082<2435:ACCITT>2.3.CO;2, 2001.García-Herrera, R., Können, G. P., Wheeler, D. A., Prieto, M. R.,
Jones, P. D., and Koek F. B.: CLIWOC: a climatological database for the
World's Oceans 1750–1854, Climatic Change, 73, 1–12,
10.1007/s10584-005-6952-6, 2005.Garcia-Herrera, R., Barriopedro, D., Gallego, D., Mellado-Cano, J., Wheeler,
D., and Wilkinson, C.: Understanding weather and climate of the last 300 years
from ship's logbooks, WIREs Clim. Change, 9, e544, 10.1002/wcc.544, 2018.Gomez-Delgado, F., Gallego, D., Peña-Ortiz, C., Vega, I., Ribera, P.,
and García-Herrera, R.: Long term variability of the northerly winds over
the Eastern Mediterranean as seen from historical wind observations, Global Planet. Change, 172, 355–364, 10.1016/j.gloplacha.2018.10.008, 2019.Gutiérrez, F. and Dracup, J. A.: An analysis of the feasibility of
long-range streamflow forecasting for Colombia using El Niño-Southern
Oscillation indicators, J. Hydrol., 246, 181–196,
10.1016/S0022-1694(01)00373-0, 2001.Hoyos, I., Dominguez, F., Cañón-Barriga, J., Martínez, J. A.,
Nieto, R., Gimeno, L., and Dirmeyer, P. A.: Moisture origin and transport
processes in Colombia, northern South America, Clim. Dynam., 50, 971–990,
10.1007/s00382-017-3653-6, 2018.
Huffman, G. J., Adler, R. F., Arkin, P., Chang, A., Ferraro, R., Gruber, A., Janowiak, J.,
McNab, A., Rudolf, B., and Schneider, U.: The Global Precipitation Climatology Project
(GPCP) Combined Precipitation Dataset, B. Am. Meteorol. Soc., 78, 5–20,
https://doi.org/10.1175/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2, 1997.Janowiak, J. E., Arkin, P. A., and Morrissey, M.: An examination of the
diurnal cycle in oceanic tropical rainfall using satellite and in situ data,
Mon. Weather Rev., 122, 2296–2311, 10.1175/1520-0493(1994)122<2296:AEOTDC>2.0.CO;2, 1994.Jaramillo, L., Poveda, G., and Mejía, J. F.: Mesoscale convective
systems and other precipitation features over the tropical Americas and
surrounding seas as seen by TRMM, Int. J. Climatol., 37, 380–397,
10.1002/joc.5009, 2017.Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A.,
Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.
C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR
40 year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471, 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.King, M. J., Wheeler, M. C., and Lane, T. P.: Mechanisms Linking Global
5-Day Waves to Tropical Convection, J. Atmos. Sci., 74, 3679–3702,
10.1175/JAS-D-17-0101.1, 2017.Martínez, I., Keigwin, L., Barrows, T. T., Yokoyama, Y., and Southon,
J.: La Niña-like conditions in the eastern equatorial Pacific and a
stronger Choco jet in the northern Andes during the last glaciation,
Paleoceanography, 18, 1033, 10.1029/2002PA000877, 2003.Meisner, B. N. and Arkin, P. A.: Spatial and annual variations in the
diurnal cycle of large-scale tropical convective clouds and precipitation,
Mon. Weather Rev., 115, 2009–2032,
10.1175/1520-0493(1987)115<2009:SAAVIT>2.0.CO;2, 1987.Murphy, R. C.: The Littoral of Pacific Colombia and Ecuador, Geogr. Rev., 29, 1–33, 10.2307/210063, 1939.
Poveda, G. and Mesa, O. J.: La Corriente de Chorro superficial del Oeste
(“del Chocó”) y otras dos corrientes de chorro en Colombia:
Climatología y variabilidad durante las fases de ENSO, Rev. Acad.
Colom. Cien., 23, 517–528, 1999 (in Spanish).Poveda, G. and Mesa, O. J.: On the existence of Lloró (the rainiest
locality on Earth): Enhanced ocean-land-atmosphere interaction by a
low-level jet, Geophys. Res. Lett., 27, 1675–1678,
10.1029/1999GL006091, 2000.Poveda, G., Jaramillo, A., Gil, M. M., Quiceno, N., and Mantilla, R. I.:
Seasonally in ENSO-related precipitation, river discharges, soil moisture,
and vegetation index in Colombia, Water Resour. Res., 37, 2169–2178,
10.1029/2000WR900395, 2001.Poveda, G., Waylen, P. R., and Pulwarty, R. S.: Annual and interannual
variability of the present climate in northern South America and southern
Mesoamerica, Palaeogeogr. Palaeocl., 234, 3–27, 10.1016/j.palaeo.2005.10.031, 2006.Poveda, G., Alvarez, D. M., and Rueda, O. A.: Hydro-climatic variability
over the Andes of Colombia associated with ENSO: a review of climatic
processes and their impact on one of the Earth's most important biodiversity
hotspots, Clim. Dynam., 36, 2233–2249, 10.1007/s00382-010-0931-y, 2011.Poveda, G., Jaramillo, L., and Vallejo, L. F.: Seasonal precipitation
patterns along pathways of South American low-level jets and aerial rivers,
Water Resour. Res., 50, 98–118, 10.1002/2013WR014087, 2014.Poveda, G.: Interactive comment on “Tracking the Choco jet since the 19th
Century by using historical wind direction measurements”, Earth Syst.
Dynam. Discuss., 10.5194/esd-2018-54-RC2, 2018.Prange, M., Steph, S., Schulz, M., and Keigwin, L. D.: Inferring moisture
transport across Central America: Can modern analogs of climate variability
help reconcile paleosalinity records?, Quaternary Sci. Rev., 29, 1317–1321,
10.1016/j.quascirev.2010.02.029, 2010.Prieto, M. R., Gallego, D., García-Herrera, R., and Calvo, N.: Deriving
wind force terms from nautical reports through content analysis, The Spanish
and French cases, Clim. Change, 73,
37–55, 10.1007/s10584-005-6956-2, 2005.Ropelewski, C. F. and Jones, P. D.: An extension of the Tahiti-Darwin
Southern Oscillation Index. Mon. Weather Rev., 115, 2161–2165,
10.1175/1520-0493(1987)115<2161:AEOTTS>2.0.CO;2, 1987.Sakamoto, M. S., Ambrizzi, T., and Poveda, G.: Moisture sources and life
cycle of convective systems over Western Colombia, Adv. Meteorol., 2011, 890759, 10.1155/2011/890759,
2011.Sierra, J. P., Arias, P. A., Vieira, S. C., and Agudelo, J.: How well do
CMIP5 models simulate the low-level jet in western Colombia?, Clim. Dynam.,
51, 2247–2265, 10.1007/s00382-017-4010-5, 2018.Small, R. J., de Szoeke, S. P., and Xie, S.: The Central American Midsummer
Drought: Regional Aspects and Large-Scale Forcing, J. Climate, 20,
4853–4873, 10.1175/JCLI4261.1, 2007.
Trojer, H.: Meteorología y climatología de la vertiente del
Pacífico colombiano, Rev. Acad. Colomb. Cienc. Ex. Fis. Nat., 10,
199–219, 1958 (in Spanish).Vega, I., Gallego, D., Ribera, P., Gómez-Delgado, F., García-Herrera
R., and Peña-Ortiz, C.: Reconstructing the Western North Pacific Summer
Monsoon since the late 19th century, J. Climate, 31, 355–368,
10.1175/JCLI-D-17-0336.1, 2018.Velasco, I. and Fritsch, J. M.: Mesoscale convective complexes in the
Americas, J. Geophys. Res., 92, 9591–9613, 10.1029/JD092iD08p09591, 1987.Wang, C., Enfield, D. B., Lee, S., and Landsea, C. W.: Influences of the
Atlantic Warm Pool on Western Hemisphere Summer Rainfall and Atlantic
Hurricanes, J. Climate, 19, 3011–3028,
10.1175/JCLI3770.1, 2006.Wang, C.: Variability of the Caribbean Low-Level Jet and its relations to
climate, Clim. Dynam., 29, 411–422, 10.1007/s00382-007-0243-z,
2007.Wilkinson, C., Woodruff, S. D., Brohan, P., Claesson, S., Freeman, E., Koek,
F., Lubker, S. J., Marzin, C., and Wheeler, D.: Recovery of logbooks and
international marine data: the RECLAIM project, Int. J. Climatol., 31,
968–979, 10.1002/joc.2102, 2011.
Wodzicki, K. R. and Rapp, A. D.: Long-term characterization of the Pacific
ITCZ using TRMM, GPCP, and ERA-Interim, J. Geophys. Res.-Atmos., 121,
3153–3170, 10.1002/2015JD024458, 2016.