Variability of the Gulf Stream
Chapter 1
The Problem and Its Setting
Introduction
The Gulf Stream is an extremely important current located in the Atlantic Ocean that carries warm water from the coast of North America towards Europe. The Gulf Stream has a significant impact on the climates of both the southeastern portion of the United States and much of the area in northern Europe. Without the Gulf Stream, northern Europe would be very cold and their economy would be totally different. If the Gulf Stream would drastically change its path, it would greatly affect life in northern Europe and cause significant problems for the world’s economy. The phenomenon known as El Niño has to do with the weakening of westward trade winds causing the warming of the ocean surface temperature. During an El Niño year, the physical relationships between wind, ocean currents, oceanic and atmospheric temperature, and the biosphere break down into pattern changes that impact weather conditions around the world. Clearly, the Gulf Stream is an extremely important geophysical phenomenon and El Niño is an important weather phenomenon and both need to be studied. This chapter will provide an introduction to this research project and focus on the basic goal of this research study.
Problem
The aim of this research
project is to use sea-surface temperature data collected from the Advanced Very
High Resolution Radiometer (AVHRR) which imaged the Atlantic Ocean over a
period of four years to track the path of the north wall of the Gulf
Stream. These data will be used to
determine the variability of the path of the north wall of the Gulf Stream over
time. The geographical positions of the
Gulf Stream will be used to determine the variability of the path of the north
wall of the Gulf Stream for El Niño years compared to a normal years. A previous study determined that the path of
the north wall did change between one normal year and one El Niño year. However, two more years of data will be used
to determine if the variation in the original data was because of El Niño or
because of normal yearly variation.
Hypothesis
From this study we hope to find a correlation between the path of the north wall of the Gulf Stream and time and be able to draw significant conclusions from our data. The hypothesis is that the path of the north wall of the Gulf Stream varies significantly over time between normal years and El Niño years.
Variables and Limitations
Variables:
·
Independent
Variable: Time
·
Dependent
Variable: The location of the north
wall of the Gulf Stream
·
Control: The data from a non El Niño year
·
We
are only measuring the north wall of the Gulf Stream as opposed to measuring
both the north and south walls to get more accurate results.
Limitations:
·
We
used only data from two civilian NOAA satellites instead of gathering data from
military weather satellites as well.
·
We
only studied one current making it impossible to the see the variability of all
currents and the total affect El Niño has on other bodies of water.
·
We
only have access to four years worth of sea-surface temperature data. If we had access to substantially more data
this study could be much more thorough and thus provide us with more conclusive
results on long term changes of climate.
·
Many
of the images of sea-surface temperature data were cloudy and hard to
interpret. The cloudiness led to the
dismissal of many images giving the researchers less data to work with.
Assumptions
·
The
current of the Gulf Stream can be found by using sea-surface temperature
data. Since the Gulf Stream is a
current, defined by flowing water and not temperature, it is impossible to know
if the exact position of the temperature matches the position of water flow of
the Gulf Stream. We assume, however,
that the north wall of the Gulf Stream is defined by the drastic change of
temperature from cold water to warm.
·
The
affects of El Niño are consistent throughout the year and do not vary over the
interval being studied.
Definition of Terms
1. Gulf Stream- warm water mid-Atlantic current flowing from southern Florida to northern Europe.
2. Advanced Very High Resolution Radiometer (AVHRR)- instrument used to measure emitted radiation for an area of about one square kilometer from a NOAA series satellite. This information can then be converted to sea-surface temperature.
3. National Oceanic and Atmospheric Administration (NOAA)- government organization responsible for the weather prediction that puts up the NOAA series of satellites.
Chapter Two
The Review of the Related Literature
Introduction
The Gulf Stream has been a very important and well-studied current for many years. Due to the increased exploration of North America in the early 1500’s the Gulf Stream was discovered and became a very important part of trade and commerce between North America and Europe. In 1513, Ponce de Leon made the first reference to the Gulf Stream after having trouble crossing its path in the area just north of what is now Cape Canaveral. After Ponce de Leon’s discovery, the Gulf Stream became a well-known current to explorers from Europe and provided a fast route to take when returning from the America’s. In the late 1700’s the United States Postmaster-General, Benjamin Franklin, compiled one of the first accurate maps of the Gulf Stream to aid his ships in the delivery of mail between North America and London. Franklin, also, noticed the effect of wind on ocean circulation and came up with the idea of using sea-surface temperature to navigate and track the ocean. The Gulf Stream was at this time regarded as a fixed and stable way to return to Europe. Along with its importance in trans-Atlantic travel, the Gulf Stream controls much of the climate in Northern Europe. By bringing the waters of the Gulf of Mexico to Europe, the Gulf Stream creates warm winds that keep the climate very moderate as opposed to the harsh conditions that exist in corresponding latitudes throughout the world. From this effect on climate, the Gulf Stream therefore has a tremendous impact on the industry in Northern Europe by allowing people there to raise livestock and farm. The Gulf Stream has an enormous influence on climate and economic human life and determining and understanding its path and variability can be extremely useful.
Background
Information
In
the 1960’s, advances in oceanography led to a more thorough study of the Gulf
Stream with more powerful measuring techniques. Multiple ship surveys organized by Fuglister provided the first
systematic description of the spatial structure between Cape Hatteras and the
Grand Banks including the waters north and south of the Gulf Stream. Also, this period presented the first use of
infrared radiation imaging to map the thermal patterns of ocean surfaces from
orbiting satellites. Through the new
application of modern measuring techniques and abundant historical information,
our knowledge of the Gulf Stream has expanded dramatically. This can be seen in Stommel’s classic modern
work on the physical descriptions of the Gulf Stream. The Gulf Stream has been found to be a wind-driven ribbon of high-velocity
water forming the boundary between the warm waters of the Sargasso Sea and the
cooler waters of the continental margin.
The sharp gradient of temperature seen across the Gulf Steam is an
expression of the balance between the horizontal pressure gradient force and
the Coriolis force brought about by wind.
With this understanding of the Gulf Stream it is possible to track its
position through the use of sea-surface temperature data and in turn study its
variability in greater depth. A study was
done in 1998 where it was determined that the north wall of the stream varied
between one normal and one El Niño year.
However it is unknown if these variations were because of El Niño or if
it was just yearly variations.
Importance
Global ocean circulation is
controlled by the “thermohaline” conveyor belt. Wind forces and pressure gradients drive ocean surface
motion. Pressure gradients are formed
by water density, which is in turn determined by temperature (thermo) and salt
concentration (haline). This “conveyor
belt” describes the motion between ocean basins and vertically between the top
and bottom of the ocean. Variability in
ocean circulation can be caused by upsets in the balance of thermohaline
circulation and, by observing variability in an ocean current, major
geophysical changes might be able to be predicted.
Since circulation is a global phenomenon, changes in one area can effect the ocean and atmosphere thousands of kilometers away. Although the El Niño phenomenon has been observed for centuries, it has recently become clear that its effect is worldwide. El Niño’s occur at several year intervals when atmospheric changes cause warm water to spread across the central Pacific. Such changes have been correlated with significant weather changes in North America and Europe. One aim in this research project is to determine if the position of the Gulf Stream changes between an El Niño year and a non-El Niño year. This change could help explain the weather changes already known to exist during an El Niño year. The problem will be distinguishing between typical seasonal variability and changes caused by El Niño.
Much previous work on Gulf Stream variability has been done which suggests a significant variability caused by several different factors. In 1975, Duing used shipboard survey measurements to determine that Gulf Stream variability occurred over 4 to 10 day periods. Likewise, in 1978, Maul et al. observed the Gulf Stream using the Geostationary Operational Environmental Satellite (GOES) to analyze the infrared data and obtain multiyear histories of Gulf Stream meanders. Maul concluded that the meanders of the Gulf Stream were related to variability associated with 4 to 16 day and 40 to 100 day periods of flow. Although these studies provided researchers with the first background information in Gulf Stream variability, there measuring techniques were not advanced and inaccurate. By using point measurements taken from ship surveys, Duing did not have a great deal of data throughout the entire ocean and many errors could have occurred in collecting the data he did receive. Maul used the more advanced method of tracking the Gulf Stream from satellite, but this still presented a problem for his study. By using a geostationary satellite, the data received was low resolution compared to the more advanced orbiting NOAA satellites because of the greater distance from the earth and also the less sensitive radiometer it was equipped with. In addition to the low quality data, Maul might have had a large amount of data for a single day, but did not conduct the research over a long period of time thus limiting his study. These inaccuracies made the studies informative, yet inconclusive and the need for future research became apparent. In 1983, Watts compiled much of the Gulf Stream data already collected from previous studies and found that variations occur over 4 to 14 day and 20 to 60 day periods. Watts suggested that the Gulf Stream had seasonal and yearly changes in the meanders and began to determine reasons for these changes. In studying ocean circulation, Watts attributed the variability of the Gulf Stream to changes in wind patterns, sea-mounts and the interaction with rings that have spun off. None of these causes of Gulf Stream variability are the sole cause and all of these factors along with other unknown factors are probably responsible for Gulf Stream variability. In this study, hopefully an accurate representation of the variability of the Gulf Stream can be found and through the comparison of data from a non-El Niño and an El Niño year the effect of Gulf Stream variability due to El Niño can be determined.
Summary
The aim of this research
project is to use sea-surface temperature data collected from the Advanced Very
High Resolution Radiometer (AVHRR) which imaged the Atlantic Ocean over a
period of four years to track the path of the north wall of the Gulf
Stream. These data will be used to
determine the variability of the path of the north wall of the Gulf Stream over
time. The geographical positions of the
Gulf Stream will be used to determine the variability of the path of the north
wall of the Gulf Stream for El Niño years compared to a normal years. These data will help to determine the effect
of El Niño on the many factors with which it is associated including the
weather in Northern Europe.
Chapter Three
Materials
and Methods
Materials
The
instruments used to measure the sea-surface temperature data were the NOAA-12
and NOAA-14 Advanced Very High Resolution Radiometers (AVHRR). Sea-surface temperature data of the northern
portion of the Atlantic Ocean was collected by Johns Hopkins University Applied
Physics Laboratory Ground Station. The
data is available to the public online at http://fermi.jhuapl.edu/avhrr. From these images we used
a program written in the Interactive Data Language (IDL) that outputs the
corresponding longitude and latitude measurements for a spot on the north wall
of the Gulf Stream.
Methods
Preliminary
Study
A
preliminary study was done on this same subject in 1998. This study collected sea-surface temperature
for the northern portion of the Atlantic Ocean over a period from August 1996
to September 1998 using the NOAA-12, NOAA-14, and NOAA-15 AVHRR. Using an IDL program that converts the click
of the mouse button into longitude and latitude coordinates, the path of the
north wall of the Gulf Stream was extrapolated from the sea-surface temperature
data by clicking on the path where the water temperature jumps from cold water
to warm water. This data was used to
determine that there was a change in the path of the Gulf Stream over a
two-year period.
Procedures
1.
Collected
sea-surface temperature images for the northern portion of the Atlantic Ocean
over a period from August 1996 to September 2000 using the NOAA-12, NOAA-14,
and NOAA-15 AVHRR.
2.
Used
an IDL program that converted the images into longitude and latitude
coordinates from the area where the temperature jumps from cold water to warm
water.
3.
Ran
the program for each day to extrapolate the path of the north wall of the Gulf
Stream from the sea-surface temperature data.
4.
Compared
the resulting data examining the variability of the path of the north wall of
the Gulf Stream with time while examining the effects El Niño had on the
position of the north wall of the Gulf Stream.
Data Collection and Analysis
The position of the Gulf
Stream Current can be found by using sea-surface temperature data. Since the Gulf Stream is a current, defined
by flowing water and not temperature, it is impossible to know if the whole
Gulf Stream is accounted for. We
assume, however, that the north wall of the Gulf Stream is defined by the
drastic change of temperature from cold water to warm water. The Sea surface temperature data were
acquired from sea-surface temperature images collected by NOAA-12, NOAA-14, and
NOAA-15 AVHRR. These data were analyzed
by using the IDL program included in the appendix.
CHAPTER 4
Results
Data
The
raw data for this experiment was obtained by the AVHRR on the NOAA-12 and NOAA-14
satellites, which compiled the data into GIF images, which displayed the
sea-surface temperature of the northern portion of the Atlantic Ocean. The sea-surface temperature images were
obtained for each day over the four-year period from May 1996 to June
2000. These images filled approximately
1000 megabytes worth of data. Using the
IDL program that takes an exact measurement of the location of the north wall
of the Gulf Stream, the measurements were interpreted from the sea-surface
temperature images and compiled into text files. After all of the images had been processed, the data was then
compiled into one large 1048 kilobyte text file which would serve as a basis
for all future statistical calculations.
This is an example of a small portion of the text file:
1996 apr 19
-79.9810 30.7692
1996 apr 19
-78.9924 32.0192
1996 apr 19
-78.0038 32.1795
1996 apr 19
-77.0152 32.8526
1996 apr 19
-76.0266 34.4872
1996 apr 19
-75.0000 35.2244
1996 apr 19
-74.0114 35.9936
1996 apr 19
-73.0228 36.5385
1996 apr 19
-71.9962 37.0513
1996 apr 19
-71.0076 37.4038
1996 apr 19
-70.0190 37.4679
1996 apr 19
-69.0304 37.5641
1996 apr 19
-67.9658 38.4615
1996 apr 19
-67.0152 38.2372
1996 apr 19
-66.0646 37.3077
1996 apr 19
-65.0380 39.1987
1996 apr 19
-64.0114 39.2949
Figure 1 is an example of one the sea-surface
temperature images:
(Figure 1)
Now that all of the raw data has been processed
descriptive statistics can be used to better understand the data and get a
clearer picture of the results of the experiment. From the data the mean and standard deviation for all of the data
(Figures 2 & 7), the first year of data (Figures 3 & 8), the second
year of data (Figures 4 & 9), the third year (Figures 5 & 10), and the
fourth year (Figures 6 & 11) was calculated.
(Figure 2)
(Figure 3)
(Figure 4)
(Figure 5)
(Figure 6)
(Figure 7)
(Figure 8)
(Figure 9)
(Figure 10)
(Figure 11)
After examining the mean position of the north wall
of the Gulf Stream the difference of the mean position between Years 1 through
4 can be calculated (Figures 12-15).
(Figure 12)
(Figure 13)
(Figure 14)
(Figure 15)
Now that the descriptive statistics have been
calculated further analysis of this data is needed to determine if there is
significant variability between the four years.
Data Analysis
To
further analyze the data using inferential statistics the two-sample t-test will be used to determine if the difference
between the four means is significant.
The two-sample t-test can be
performed to make final conclusions about the data. The two-sample t-test
is a test to determine to what degree, if any, the difference between two means
is significant. This test is used to
determine how large 
must be for two means
to be statistically significant and not just a statistical fluctuation. The two-sample t-test is defined as:
(2)
where 
is the mean, 
is the number of
significant measurements and 
is the standard
deviation. The 
in this case in each
year is 25. After calculating the t-values a standardized table of values
can be used to determine the significance of the measurements and either accept
or reject the hypotheses, 
and 
. The following table
(Figure 16) provides t-test results
for each longitude, the critical values, their corresponding levels of
significance and the direction of the variation through the years:
|
Longitude
(d) |
T-test
Value |
1.3
(10%) |
1.7 (5%) |
2.069
(2.5%) |
|
-80 |
0.1005 |
|
|
|
|
-79 |
0.3125 |
|
|
|
|
-78 |
0.2948 |
|
|
|
|
-77 |
0.4433 |
|
|
|
|
-76 |
1.1363 |
|
|
|
|
-75 |
0.6612 |
|
|
|
|
-74 |
0.2776 |
|
|
|
|
-73 |
1.7039 |
x |
x |
|
|
-72 |
1.4470 |
x |
|
|
|
-71 |
1.7420 |
x |
x |
|
|
-70 |
0.3029 |
|
|
|
|
-69 |
0.3621 |
|
|
|
|
-68 |
0.3074 |
|
|
|
|
-67 |
0.4772 |
|
|
|
|
-66 |
0.7129 |
|
|
|
|
-65 |
1.0895 |
|
|
|
|
-64 |
0.2884 |
|
|
|
|
-63 |
0.6521 |
|
|
|
|
-62 |
0.6304 |
|
|
|
|
-61 |
0.2405 |
|
|
|
|
-60 |
0.1284 |
|
|
|
|
-59 |
0.5230 |
|
|
|
|
-58 |
0.4032 |
|
|
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