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Synoptic Variability of Rainfall and Cloudiness along the Coasts of Northern Peru and

Ecuador during the 1997/98 El Nio Event

MICHAEL W. DOUGLAS

National Severe Storms Laboratory, Norman, Oklahoma

JOHN MEJIA

Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma

NORMA ORDINOLA

Universidad de Piura, Piura, Peru

JOSHUA BOUSTEADNational Weather Service, Omaha, Nebraska

(Manuscript received 6 March 2007, in final form 3 June 2008)

ABSTRACT

This paper describes the meteorological conditions associated with large fluctuations in rainfall over the

coastal regions of northern Peru and Ecuador during the 1997/98 El Nio event. Using data from a network

of routine rain gauges and special gauges established just prior to the onset of heavy rains, it is shown that

large variations in the daily rainfall on quasi-weekly time scales occurred during the period JanuaryApril

1998. These rainfall fluctuations were approximately in phase along the coast from near the equator to

7S. The daily rainfall data was averaged to develop a subset of wet and dry days, and then these dates

were used as the basis for compositing. Special pilot balloon observations were composited with respect to

the wet and dry days, showing that westerly and northerly wind anomalies are associated with wet spells.Composites of the National Centers for Environmental PredictionNational Center for Atmospheric Re-

search (NCEPNCAR) reanalysis and outgoing longwave radiation (OLR) data support a modest asso-

ciation of anomalous westerly wind events with enhanced rainfall.

The relationship observed between westerly zonal wind anomalies and rainfall west of the Andes during

1998 suggested using the NCEP reanalysis to develop composites based on westerly wind events observed

during other years. Zonal wind anomalies at 700 hPa were used as the primary criterion for stratifying wet

and dry days, despite reservations about the association between rainfall and zonal wind. Compositing

Geostationary Operational Environmental Satellite (GOES) and OLR data for 220 west wind anomaly

events from the months of JanuaryApril for the years 19902005 showed that they are associated with

enhanced cloudiness that propagates eastward at 10 m s1. The composites using NCEP reanalyses show

the evolution of the wind field associated with the wet days and suggest a link between extratropical wave

passages across North America and anomalous westerly wind events off the coast of Ecuador and northern

Peru.

1. Introduction

The El Nio phenomenon has been the subject of

many research studies, numerous reviews (e.g., Enfield

1989), many books (e.g., Philander 1990, 2004) and ar-

ticles in the popular literature. In large part this has

been a consequence of the relatively recent, and very

large, El Nio events of 1982/83 and 1997/98. Associ-

ated with major El Nio events is an extreme enhance-

ment in the rainfall over the coastal regions of northern

Peru and Ecuador, and this has been known for some

time as one of the most dramatic climatic anomalies

found anywhere on earth (Trewartha 1962).

Corresponding author address: Dr. Michael W. Douglas, Na-

tional Severe Storms Laboratory, 120 David L. Boren Blvd., Nor-

man, OK 73072.

E-mail: [email protected]

116 M O N T H L Y W E A T H E R R E V I E W VOLUME 137

DOI: 10.1175/2008MWR2191.1

2009 American Meteorological Society


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a. Previous studies of daily rainfall variability

Although many studies have involved planetary-scale

aspects of the El Nio phenomenon, especially since

1983, comparatively few studies have focused on the

regional or local aspects of the rainfall along the coast

of northwestern South America. Even fewer studies

have considered the synoptic, or high-frequency vari-

ability of rainfall during these events, despite the ob-

servation of large daily rainfall fluctuations that occur

over northern Peru. Horel and Cornejo-Garrido (1986)

described the evolution of the 1982/83 El Nio event

over the eastern Pacific, with special emphasis on the

Peruvian coast. Using outgoing longwave radiation

(OLR) and surface wind data they described the dif-

ferences between the previous year and the El Nio

year, showing that weaker surface winds were present

during 1983. They also noted that daily rainfall data,

averaged over 17 stations, showed that the main heavyrainfall events were episodic and separated by dry pe-

riods. OLR data also showed this, as well as a large

diurnal variation in convection, with an offshore early

morning maximum similar to many other tropical re-

gions. Goldberg et al. (1987) described the peculiar me-

soscale features of the rainfall around Piura, Peru (see

Fig. 1 for geography) during the 1983 rains and their

relation to the topography of northern Peru. Their

study focused on the daily rainfall data from 66 stations

and examination of geostationary imagery and loops.

They forcefully made the point that, within the envelop

of the overall El Nio seasonal enhancement of rainfall,the especially destructive rain events responsible for

the most significant flooding and mudflows were epi-

sodic and quasi-periodic. They also speculated on the

possible forcing for these heavy rain events, and evalu-

ated the hypothesis that disturbances over the Amazon

basin might be a possible inducement for coastal con-

vective events. Bendix (2000), working principally with

satellite imagery and cloud track winds, described char-

acteristics of the cloudiness and its diurnal variation

over the region of Ecuador and northern Peru during

the 1991/92 El Nio. The role of landsea breeze cir-

culations was stressed in controlling the daily cloudi-

ness.

A recent study involving daily rainfall over northern

Peru is that of Takahashi (2004), where he examined

two recent years (1998 and 2002) when elevated sea

surface temperatures favored deep convection over

northern Peru. The unique feature of this study was the

analysis of boundary layer wind profiler observations

from Piura, which allowed for a detailed depiction of

the diurnal cycle of the winds up to the midtroposphere.

By comparing wet and dry day composites of the pro-

filer data, Takahashi showed that wet days had a stron-

ger westerly wind component and that this was concen-

trated in the late afternoon to early evening hours. The2002 results showed evidence of a deep positive zonal

wind anomaly during wet days that extended to 5-km

altitude. Takahashi also composited the National Cen-

ters for Environmental PredictionNational Center for

Atmospheric Research (NCEPNCAR) reanalyses for

the wet and dry days for both years, and showed that

the westerly wind anomalies extended over a 3500-km

zonal extent. The small sample size during 2002 (8 wet

days) limited the significance of the results compared

with those from 1997/98.

b. Overview of the present study

A natural step toward the possible prediction of days

with high and low rainfall during El Nio events (or

even other years) is to determine whether a large-scale

signal is present in meteorological fields that can be

resolved by either direct meteorological measurements

(such as pilot balloon or radiosonde observations) or

from routinely available analyses or satellite measure-

ments. This paper seeks to advance this goal, with its

main objective being to describe the relationship be-

tween the rainfall variability on synoptic time scales

FIG. 1. The special sounding sites established for the 1997/98 El

Nio event.

JANUARY 2009 D O U G L A S E T A L . 117


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over the coastal region of northern Peru and Ecuador

and larger-scale meteorological fields. Special experi-

ment data collected during the 1997/98 El Nio event

(described in section 2), served as the initial motivation

for our work. Although a preliminary analysis of the

special observations was carried out and informally re-

ported (Douglas et al. 1999), the availability of addi-tional data sources, including daily rainfall observa-

tions from the Ecuadorean National Meteorological

Service [i.e., the Instituto Nacional de Meteorologia

e Hidrologia (INAMHI)], along with 10-km Geosta-

tionary Operational Environmental Satellite (GOES)

imagery for the period, motivated expansion and ex-

tension of our original effort. Concerns about the gen-

erality of the 1998 results led to an expansion of the

work, and this paper now presents results from our

investigation of the synoptic variability of cloudiness

over the period 19902005. To this end we have used

OLR and NCEPNCAR reanalyses to describe thesevariations.

2. Data used in this study

The Pan American Climate Studies Sounding Net-

work (PACS-SONET) project (Douglas and Fernandez

1997; Douglas and Murillo 2008) established 12 pilot

balloon stations from southern Mexico to northern

Peru in early 1997, which were to make twice-daily ob-

servations for a 6-month period. The projects initial

focus was to describe atmospheric circulation variationsassociated with wet and dry spells over Central

America (Pea and Douglas 2002). A special adapta-

tion of the projects activities for the 1997/98 El Nio

event provided additional measurements that have

been used in this study, and are described below.

a. The special El Nio pilot balloon network

The PACS-SONET project had established pilot bal-

loon stations in May 1997 at Piura, Peru, and in Ecua-

dor at Guayaquil, Esmeraldas, and San Cristobal (in

the Galapagos Islands). Support was requested in late

1997 to establish two additional pilot balloon sites in

Ecuador and five additional sites in Peru (Fig. 1). Ob-

server training was carried out between late November

1997 and early January 1998. Together, all of the sta-

tions attempted to make twice-daily observations

through May 1998. Unfortunately, major logistical

problems associated with gas cylinder transportation

occurred after the start of heavy rains. Many road seg-

ments were washed out in northern Peru, making the

delivery of the gas cylinders from the south difficult or

impossible. The frequent occurrence of low cloudiness

also prevented tracking many of the balloons to high

levels. Despite these unfavorable conditions, some 1467

pilot balloon observations were made from 1 December

1997 to 31 May 1998, with March 1998 being the most

densely sampled, with 391 observations. (The complete

dataset is available from the PACS-SONET Web site:http://www.nssl.noaa.gov/projects/pacs).

b. Rain gauge data

The rainfall data used in this study included available

Peruvian Servicio Nacional de Meteorologa e Hidrologa

(SENAMHI) and Ecuadorean (INAMHI) Meteoro-

logical Service observations, other regional network

observations, and special PACS-SONET rain gauge ob-

servations. The routine SENAMHI and INAMHI rain

gauges, with a 20-cm aperture, were read manually. The

PACS-SONET rain gauges, of which about 100 wereinstalled prior to the onset of heavy rains, were of a

wedge-shaped design (Tru-Chek brand) with an 6

cm by 6 cm rectangular opening. These gauges were

compared with the SENAMHI gauges at a few sites

and the differences between these gauges and the

SENAMHI were found to be small. For this study, any

systematic differences between the rain gauges have

been ignored.

The rain gauges were read each morning at between

0700 and 0800 LT (12001300 UTC). Local observa-

tions and satellite imagery suggested that the rainfall

over land had a strong diurnal cycle, with most rainoccurring from early afternoon to late evening. The

time of the rain gauge observation was a minimum in

the rainfall, allowing clear separation of the rainfall

events, with the morning rainfall measurement being

assigned to the previous day.

c. NCEPNCAR reanalyses and satellite imagery

To complement, and to compare with, the pilot bal-

loon observations, we also have used in this study the

NCEPNCAR reanalyses (Kalnay et al. 1996; hereafter

NCEP reanalyses). The GOES infrared imagery,

available at 3-hourly intervals, was obtained from the

National Oceanic and Atmospheric Administration

(NOAA) National Climatic Data Center (NCDC)

International Satellite Cloud Climatology Project

(ISCCP; Knapp 2004). We have used these data, with

10-km resolution, for the period 19982005. In addition,

we have also used daily-averaged OLR data (Liebmann

and Smith 1996) available at 2.5 resolution for com-

parison with the NCEP reanalyses and with the GOES

imagery.



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3. Methodology

a. Identifying wet and dry days

The basic methodology of our work was that of a

compositing study, whereby we hoped to distinguish

the differences between the conditions associated with

very wet days and those associated with relatively dry

days. To develop such composites required a procedure

to distinguish wet days from dry days. Since tropical

convective rainfall can be highly variable in space, we

averaged over the rain gauge network, as done by both

Horel and Cornejo-Garrido (1986) and Goldberg et al.

(1987), to obtain a signal more representative of larger

spatial scales. Averaging the rain gauges also produced

a product with a spatial scale comparable to the pilot

balloon station separation and the 2.5 resolution of the

NCEP reanalyses. The rain gauge data were averaged

over all stations from the PeruEcuador border (3.5S)

to just north of Trujillo (8S). Only stations west of

the Andean highest terrain were used in the averaging.

Figure 2 summarizes the essential aspects of the spa-

tially averaged daily rainfall. The daily number of Pe-

FIG. 2. (a) Number of rain gauges reporting observations each day in northern Peru. (b)

Percentage of the number of station reporting rainfall each day in northern Peru. (c) Average

daily rainfall (mm) for all rain gauges reporting on a particular day (solid circles indicate the

wet spell days, solid squares indicate the dry spell centers, and open squares for all other days).

(d) As in (c), but for an average of 27 Ecuadorean stations west of the Andes. The dashed lines

in (c) and (d) show a 30-day running mean.



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ruvian rainfall reports received varied from approxi-

mately 30 in early December 1997 to just over 100 in

March and April 1998 (Fig. 2a); Ecuadorean stationswere more uniform in number throughout the period

(not shown). A plot of the percentage of stations re-

porting rain showed some evidence of synoptic variabil-

ity (Fig. 2b). However, the variability became much

more evident when the total daily rainfall (sum of rain-

fall from all stations) was divided by the number of

stations reporting (Fig. 2c). The resulting daily aver-

aged rainfall varies from more than 30 mm day1 on

wet days to less than 10 mm day1 on drier days. Days

when the rainfall over the network was clearly a maxi-

mum relative to days before or after were deemed wet

and those with a distinct minimum were considered dry.

This selection was somewhat subjective, but sufficient

to clearly distinguish wet days from dry days. Because

the rainfall increased from mid-December to February

the wet days in the early season could have less rainfall

than those later in the wet season. A total of 18 wet

events and 17 dry events were selected; this gave an

average period of6 days for the eventsthough con-

siderable variability about this value is evident.

The quasi-periodicity of the events evident from Fig.

2c and the fact that these variations reflect rainfall over

the coastal region of northern Peru suggested that the

rainfall might be modulated by larger-scale controls. A

time series for the average rainfall of the 27 stationsreporting in coastal Ecuador (Fig. 2d), though less nu-

merous and less dense than those in northern Peru,

shows a general similarity, though not a close match, to

the time series from the Peruvian stations.

FIG. 3. (a) Analysis of mean rainfall (mm day1) for JanuaryApril 1998, based on rain gauge observations over northern Peru and

southern Ecuador. Special rain gauges installed for the season are shown as open dots. Average (b) wet and (c) dry days (mm day1),

and (d) relative amplitude (%) between wet and dry spells compared to mean daily rainfall. The solid (open) circles in (d) denote

positive (negative) relative amplitude between wet and dry spells. The shaded contours represent the elevation in meters.

FIG. 4. Average daily rainfall of northern Peru (mm) vs daily

rainfall of southern Ecuador (mm). The solid line is least squares

fit to all data points.



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b. Compositing with respect to wet and dry days

With the wet and dry days identified, the next step

involved calculating mean fields with respect to these

dates. The special pilot balloon data are available only

during 1998 (with some limited exceptions), and thus

the initial focus has been on this year. However, the

results motivated the study of additional years, eventu-

ally leading us to generalize the results over a 16-yr

period extending from 1990 to 2005. We have focused

only on the period JanuaryApril, since this is the

height of the wet season in the coastal regions of north-

ern Peru and Ecuador, and relatively little rain falls in

the coastal parts of northern Peru during other months.

For both 1998 and the other years in this period we

have used the NCEP reanalyses and OLR data. We

averaged the 1200, 1800, 0000, and 0600 UTC NCEP

data to produce daily-averaged analyses. This yielded

an analysis centered about 2100 UTC, which was rela-

tively close to the peak time of precipitation over the

land stations. OLR data, available daily, were similarly

used to develop composite fields. GOES infrared im-

FIG. 5. (a) The wet day mean winds, averaged over the 01 km AGL layer, for all wet days.

(b) As in (a), but for dry days. (c) As in (a), but for wet day mean minus dry day mean winds.

Because all stations were within 100 m of sea level, AGL is approximately equal to above sea

level. Full wind barbs are 1 m s1, half are 0.5 m s1; numbers next to observations are the

speed in m s1. Elevations above 1000 m are shaded.



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agery, available at 3-hourly intervals, have similarly

been averaged to produce daily averages, which are

24-h intervals centered on 0000 UTC.

4. Characteristics of the wet and dry days during

1998

a. Rainfall patterns on wet and dry days

In general terms the mean precipitation during the

period JanuaryApril 1998 (Fig. 3a) is similar in spatial

structure to that shown for the 1982/83 El Nio event

(see Fig. 11b in Goldberg et al. 1987). The largest rain-

fall is close to the base of the mountains on the Pacific

slope, with much smaller amounts being reported to the

east of the continental divide and smaller quantities

along the coast.

Average rainfall during wet and dry days is shown in

Figs. 3b,c. Wet days clearly have larger rainfall amounts

than dry days, though the enhancement is less evident

in Ecuador than in northern Peru. This is more easily

seen from Fig. 3d, which shows the percentage increase

of wet day rainfall relative to dry day rainfall. The

greatest enhancement of rainfall on wet days is found

around the Piura area. This result is, in part, due to

selecting the wet days based on rainfall from the Peru

stations, which are most densely concentrated in the

region around Piura. Had we used the rainfall from

Ecuadorean stations as our criteria for wet days the

anomalies would likely have been larger in Ecuador.

Only four stations showed less rainfall on the wet days,and these were by relatively small amounts. All other

sites show higher rainfall during wet days. The relation-

ship between daily mean rainfall in Ecuador and in

northern Peru over the JanuaryApril period is shown

in Fig. 4. The agreement is reasonable (correlation 0.69),

showing that coherent rainfall variations, suggested by

Fig. 3d, extend from near the equator to near 8S.

b. Pilot balloon-based wind analyses

To seek an explanation for the strong synoptic vari-

ability in the rainfall series (Figs. 2c,d) we first examine

the pilot balloon data. Using the criteria mentioned in

section 3 the wet and dry day mean profiles of the

vector wind were calculated for each pilot balloon sta-

tions data (Figs. 5a,b). Differences between the wet

and dry day mean winds were then calculated to more

clearly show the differences (Fig. 5c). The observa-

tional period and total number of observations varied

with the station and it was not possible to produce a

uniform composite. Figure 5 shows the composite based

only on observations made during the period 1 January

30 April, when the observations were most complete.

Overall, the wet and dry day means show a change in

the position of the zero-meridional wind in the 01-km

layer along the coast of Ecuador, with a southward dis-

placement during wet days. The difference between the

wet and dry day means (Fig. 5c) shows most stations

with a northerly wind anomaly during wet days, except

for those in Central America, and at Cartagena and

Iquitos. The anomaly flow at most Ecuadorean and Pe-

ruvian stations is approximately parallel to the coastline.

Because there are variations in the observational pe-

riods at the different coastal pilot balloon sites and the

heights reached by different balloons varied from day

to day, we prepared a multistation mean of the zonal

and meridional winds during wet and dry days. Three

stations with the most complete records were used:

Tumbes, Piura, and Chiclayo. The zonal winds (Fig. 6a)

show a stronger westerly component during wet days,

of about 1.5 m s1, through a layer extending to above

4 km. The mean meridional wind (Fig. 6b) is about 1

FIG. 6. Mean profiles of the (a) zonal and (b) meridional wind

during wet (solid circles) days and dry (open circles) days, based

on observations from three coastal pilot balloon stations (Piura,

Tumbes, and Chiclayo) in northern Peru and NCEP reanalysis

data (squares) for a grid point (5

S, 82.5

W) offshore northernPeru. Mean profiles are obtained by including morning (AM) and

afternoon (PM) soundings.



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m s1 stronger (southerly) during dry days than on wet

days below 2 km ASL. Above 2.5 km ASL, the merid-

ional wind is more northerly during wet days. The re-

sults from the pilot balloon observations are quite simi-

lar to those reported by Takahashi (2004) using profiler

data at Piura for the same period.

Previous studies, notably Bendix (2000) and Taka-

hashi (2004) have examined the diurnal cycle relation-

ship with rain events. The twice-daily pilot balloon

data, though limited by cloudiness, do permit a depic-

tion of the diurnal variation of the wind field. Figure 7a

shows the diurnal variation during both wet and dry

days. In general, the mean zonal wind is more westerly

during wet days than during dry days. The difference

between the PM and AM profiles for the wet and dry

day means (Fig. 7b) shows that the amplitude of the

diurnal cycle of the zonal wind is approximately the same

(2.5 m s1) in the lowest 1 km but the profiles diverge

above this, with the dry day profile showing little change

in the 1.53-km layer. During wet days the PM zonal wind

is stronger than the AM zonal wind by about 1 m s1 up

to 5 km. These results agree with the Piura diurnal cycle

shown by Takahashi (2004) in that the afternoon west-erly flow is much deeper during wet days.

5. Structure of wet and dry days from

NCEPNCAR reanalyses, GOES infrared

imagery, and OLR data

a. Selecting wet and dry days from NCEPNCAR

reanalysis and OLR data alone

The generation of composite wind fields associated

with wet and dry days during 1998 is relatively straight-

FIG. 8. (a) Relationship between 1998 rainfall in northern Peru

and zonal wind based on observations from three coastal pilot

balloon stations (solid dots) averaged over the 01 km AGL layerand the zonal wind based on daily NCEPNCAR reanalysis data

(open dots) at 925 hPa for a grid point (5S, 82.5W) near the

center of the Peruvian rain gauge network. Dotted (dashed) line

is least squares fit between Peruvian rainfall and pilot balloon

observations (pibals) (NCAPNCAR reanalysis). (b) Correlo-

grams for the rainfall and zonal wind data shown in (a) and also

for OLR and 700-hPa wind anomalies with daily rainfall.

FIG. 7. (a) Mean profiles of the zonal wind for morning (circles)

and afternoon (triangles) soundings during wet (solid circles) days

and dry (open circles) days, based on observations from three

coastal pilot balloon stations (Piura, Tumbes, and Chiclayo) innorthern Peru. (b) Mean profiles of zonal wind for afternoon

minus morning soundings during wet (solid circles) days and dry

(open circles) days.



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forward using the selected wet and dry days. Likewise,

the evolution of these days can be determined by

choosing days prior to and after the wettest days. How-

ever, to anticipate results that we later show related to

the generality of the 1998 results, it is not straightfor-

ward to identify wet and dry days for years other than

1998. First, during nonEl Nio years there is little rain-

fall in northern Peru, making the identification of wet

and dry days difficult. Then there is the unavailability

of sufficient Ecuadorean rainfall data for other years,

making a rainfall-based index unreliable. We are left

with several nonrainfall based indices to estimate wet

and dry days.

To generate a multiyear composite of wet and dry

events we needed a quantity that could ideally be re-

lated to rainfall along the Peruvian and Ecuadorean

coast. Perhaps the most obvious index related to rain-

fall would be OLR or some quantification of GOES

FIG. 9. (a) Timelongitude Hovmller plots of NCEP reanalysis zonal wind for 700 hPa averaged between 7.5 S and 2.5N during

JanuaryApril 1998. (b) As in (a), but for 925 hPa. (c) As in (a), but for OLR. The black squares in (a)(c) are wet days determined

from Peruvian rain gauge data, red squares in (a) are dry days. The dash marks at 85 W in (a) show subjectively selected 700-hPa

anomalous westerly wind events.



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infrared imagery. However, we were initially motivated

to use zonal wind anomalies as an index, based on the

difference between wet and dry day mean zonal winds

evident from the pilot balloon data (Fig. 5). Despite the

clear difference in the mean profiles from Fig. 5, the

daily data (Fig. 8a) show considerable scatter. Compari-

son of the correlations with NCEP 925-hPa zonal winds

(roughly the same level as the pilot balloon data), 700-

hPa zonal winds, and OLR for 1998 shows that the

NCEP winds are the least correlated with rainfall (Fig.

8b), though the differences are not large.

Figure 9 shows three Hovmller diagrams for 1998.

The first two show NCEP zonal wind anomalies, while

the third displays OLR anomalies. The agreement be-

tween wet and dry days (determined from the Peruvian

rainfall data) and the zonal wind (and OLR) anomalies

is clearly imperfect. This reflects the scatter evident in

Fig. 8a. Dates of 700-hPa westerly zonal wind events,

identified subjectively, are also shown in Fig. 9. It is

clear that the wind-based Hovmller diagrams are rela-

tively insensitive to the particular level, with both 925

and 700 hPa showing similar patterns. The OLR Hov-

mller shows greater variability than those of zonal

wind, both in time, and importantly, along a given lon-

gitude. These variations make identifying synoptic-

scale variations from OLR data more difficult than

from zonal wind variations, and they appear to reflect

smaller longitudinal scales.

We evaluated different options for identifying wet

and dry days. Figure 10 shows the average wettest

day wind field at 925 hPa, based on four criteria we

used for selecting the wet and dry days. One criterion

was based on maxima and minima in OLR, two used

zonal wind anomalies at 700 hPa [one subjectively de-

termined from Hovmller examination (see the ex-

ample in Fig. 9) and one objectively determined], and

one used objectively determined zonal wind anomalies

at 925 hPa. The same domain was used for all criteria,

FIG. 10. Comparison of wet day minus dry day composite wind fields for 925 hPa, using four different criteria for

determining the wet and dry days for the months of JanuaryApril 19902005. See text for an explanation of each.

The gray shaded region indicates where the differences between westerly and easterly composites exceed the 95%significance level of the Students t test.



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from 2.5N7.5S to 8090W, though the subjective

procedure used a slightly broader longitudinal band for

evaluating zonal continuity of the anomalies. The im-

portant aspect of Fig. 10 is that all composites repro-

duce certain basic features of the wind field. The north-

erly winds over the western Gulf of Mexico, the cy-

clonic circulation near the east coast of the United

States, and westerly winds over the equatorial eastern

Pacific are common to all analyses, though the intensity

and precise positions vary. Not surprisingly, the three

zonal wind-based composites tend to be more similar

and to show stronger westerly wind anomalies along the

equator than does the OLR-based composite. We

chose to use the 700-hPa zonal wind as the index for

developing our composites, with positive u-wind events

being the equivalent of wet days and negative u

anomalies being dry days. We adopt this terminology

hereafter for ease of expression. However, it should be

clearly stated that this index should be considered more

an indication of westerly wind events over the domain

FIG. 11. (a) Difference between cloud frequency for days with westerly wind anomalies and cloud frequency for

days with easterly wind anomalies for years 19982005 during the period JanuaryApril. The cloudiness was

quantified by using a temperature threshold of38C. (b) As in (a), but only for JanuaryApril 1998. (c) As in (b),

but for frequency differences between wet and dry days based on the Peruvian rainfall data. (d) As in (c), but for

the one day after wet and dry days based on the Ecuadorean rainfall data.



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of interest (coastal Ecuador and northern Peru) rather

than a reliable indication of precipitation.

In summary, to determine the specific dates of

anomalous zonal wind events we restricted our com-

parison to the months of JanuaryApril (rainy season in

northern coastal Peru) for the years 19902005 and gen-

erated Hovmller diagrams of 700-hPa zonal wind

anomalies from the NCEP climatology, averaged over

the latitude band of 2.5N7.5S. These were inspected

to identify the dates of anomalous westerly wind events

and anomalous easterly wind events at 85W. A total

of 220 westerly wind events and 215 easterly wind

events were identified over the 16 yr examined, though

the selection was subjective and the events varied in

intensity and duration. An average period was 9 days

(1920 total days divided by 215 wet events), though

there was considerable variation in the period between

events. This average period is longer than that obtained

from using the 1998 rainfall data (6 days). Without

rainfall data for other years, and for more Ecuadorean

stations as well, it is not possible to determine the

source of this difference.

b. OLR- and GOES-based cloudiness for wet and

dry days

Using the 700-hPa zonal wind criterion described in

the previous section we can describe the satellite-

observed evolution of the wet spells (positive zonal

wind events) along the coast of Ecuador and Peru. To

this end we use the data discussed in section 2c.

1) WET DAY CLOUDINESS FROM GOES IMAGERY

GOES-estimated cloudiness was quantified by deter-

mining the number of times a particular pixel was

colder than 38C. This was done independently for

each 3-hourly image, which were then summed to pro-

duce daily frequency values. These values were then

averaged over all of the west wind events for the 8 yr.

Figure 11a shows that enhanced cloudiness is concen-

trated south of Costa Rica, and extends to the Colom-

bian coastline. The maximum anomaly is close to the

mean position of the ITCZ cloudiness during the boreal

winter (Wang et al. 2004). The result for 1998 is shown

in Fig. 11b. The positive cloudiness anomalies are more

FIG. 12. Hovmller diagram of the difference between OLR for days with westerly wind anomalies and OLR with easterly wind

anomalies during the period JanuaryApril (left) 19902005 and (right) 1998. The evolution is from three days prior to three days after

the westerly/easterly wind anomalies in the eastern equatorial Pacific. The latitudinal extent ranges from 10S to 10N. An eastward

propagation is evident.



13/21

widespread and are larger, especially south of the

equator. This is not surprising, since the higher seasurface temperatures south of the equator during 1998

favored more convection in this region than in other

years. And, where the 8-yr mean cloudiness shows the

western Amazon basin to have somewhat more fre-

quent cloudiness during wet days, the opposite is seen

in 1998.

Cloud frequencies were also computed using the wet

and dry days based on the Peruvian rainfall data. This

produced Fig. 11c, which while showing a maximum

over northern Peru, was considerably different from

the wind-based composite in other areas. In particular,

large differences are evident over southern Peru and

most of Bolivia, and the frequencies are lower over the

Pacific coast of Colombia and Ecuador. Using a rainfall

index based on only the Ecuadorean rain gauges pro-

duced still different results, with the greatest frequency

of cloudiness along the Ecuadorean coast apparent on

the day after the wet day (Fig. 11d). It may be that the

number of rain gauges is insufficient to provide a reli-

able indicator of wet events, or that the number of

events is too small during one year for stable means to

be obtained.

2) PROPAGATION OF THE CLOUDINESS FROM OLRDATA

Hovmller diagrams of the OLR wet day minus dry

day OLR values for both the 19902005 period and the

1998 period alone were constructed using the 700-hPa

zonal wind features described in section 5a (Fig. 12).

The most striking feature of each diagram is the east-

ward propagation of the OLR anomalies over the equa-

torial eastern Pacific. The 1998 anomalies appear some-

what more distinct than those of the multiyear mean,

but the propagation velocity is similar (10 longitude

day1 or 12 m s1). The wavelength estimated from

successive positive or successive negative OLR anoma-

lies in Fig. 12 is about 50006000 km.

A Hovmller diagram of the OLR wet dry day dif-

ferences, similar to Fig. 12 but based on a selection of

212 negative anomaly OLR days (wet days) and 200

positive anomaly days (dry days), is shown in Fig. 13.

The eastward propagation of the OLR patterns is less

obvious than in Fig. 12, but is still apparent in the 16-yr

composite. However, there is an obvious nearly station-

ary aspect, strongest around day zero, and some evi-

dence of a westward-propagating signal as well.

FIG. 13. As in Fig. 12, but based on an index using OLR instead of zonal wind.



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The differences between the zonal wind-based and

OLR-based Hovmller diagrams are not easy to ex-

plain. It is possible that heavy, but localized, rainfall

such as might occur along the coastal strip of northern

Peru, might not be fully represented in the coarser reso-

lution (2.5) OLR data. OLR variations often are asso-

ciated with broad cirrus shields, and although these are

generally indicative of convective precipitation in the

tropics, such canopies can be extensive or relatively

small depending on the strength of upper-level winds

and the upper-tropospheric relative humidity. Synop-

tic-scale wind perturbations associated with tropical

waves, of the spatial scale that can be resolved by the

NCEP reanalyses, tend to have better time continuity

than their associated cloud fields, which are related to

variations in the moisture field, static stability, and

small variations in the vertical motion field. The data

assimilation procedure used to produce the NCEP re-

analyses also ensures a level of time continuity in the

wind field that the OLR data, interpolated from an

independent satellite dataset (Liebmann and Smith

1996), do not possess.

c. Vertical structure of the wet minus dry day wind

fields

Figure 14 shows the vertical structure of the wet mi-

nus dry day mean wind field for the period 19902005

using the 700-hPa zonal wind index described in section

FIG. 14. Difference between the mean wind field for

days with westerly wind anomalies and the mean wind

field for days with easterly wind anomalies during

JanuaryApril 19902005. Wind fields based on dailyNCEPNCAR reanalysis data for (a) 1000, (b) 850, (c)

700, (d) 500, and (e) 300 hPa. Westerly and easterly

wind anomalies are determined from the 700-hPa wind

field in the equatorial eastern Pacific (see text). Dif-

ferences significant at the 95% level are shaded.



15/21

5a. The most striking feature associated with wet days is

the strong westerly wind anomaly in the lower tropo-

sphere along the equator, being strongest from 100 to70W. This is not unexpected, since the compositing

procedure was based on zonal anomalies over this re-

gion. The westerly anomaly is largest at the 850- and

700-hPa level, becoming notably weaker and more

southwesterly by 500 hPa. The anomaly winds at 1000

hPa, while zonal on the equator, are strongly diffluent

at the coast, with northwesterly wind anomalies along

the Peruvian coast and southwesterly anomalies west of

Colombia and extending over Panama. The anomalies

along the Peruvian coast agree with the pilot balloon

observations (Fig. 5), however, major differences exist

over Central America.

Perhaps the most surprising result of the compositingprocedure is the cyclonic vortex off the east coast of

North America that tilts westward with height. Rela-

tively strong northerly flow is present over the Gulf of

Mexico at low levels. Taken together, the composite re-

sembles an extratropical cyclone off the central east coast

of the United States, with trailing cold frontal zone

extending toward Central America. At higher levels

(500 and 300 hPa) a wave train extends zonally across

the entire domain at 3040N, with one cyclonic and

two anticyclonic eddies evident at 300 hPa along 40N.

FIG. 15. As in Fig. 14, but for JanuaryApril 1998.



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Figure 15 shows the same mean fields as Fig. 14, but

for 1998. There are many similarities with the 16-yr

mean, including 1) the westerly wind anomalies along

the equator from 1000 to 700 hPa, 2) the cyclonic vortex

off the U.S. east coast, 3) the cyclonic eddy/trough

southwest of Peru over the southeastern Pacific (most

evident at 850700 hPa), 4) the pronounced trough off

the north Chilean coast at 300 hPa, and 5) the easterly

flow at 300 hPa over the equatorial eastern Pacific near

90W. There are numerous differences, especially in

higher latitudes, but the overall impression is one of

moderate agreement between the 1998 anomaly com-

posite and the 16-yr mean composite. In fact, Takahashi

(2004), using rainfall-based wet and dry days, found

NCEP reanalysis wet minus dry day wind differences at

850 and 700 hPa that were quite similar to those shown

in Fig. 15. This suggests that the synoptic-scale condi-

tions associated with wet days in 1998, despite the

strong El Nio conditions, may be generally similar to

those associated with wet days during other years. It

FIG. 16. Evolution of the difference between the mean SLP for days with westerly wind anomalies and the mean

SLP for days with easterly wind anomalies for JanuaryApril 19902005. Differences for (a) 3, (b) 2, (c) 1,

(d) 0, (e)1, and (f) 2 days about westerly/easterly wind anomalies in the eastern equatorial Pacific. The contour

interval is 0.5 hPa. Differences significant at the 95% level are shaded.



17/21

also indicates that our zonal wind-based compositing

approach yields results similar to one based directly on

the rainfall data.

d. Evolution of the wet minus dry day anomalies

A natural extension of compositing the NCEP re-

analyses to describe the wet day conditions is to com-

posite days prior to and after the wet day. This was

done from three days prior to the wet day to three days

after the wet day. For brevity, we discuss only sea level

pressure and 850- and 500-hPa wind evolutions; the lat-

ter only in the Northern Hemisphere. Also, 1998 analy-

ses are shown only for 850 hPa, since the confidence is

greater for the 16-yr means.

1) SEA LEVEL PRESSURE EVOLUTION

The main feature in the evolution of sea level pres-

sure (Fig. 16) is the strong extratropical signal over

North America that moves eastward with time. The

major tropical feature is the broad westeast gradient in

FIG. 17. Evolution of the difference between the mean 850-hPa wind field for days with westerly wind anomalies

and the mean wind field for days with easterly wind anomalies during JanuaryApril 19902005. Evolution for (a)

3, (b) 2, (c) 1, (d) 0, (e) 1, and (f) 2 days about westerly/easterly wind anomalies in the eastern equatorial

Pacific. Differences significant at the 95% level are shaded.



18/21

pressure, with positive anomalies over the Pacific and

lower values over South America during days t 2 to

t 0.

2) 850-HPA WIND FIELD EVOLUTION

The equatorial eastern Pacific westerly wind anoma-

lies (Fig. 17) seen on day t 0 are evident on both the

day before and day after, reflecting the duration of the

event and probably also the difficulty in assigning a

precise time to these events from the NCEP analyses

(Fig. 9). The largest extratropical changes are over

North America, with southerly flow over the central

United States and the Gulf of Mexico at t 3 be-

coming northerly at t 0. The amplitudes of the

anomalies decay noticeably after t 1, and day t

3 is not shown, with only small-amplitude featuresbeing present.

The 1998 wind field anomaly evolution at 850 hPa

(Fig. 18) is qualitatively similar to the 16-yr mean, but

differs in many details. Areas of agreement are the an-

ticyclonic anomaly off the U.S. east coast on days prior

to t 0 and the cyclonic vortex to its west. However,

the position of this cyclonic vortex is somewhat east of

the position in the 16-yr mean. The equatorial westerly

wind anomalies from day t 1 to day t 1 are

broadly similar in both composites. Given the small

FIG. 18. As in Fig. 17, but only for JanuaryApril 1998.



19/21

FIG. 19. Hovmller diagram of the difference between the mean wind field at 500

hPa for days with westerly wind anomalies and the mean wind field for days with

easterly wind anomalies during JanuaryApril 19902005. Evolution is from three

days prior to three days after the westerly wind anomaly in the eastern equatorial

Pacific. The latitudinal extent ranges from 10 to 45N. Differences significant at

the 95% level are shaded.



20/21

sample size for 1998 perhaps not much more can be

made of the similarities.

The clear link between extratropical waves of the

Northern Hemisphere and the zonal west wind anoma-

lies along the equator is provided by a Hovmller dia-

gram of the 500-hPa wind anomalies for the 16-yr mean

fields (Fig. 19). The wave train shown in Fig. 19 main-tains its intensity until day t 0 and thereafter decays

rapidly. It is not clear why the anomaly wind field

should show a stronger correlation with days prior to

the reference day, as opposed to days after. The west-

ward propagation of the eddies is 10 m s1 (10

longitude day1 at 35N) and the wavelength is close to

5000 km, estimating from the positions of the cyclonic

and anticyclonic circulation centers on day t 0.

6. Summary

Rain gauge measurements along the coast of north-ern Peru and the Pacific coast of Ecuador during the

strong El Nio event of 1997/98 showed large variabil-

ity on synoptic (1 week) time scales. With rain gauge

observations serving to identify relatively wet and dry

days over this region, pilot balloon observations, NCEP

reanalyses, GOES infrared imagery, and OLR data

were used to describe the characteristics of these wet

and dry days. The 1998 results motivated an additional

effort to evaluate the generality of the 1998 results to a

longer period, from 1990 to 2005. The lack of rainfall

data forced a different compositing approach, and the

procedure selected used zonal wind anomalies at 700hPa. The main results of our study are as follows:

1) Wet days along the coasts of Peru and Ecuador are

associated locally with reduced southerly boundary

layer flow and stronger than normal westerly winds

extending at least 1000 km offshore and up to 4

km ASL.

2) Wet days are associated with enhanced cloudiness

over the eastern Pacific. The 1998 El Nio event

departed from this mean pattern with more cloudi-

ness south of the equator.

3) Multiyear composites of NCEP reanalysis and OLRdata suggest that extratropical waves crossing North

America are associated with the near-equatorial en-

hanced cloudiness and positive zonal wind anoma-

lies. Both the extratropical waves and the OLR pat-

terns propagate eastward at 10 of longitude

day1.

Limitations of this study stem from the lack of mul-

tiyear daily rain gauge data from coastal Ecuador and

northern Peru that could be used to improve the deter-

mination of wet and dry days. In this regard, Ecuador-

ean stations receive rainfall every year, whereas Peru-

vian stations may not, so the detection of synoptic

variations in the rainfall data should be easier at Ecua-

dorean stations. Wind soundings from this region have

been uncommon and sporadic, but it may be possible to

develop daily indices from a mix of wind profiler, ra-

diosonde, and pilot balloon observations that havebeen made in the region during the past two decades. In

addition, it may be possible to relate surface wind vari-

ability over the ocean to coastal rainfall variations using

satellite scatterometer data.

Given the apparent relationship between the North-

ern Hemisphere synoptic-scale extratropical waves,

which may be predictable to a week or more, and wind

and rainfall variations along the Ecuadorean and north

Peruvian coasts, this could be an area of fruitful re-

search for the meteorological services of the region.

Acknowledgments. The present work was supportedby the NOAAs Office of Global Programs, during the

early stages of the PACS-SONET project. PACS-

SONET funding was provided by the NOAA/Office of

Oceanic and Atmospheric Research under NOAA

University of Oklahoma Cooperative Agreement

NA17RJ1227, U.S. Department of Commerce. The

various program managers are thanked for their sup-

port of the 1998 special measurements. This study was

initially started during a visit by one of the authors

(NO) to NSSL and while one author (JB) was partici-

pating in a Research for Undergraduates activity sup-

ported by the National Science Foundation underGrant ATM-9820587. Antonio Rodriguez of INAMHI

graciously provided the INAMHI rainfall data from Ec-

uador. Ken Knapp of NESDIS made the GOES imag-

ery available for this work. Many observers made the

observations used in this study and many others as-

sisted in different aspects of the field work. Special

thanks are due to the reviewers (Ken Takahashi and

two anonymous reviewers) of this manuscript for en-

couraging us to explore in more detail some ideas that

led to the expansion of this papers scope.

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