line p ocean temperature and salinity, 1956–2005

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Progress in Oceanography 75 (2007) 161–178

Progress inOceanography

www.elsevier.com/locate/pocean

Line P ocean temperature and salinity, 1956–2005

William Crawford a,*, Jake Galbraith b, Nick Bolingbroke c

a Institute of Ocean Sciences, Fisheries and Oceans Canada, P.O. Box 6000, Sidney, BC, Canadab 1920 Haultain Avenue, Victoria, BC, Canada

c Department of Physics, University of Toronto, Toronto, ON, Canada

Available online 31 August 2007

Abstract

Vertical profiles of temperature and salinity have been measured for 50 years along Line P between the North Americanwest coast and mid Gulf of Alaska. These measurements extend 1425 km into the gulf at 13 or more sampling stations. The10–50-m deep layer of Line P increased in temperature by 0.9 �C from 1958 to 2005, but is significant only at the 90% leveldue to large interannual variability. Most of this increase in temperature accompanies the 1977 shift in wind patterns. Tem-perature changes at 100–150 m and salinity changes in both layers are not statistically significant. Much of the variance intemperature is in the upper 50 m of Line P, and temperature changes tend to be uniform along Line P except for waters onthe continental margin. Salinity changes are dominated by variability in the halocline between 100 and 150 m depth andare less uniform along Line P. Largest oscillations in temperature and salinity are between 1993 and 2003. These events canbe understood by considering changes in eastward wind speed and wind patterns that are revealed in the first two modes ofthe Pacific Decadal Oscillation. Changes in these patterns are indicators for both Ekman surface forcing (Surface oceancurrents flow to the right of the wind direction) and Ekman pumping (Surface waters diverge away from regions of positivewind stress curl, leading to upwelling of colder saltier water). Changes in temperature along the nearshore part of Line Psuggest Ekman surface forcing is the stronger of the two processes in the upper layer. The change in salinity anomalies inthe halocline along the seaward end of Line P, following the wind shift in 1977, is in agreement with enhanced upwellingcaused by stronger Ekman pumping in this region.� 2007 Published by Elsevier Ltd.

Regional Index Terms: Northeast Pacific Ocean; Gulf of Alaska; Alaska Gyre

Keywords: Climate Physical oceanography; Water properties; Time series; Ocean stations

1. Introduction

Oceanographic stations have been sampled along Line P of the eastern Gulf of Alaska since the late 1940s,and regularly since the mid 1950s (Fig. 1). This set of observations forms one of the longest deep-ocean seriesboth in time and space (50 years, 1425 km long, at least 1500 m deep). The initial 13 stations extended from the

0079-6611/$ - see front matter � 2007 Published by Elsevier Ltd.

doi:10.1016/j.pocean.2007.08.017

* Corresponding author. Tel.: +1 205 363 6369; fax: +1 250 363 6746.E-mail address: [email protected] (W. Crawford).

mailto:[email protected]

Fig. 1. Map showing the geographical locations of the Line P stations.

162 W. Crawford et al. / Progress in Oceanography 75 (2007) 161–178

North American continental shelf to Ocean Station Papa (OSP) at 50�N, 145�W, and were sampled by Cana-dian weatherships every 6 weeks during their outbound and inbound transits between Vancouver Island andOcean Station Papa. The 13 stations were expanded to 27 by sampling between the original stations, beginningin the 1960s. These 27 station locations are listed in Table 1 and plotted in Fig. 1. (Stations are numbered P1–P26 and P35, with station P35 added last.) The weathership program ended in 1981 and the Canadian Depart-ment of Fisheries and Oceans (DFO) has continued the ocean observation program since then, with 2–5 tran-sits along Line P every year.

Reviews of these observations have been undertaken by Susumu Tabata, the oceanographer associated thelongest with this program and the champion of its continuation after 1981 (e.g. Tabata et al., 1986; Tabata,1978, 1991; Tabata and Weichselbaumer, 1992; Tabata and Brown, 1994). Many short-term, intensive ocean-ographic studies took place at Ocean Station Papa (MILE, SUPER, STREX, SERIES) or midway along LineP (Ocean Storms) in the past 30 years.

Several detailed analyses have been undertaken of Line P data since the retirement of Sus Tabata in the1990s. Freeland et al. (1997) examine changes in mixed layer depth at Ocean Station Papa. Whitney and Free-land (1999) examine temperature, salinity and density changes over the period of 1956–1997. They note thewaters warmed in the upper 400 m and became fresher in a shallower surface layer during this interval. Muchof their analysis is focussed on the warm era of the 1990s that was accompanied by declining near-surfacenitrate levels. Freeland (2002) determines the heat flux across the near-shore stations of Line P in the1990s, noting large interannual variability, and strong northward transport in 1997–1998 coinciding withEl Nino; Whitney and Welch (2002) examine changes in nutrient supply along Line P; Harrison (2002)describes ecosystem dynamics of Line P; Crawford et al. (2005) document the eastward movement of asub-surface cold-water anomaly in the Gulf of Alaska in 2002. Freeland and Cummins (2005) examine recentocean dynamic height variability in the Gulf of Alaska and mixed layer depth at Ocean Station Papa.

Laine et al. (2006) compare temperature anomalies from 1956 to 2002 in the top 500 m with several atmo-spheric series. They remove the annual cycle and subtract a five-year running-mean temperature at each point

Table 1Latitude/longitude coordinates of the locations of the 27 Line P stations

No. Latitude (N) Longitude (W) No. Latitude (N) Longitude (W) No. Latitude (N) Longitude (W)

1 48�34.50 125�30.00 10 48�53.6 0 129�40.0 0 19 49�30.0 0 137�40.0 0

2 48�36.00 126�00.00 11 48�56.0 0 130�10.0 0 20 49�34.0 0 138�40.0 0

3 48�37.50 126�20.00 12 48�58.2 0 130�40.0 0 21 49�38.0 0 139�40.0 0

4 48�39.00 126�40.00 13 49�02.6 0 131�40.0 0 22 49�42.0 0 140�40.0 0

5 48�41.50 127�10.00 14 49�07.4 0 132�40.0 0 23 49�46.0 0 141�40.0 0

6 48�44.60 127�40.00 15 49�12.0 0 133�40.0 0 24 49�50.2 0 142�40.0 0

7 48�46.60 128�10.00 16 49�17.0 0 134�40.0 0 25 50�00.0 0 143�36.3 0

8 48�49.00 128�40.00 17 49�21.0 0 135�40.0 0 35 50�00.0 0 144�18.2 0

9 48�51.40 129�10.00 18 49�26.0 0 136�40.0 0 26 50�00.0 0 145�00.0 0

W. Crawford et al. / Progress in Oceanography 75 (2007) 161–178 163

along Line P. The latter step removes the dominant decadal signals whose statistical significance would be dif-ficult to establish with their analyses techniques, but restricts their application to a narrow band of frequen-cies. They observe significant correlations between zonal winds along Line P and the sum of the first ninemodes of temperature variability on Line P. Their canonical correlation analysis provides useful insight intothe response of Line P temperatures to fluctuations in meridional winds along Line P, with the largest responsenear 50-m depth over the continental shelf break. A second comparison, using only along-shore winds nearVancouver Island as forcing, reveals the temperature response to lie in two locations, with one in the upper100 m at P1 (zero kilometres along Line P) and a second at 30 m depth over the shelf break, at 87 km alongLine P. Their analysis identifies the strong near-shore response to along-shore winds.

We present 50 years of temperature and salinity observations along Line P in the upper 300 m to determinehow these properties compare with larger scale ocean and atmospheric signals. Our time series begin in 1956and extend to 2005. We present, for the first time, Hovmøller plots of temperature and salinity variability overthe full time series of Line P at several depths. These plots reveal how the nature of variability has changed intime along Line P over these 50 years. Changes in both temperature and salinity have been especially large inthe past 10 years, so our observations provide new insight not available to Whitney and Freeland (1999) at thetime of their analyses.

The data sources and time series preparation methods are described in Section 2. Time series of tempera-ture, salinity, winds and climate indices as well as statistical relationships among these series are presented inSection 3. Section 4 describes weather patterns that account for warm and cool, salty and fresh intervals.

2. Data preparation

2.1. Input observations

The archive of temperature and salinity observations at the Institute of Ocean Sciences includes all mea-surements from Line P cruises. We base our analyses on these observations as well as on observations fromother sources (XBT observations in early years and Argo profiles since 2000) within a 100-km swath on eitherside of this line. Longitudes of these additional profiles determine their locations along Line P for subsequentanalyses.

Standard-depth temperature and salinity were computed through linear interpolation of neighboring valuesin each profile. The standard depths were those established for multi-level modelling by Foreman et al. (2000):at ocean surface and 5 m below surface, then every 10–200 m, and every 20–400 m, with wider spacing below.Large data gaps in depth were not filled. If a data gap exceeded two standard depths, we interpolated only atone standard depth closest to the top of the gap, and at one standard depth closest to the bottom of the gap.

Quality control of Line P observations began with collection of the data on each cruise. Tabata (1978) per-sonally examined most early observations to eliminate those of poor quality. More recent measurements col-lected as part of the Line P program were passed through high-quality processing and analysis by staff of theOcean Sciences Division at the Institute of Ocean Sciences before entry into the data archives. Hydro-bottleand CTD observations out to station P14 were examined again for preparation of climatology of coastal andslope waters, as part of another project. We introduced a final quality control algorithm based on standarddeviations of temperature and salinity measurements in bins centred every 100 km, identifying suspect profiles,which were expunged only if they were determined to be poor quality.

Fig. 2 presents a Hovmøller plot of the positions of temperature and salinity observations in the upper 50 mover longitude and time, revealing significant eras of observations. (Almost all profiles extend to 400 m depthor more, so Fig. 2 represents positions of observations in the upper 400 m.) Irregular sampling actually beganin the late 1940s, before the first plotted point in Fig. 2, but denser sampling began after 1950. The first set of13 stations was standardized in the early 1960s. The number of temperature stations increased in late 1960s,with sampling at these extra stations by XBT probes. Salinity measurements were extended to these additionalstations when DFO assumed responsibility for Line P in 1981. The number of cruises per year was approxi-mately 7–10 from 1956 to 1981, during the weather ship era, and decreased to 3 by the late-1980s. Argo pro-filers began adding observations to the time series in 2001; their sample points can be seen interspersed withship-based measurements in both temperature and salinity series of Fig. 2. Present sampling aims for three

Fig. 2. Hovmøller diagram of locations of valid profiles over 10–50 m depth along Line P. Horizontal axis is degrees East: (a) temperature;(b) salinity.


cruises per year, in February, May/June and August/September, supplemented by Argo profiles samplingevery 10 days at irregular locations.

2.2. Seasonal climatology

A seasonal climatology was determined first. Data from dedicated Line P cruises in 1960–2005 were appliedto the climatology, since earlier observations were too sparsely sampled. Our analysis updates the earlier cli-matology of Whitney and Freeland (1999) with better resolution of late winter temperature and salinity. Toremove undue bias in the climatology due to abnormally warm or cool years associated with El Nino and LaNina events, we removed twelve months of observations starting on 1 October of each the following years:1957, 1982, 1991, 1997, and 1998. In addition the observations of exceptionally warm waters of 2004 andthe first nine months of 2005 were removed. Average values were computed every 8 km and 4 days along LineP by searching all values with a 200-km by 18-day box, applying the Kriging algorithm in the software productSurfer�. Then a second analysis averaged values in a 50-km by 36-day box. This two-step process was intendedto first fill gaps along Line P, then to fill gaps in time. The procedure was repeated at standard depths down to2400 m below surface.

Fig. 3 presents the seasonal climatology at 10-m depth for temperature and salinity. Coolest and saltiestwaters at 10-m depth are centred in March at Station Papa. This layer freshens toward shore due to the enor-mous fresh water inputs all along the coast in later autumn and winter. Surface water becomes warmer towardshore due to the cyclonic, wind-driven circulation of the Alaska Gyre, which upwells cold water in mid-gyre,and downwells warmer surface waters closer to shore. This cyclonic circulation also advects warmer watersfrom the south along the USA and Canadian continental margin in late autumn and winter. Freshest watersat 10-m depth are centred in April–May at Station P1, near the spring freshet and before the late-spring andsummer upwelling season begins. Warmest waters are in late-August and early September between 200 and600 km from shore. Surface waters closer to shore are cooler in mid-summer than waters offshore due to

Fig. 3. Seasonal climatology along Line P at 10 m depth: (a) temperature; (b) salinity.


upwelling along the Vancouver Island coast and tidal mixing in Juan de Fuca Strait and adjacent channels(Crawford, 1991).

Fig. 4 presents the January climatology for temperature and salinity in the top 500 m along Line P. Thetemperature cross-section in Fig. 4a reveals the base of the winter surface-mixed layer to lie near 100 m depth,slightly shallower than the mid-point of the winter halocline presented in Fig. 4b. Density above 100 m depthand below 150 m depth is generally controlled by temperature. Within the halocline at 100–150 m it is salinitythat determines density changes. These depth ranges are somewhat shallower along the eastern end of Line P.The top 500 m is warmer at all depths near the coast than at Ocean Station Papa, with temperature differencesvarying from more than 3 �C at 50 m depth to about 1.5 �C at 500 m. In contrast, the horizontal salinity gra-dient changes sign with depth, with fresher coastal waters near surface, and saltier continental margin watersbelow the halocline. These deep, warm and salty waters on the continental margin are attributed to the north-ward-flowing California Undercurrent advecting waters from the south along the continental slope. (Landryand Hickey, 1989).

2.3. Anomalies of temperature and salinity

All XBT, Argo and dedicated Line P observations were used to determine variability of temperature andsalinity over the full Line P period. The climatological values were subtracted from each observation of tem-perature and salinity along Line-P by interpolating the climatological value to the distance along Line-P and

Fig. 4. January climatology along Line P from surface to 500 m depth: (a) temperature; (b) salinity.


day of year of the observation. Resulting anomalies were input to longitude-time Kriging interpolation andgridding algorithms of the Golden Software Ltd. product Surfer�, to produce time series since 1956 at inter-vals of 5 km and 0.2 years along Line P. Time series of anomalies were computed for five layers, of 10–50, 50–100, 100–150, 150–200 and 200–300 m depth ranges. Temperature changes in the two layers at 10–50 m and100–150 m are displayed in Fig. 5 as Hovmøller diagrams, with longitude along the x-axis and years since 1956along the y-axis. Initially we applied small search radii in the Kriging algorithms to allow bad data points toproduce ‘‘bull’s-eyes’’ in the resulting contour plots. Suspect data identified in this manner were examined, andwere rejected based on relative confidence in the source, mismatch with surrounding observations and ourknowledge of the presence of mesoscale eddies. Spurious data were removed, but valid measurements of unu-sual ocean features were retained. Salinity variability was processed in a similar manner, with Hovmøller plotspresented in Fig. 6 for the same two depth ranges.

There are several reasons for starting the sampling in the top layer at 10 m rather than ocean surface. Wefound more profiles starting at 10 m depth than at 0 m depth. Ship-induced turbulence often mixes the top 5–8 m of the ocean. Argo profilers sample at only one depth between the ocean surface and 10 m, so the surfacetemperature must always be extrapolated from deeper measurements.

Stations P1 and P2 are on the continental shelf, P3 and P4 on the continental slope. Station P5 at 124 kmfrom P1 marks the base of the continental margin.

Temperature anomalies of Fig. 5 reveal a cool period beginning in 1964 and extending to early 1970s, and awarm period beginning in about 1976–1977, during the ‘‘regime shift’’ observed in many ocean time series in

Fig. 5. Hovmøller diagrams of temperature anomalies along Line P, 1956–2005. Colour scales of anomalies are at bottom of figure.

Fig. 6. Hovmøller diagrams of salinity anomalies along Line P, 1956–2005. Colour scales of anomalies are at bottom of figure.


the northeast Pacific (Ebbesmeyer et al., 1991). After 1977, cool events were observed in several interannualperiods, with the cold waters of 1999–2003 emerging as most noticeable in the records at 10–50 m depth. Thiscool event arrived a few years later at 100–150 m depth and persisted after 2003. Temperatures on the conti-nental margin tend to differ from the rest of Line P and the range of temperature variability is greater in thetop layer than at 100–150 m depth or deeper.

We compute linear temperature trends along line P in both 10–50 and 100–150 m layers from 1958 to 2005using least-squares fit. These temperature increases in the 10–50 and 100–150 m layers are 1.8 and 0.6 �C per100 years, respectively. This increase is statistically significant only at the 90% level in the upper layer, but notsignificant at 90% at 100–150 m depth, based on effective degrees of freedom, N*, of 22 in the upper layer and10 in the deeper layer. (N* is defined in the following section.) The upper layer temperature increase is con-centrated in the years between 1976 and 1978. Average salinities in these two layers do not indicate any sig-nificant trend.

Salinity anomalies (Fig. 6) are greater in the subsurface layer at 100–150 m depth. The relative shift in salin-ity in 1976–1977 is less prominent than the shift in temperature. Saltiest and freshest waters at 10–50 m depthare in 1999 and 2005, respectively, separated by only 6 years. Similarly, saltiest waters at 100–150 m are in1996–2000, followed by the freshest waters of the entire time series in 2002, a separation time of only 2–6 years.

The sub-surface fresh events in August 1998 at 600 km and August 1995 at 700 km are mesoscale HaidaEddies that advected from the north, as noted by Whitney and Robert (2002) and Crawford (2002). Theseare unrelated to other ocean processes and will not be discussed further.


3. Time series analyses

3.1. Empirical orthogonal functions

Large data sets spanning all four dimensions are often passed through empirical orthogonal function (EOF)analysis to determine the dominant statistical modes of variability. If the first few modes contain a high per-centage of variance in the time series, they usually correspond to dominant physical processes and provideinsight into these processes.

We decided that quantitative analyses should begin at May 1958 because earlier observations were toosparse in both space and time, as can be seen in the Hovmøller diagrams of Fig. 2a and b. Anomalies wereinterpolated to the 27 Line P stations and subsampled at five samples per year and averaged into five layers:10–50, 50–100, 100–150, 150–200, and 200–300 m depth. The resulting 47-year time series at 27 points alongLine P and at the five depth ranges were input to an empirical orthogonal function (EOF) analysis to deter-mine dominant statistical modes of variability.

The first mode of temperature anomaly accounts for 50% of the variance, with the next two modes account-ing for only 11% and 8% of total variance. Only mode 1 is examined, and is henceforth referred to as T1. Thespatial pattern of T1 is plotted in Fig. 7a and its temporal variability is presented in Fig. 7b, along with spa-tially averaged temperature anomalies along Line P in the 10–50 and 100–150 m layers. The correlation coef-ficients between T1 and the 10–50 and 100–150 m layers are 0.94 and 0.84, respectively. The spatial pattern of

Fig. 7a. Spatial distribution of temperature mode 1 along Line P. Stars denote data grid points.

Fig. 7b. Time series of temperature mode 1 (top panel) and of temperature anomalies (�C) averaged along Line P in the two layers(bottom panel). Resolution is 0.2 years. Units on EOF modes are arbitrary.

Fig. 8a. Spatial distribution of salinity modes along Line P.

Fig. 8b. Time series of salinity mode 1 and 2 (top panels) and of salinity anomalies averaged along Line P in two layers (bottom panels).Resolution is 0.2 years. Units on EOF modes are arbitrary.


T1 reveals concentration of variance in the 10–50 m layer just seaward of the continental margin. Variancedeclines rapidly toward shore and much more slowly toward deeper waters. Variance decreases fairly uni-formly with depth, and is a minimum in the deepest layer seaward of the continental margin. The region ofmaximum variance overlaps in space with the zone of large annual temperature range at 10–50 m depth justseaward of the continental margin, as displayed in Fig. 3a.

The first two salinity modes account for 31% and 19% of variance, respectively, in the anomalies of salinityin the five layers. Spatial patterns of these two modes are presented in Fig. 8a. Time series of these modes andaverage along-Line P salinity are plotted in Fig. 8b. Both modes concentrate variance in sub-surface layers,


with S1 placing most variance in the halocline at 100–150 m depth and between 200 and 600 km from shore.S1 changes sign very close to shore, no doubt because near-shore salinity is determined by local winds andrunoff whose impact on deep-sea salinity is weak. S2 changes sign at 400 km from shore. S1 therefore repre-sents in-phase changes almost all along Line-P and S2 represents out-of-phase changes. For example, S1 islargest positive in 1999 (Fig. 8b), a year that the Hovmøller diagram of 100–150 m depth in Fig. 6b revealsas saltier than normal all along Line P. S2 is largest positive in 1984 and 1998, when Fig. 6b reveals watersto be fresh near shore and salty near OSP. S1 is most similar to the salinity anomaly at 100–150 m depth aver-aged along Line P; correlation coefficients between S1 and salinity at 10–50 m and 100–150 m are 0.64 and0.89, respectively. Correlations with S2 are �0.35 and 0.45.

3.2. Time series of EOF modes compared to climate indices and winds

We plot time series of T1, S1 and S2 along with several climate indices and wind time series in Fig. 9. Fig. 9apresents the Multi-Variate El Nino Index (MEI) that includes tropical ocean and atmospheric times seriesrelated to the El Nino – Southern Oscillation (Wolter and Timlin, 1993, 1998). The Internet site http://www.cdc.noaa.gov/people/klaus.wolter/MEI/table.html provides numerical values.

Next is the time series of the Aleutian Low Pressure Index (ALPI, Fig. 9b), defined as the relative intensityof the Aleutian Low pressure system of the North Pacific from December through March, and is thereforeavailable only at 1-year intervals (McFarlane and Beamish, 1992). It is calculated as the mean area (km2) withsea level pressure less than or equal to 100.5 kPa and expressed as an anomaly from the 1950 to 1997 mean.Positive ALPI indicates a larger Aleutian Low. Values are available at the Fisheries and Oceans Canada Inter-net site http://www.pac.dfo-mpo.gc.ca/sci/sa-mfpd/climate/clm_indx_alpi.htm.

Temperature mode 1 (T1) is plotted in Fig. 9c and again in Fig. 9h; the two salinity modes are plotted inFig. 9f and g.

The Pacific Decadal Oscillation (Fig. 9d, PDO) is defined as mode 1 of the winter sea surface temperatureanomalies of the North Pacific Ocean north of 20�N (Mantua et al., 1997). We present year-round monthlyvalues downloaded from the Internet site maintained by Nate Mantua of the University of Washington:

Fig. 9. Comparison of T1, S1 and S2 time series with wind and climate indices.

http://www.cdc.noaa.gov/people/klaus.wolter/MEI/table.html

http://www.cdc.noaa.gov/people/klaus.wolter/MEI/table.html

http://www.pac.dfo-mpo.gc.ca/sci/sa-mfpd/climate/clm_indx_alpi.htm


http://jisao.washington.edu/pdo/. Bond et al. (2003) extend this analysis to include a second EOF mode,informally named the Victoria Mode (Fig. 9e), noting it has dominated the time series since about 1990.The annual time series of this mode was provided by M. Wang of NOAA/PMEL. (Annual values are 5-monthaverages from November of the previous year to March.)

Fig. 9i presents a running 1-year average of east–west wind anomalies along Line P. The series derives fromthe NCEP re-analyses winds for three locations near Line P: 47.5�N, 125�W; 50�N, 135�W; and 50�N, 145�W,representing near-shore, mid-Line P and Ocean Station Papa, respectively. The anomaly is averaged over thesethree sites and is positive with greater eastward wind speed. The surface Ekman response to stronger winds tothe east will push colder water to the south across Line P.

North–South winds at various sites along Line-P were also compared to T1 and S1 with little agreementand they are not presented here. The analysis of Laine et al. (2006) suggests the response of temperature alongLine P to the N–S component of wind is mainly on the continental margin.

Fig. 9j is the anomaly of global ocean sea surface temperature (SST) anomaly, provided by NCDC ofNOAA. (http://www.ncdc.noaa.gov/oa/climate/research/monitoring.html). The time series extends back to1880, and anomalies are referenced to this longer period.

The NOAA/NCDC global ocean temperature anomaly of Fig. 9j reveals the relatively cool period from1964 to 1976 followed by 4–5 years of rapid warming. T1 follows this same pattern with transitions in the sameyears; ALPI and PDO follow similar paths with somewhat different transition years. The interannual variabil-ity of T1 since about 1977 appears best correlated visually with PDO and E–W winds of Fig. 9. (Since PDO isitself a measure of SST variability, its correlation with T1 is not surprising.) S2 tracks PDO reasonably welland also shares many features with T1. However, S1 presents a distinct pattern from the others, with maxi-mum salinity in 1999 and minimum near the end of 2002, and weaker oscillations at earlier periods that donot appear to match those of other time series. Victoria mode seems to match variability in T1 and S1 sinceearly 1990s.

3.3. Correlation analyses

Linear trends and averages of each time series in Fig. 9 were removed and the resulting series were input tolagged correlation analyses for the period 1958–2005. Series such as ALPI and Victoria mode that are definedonly for 1-year intervals were correlated with mid-year 12-month averages of the modal series. Then all serieswere split into two equal periods of 1958–1981 and 1982–2005 for a second set of correlations (with each seriesagain de-trended and de-meaned), to determine if the ocean response to winds and large-scale forces differed inmore recent years. Results are tabulated in Table 2.

The test of significance of a correlation between two time series depends on the effective number of degreesof freedom. Most geophysical time series have relatively more energy at lower frequencies (a ‘‘red’’ spectrum).For these series, the autocorrelation function is best fit by an exponential decay. We computed the e-foldingdecay time, s, of the autocorrelation of each de-trended time series of our study, and then determined an effec-tive number of independent samples, N*, using the formula N* = NDt/2s, where N is the number of datapoints in the time series and Dt is the time step between data points. For each of our correlation pairs, weran a thousand correlations, inputting time series of random numbers whose lengths equaled the numberN* of the geophysical series. We accounted for the mismatch in lengths of series by interpolating and subsam-pling the shorter series of each pair so its actual number of points matched that of the longer time series. Wethen determined the percentage of times the random pairs were correlated at the 95% and 99% levels. Values ofN* were computed separately for the full time series of 47 years, and the shorter 24-year series.

Table 2 includes correlations with the Pacific/North America Pattern (PNA) index, which is constructed byprojecting the daily (0000Z) 500 mb height anomalies over the Northern Hemisphere onto the loading patternof the PNA. The PNA loading pattern is defined as the second mode of Rotated Empirical Orthogonal Func-tion (REOF) analysis of monthly mean 500-mb height during 1950–2000. This definition of PNA and the tab-ulated values were downloaded from the Internet site of the Climate Prediction Center of the US NationalWeather Service. This index captures weather events, which often accompany El Nino events, over the Gulfof Alaska and western North America in the Northern Hemisphere winter, when the Aleutian Low is deeperthan normal and the high pressure system over western Canada is higher than normal.

http://jisao.washington.edu/pdo/

http://www.ncdc.noaa.gov/oa/climate/research/monitoring.html

Table 2Lagged correlation analyses of EOF modes with various wind time series and climate indices: (a) temperature mode 1; (b) salinity mode 1; (c) salinity mode 2

Autocorrel. time (years) Max. correl. 1958–2005 Max. correl. 1958–1981 Max. correl. 1982–2005

(a) Correlations with temperature mode 1 (T1)

Temperature mode 1 (T1) 1.05Salinity mode 1 (S1) 1.29 + (1.2) + (�1.4) + (1.6)Salinity mode 2 (S2) 0.79 ++ (0.2) + (0.2)Global ocean temperature 0.80 + (0.2)PDO 0.54 ++ (0.2) ++ (0.2) ++ (0.2)Victoria mode 1.16 + (1) ++ (1)PNA 0.15 ++ (0.0) ++ (0.2) + (0.0)ALPI 0.61 ++ (0) ++ (0)MEI 0.59 ++ (0.4) ++ (0.4)Average eastward wind 0.14 – – (0.2) – (0.2) – – (0.4)

(b) Correlations with Salinity mode 1 (S1)

Salinity mode 2 (S2) 0.79 ++ (2.0) + (1.8) ++ (1.8)Global ocean temperature 0.80PDO 0.54 ++ (1.8) ++ (1.6) ++ (2.0)Victoria mode 1.16 – (3) – (3)PNA 0.15 + (1.2) ++ (1.6)ALPI 0.61 + (�3) + (0)MEI 0.59 + (2.0)Average eastward wind 0.14 – –

(c) Correlations with Salinity mode 2 (S2)

Global ocean temperature 0.80PDO 0.54 ++ (0.6) ++ (0.6)Victoria mode 1.16 + (1) ++ (2)PNA 0.15 ++ (0.6) + (0.4) + (0.6)ALPI 0.61 ++ (0) + (0)MEI 0.59 + (0.8) + (2.6) + (0.6)Average eastward wind 0.14 – – – –

Numbers in parentheses denote the years at which the lagged correlation is a maximum. For example, lag in (a) is positive when T1 lags other series. Ambiguous lags are not listed.Symbols + and ++ denote positive correlations significant at the 95% and 99% levels, respectively. Symbols – and – – denote negative correlations. Autocorrelation time is for the fulltime series of 1958–2005 and is defined as the time lag at which the autocorrelation drops to 1/e.

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Most time series are significantly correlated at 99% with T1 over the full time interval of 1958–2005, indi-cating the Line P temperatures are responding strongly to North Pacific and Gulf of Alaska weather patterns.Only the global ocean temperature correlates below the 95% level. S1 and Victoria mode correlate with T1 at95% but not at 99%. T1 decreases in magnitude (and therefore Line P temperatures decrease) as eastwardwinds increase. Positive values of PNA, PDO, ALPI and MEI correlate with positive values of T1. All arelinked to intensification of cyclonic winds around the Aleutian low pressure system. However, negative valuesof Victoria Mode also indicate a more intense Aleutian low pressure system, yet negative Victoria mode cor-relates with negative T1 and lower temperatures along Line-P. We attribute this correlation to the unique spa-tial pattern of Victoria mode and the winds associated with it, as noted in the following section.

Different relationships emerge when the two shorter time intervals are examined. Correlation of T1 withVictoria mode is greater in the second half of the time series, whereas correlation with ALPI is not significantin the second period. T1 correlates reasonably well with east–west wind along Line P in both shorter periods,but the significance is 95% in the 1958–1981 versus 99% in 1982–2005. Correlation of T1 with global oceantemperature is significant only for the first period of 1958–1981.

Salinity correlations are more intricate. Although S1 and S2 have zero correlation at zero lag, as requiredby the nature of EOF calculations, they attain a maximum correlation of 0.5 at a lag of 2.0 years, S2 leading,indicating these two modes together might account for a signal propagating along Line P. It is possible to seepropagation of signals along Line P in the Hovmuller diagrams of Fig. 6, but no specific phase speed or evendirection of propagations seems to dominate. Among the climate indices, both salinity modes correlate withPDO at 99% over 1958–2005. Only S2 correlates well with the east–west wind, and only for the 1982–2005period. Neither S1 nor S2 correlate significantly with global ocean temperature anomalies.

ENSO events tend to recur every 4 years or so, providing shorter-period variability in the time series thanattributed to the decadal-scale events such as global warming since 1950 and Pacific Decadal Oscillations. Toisolate the impact of ENSO we computed spectral characteristics between MEI and the temperature and salin-ity modes. Both series were de-trended prior to analyses. Fig. 10 presents power spectra of MEI and T1 for1958–2005 inclusive, based on semi-annual sub samples of these series. Fig. 10a indicates both share a peak intheir power spectra near 0.3 cycles per year. Fig. 10b reveals the two signals are coherent at the 99% level atand near this peak. T1 lags MEI by six months at this frequency. However, compared to MEI, the T1 timeseries holds more lower-frequency energy. Coherence analyses between MEI and S1 and S2 reveal less coher-ent covariability in ENSO frequency bands.

Fig. 10. Spectral features of MEI and T1. Both series were passed through a 1-year running mean filter, and subsampled at 2 cycles peryear. Circles in each panel denote a peak in the T1 spectrum near 0.3 cycles/year. (a) Power spectra of MEI and T1 (relative units); thickline denotes T1. (b) Coherence spectrum between T1 and MEI.


4. Discussion

Changes in T1 and S1 accompany changes in most of the climate indicators of the Gulf of Alaska, but theresponse to these indicators changes over the full Line P time series. We believe much of the complexity amongtime series relating to Line P arises from changes in the spatial patterns and speeds of winds over the Gulf ofAlaska. For example, the intensity of the Aleutian Low pressure system (as indicated by ALPI in Fig. 9b) hasincreased since 1950. Most annual values of ALPI are positive after 1976, but previous values are mostlynegative.

4.1. Temperature anomalies

This increased intensity of the Aleutian Low in late 1970s was followed by a shift in the spatial weatherpatterns over the Gulf of Alaska in late 1980s, as noted by Bond et al. (2003). These patterns are presentedin Fig. 11 (from Schwing et al., 2005) along with time series of PDO and Victoria Mode. The winter-average

Fig. 11. Time series of PDO and Victoria modes, with spatial distribution of surface air pressure (top panel) and temperatures (middlepanel) in winter for selected periods. Arrows denote directions of anomalous winds of each period. L and H denote low and high pressureanomalies. C and W denote cold and warm ocean anomalies. Adapted from Schwing et al. (2005).


sea surface temperature (SST) and sea surface air pressure (SSP) anomalies are presented in the top panel ofFig. 11. Winters of negative PDO in 1972-1976 experience positive SSP anomalies in the Gulf of Alaska andnegative anomalies over western USA and Canada, with a nearly complete reversal of all these anomalies in1977–1981. The shape of the weather anomalies in the two top left panels of Fig. 11 resembles that of thePDO, whereas the top right pattern is similar to the Victoria mode.

Two features of the wind accompany this shift in air pressures. Cummins and Lagerloef (2002) describe amajor change in the wind stress curl and Ekman pumping in 1977, with evidence for a shift to stronger Ekmanpumping (shallower mixed layers) over most of the northeast Pacific north of 35�N, including Ocean StationPapa, but a shift to weaker pumping on the inshore half of Line-P. One normally expects shallow mixed layerdepths to bring colder waters toward the surface inside low pressure regions. The second feature is the decreasein strength of eastward winds along Line P (Fig. 9h). Ekman surface forcing by eastward winds pushes colderwater to the south across Line-P. The decrease in eastward winds after 1977 would increase surface temper-atures along Line-P. Therefore, we expect these two Ekman processes to reinforce and warm Line-P watersnear the coast, but push temperature in opposing directions at Ocean Station Papa and adjacent stations.

Temperature all along Line-P increased in the 1977 shift (Fig. 5). Ocean surface temperatures in winterbecame less cold after 1977 (Fig. 11) over most of the Gulf of Alaska, including Line-P. These temperatureincreases are in the direction indicated by the two Ekman processes noted above on the near-shore part ofLine P, whereas Ekman surface forcing appears to dominate temperature changes along the outer line.

A second major feature of the time series plots is the extreme high and low temperatures between 1998 and2003. To investigate this feature we follow the atmospheric events described by Bond et al. (2003) and Schwinget al. (2005). The winter air pressure anomalies from 1991 to 2002 appeared in different regions than in the1970s and 1980s. The anomalies of 1999–2002 were accompanied by much stronger geostrophic winds towardthe east. The Victoria mode captures these anomalies well. Although not shown in Fig. 11, the anomalies of1991–1998 formed a similar spatial pattern but of opposite sign from the 1999–2002 anomalies, with muchweaker winds toward the east. In both cases the wind anomalies are directed more along an East–West direc-tion than in the years preceding and following the 1977 event. This direction is most efficient for Ekman sur-face forcing of cold water northward and southward across Line P and perhaps accounts for the extremes intemperature associated with the two eras of prolonged positive (1991–1997) and negative (1999–2002) Victoriamode.

Strub and James (2003) examine anomalies of sea surface slope derived from satellite altimetry observationsin the eastern Gulf of Alaska. Sea surface slope is a measure of geostrophic (non-Ekman) surface currents.They find anomalous transports southward within 300 km of the coast from 2000 to 2002, with displacementanomalies of 800 km southwards. They find ‘‘accumulated anomalous onshore displacements of 300–400 kmoccurred first between 52–54N and 48–50N from mid-2000 to mid-2001, then between 50–52N from March2001 to February 2002, then again between 48–50N from June 2001 to May 2002.’’ These displacements coin-cide with periods of significant cooling and freshening of waters averaged along Line P, as revealed in Figs. 6band 7b. Eastward movement can account for cooling along Line P, given the general decrease in average tem-perature toward the west (Fig. 4a).

Cummins and Lagerloef (2004) examine changes in Ekman pumping over these years. They note a dampingtime scale of 2–3 years. Their model predicts shoaling of the pycnocline in much of the Gulf of Alaska includ-ing all of Line-P for 1999–2002, and their analysis of sea surface height anomaly as a proxy for pycnoclinedepth supports their model findings. Capotondi et al. (2005) compare this Ekman pumping with a full oceanmodel, with similar results. Therefore, the anomalies in wind stress curl also lead to cooling of Line P in 1999–2002.

4.2. Salinity anomalies

The 100 to 150 m layer usually lies below the wind mixed layer (except in late winter) and encloses all of thehalocline. We expect it will be more sensitive to Ekman pumping than to Ekman surface forcing. This seems tobe the case immediately after 1977 when salinity increased along the offshore end of Line-P in this layer(Fig. 6) in response to increased Ekman pumping in this region. Decreased Ekman pumping prior to 1977brought fresher water to this layer.


Between 1999 and 2003 the salinity in the halocline decreased from saltiest to freshest of the entire timeseries, as noted in Fig. 9f, and the right panel of Fig. 6. Saltiest and freshest waters of these years were inthe central part of Line P. As noted above, the years of 1999–2002 experienced much stronger eastward windsand stronger Ekman pumping along Line-P. Surface Ekman transport of the first effect should decrease anyadvection of warmer and saltier water from the South. The second should advect saltier water from below.Although we cannot prove that Ekman surface forcing dominated, the observed change in salinity is in phasewith Ekman surface forcing and opposite to that expected for Ekman pumping.

Freshest waters in both layers appeared in 2002. Murphree et al. (2003) note that large scale atmosphere-ocean anomalies in the northeast Pacific from winter 2001–2002 through fall 2002 set up wind stress anom-alies that led to anomalous transport of subarctic (fresher) waters into the North Pacific Current. Curchitseret al. (2005) attribute appearance of the cold, fresh anomaly in 2002 to enhanced mixing during the precedingwinter in central waters of the gulf. This anomaly was able to penetrate eastward toward and along Line-P onanomalous density surfaces, which themselves were likely due to winds of the preceding year or years. Theirmodel results match the extreme fresh waters along Line P in 2002, as well as the sequence of events noted byMurphree et al. (2003) and Crawford et al. (2005) in ocean observations through the Gulf of Alaska for thisevent.

5. Conclusions

� The upper layer of Line P, between 10 and 50 m below surface, increased in temperature by 0.9 �C from1958 to 2005. This increase is centred at the 1977 regime shift. No significant increase in temperaturewas observed before 1972 or after 1981. From 1958 to 1972 the temperature along Line-P actuallydecreased. The mid-1970s shift in temperature also dominates the ocean temperature record on the Alaskanshelf at GAK1 (60N, 150E) as reported by Royer and Grosch (2006).� Much of the variance in temperature is in the upper 50 m of Line P, and temperature changes tend to be

uniform along Line P except for waters on the continental margin. Salinity changes are dominated by var-iability in the halocline between 100 and 150 m depth and are less uniform along Line P.� Many of the temperature and salinity changes, especially the rapid temperature changes in 1977 and both

temperature and salinity change in 1998 to 2002, can be understood by considering changes in wind pat-terns and speed. These wind patterns are revealed in the Pacific Decadal Oscillation and the second modeof this pattern, informally denoted the Victoria mode (as represented by the anomalies of SST and SSPplotted in Fig. 11 for several winters). Changes in the amplitudes of these modes are indicators for bothEkman surface forcing (Surface ocean currents flow to the right of the wind direction.) and Ekman pump-ing (Surface waters diverge away from regions of positive wind stress curl, leading to upwelling of coldersaltier water.).� Temperature and salinity in the upper 300 m, as represented by their first two EOF modes, T1 and S1,

respond to changes in wind stress curl and wind direction. Wind stress curl upwells cooler, saltier water;stronger winds toward the east are expected to reduce the northward advection of warmer saltier watersto Line P. The second process appears to dominate, especially along the nearshore part of Line P. However,these processes do not consider the strength of winter mixing due to variations in wind speed, nor surfaceheat transport.� The change in sign of salinity anomalies along the seaward end of Line P, following the wind shift in 1977,

is in agreement with enhanced upwelling caused by stronger Ekman pumping in this region.

Acknowledgements

N.B. conducted this research while a student at the University of Victoria, Department of Physics andAstronomy. He was funded by CFCAS research Grant GR303 to Michael Stacey of Royal Military College,Kingston Ontario. J.G. was funded by Fisheries and Oceans Canada. Patrick Cummins provided software andadvice for the EOF analyses. This paper was presented at the PICES/DFO Symposium on ‘‘Time Series of theN.E. Pacific: A symposium to mark the 50th anniversary of Line P’’ in Victoria, BC, Canada, July 2006.


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