patrickbdevaney/mia9 · Datasets at Hugging Face

text stringlengths 0 6.44k
Assessment Report (AR5) [8] including projections of global sea level rise based on different
Representative Concentration Pathway (RCP) scenarios reflecting possible future concentrations
of greenhouse gases1
. RCP 8.5, also known as the business-as-usual scenario, is the highest emission
and warming scenario under which greenhouse gas concentrations continue to rise throughout the
21st Century, while RCP 6.0 and RCP 4.5 expect substantial emission declines to begin near 2080 and
2040, respectively.
The IPCC sea level rise scenarios are comprehensive, but do not include contributions from a
rapid collapse of Antarctic ice sheets. However, recent evidence suggests that such a collapse may
be underway [6,7]. In addition, the IPCC projections do not account for local processes such as land
uplift/subsidence and ocean circulation and do not provide precise estimates of the probabilities
associated with specific sea level rise scenarios.
A contemporary study that does estimate local effects and comprehensive probabilities for the
RCP scenarios is provided by Kopp et al. [9] based on a synthesis of tide gauge data, global climate
models and expert elicitation, including contributions from the Greenland ice sheet, West Antarctic ice
sheet, East Antarctic ice sheet, glaciers, thermal expansion, regional ocean dynamics, land water storage
and long-term, local, non-climatic factors, such as glacial isostatic adjustment, sediment compaction
and tectonics. Even though this model includes contributions from the Antarctic ice sheets, these
contributions are from dynamic equilibrium models and do not yet account for an incipient rapid
collapse as noted above. Nonetheless, we find the Kopp et al. [9] projections to be among the most
mature and useful sea level rise paradigms and base our South Florida projections on their results at
Vaca Key, Florida.
South Florida Sea Level Rise Projection
Examination of local sea level rise projections around South Florida finds small differences
between Naples, Virginia Key, Vaca Key and Key West. We chose the Vaca Key station sea level data
as representative of South Florida since they best reflect local oceanographic processes that influence
coastal sea levels [10].
Next, we select the RCP scenario that best fits our understanding for future greenhouse gas
emissions. Although significant effort is aimed at global emission reduction, atmospheric CO2 and
emissions continue to escalate [11], and there is presently no clear socio-economic driver to depart
from a carbon-based energy infrastructure. Further, recent assessments of global energy production
and population conclude that the the achievement of emission scenarios corresponding to a desired
2
◦C limit in global mean temperature increase require the global fraction of Renewable Energy Sources
(RES) to reach 50% by 2028 [12].
We note that the International Energy Agency (IEA) reports that global RES could reach 28%
by 2021 [13]. This is consistent with a 2015 estimate of 24% RES by the United Nations [14] and,
if accurate, would leave seven years to achieve a near doubling to 50% to meet the Jones and
Warner [12] constraint. Currently, RES is dominated by hydropower, a resource that is not easily
scalable or quick to bring online. In the absence of a technological breakthrough, we conclude it is
unlikely that global RES will reach 50% by 2028. This leads us to expect that the RCP 4.5 emission
scenario is unobtainable and that there is significant uncertainty as to whether the RCP 6.0 scenario
can be realized. We therefore restrict our projection to the RCP 8.5 scenario.
1 The number following RCP quantifies the expected thermodynamic radiative forcing relative to pre-industrial values.
For example, RCP 8.5 denotes an additional 8.5 W/m2
thermal forcing from greenhouse gases.
J. Mar. Sci. Eng. 2017, 5, 31 4 of 26
Finally, we select conservative projection probabilities appropriate for informing authorities of
anticipated sea level rise for adaptation and planning purposes. In light of the significant uncertainties
inherent in the generation of the projections and future climate dynamics, it is prudent to consider
the upper percentile range of projections leading us to select the RCP 8.5 median (50th percentile) as
the lower boundary and the 99th percentile as the upper boundary. Although the high projection is
deemed to have a 1% chance of occurrence under current climate conditions and models, in the event
of Antarctic ice sheet collapse, this high projection is consistent with estimates of the Antarctic ice melt
contribution [15].
The resultant sea level rise projection for South Florida referenced to the North American Vertical
Datum of 1988 (NAVD88, Appendix A) is shown in Figure 2 and tabulated in Appendix B. Projection
starting points have been offset to coincide with observed mean sea level in Florida Bay over the
period 2008–2015 (Appendix C). The projection does not incorporate local processes such as tides,
storm surges, waves or their non-linear interactions with inundation impacts, issues that are discussed
in Appendix D.
Figure 2. South Florida sea level rise projection with respect to 2015 mean sea level in Florida Bay for
the RCP 8.5 greenhouse gas emission scenario. Units are cm NAVD88. Low projection is the median
(50th percentile); high projection the 99th percentile. Tides and storm surges are not included in this
projection. Values are tabulated in Appendix B to year 2120.
2.2. Inundation Coverage
Geospatial inundation coverages for mean sea level are created in ArcMap by application of the
sea level rise projections for the years 2025, 2050, 2075 and 2100 across southern Florida. Topographical
elevations are based on a synthesis of the best available high-resolution digital elevation data [16] with
variable spatial resolution, but a nominal horizontal grid cell size of 50 m. The resulting inundation
coverages represent a static land-masking of mean sea level at the four time horizons and do not
represent influences from tides, seasonal oceanographic cycles, teleconnections, weather, such as
storms, or inverse barometric adjustments, as discussed in Appendix D, or for changing morphological
structure in submerged and inundated sediments or hydraulic connectivity [17]. A review of these
issues and how the dynamic effects of sea level rise interact with low-gradient coastal landscapes can
be found in Passeri et al. [18].
2.3. Water Level and Salinity
Water levels are obtained from eight hydrographic stations operated by Everglades National
Park over the period 1 June 1994–31 December 2016 with station locations and names shown in
Table 1. Water levels are collected at 6-, 15- or 60-min intervals by WaterLog shaft-encoded float gauges
recorded by a Sutron SatLink2 data recorder. Water levels are then aggregated into daily mean values
as shown in Figure 3.
J. Mar. Sci. Eng. 2017, 5, 31 5 of 26
Salinity is estimated from specific conductivity measured at 30- or 60-min intervals by a YSI
600R Water Quality Sonde and application of the International Equation of State of Seawater 1980
and Practical Salinity Scale 1978 as recommended by the United Nations Educational, Scientific and
Cultural Organization (UNESCO) Joint Panel on Oceanographic Standards and Tables [19]. Daily
mean salinities are shown in Figure 4, and summary statistics of the water level and salinity time series
are presented in Table 2.
Figure 3. Daily mean water level with respect to the National Geodetic Vertical Datum of 1929
(NGVD29) at 5 stations in Florida Bay and the southern Everglades. Stations BK (a) and LM (b) are in
Florida Bay; stations TR (c), E146 (d) and TSH (e) are within Taylor Slough.
Figure 4. Daily mean salinity at 3 stations in Florida Bay. The horizontal line at 35 ppt represents
nominal seawater salinity. (a) MK; (b) BK; (c) LM.
J. Mar. Sci. Eng. 2017, 5, 31 6 of 26
Table 2. Station time series statistics.
Station Location Water Level (m) NGVD Salinity (ppt)
min mean max σ min mean max σ
BK Buoy Key −0.12 0.29 1.03 0.109 9.94 35.91 66.07 5.70
LM Little Madeira Bay −0.03 0.31 0.89 0.110 3.70 22.92 48.76 8.02

Assessment Report (AR5) [8] including projections of global sea level rise based on different

Representative Concentration Pathway (RCP) scenarios reflecting possible future concentrations

of greenhouse gases1

. RCP 8.5, also known as the business-as-usual scenario, is the highest emission

and warming scenario under which greenhouse gas concentrations continue to rise throughout the

21st Century, while RCP 6.0 and RCP 4.5 expect substantial emission declines to begin near 2080 and

2040, respectively.

The IPCC sea level rise scenarios are comprehensive, but do not include contributions from a

rapid collapse of Antarctic ice sheets. However, recent evidence suggests that such a collapse may

be underway [6,7]. In addition, the IPCC projections do not account for local processes such as land

uplift/subsidence and ocean circulation and do not provide precise estimates of the probabilities

associated with specific sea level rise scenarios.

A contemporary study that does estimate local effects and comprehensive probabilities for the

RCP scenarios is provided by Kopp et al. [9] based on a synthesis of tide gauge data, global climate

models and expert elicitation, including contributions from the Greenland ice sheet, West Antarctic ice

sheet, East Antarctic ice sheet, glaciers, thermal expansion, regional ocean dynamics, land water storage

and long-term, local, non-climatic factors, such as glacial isostatic adjustment, sediment compaction

and tectonics. Even though this model includes contributions from the Antarctic ice sheets, these

contributions are from dynamic equilibrium models and do not yet account for an incipient rapid

collapse as noted above. Nonetheless, we find the Kopp et al. [9] projections to be among the most

mature and useful sea level rise paradigms and base our South Florida projections on their results at

Vaca Key, Florida.

South Florida Sea Level Rise Projection

Examination of local sea level rise projections around South Florida finds small differences

between Naples, Virginia Key, Vaca Key and Key West. We chose the Vaca Key station sea level data

as representative of South Florida since they best reflect local oceanographic processes that influence

coastal sea levels [10].

Next, we select the RCP scenario that best fits our understanding for future greenhouse gas

emissions. Although significant effort is aimed at global emission reduction, atmospheric CO2 and

emissions continue to escalate [11], and there is presently no clear socio-economic driver to depart

from a carbon-based energy infrastructure. Further, recent assessments of global energy production

and population conclude that the the achievement of emission scenarios corresponding to a desired

2

◦C limit in global mean temperature increase require the global fraction of Renewable Energy Sources

(RES) to reach 50% by 2028 [12].

We note that the International Energy Agency (IEA) reports that global RES could reach 28%

by 2021 [13]. This is consistent with a 2015 estimate of 24% RES by the United Nations [14] and,

if accurate, would leave seven years to achieve a near doubling to 50% to meet the Jones and

Warner [12] constraint. Currently, RES is dominated by hydropower, a resource that is not easily

scalable or quick to bring online. In the absence of a technological breakthrough, we conclude it is

unlikely that global RES will reach 50% by 2028. This leads us to expect that the RCP 4.5 emission

scenario is unobtainable and that there is significant uncertainty as to whether the RCP 6.0 scenario

can be realized. We therefore restrict our projection to the RCP 8.5 scenario.

1 The number following RCP quantifies the expected thermodynamic radiative forcing relative to pre-industrial values.

For example, RCP 8.5 denotes an additional 8.5 W/m2

thermal forcing from greenhouse gases.

J. Mar. Sci. Eng. 2017, 5, 31 4 of 26

Finally, we select conservative projection probabilities appropriate for informing authorities of

anticipated sea level rise for adaptation and planning purposes. In light of the significant uncertainties

inherent in the generation of the projections and future climate dynamics, it is prudent to consider

the upper percentile range of projections leading us to select the RCP 8.5 median (50th percentile) as

the lower boundary and the 99th percentile as the upper boundary. Although the high projection is

deemed to have a 1% chance of occurrence under current climate conditions and models, in the event

of Antarctic ice sheet collapse, this high projection is consistent with estimates of the Antarctic ice melt

contribution [15].

The resultant sea level rise projection for South Florida referenced to the North American Vertical

Datum of 1988 (NAVD88, Appendix A) is shown in Figure 2 and tabulated in Appendix B. Projection

starting points have been offset to coincide with observed mean sea level in Florida Bay over the

period 2008–2015 (Appendix C). The projection does not incorporate local processes such as tides,

storm surges, waves or their non-linear interactions with inundation impacts, issues that are discussed

in Appendix D.

Figure 2. South Florida sea level rise projection with respect to 2015 mean sea level in Florida Bay for

the RCP 8.5 greenhouse gas emission scenario. Units are cm NAVD88. Low projection is the median

(50th percentile); high projection the 99th percentile. Tides and storm surges are not included in this

projection. Values are tabulated in Appendix B to year 2120.

2.2. Inundation Coverage

Geospatial inundation coverages for mean sea level are created in ArcMap by application of the

sea level rise projections for the years 2025, 2050, 2075 and 2100 across southern Florida. Topographical

elevations are based on a synthesis of the best available high-resolution digital elevation data [16] with

variable spatial resolution, but a nominal horizontal grid cell size of 50 m. The resulting inundation

coverages represent a static land-masking of mean sea level at the four time horizons and do not

represent influences from tides, seasonal oceanographic cycles, teleconnections, weather, such as

storms, or inverse barometric adjustments, as discussed in Appendix D, or for changing morphological

structure in submerged and inundated sediments or hydraulic connectivity [17]. A review of these

issues and how the dynamic effects of sea level rise interact with low-gradient coastal landscapes can

be found in Passeri et al. [18].

2.3. Water Level and Salinity

Water levels are obtained from eight hydrographic stations operated by Everglades National

Park over the period 1 June 1994–31 December 2016 with station locations and names shown in

Table 1. Water levels are collected at 6-, 15- or 60-min intervals by WaterLog shaft-encoded float gauges

recorded by a Sutron SatLink2 data recorder. Water levels are then aggregated into daily mean values

as shown in Figure 3.

J. Mar. Sci. Eng. 2017, 5, 31 5 of 26

Salinity is estimated from specific conductivity measured at 30- or 60-min intervals by a YSI

600R Water Quality Sonde and application of the International Equation of State of Seawater 1980

and Practical Salinity Scale 1978 as recommended by the United Nations Educational, Scientific and

Cultural Organization (UNESCO) Joint Panel on Oceanographic Standards and Tables [19]. Daily

mean salinities are shown in Figure 4, and summary statistics of the water level and salinity time series

are presented in Table 2.

Figure 3. Daily mean water level with respect to the National Geodetic Vertical Datum of 1929

(NGVD29) at 5 stations in Florida Bay and the southern Everglades. Stations BK (a) and LM (b) are in

Florida Bay; stations TR (c), E146 (d) and TSH (e) are within Taylor Slough.

Figure 4. Daily mean salinity at 3 stations in Florida Bay. The horizontal line at 35 ppt represents

nominal seawater salinity. (a) MK; (b) BK; (c) LM.

J. Mar. Sci. Eng. 2017, 5, 31 6 of 26

Table 2. Station time series statistics.

Station Location Water Level (m) NGVD Salinity (ppt)

min mean max σ min mean max σ

BK Buoy Key −0.12 0.29 1.03 0.109 9.94 35.91 66.07 5.70

LM Little Madeira Bay −0.03 0.31 0.89 0.110 3.70 22.92 48.76 8.02