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2017 NORTHEASTERN NATURALIST 24(4):467–482
Multidecadal Trends in Atmospheric and Ocean Conditions
in Offshore Waters near Cape Cod, Massachusetts
Stephen M. Smith*
Abstract - Climate change is influencing the ocean environment in myriad ways and
many of its effects can directly or indirectly impact coastal ecosystems. In this study, I analyzed
data for a number of variables describing atmospheric and ocean conditions (AOC)
from a National Oceanographic and Atmospheric Administration (NOAA) data buoy
located near the Cape Cod, MA, peninsula. The data suggest that a number of significant
trends have occurred during the period of data collection spanning 1982–2015. Changes
include up to a 2 °C and 3 °C warming of air and water temperatures in summer, reduced
barometric pressure in the summer/fall, declining wind speeds in the spring, shorter average
wave-periods in the winter and spring, a clockwise change in wind direction in the
summer, and increased wave heights in the summer and fall. The AOC variables also
exhibited a number of relationships with each other, which helped explain some mechanisms
of change. With the exception of barometric pressure and fall wave-height, none of
the variables exhibited significant correlations with the North Atlantic Oscillation (NAO)
indices, which themselves have exhibited a declining trend over the last several decades.
The analyses indicate that greenhouse gas emissions may be the primary driver of these
changes. Herein, I further discuss the results in the context of potential consequences for
coastal ecosystems of the Cape Cod region.
Introduction
Climate change is manifested at many different geographic scales. In the northeastern
US, the influence of climate change on land-based climatic variables has
been well-studied, and researchers have documented a variety of responses. In this
century, air temperatures over land have increased throughout the region (Frumhoff
et al. 2007, Pilson 2008). Over the last 30 years, winter/spring maximum river-flow
dates have become earlier by as much as 2 weeks in areas where snowmelt runoff
has the most effect on spring river-flows (Hodgkins et al. 2003). Lake ice-out is
also occurring earlier in the year (Hodgkins et al. 2002). Similarly, the date of the
last, hard, spring freeze has gotten earlier during the period 1961–1990, and less
precipitation fell as snow between 1949 and 2000 (Huntington et al. 2004).
While there is a plethora of studies on changes in land-based climatological
variables, much less attention has focused on changes in offshore coastal waters
around New England. The latter is important given that the ocean can have
a profound effect upon the coastal environment and the physical and biological
processes of its ecosystems. Previous work by Nixon et al. (2004) revealed that
surface-water temperatures at Woods Hole, MA, averaged ~1.2 °C warmer during
*National Park Service, Cape Cod National Seashore, Wellfleet, MA 02667;
stephen_m_smith@nps.gov.
Manuscript Editor: Ryan Stanley
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the 1990s than between 1890 and 1970, with warming more pronounced in winter
than summer. Since the 1960s, winter sea-surface temperatures in salt ponds
around Narragansett Bay, RI, have exhibited an increase of 2.2 °C (Heffner et al.
2012). Shearman and Lentz (2010) found that mean annual surface-water temperatures
warmed in the Gulf of Maine at a rate of 1.0 ± 0.38 °C per century between
1875 and 2007.
Ocean and atmospheric conditions in this region can also be influenced by variances
in the North Atlantic Oscillation (NAO; Oviatt 2004), which is the difference
in atmospheric mass between the Arctic and the subtropical parts of the Atlantic, as
defined by sea-surface pressure. The effects of NAO fluctuations on weather patterns
over North America have been well documented (Wettstein and Mearns 2002).
In general, the NAO influences wind speed and direction over the North Atlantic,
thereby affecting heat and moisture transport over land adjacent to the ocean. The
NAO has been correlated with changes in a number of ocean parameters, including
air and water temperatures, wind fields, and wave heights (Gulev and Grigorieva
2004, Hurrell 1995, Hurrell and Deser 2010, Hurrell et al. 2003). There are strong
short-term positive and negative trends in NAO indices that tend to make interpretations
of long-term patterns more difficult. However, a decline in summer values
and increase in winter variability during recent decades has been reported (Hanna
et al. 2015, Yuan and Sun 2009).
In the following study, I analyzed atmospheric and ocean conditions (AOC)
reported from an oceanographic station ~54 nautical miles southeast of Nantucket
(established and maintained by the National Oceanographic and Atmospheric
Administration; NOAA) to assess temporal change between 1982 and 2015 on an
annual and seasonal basis. The results are discussed within the context of regional
climate trends, the NAO, and the potential impacts on the coastal environment of
Cape Cod. This study has important implications for understanding how changing
conditions of coastal waters surrounding the peninsula, and their seasonality,
can potentially influence shoreline change, erosion, and the physical structure of
nearshore marine ecosystems. It also provides some basis for predicting future conditions,
should some or all of the observed trends continue.
Methods
I downloaded all AOC data for station 44008 from the National Buoy Data
Center website (http://www.ndbc.noaa.gov; Fig. 1). This station is a 3-m discus
buoy that collects hourly data on atmospheric and ocean conditions, and is the only
offshore weather station within 100 km of Cape Cod with verified data spanning
more than 2 decades. I extracted data spanning the period 1982–2015 (the longest
period of verified records available) and examined the following variables: (1) wind
direction (degrees, WDIR); (2) wind speed (m/s, WDSP; averaged over an 8-min
period); (3) wind gusts (m/s, GUST; peak 5- or 8-s gust-speed measured during an
8-min period); (4) significant wave height (m, WVHT; average of the highest ⅓ of
all the wave heights during a 20-min sampling period); (5) mean dominant wave
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period (sec, MDPD; period with the maximum wave energy), (6) mean average
wave period (sec, MAPD; average period of all waves during a 20-min sampling
period), (7) barometric pressure (hPa, BAR; atmospheric pressure at sea level),
(8) air temperature (°C, ATMP; temperature at 4 m above sea level); and (9) water
temperature (°C, WTMP; temperature at 0.6 m below sea surface). Monthly mean
NAO indices between 1982 and 2015 were downloaded from NOAA’s Earth System
Research Laboratory website (www.esrl.noaa.gov).
Figure1. Location of NOAA’s oceanographic buoy from which all data was acquired
(▲ represents station location).
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I calculated mean annual and seasonal values to obtain a single data point (the
mean) for each year or season (winter = January–March, spring = April–June,
summer = July–September, fall = October–December). Responses can sometimes
be manifested to a higher degree in extreme events; thus, I also calculated mean
daily minimum and maximum values. Mean WDIR values were determined by
converting degree values into radians and then breaking these down into their
north–south (cosine of WDIR multiplied by WDSP) and east–west (sine of WDIR
multiplied by WDSP) components. I summed these components for the time period
of interest and converted the sums to a mean direction using the arctan2 transformations.
Maximum and minimum daily WDIR were excluded from these analyses
because winds continuously shift throughout the day. Only datasets that had at least
70% of the total number of possible annual values (based on hourly sampling) for
that period of time were included in the calculation of means. In this way, mean
values would not be disproportionately skewed by the absence of data. Specific
years with insufficient data varied with season and AOC variable, but 1989, 1996,
2010, 2013, and 2014 were generally excluded from the analyses.
Most of data were found to be normally distributed (based on tests for normality)
and heterogeneous, and were therefore analyzed using linear regression, whereas
non-normal datasets were subjected to non-linear analyses (lognormal) using JMP®
ver. 10.0.2; statistical significance was assessed at an α level of 0.05. I calculated
both the magnitude and percent change of AOC variables during 1982–2015 as the
difference between the final and initial values based on the corresponding regression
equations. In addition to analyzing temporal trends in the AOC variables, I
conducted multivariate correlation analysis to examine inter-relationships among
these variables. NAO data were similarly analyzed by regression analysis to determine
temporal trends in NAO during this time period, followed by multivariate
correlation analysis for relationships with AOC variables (JMP® ver. 10.0.2).
Results
Annual and seasonal means
On an annual basis, only 3 AOC variables exhibited significant trends over time.
MAPD decreased by 0.2 s, and ATMP and WTMP increased by 1 °C and 1.4 °C,
respectively (Table 1). On a seasonal basis, each AOC variable exhibited at least
one significant trend. ATMP increased significantly by 2 °C and BAR decreased by
1.9 hPa and 2.9 hPa in both summer and fall. In spring, GUST exhibited a declining
trend, decreasing by 1.0 m/s, and WDSP fell by 0.9 m/s. MAPD declined significantly
in the winter and spring by 0.3 s and 0.5 s, respectively, while WDIR shifted
clockwise by 76° from ~202° to 278° in the summer. WTMP exhibited significant
increases in all seasons except fall, rising by 0.8 °C in winter, 1.7 °C in spring,
and 3.1 °C in summer. There were also increases in WVHT on the order of 0.2 m
and 0.3 m in the summer and fall, respectively. Figure 2 shows significant trends
with the highest R2 values for each AOC variable to illustrate the extent of interannual
variability and temporal change.
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Annual and seasonal daily maximum and minimums
Slightly different trends were revealed when I parsed the data into the mean
daily maximums and minimums. For example, although annual maximum daily
ATMP and WTMP showed no changes, these variables increased significantly
in summer/fall and spring/summer, respectively, with the magnitude of change
ranging between 1.6 °C and 3.0 °C (Table 1). Maximum daily BAR exhibited a
declining trend on all temporal scales except spring—significantly so in summer
and fall (by >2 hPa). In contrast, MDPD increased annually and in summer/fall by
≥0.5 s. The trend for maximum daily BAR was different than for MAPD, which
decreased significantly on an annual and spring-season basis by ≥0.5 s. Maximum
daily WVHT also trended positively and significantly in summer and fall by 0.3
m and 0.5 m, respectively. Although GUST decreased in spring by 1.7 m/s, WDSP
showed no significant trends over time.
Table 1. Total change (Δ) in annual and seasonal means, daily maximums, and daily minimums in
AOC variables between 1982 and 2015. ATMP = air temperature, BAR = barometric pressure, GUST =
gust speed, MAPD = mean average wave period, MDPD = mean dominant wave period WDIR = wind
direction, WDSP = wind speed, WTMP = water temperature, and WVHT = significant wave height.
Statistically significant trends have P values in parentheses.
AOC variables Annual Winter Spring Summer Fall
Δ Annual means
ATMP (°C) 1.0 (0.05) 1.1 0.7 2.0 (less than 0.01) 2.0 (0.01)
BAR (hPa) -0.4 -0.3 0.2 -1.9 (less than 0.01) -2.9 (0.03)
GUST (m/s) -0.2 -0.1 -1.0 (less than 0.01) -0.4 0.6
MAPD (s) -0.2 (0.04) -0.3 (0.03) -0.5 (less than 0.01) -0.1 0.0
MDPD (s) 0.2 -0.4 0.0 0.6 (0.03) 0.5
WDIR (°) 16.2 11.3 33.1 75.5 (0.03) -6.4
WDSP (m/s) -0.1 0.2 -0.9 (less than 0.01) -0.2 0.7
WTMP (°C) 1.4 (0.01) 0.8 (0.05) 1.7 (less than 0.01) 3.1 (less than 0.01) 1.9
WVHT (m) 0.1 0.0 0.0 0.2 (0.01) 0.3 (0.02)
Δ Maximum daily means
ATMP (°C) 0.9 1.2 0.0 1.6 (0.01) 1.7 (0.03)
BAR (hPa) -0.5 -0.4 0.2 -2.1 (less than 0.01) -2.9 (0.04)
GUST (m/s) -0.4 0.4 -1.7 (less than 0.01) -0.3 0.7
MAPD (s) -0.3 (0.02) -0.2 -0.5 (less than 0.01) -0.2 -0.1
MDPD (s) 0.5 (0.01) 0.3 0.3 0.9 (0.02) 0.6 (0.02)
WDSP (m/s) 0.0 0.7 -1.1 -0.3 0.8
WTMP (°C) 1.5 (less than 0.01) 0.7 1.7 (less than 0.01) 3.0 (less than 0.01) 1.1
WVHT (m) 0.2 0.2 0.0 0.3 (0.01) 0.5 (0.02)
Δ Minimum daily means
ATMP (°C) 1.2 (0.03) 1.0 0.0 2.1 (less than 0.01) 2.2 (less than 0.01)
BAR (hPa) -0.4 -0.2 0.2 -1.7 (0.02) -3.1 (0.03)
GUST (m/s) 0.0 0.5 -0.8 (0.01) -0.2 0.8
MAPD (s) -0.2 -0.1 -0.4 (0.01) -0.1 0.1
MDPD (s) -0.1 -0.1 -0.3 0.2 0.3
WDSP (m/s) 0.0 0.5 -0.8 (less than 0.01) -0.2 0.7
WTMP (°C) 1.3 (0.01) 0.7 1.6 (less than 0.01) 2.9 (less than 0.01) 1.6 (0.01)
WVHT (m) -0.1 0.0 -0.2 0.0 0.2
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Mean daily minimum ATMP and WTMP values exhibited more statistically significant
trends than did maximums, increasing annually by ≥1.2 °C and in summer
and fall by ≥1.6 °C, although WTMP also trended positively in spring by 1.6 °C
(Table 1). BAR decreased on all temporal scales, except spring, and did so significantly
in summer and fall by 1.7 and 3.1 hPa, respectively. Minimum daily GUST
and WDSP were both reduced in spring by 0.8 m/s, while MAPD decreased by 0.4 s.
MDPD and WVHT showed no significant change.
Relationships among AOC variables
My analyses revealed a number of correlations among AOC variables. I
excluded certain variables that are auto-correlated, such as WDSP-GUST and
MADP-MDPD. The strongest correlations were between ATMP and WTMP, which
were statistically significant across all time periods (Table 2). Relationships between
BAR and WDIR, GUST and WVHT, and MPDP and WVHT were also quite
strong, although the latter pair may be somewhat auto-correlated as well. Other
correlations were also significant, but they yielded weaker R2 values and were
rather less obvious in their presumed interaction (Table 2). For example, WVHT
was significantly and negatively correlated with BAR in all seasons except summer.
Additionally, lower BAR conditions were associated with higher GUST strengths in
winter and fall. Interestingly, periods of higher winds in the spring were also significantly
correlated with lower ATMP and WTMP values. However, it should be noted
Figure 2. Temporal trends in mean AOC variables with the highest R2 values between
1982 and 2015.
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that some of these relationships may not represent direct cause and effect, and are
likely incidentally correlated. Figure 3 illustrates examples of the 3 relationships
that had the highest R2 values (summer ATMP–WTMP, winter BAR–WDIR, and
winter GUST–WVHT).
Table 2. R2 and P values between pairings of AOC variables (1982–2015) that yielded at least 1 significant
result for the 5 specified time periods. - indicates results not statistically significant; pairings
with no significant results for any time period are not included .
AOC variable Annual Winter Spring Summer Fall
pairings R2 P R2 P R2 P R2 P R2 P
ATMP–GUST 0.20 0.05 0.27 0.03 0.28 0.01 - - - -
ATMP–WDSP 0.21 0.05 0.22 0.05 0.27 0.01 - - - -
ATMP–WTMP 0.85 less than 0.01 0.59 less than 0.01 0.67 less than 0.01 0.89 less than 0.01 0.80 less than 0.01
ATMP–WVHT - - 0.19 0.04 - - 0.16 0.04 - -
BAR–GUST - - 0.35 0.01 - - 0.14 0.05 0.16 0.05
BAR–MDPD - - 0.17 0.05 - - - - - -
BAR–WDIR - - 0.48 less than 0.01 - - - - - -
BAR–WDSP - - - - - - - - 0.17 0.04
BAR–WTMP - - - - - - 0.22 0.01 - -
BAR–WVHT 0.14 0.05 0.36 less than 0.01 0.20 0.02 - - 0.46 less than 0.01
GUST–MAPD 0.19 0.02 - - 0.38 less than 0.01 - - - -
GUST–WDIR - - 0.28 0.04 - - 0.18 0.03 - -
GUST–WTMP - - - - 0.23 0.02 - - - -
GUST–WVHT - - 0.56 less than 0.01 - - - - 0.24 0.02
MAPD–WDIR - - - - - - 0.21 0.02 - -
MAPD–WDSP 0.18 0.03 - - 0.37 less than 0.01 - - - -
MAPD–WVHT - - - - - - - - 0.24 0.02
MDPD–WDIR 0.17 0.03 0.31 0.03 - - - - - -
MDPD–WVHT - - 0.20 0.03 0.17 0.03 0.44 less than 0.01 0.43 less than 0.01
WDIR–WDSP - - - - - - 0.16 0.04 - -
WDIR–WVHT 0.18 0.03 0.27 0.04 - - - - - -
WDSP–WTMP - - - - 0.25 0.02 - - - -
WDSP–WVHT - - - - - - - - 0.21 0.03
Figure 3.Relationships between (A) summer mean water temperature (WTMP) and
mean air temperature (ATMP), (B) winter mean wind direction (WDIR) and barometric
pressure (BAR) , and (C) winter mean wave height (WVHT) and gust speeds
(GUST) between 1982 and 2015.
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Annual and seasonal trends in NAO indices
Despite considerable inter-annual variability, NAO has generally been declining
since 1982, with significant (P < 0.05) trends observed during annual and summer
periods (Fig. 4). Although also trending negatively, the data showed substantially
more inter-annual variability during winter, spring, and fall, with indices shifting
from positive to negative values.
Relationships between AOC variables and NAO
When I plotted NAO indices against AOC variables on the various temporal
scales, there were few significant correlations (Table 3, Fig. 5). The exception was
BAR, which exhibited significant positive relationships with NAO on an annual
and seasonal basis (winter, spring, and fall). In other words, the declining trends in
BAR were associated with the declining NAO values. The only other correlation
Figure 4. Annual and seasonal trends in NAO indices between 1982 and 2015.
Table 3. R2 values between annual and seasonal AOC variables and corresponding NOA indices (P
values for statistically significant results in parentheses). Each AOC value represents the same timeframe
as the associated NOA value (i.e., the correlation between ATMP and winter NAO is the correlation
between winter ATMP and winter NAO).
AOC
variables Annual NAO Winter NAO Spring NAO Summer NAO Fall NAO
ATMP 0.09 0.01 0.05 0.15 0.00
BAR 0.38 (less than 0.01) 0.34 (less than 0.01) 0.24 (0.01) 0.16 (0.03) 0.57 (less than 0.01)
GUST 0.03 0.00 0.13 0.07 0.02
MAPD 0.15 0.02 0.08 0.01 0.06
MDPD 0.00 0.01 0.01 0.02 0.11
WDIR 0.01 0.01 0.06 0.00 0.03
WDSP 0.03 0.07 0.16 0.03 0.03
WVHT 0.02 0.06 0.00 0.01 0.33 (0.01)
WTMP 0.08 0.01 0.08 0.12 0.00
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that emerged was between WVHT and NAO in the fall season, which exhibited a
negative relationship (correlation value of -0.57).
Discussion
The AOC variables examined in this analysis have exhibited substantial changes
since 1982, and seasonal responses were frequently more pronounced than annual
trends. Air temperature over the ocean has risen markedly, particularly in the summer
(by 2 °C), which mirrors air-temperature trends across the northeastern US. The
strong correlation between ATMP and WTMP (R2 > 0.9) indicates a close association.
That this correlation was so strong is somewhat surprising given that WTMP is
also affected by ocean currents from other areas. It is noteworthy that this data buoy
is situated over Georges Bank in relatively shallow water and might be more responsive
to air temperatures. It is also possible that the reduced wind strength in the
spring may be enhancing the onset of thermal stratification in subsequent months
by limiting the extent of vertical mixing that would otherwise cool surface waters.
The summer/fall increase in WVHT is difficult to explain given that this trend does
not correspond with higher winds. However, it may be that larger waves are being
generated from well beyond this particular location. The contemporaneous increase
in MPDP (particularly maximum daily values) suggests that long-period swell from
other regions may be playing a role in this change.
With the exception of fall WVHT, NAO indices were significantly correlated
with only BAR. Barometric pressure showed consistent declines on most temporal
scales, and this relationship was associated with a negative trend in NAO. The eastern
US tends to experience wetter weather with stronger storms during the winter
when the NAO is in a positive phase, primarily due to increased upper-level winds
(Hurrell et al. 2003). A weak NAO promotes a strengthened jet stream that would
otherwise pull weather systems into the Atlantic Basin. Under these circumstances,
it is possible that a weak summertime NAO contributes to heat buildup over the
eastern US and, as air rises rapidly over land, a frequent lowering of offshore barometric
pressure as well. In the same way, increases in summer ATMP and WTMP
Figure 5. Relationships between mean North Atlantic Oscillation (NAO) indices
and barometric pressure (BAR) (A) annually and (B) in the fall between 1982 and
2015.
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may also be linked to declining summertime NAO, and the R2 values for these
relationships were somewhat higher than other variables. Notwithstanding, there
are other atmospheric and oceanic cycles such as the Atlantic Meridional Overturning
Circulation (AMOC), the Atlantic Multidecadal Oscillation (AMO), and the
Arctic Oscillation (AO) that each play a role in AOC along the east coast of North
America. However, it is not known whether continued greenhouse-gas–induced
climate change may force these processes into a particular pattern (Goodkin et al.
2008, Paeth et al. 1999, Rind et al. 2005, Schlesinger and Ramankutty 1994).
Regardless of the underlying mechanisms, which may be exceedingly complex,
many of the observed trends are similar to those reported in other studies. Overall
global sea-surface temperatures have been increasing for some time (Blunden et al.
2013, Cane et al. 1997, Kaplan et al. 1998), despite the large amount of geographic
variation due to both local and large-scale factors (Burrows et al. 2011). As mentioned
previously, annual mean water temperature at Woods Hole, on Cape Cod,
MA, increased by 1.7 °C between 1960 and 2002 (Nixon et al. 2004). Likewise, the
waters of Newfoundland and Labrador have been warming since the 1950s, with
extremely high temperatures occurring in the late 1990s (Colbourne 2004). Wave
heights have been increasing in both the North/Northeast Atlantic and North Pacific
(Dodet et al. 2010, Gulev and Grigorieva 2006, Trends 2000) and the North Sea
(Grabemann and Weisse 2008). Moreover, wave heights in the Northeast and North
Atlantic are projected to increase in the future (Kushnir et al. 1997, Mori et al. 2010,
Wang and Swail 2001, Wang et al. 2004).
Negative trends in BAR have similarly been reported in the polar regions, the
North Pacific Ocean, and Alaska (Gillett et al. 2003, Walsh et al. 1996, Wendler and
Shulski 2009). The BAR reduction reported here may in part be due to rising air temperatures,
as the former tends to descend as warm air rises, although there has been
no discernible long-term trend in the frequency and intensity of coastal storms in this
region during this century (Hanna et al. 2008, Zhang et al. 2000). Changes in global
wind speeds have gone in both directions, although notable reductions have been reported
in several areas near Georges Bank (Young et al. 2011) and in southern New
England (Pryor et al. 2009, Vautard et al. 2010). In this study, wind speed showed seasonal
differences with a significant reduction in the spring contrasted by an increase
(albeit statistically insignificant) in the fall. Interestingly, summer wind direction also
rotated significantly to the west, which could have an influence on waves, currents
(and hence, sediment transport), and upwelling events along the coastline.
Changes in ocean conditions proximal to Cape Cod could alter the physical
and biological structure and function of its coastal ecosystems. Increasing water
temperatures can affect phytoplankton (Beaugrand and Reid 2003, Hallegraeff
2010, Townsend et al. 1994), zooplankton (Beaugrand and Reid 2003, Brodeur et
al. 1999, Hays et al. 2005, Richardson 2008, Roemmich and McGowan 1995), fish
abundance and distributions (Battin et al. 2007, Cheung et al. 2010, Kennedy 1990,
Knights 2003, Roessig et al. 2004), fish migration (Beaugrand and Reid 2003),
the abundance of sharks (e.g., Carcharodon carcharias L. [Great White Shark];
Adams et al. 1994), and cetacean food supplies (MacLeod 2009). Warmer surface
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waters enhance thermal stratification and therefore impact primary and secondary
productivity (Behrenfeld et al. 2006, Boyd and Doney 2002, Keller et al. 1999,
Roemmich and McGowan 1995). Major changes in species distribution and abundance
in North Pacific marine ecosystems have been correlated with climatic shifts
in the twentieth century (Chen and Hare 2006, Overland and Wang 2007, Peterson
and Schwing 2003, C. Zhang et al. 2004). Similarly, Perry et al. (2005) reported
species-distribution changes in the Northeast Atlantic, and Pershing et al. (2015)
suggest that sea-surface warming in the Gulf of Maine is linked to declining Gadus
morhua L. (Atlantic Cod) abundance. Warmer water temperatures can also facilitate
the spread of certain marine diseases (Lejeusne et al. 2010) and invasive species
(Carlton 2000, Stachowicz et al. 2002). On a broader scale, estuarine and coastal
systems could experience northward shifts of cold-tolerant species and range expansions
of warm-tolerant species. All of these potential effects could have strong
economic impacts on Cape Cod, where a large portion of the economy is driven by
commercial/recreational fishing and ecotourism (e.g., whale watches; Georgianna
and Amaral 2000, O’Connor et al. 2009).
From the standpoint of physical processes, increasing wave heights can have
substantial impacts on the rate of coastal erosion (K. Zhang et al. 2004). Moreover,
the changes in barometric pressure revealed in this study are important because a
decrease in atmospheric pressure of ~1 hPa translates to a 1-cm increase in seasurface
elevation (Weisse 2010). In effect, declining BAR has accounted for up
to 6–21% of sea-level rise during the last several decades (Smith 2016), and the
latter has already had substantial impacts on salt-marsh ecosystems (Donnelly
and Bertness 2001, Smith 2015, Warren and Neiring 1993) and coastal erosion
(Leatherman et al. 2000) in this region. It is well known that stronger thermal stratification
(from elevated sea-surface temperatures) can influence internal circulation
(e.g., water-column mixing). Higher water temperatures may even translate to an
increased moderating effect on the climate of the Cape Cod peninsula, as well as
the occurrence and severity of droughts. Notably, recent droughts in the US (e.g.,
1996, 1999–2002) have been linked to warming of the North Atlantic (McCabe et
al. 2004).
This study has certain limitations given that I analyzed data from only 1 offshore
weather station. Thus, the trends reported only pertain to the near vicinity of this
station. As mentioned previously, however, long-term oceanographic data from
this region are extremely scarce. The nearest alternate station (24 nautical miles
east of Provincetown) began collecting data in 2002, and all others in the vicinity
have even smaller datasets. Although these trends in AOC variables represent a relatively
short time period of ~3 decades, and it is unknown whether these trends will
persist, they are important to ecosystems operating on much shorter time scales. As
such, they may impact Cape Cod’s coastal communities that are greatly affected by
physical and biological processes within the coastal environment (fish and shellfish
communities, erosion, sediment transport, etc.).
It is noteworthy that this analysis revealed a strong seasonal component to the
changes because certain variables exert the greatest effect on ecosystems at certain
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times of year. For example, many variables (e.g., ATMP, WTMP) experienced the
largest shifts during the summer months, which are most often associated with
key biological processes (e.g., phytoplankton productivity, fish distributions, saltmarsh
plant growth). Furthermore, some of the observed changes may be relevant
in the context of ecological and physical thresholds. If such thresholds are exceeded
with higher frequencies, there may be increasing impacts on coastal and oceanic
ecosystems (Harley et al. 2006, Walther 2010). Notwithstanding, it is reasonable to
assume that these multidecadal annual and seasonal shifts in AOC variables could
influence myriad processes, including shoreline change, bluff erosion, strength of
thermoclines, and the biological structure and functioning of the nearshore marine
environment of Cape Cod.
Acknowledgments
This work was supported by the National Park Service, Cape Cod National Seashore.
Special thanks to the National Oceanographic and Atmospheric Administration for providing
public data.
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