Time commitment

Monitoring
Sea Level
Rise in
Panama
ENVR 451: Research in Panama
Final Internship Report
Submitted to Professors Rafael
Samudio and Roberto Ibanez
April 27, 2011
Associated organisation
Smithsonian Tropical Research Institute
Supervisor
Dr. Rachel Collin
Address:
MRC 0580-08
Unit 9100 Box 0948
DPO AA 34002-9998
USA
Telephone: +507 212-8766
FAX: +507 212-8790
E-mail: [email protected]
Acknowledgements
I appreciated the help from my supervisor Rachel Collin and from Sergio Dos Santos who
supported me throughout this project, answered my numerous questions and attended to
my problems in the data analysis process. I wish to thank professors Rafael Samudio and
Roberto Ibanez and Kecia Kerr for their feedback. A special thank you goes to Tanya Tran
and Olivier Pahud for sharing their statistical and computing expertise. Thank you to McGill
University and the Smithsonian Tropical Research Institute for giving me the opportunity
to undertake this project.
Time commitment
Period: January 2011 – April 2011
Total number of hours allotted to research and analysis: 160
Equivalent number of work days: 20
2
Table of Contents
Index of Tables and Figures ______________________________________________________________________ 4
Executive Summary – English ____________________________________________________________________ 5
Executive Summary – Spanish ____________________________________________________________________ 6
1. Host Institution Information ___________________________________________________________________ 7
2. Introduction _____________________________________________________________________________________ 8
2.1. Justification ___________________________________________________________________________ 8
2.2. Tide Gauges ___________________________________________________________________________ 8
2.3. Study Sites _____________________________________________________________________________ 9
3. Objectives ______________________________________________________________________________________ 10
4. Hypothesis _____________________________________________________________________________________ 10
5. Method _________________________________________________________________________________________ 10
5.1. Data set selection and acquiring of data ___________________________________________ 10
5.2. Formatting of the data ______________________________________________________________ 11
5.2.1. STRI Physical Monitoring Stations _______________________________________ 11
5.2.2. JASL & PSMSL _____________________________________________________________ 11
5.3. Analysis ______________________________________________________________________________ 11
5.3.1. Relative Monthly Average Sea Level _____________________________________ 11
5.3.2. Extreme events ____________________________________________________________ 12
5.4. Ethics _________________________________________________________________________________ 12
6. Results _________________________________________________________________________________________ 12
7. Discussion ______________________________________________________________________________________ 17
7.1. Recommendations for further analysis ____________________________________________ 18
8. Conclusion _____________________________________________________________________________________ 19
9. Bibliography ___________________________________________________________________________________ 20
10. Annexes _______________________________________________________________________________________ 21
Annex 1: Tide gauge platform in Bocas del Toro ______________________________________ 21
Annex 2: Example of tide gauge mechanism ___________________________________________ 22
Annex 3: Aquatrak sensor _______________________________________________________________ 22
Annex 4: RLR diagram for Cristobal ____________________________________________________ 22
3
Index of tables and figures
Table 1: Dataset information; sea level trend, standard error and P-value _________________ 16
Table 2: Extreme tide trend, standard error and P-value ____________________________________ 17
Figure 1: Map showing location of monitoring stations chosen for this study _______________ 9
Figure 2: Relative monthly average sea level for the Atlantic Ocean ________________________ 13
Figure 3a: Relative monthly average sea level for the Pacific Ocean _________________________ 14
Figure 3b: Relative monthly average sea level for the Pacific Ocean (continued) __________ 15
Figure 4: Relative monthly extreme tides ______________________________________________________ 17
4
Executive Summary
Monitoring Sea Level Change in Panama
Author: Claudia Atomei
Host Institution: Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Roosvelt
Ave., Tupper Building – 401, Balboa, Ancón, Panamá, República de Panamá.
Sea level change is a source of increasing concern for environmental scientists
everywhere. Numerous studies suggest that in most parts of the world, sea levels are rising
and there are doing so at increasingly rapid rates. The consequences of sea level rise are
quite extensive, starting with changes in the morphology of coastal environments which in
turn affect the resident plant and animal communities and continuing with impacts on
human populations due to increased flooding, erosion and submersion of the coastal land.
In view of these outcomes, it is of foremost importance to try and understand the
mechanisms driving sea level change by monitoring the environment and analysing the
patterns of change to allow for the development of effective mitigation strategies.
The goal of the present study is to analyse sea level measurements taken by tide
gauges at six different stations along both the Atlantic and Pacific coasts of Panama to
determine the trends of sea level change at those specific locations. Datasets from 3 sources
were acquired for the analysis: data from Bocas del Toro and Colon were obtained from the
STRI Physical Monitoring Program; data from Cristobal, Balboa, Naos and Puerto Armuelles
were taken from the databases of JASL and PSMSL.
The regression analysis performed on the datasets showed an increase in sea levels
for all the stations on the Atlantic coast, an increase for two stations out of the three Pacific
coast stations, with the last station showing a decrease in sea levels. To test for a change in
the magnitude of extreme events, the highest recorded value from each month was taken
from the Bocas and Galeta datasets. The analysis yielded a positive trend for both stations.
The results from this analysis for the Atlantic coast seem to follow the hypothesized
trends. On the Pacific coast, the dataset for Puerto Armuelles from JASL between the years
1983 and 2001 is the only one that matches with the conclusions given in the Fourth
Assessment Report. The shorter datasets show a higher acceleration in sea level rise than
the longer datasets and could hint towards acceleration in sea level rise rates in the past 10
years at these stations. Uncertainty due to the measurement method is to be taken into
account.
Suggested research for further analysis include working out a common reference
point for the tide gauge measurements to allow the merging of datasets from the same
station and the computing of a trend for each of the two oceans as well as a total trend for
Panama. Comparisons with measurements of tides, wind, rain and of temperature recorded
at the same location would allow to understand how much of sea level change can be
explained by atmospheric events and how much can be attributed to a thermal expansion
and changes in land ice. A more extensive look at extreme events could lead into
discussions about climate change.
5
Resumen Ejecutivo
Seguimiento de la elevación del mar en Panamá
Autor: Claudia Atomei
Institución hospedante: Instituto Smithsonian de Investigaciones Tropicales, Apartado postal
0843-03092, Ave. Roosevelt, Edificio Tupper -. 401, Balboa, Ancón, Panamá, República de Panamá.
El cambio del nivel del mar es una fuente de creciente preocupación para los científicos
del medio ambiente en todas partes. Numerosos estudios sugieren que en la mayor parte del
mundo, los niveles del mar están subiendo y lo hacen a ritmo cada vez más rápido. Las
consecuencias de la subida del nivel del mar son muy amplias, a partir de los cambios en la
morfología de los ambientes costeros que a su vez afectan a las plantas y animales residentes y
continuando con los impactos sobre las poblaciones humanas debido al aumento de las
inundaciones, la erosión y la sumersión de las tierras costeras. En vista de estos resultados, es
de la mayor importancia de tratar de comprender los mecanismos que inducen el cambio del
nivel del mar por el seguimiento del medio ambiente y el análisis de los patrones de cambio
para permitir el desarrollo de estrategias eficaces de mitigación.
El objetivo del presente estudio es analizar las mediciones del nivel del mar tomadas por
los mareógrafos en seis estaciones diferentes a lo largo de ambas costas del Atlántico y del
Pacífico de Panamá para determinar las tendencias del cambio del nivel del mar en esos lugares
específicos. Conjuntos de datos fueron adquiridas de 3 fuentes para el análisis: los datos de
Bocas del Toro y Colón se obtuvieron del Programa de Monitoreo de STRI física, los datos de
Cristóbal, Balboa, Naos y Puerto Armuelles se tomaron de las bases de datos de JASL y PSMSL.
El análisis de regresión realizado sobre los conjuntos de datos mostraron un aumento
del nivel del mar para todas las estaciones en la costa del Atlántico, un aumento en dos
estaciones sobre las tres estaciones de la costa del Pacífico, con la última estación que muestra
una disminución del nivel del mar. Para probar si un cambio en la magnitud de los fenómenos
extremos ocurre, el valor más alto de cada mes se tomó de los conjuntos de datos de Bocas y
Galeta. El análisis arrojó una tendencia positiva para ambas estaciones.
Los resultados de este análisis para la costa del Atlántico parecen seguir las tendencias
de la hipótesis. En la costa del Pacífico, el conjunto de datos para Puerto Armuelles de JASL
entre los años 1983 y 2001 es el único que coincide con las conclusiones que figuran en el
Cuarto Informe de Evaluación de IPCC. Los conjuntos de datos más cortos muestran una mayor
aceleración en la subida del nivel del mar que los conjuntos de datos más largos y podría
indicar la aceleración del ritmo de aumento del nivel del mar en los últimos 10 años en estas
estaciones. La incertidumbre por el método de medición debe ser tomada en cuenta.
Investigaciones adicionales pueden incluir la elaboración de un punto de referencia
común para las mediciones de mareógrafos para permitir la fusión de los conjuntos de datos de
la misma estación y la calculación de una tendencia para cada uno de los dos océanos así como
una tendencia total por Panamá. Las comparaciones con las mediciones de las mareas, el
viento, la lluvia y la temperatura registrados en el mismo lugar permitirían entender la
envergadura del cambio del nivel del mar que puede ser explicada por fenómenos atmosféricos
y en qué medida se le puede atribuir a la expansión térmica y los cambios en la cubierta de
hielo. Una mirada más amplia sobre los eventos extremos podría dar lugar a debates sobre el
cambio climático.
6
1. Host Institution Information
The Smithsonian Tropical Research Institute (STRI) was established in Panama
since the beginning of the construction of the Canal in the early 1900s. The first research
station was set on the Barro Colorado Island which has now become one of the most
studied biological reserves of the tropics. Research in diverse domains such as
archaeology/anthropology, conservation, ecology and evolution is presently sustained by
38 resident scientists and around 900 visiting scientists from all over the world. Its mission
is to “increase understanding of the past, present and future of tropical biodiversity and its
relevance to human welfare.” STRI has four main research centers: Barro Colorado Island,
Galeta Marine Laboratory, Punta Culebra and Bocas Del Toro Research Center on Isla
Colon. Activities undertaken by the institution include: research programs; academic
programs (pre-graduate, graduate and postgraduate students); internships; field courses;
conservation forum and classes; visitor centers.
The supervisor for this project is Dr. Rachel Collin. She is the director of the STRI
Bocas Del Toro Research Station since 2002. She studies the evolutionary history of marine
gastropods in the Collin Lab on Isla Naos, in Panama City. More specifically, she looks at
dispersal strategies, sex changes and their implications for evolutionary life histories of
benthic marine invertebrates.
7
2. Introduction
“The global average sea level has risen since 1961 at an average rate of 1.8 [1.3 to 2.3]
mm/yr and since 1993 at 3.1 [2.4 to 3.8] mm/y”.
- IPCC Fourth Assessment Report
2.1 Justification
Sea level change is a source of increasing concern for environmental scientists
everywhere. Sea level rise causes changes in the morphology of shorelines, disrupts fragile
environments such as wetlands, marshes, beaches and barrier islands through increased
erosion and inundation (Vellinga and Leatherman 1989). These changes affect the
terrestrial biodiversity of these areas due to the loss of habitat. Human livelihoods are also
impacted due to floods and loss of land. It is therefore of crucial importance to understand
the variability of sea level. Data from tide gauges is easily acquired and analysed and
although it does not provide a precise measure of absolute sea level change as can be
obtained from satellite altimetry, benefits can be derived from the analysis of data from
individual stations. The results obtained at a small scale can be further integrated into
larger scale studies, at mega-regional levels to gain better understanding of the nature of
sea level change (Dias and Taborda 1992) with the purpose of developing better mitigation
methods.
2.2 Tide Gauges
Tide gauges are installations that measure relative sea level at a specific point along
the shoreline. They are usually secured on piers or on platforms a few meters off shore
(Annex 1). Their mechanism can vary with the station but most commonly, they are either
made up of a well containing a floating device tied to a wire and an electronic device that
8
records the length of the string or they use a sensor (Annex 3) that sends a pulse in the
direction of the water, within a PVC pipe, and records the time it takes for the signal to
come back up (Annex 2). The latter is the modern standard. Depending on the station,
measurements are taken with a frequency of 15 minutes or one hour. To be able to use the
measurements made by tide gauges, benchmarks or reference points need to be set up.
Every tide gauge has a system of benchmarks which allows for periodic surveys of the
surrounding environment. This is necessary for insuring that the tide gauge is stable with
respect to the land, for reasons of accuracy, and to provide information for the calculation
of mean sea level (EPA 2009). An example of diagram showing the reference point system
for the tide gauge in Cristobal, on the Atlantic coast, can be seen in Annex 4.
2.3. Study Sites
Three monitoring stations were chosen on the coast of each ocean. They are not
evenly distributed because most Panamanian stations are situated close to the Panama
Canal out of the necessity of monitoring the physical environment surrounding it.
Fig. 1 - Map showing location of monitoring stations chosen for this study
9
3. Objectives
The objectives of this internship were to organise and analyse sea level data from
STRI monitoring stations for the purpose of this study and for future use by scientists and
to look at trends of sea level change around Panama and write a short scientific paper
describing the results of the analysis.
4. Hypothesis
Based on past studies of sea level change such as the IPCC Fourth Assessment
Report, it was hypothesised that an increase in sea level and in height of high tides
(extremes) will be observed from data collected by tide gauges on the Atlantic coast of
Panama while a decrease will be observed on the Pacific coast.
5. Method
5.1. Data set selection and acquiring of data
The first step was to research what organisations freely provide tide gauge data
recorded around Panama, especially from the Pacific coast. These would be used to
complement the data coming from the two STRI physical monitoring stations on the
Atlantic coast in Bocas del Toro and in Colon that were already provided to me along with
its metadata by my supervisor and Sergio Dos Santos in raw data format. The raw data as
well as the metadata from the other four selected sited was downloaded from two other
sources, the Joint Archive for Sea Level (JASL) and Permanent Service for Mean Sea Level
(PSMSL). An index of the data was created to keep track of the different datasets and of the
related metadata.
10
5.2. Formatting of the data
All datasets were imported into Microsoft Excel, scanned and cleaned of outliers and
faulty data points as described in the metadata for each of the sets. Further formatting
varies with source of dataset.
5.2.1. STRI Physical Monitoring Stations
The raw data recorded by the sensors needed to be formatted in such a way to give
a measure of average sea level. Using schematics of the tide gauge mechanisms, the
formulas (2.3252 - wdist) x 100 and (2.2672 - wdist) x 100, where wdist is the value
recorded by the sensor, were determined for the Bocas and Galeta datasets respectively
and were used for obtaining the average sea level in cm from the original data. The data
was then converted to units of mm.
The data was rearranged to allow for calculation of monthly averages. Where there
were multiple, non overlapping datasets available for one station, they were combined to
create a timeline. Months with 7 or more days worth of data missing were flagged to be
later excluded from the analysis. This measure was taken to follow the formatting of the
JASL data and to allow for the standardization of datasets.
5.2.2. JASL & PSMSL
Where there were multiple, non overlapping datasets available for one station, they
were combined to create a timeline.
5.3. Analysis
5.3.1. Relative Monthly Average Sea Level
Each dataset was imported into JMP8 where linear and non-linear regression plots
were created. The plot that gave the most significant trend for each dataset was kept. The
11
slope of the linear regression was recorded as well as the p-value for each plot. Standard
error was calculated in Microsoft Excel.
5.3.2. Extreme events
To test for a change in frequency of extreme events, the highest recorded value from each
month was taken from the Bocas and Galeta datasets. A regression analysis was performed
on these 2 new datasets. The slope of the trend, its standard error and the p-value were
recorded.
5.4. Ethics
This project was carried out following the McGill University Code of Ethics.
6. Results
Out of the twelve datasets analysed, three did not yield statistically significant
results (P>0.05) (Table 1). All of these three datasets come from the same station on the
Pacific coast of Panama, Puerto Armuelles. All stations on the Atlantic coast showed
increasing trends in sea levels (Fig. 2). Most stations on the Pacific coast showed increasing
trends in sea levels except for Puerto Armuelles which shows a decreasing trend (Fig 3a
and 3b.).
The analysis of magnitude of extreme events yielded increasing trends at both STRI
stations (Fig. 4) and can be considered statistically significant (Table 2).
12
a.
13
25
37
49
61
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
1
b.
Cummulative months - January 2005 to December 2010
c.
1
Cummulative months - January 1907 to December 2010
d.
61 121 181 241 301 361 421 481 541 601 661 721 781 841
Cummulative months - January 1909 to December 1980
1
13
25
37
49
61
73
85
97
109
Cummulative months - January 2002 to December 2010
Fig. 2 - Relative monthly average sea level (mm). Regression plots for stations on the coast of the Atlantic
Ocean. (a) BocasSTRI2005-2010, (b) CristobalJASL1907-2010, (c) CristobalPSMSL1909-1980, (d)
GaletaSTRI2002-2010. Each gridline represents a 5 year span.
13
a.
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1
61
121
181
241
301
361
421
481
541
601
661
721
781
841
901
961
1021
1081
1141
1201
b.
Cummulative months - January 1908 to December 2003
Cummulative months - January 1907 to December 2010
c.
1
d.
61
121
181
241
301
361
421
Cummulative months - January 1961 to December 1997
1
61
121
181
241
301
361
421
481
541
Cummulative months - January 1949 to December 1995
Fig.3a - Relative monthly average sea level (mm). Regression plots for stations on the coast of the Pacific
Ocean. (a) BalboaJASL1907-2010, (b) BalboaPSMSL1908-2003, (c) NaosJASL1961-1997, (d)
NaosPSMSL1949-1995. Each gridline represents a 5 year span.
14
e.
13 25 37 49 61 73 85 97 109 121 133 145 157
1
13
25
37
49
61
73
85
97
109
121
133
145
157
169
181
193
205
217
1
f.
Cummulative months - January 1955 to December 1968
g.
Cummulative months - January 1983 to December 2001
1
13
25
37
49
61
73
85
97
109
121
133
145
157
169
181
193
205
h.
Cummulative months - January 1951 to December 1968
1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181
Cummulative months - January 1983 to December 1998
Fig.3b - Relative monthly average sea level (mm). Regression plots for stations on the coast of the Pacific
Ocean. (e) PArmuellesJASL1955-1968, (f) PArmuellesJASL1983-2001, (g) PArmuellesPSMSL1951-1968, (h)
PArmuellesPSMSL1983-1998. Each gridline represents a 1 year span.
15
Atlantic Ocean
Pacific Ocean
Station
Name
Dataset
source
Year Range
Total #
months
# Months with
≥ 7 missing
days
Sea Level
Trend
(mm/month)
Sea Level
Trend
(mm/year)
Standard
Error
P-value
Bocas
STRI
2005-2010
72
16
1.149
13.788
44.696
0.0017
Cristobal
JASL
1907-2010
1248
104
0.1322
1.5861
48.516
<0.0001
Cristobal
PSMSL
1909-1980
864
0
0.1193
1.4313
41.016
<0.0001
Galeta
STRI
2002-2010
108
40
1.1423
13.707
49.228
<0.0001
Balboa
JASL
1907-2010
1248
35
0.1291
1.5494
112.7
<0.0001
Balboa
PSMSL
1908-2003
1152
8
0.1251
1.5011
111.29
<0.0001
Naos
JASL
1961-1997
444
321
0.1648
1.9773
109.23
0.0022
Naos
PSMSL
1949-1995
564
273
0.1063
1.2759
99.276
0.0021
Puerto
Armuelles
JASL
1955-1968
168
19
-0.099
-1.193
58.947
0.3259
Puerto
Armuelles
JASL
1983-2001
228
3
-0.277
-3.324
88.042
0.0021
Puerto
Armuelles
PSMSL
1951-1968
216
12
0.0108
0.1294
62.454
0.8764
Puerto
Armuelles
PSMSL
1983-1998
192
2
-0.214
-2.566
85.304
0.0557
Table 1 - Dataset information; sea level trend (slope of linear regression line), standard error and
P-value.
16
a.
1
b.
13
25
37
49
61
Cummulative months - January 2005 to December 2010
1
13
25
37
49
61
73
85
Cummulative months - Janurary 2002 to December 2010
Fig.4 - Relative monthly extreme tides (mm). Regression plots for STRI stations on the coast of the
Atlantic Ocean. (a) BocasSTRI2005-2010, (b) GaletaSTRI2002-2010. Each gridline represents a 1 year span.
Station Name
Bocas
Galeta
Extreme tide trend
(mm/month)
1.372219
2.476677
Extreme tide trend
(mm/year)
16.466628
29.720124
Standard Error
P-value
57.7056748
65.2765221
0.0039
<0.0001
Table 2 - Extreme tide trend (slope of regression line for the highest tides for each month), standard
error and P-value.
7. Discussion
The IPCC Fourth Assessment Report states that satellite measurements indicate an
increase in sea levels for the Atlantic Ocean and a fall in sea levels for the eastern Pacific
Ocean. The results from this analysis for the Atlantic coast seem to follow the hypothesized
trends. On the Pacific coast, the dataset for Puerto Armuelles from JASL between the years
1983 and 2001 is the only one that matches with the conclusions given in the Fourth
Assessment Report. The tests made with the two STRI datasets to examine the trends in the
17
extreme events seem to show an increase in magnitude corresponding to IPCC’s
characterisation of the increased intensity of these events as likely.
Although the analysis mostly yielded expected results, there are a few sources of
error that need to be taken into account. Because of the nature of the measurement system,
there are uncertainties introduced in the calculations. These uncertainties come partially
from the sensor itself, and from the movement of the tide gauge platforms, which are
currently not considered to be the most accurate methods for measuring sea level.
Additionally, breaks in installations occur quite often and this causes gaps in datasets. The
major source of error in these results is the short length of most datasets. In order to make
a confident conclusion about the magnitude of sea level change, datasets of at least 30 years
are required for the analysis. While the datasets used for this study ranged between 104
and 6 years, half were shorter than 30 years. The shorter datasets from the STRI
monitoring stations show a higher acceleration in sea level rise than the longer datasets.
This could indicate that sea level rise rates have actually been accelerating in the past 10
years at these stations but it is impossible to conclude anything about the causes of this
acceleration. Further analysis and consideration of other factors involved is required.
7.1. Recommendations for further analysis
Due to limitations in time and expertise, only a partial analysis of the datasets was
possible. The next step in this study would be to work out a common reference point for
the tide gauge measurements to allow the merging of datasets from the same station and
the computing of a trend for each of the two oceans as well as a total trend for Panama. This
would permit a comparison between the rate of sea level change in the Atlantic and Pacific
oceans. A number of additional computations can be made from the data to isolate the
18
variability caused by atmospheric changes by subtracting the values of tidal predictions
from the values recorded by the tide gauges. The residual value could be compared with
measurements of wind, rain and of temperature recorded at the same location to
understand how much of sea level change can be explained by atmospheric events such as
changes in wind and ocean circulation patterns and how much can be attributed to a
thermal expansion and changes in land ice. A more extensive look at extreme events,
including all 6 stations could also lead into a discussion about climate change. Finally, the
results from the analysis on the tide gauge data could be compared to data obtained by
satellite altimetry for the same locations.
8. Conclusion
Although it is difficult to set a common reference point for different tide gauge
datasets and though tide gauges do not provide the most accurate measurements of sea
level, it was possible to distinguish expected trends from analysing data available to the
general public. It is important to highlight the value of small scale analysis of
environmental change not only because it can supply local biodiversity and developmental
studies with information but also because it provides a basis for larger, global scale studies
that can help the international decision-making process concerning the mitigation of
climate change.
19
9. Bibliography
Bindoff, N.L.; Willebrand, J.; Artale, V.; Cazenave, A.; Gregory, J.; Gulev, S.; Hanawa, K.; Le
Quere, C.; Levitus, S.; Noijiri, Y.; Shum, C.K.; Talley, L.D.; and Unnikrishnan, A., 2007.
Observations: oceanic climate change and sea level. In: Solomon, S., et al. (eds.),
Climate Change 2007: The Physical Science Basis, Intergovernmental Panel on
Climate Change. Cambridge: Cambridge University Press. Can be accessed at:
<http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter5.pdf>
Dias, J.A. and Taborda, R. 1992. Tidal gauge data in deducing secular trends of relative sea
level and crustal movements in Portugal. Journal of Coastal Research 8(3): 644-659.
Smithsonian Tropical Research Institute official website. Last accessed on April 27, 2011.
Can be accessed at: < http://www.stri.si.edu/>
United States Environmental Protection Agency. 2009. Report on the Environment: Sea
Level. Last accessed on April 27, 2011. Can be accessed at:
<http://cfpub.epa.gov/eroe/index.cfm?fuseaction=detail.viewMeta&ch=50&lShowI
nd=0&subtop=315&lv=list.listByChapter&r=216636>
Vellinga, P. and Leatherman, S.P. 1989. Sea Level Rise, Consequences and Policies. Climatic
Change 15: 175-189.
20
Annexes
Annex 1: Images of the tide gauge platform in Bocas del Toro.
21
Annex 2: Example of tide gauge mechanism
Annex 3: Aquatrak sensor
Annex 4: Example of RLR (revised local reference) diagram from Cristobal. PBM: permanent
benchmark; TGZ: tide gauge zero; MSL: mean sea level.
22