Turks and Caicos Islands

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Annual DJF MAM JJA SON Observed Mean 1970-99 Turks and Caicos Islands: Country scale changes in Rainfall Extremes Observed Trend 1960-2006 mm Change in mm per decade A2 A1B B1 A2 A1B B1 A2 A1B B1 A2 A1B B1 A2 A1B B1 3.10. Hurricanes and Tropical Storms Projected changes by Projected changes by Projected changes by the 2020s the 2050s the 2080s Min Median Max Min Median Max Min Median Max Maximum 5-day Rainfall (RX5day) Change in mm Change in mm 28 -14 -1 17 -18 -3 11 -18 0 12 -16 0 29 -13 0 23 -15 -4 18 -9 0 9 -9 1 9 -7 0 9 -9 0 9 -7 -1 8 -8 0 3 -12 -4 14 -18 -7 6 -14 -3 12 -15 -4 13 -8 -1 12 -10 0 25 -16 -3 11 -21 -6 -1 -16 -3 3 -28 -5 0 -13 -2 18 -13 -3 5 -11 -4 13 -18 -2 12 -19 0 12 -13 0 33 -11 0 22 -13 -3 10 Historical and future changes in tropical storm and hurricane activity have been a topic of heated debate in the climate science community. Drawing robust conclusions with regards to changes in climate extremes is continually hampered by issues of data quality in our observations, the difficulties in separating natural variability from long-term trends and the limitations imposed by spatial resolution of climate models. Tropical storms and hurricanes form from pre-existing weather disturbances where sea surface temperatures (SSTs) exceed 26˚C. Whilst SSTs are a key factor in determining the formation, development and intensity of tropical storms, a number of other factors are also critical, such as subsidence, wind shear and static stability. This means that whilst observed and projected increases in SSTs under a warmer climate potentially expand the regions and periods of time when tropical storms may form, the critical conditions for storm formation may not necessarily be met (e.g. Veccchi and Soden, 2007; Trenberth et al., 2007), and increasing SSTs may not necessarily be accompanied by an increase in the frequency of tropical storm incidences. Several analyses of global (e.g. Webster et al., 2005) and more specifically North Atlantic (e.g. Holland and Webster, 2007; Kossin et al., 2007; Elsner et al., 2008) hurricanes have indicated increases in the observed record of tropical storms over the last 30 years. It is not yet certain to what degree this trend arises as part of a long-term climate change signal or shorter-term inter-decadal variability. The available longer term records are riddled with in homogeneities (inconsistencies in recording methods through time) - most significantly, the advent of satellite observations, before which storms were only recorded when making landfall or observed by ships (Kossin et al., 2007). Recently, a longer-term study of variations in hurricane
frequency in the last 1,500 years based on proxy reconstructions from regional sedimentary evidence indicate recent levels of Atlantic hurricane activity are anomalously high relative to those of the last one- and -a -half millennia (Mann et al., 2009). Climate models are still relatively primitive with respect to representing tropical storms, and this restricts our ability to determine future changes in frequency or intensity. We can analyse the changes in background conditions that are conducive to storm formation (boundary conditions) (e.g. Tapiador, 2008), or apply them to embedded high-resolution models which can credibly simulate tropical storms (e.g. Knutson and Tuleya, 2004; Emanuel et al., 2008). Regional Climate Models are able to simulate weak ‘cyclone-like’ storm systems that are broadly representative of a storm or hurricane system but are still considered coarse in scale with respect to modelling hurricanes. The IPCC AR4 (Meehl et al., 2007) concludes that models are broadly consistent in indicating increases in precipitation intensity associated with tropical storms (e.g. Knutson and Tuleya, 2004; Knutson et al., 2008; Chauvin et al., 2006; Hasegawa and Emori, 2005; Tsutsui, 2002). The higher resolution models that simulate storms more credibly are also broadly consistent in indicating increases in associated peak wind intensities and mean rainfall (Knutson and Tuleya, 2004; Oouchi et al., 2006). We summarise the projected changes in wind and precipitation intensities from a selection of these modelling experiments in Table 3.10.1 to give an indication of the magnitude of these changes. With regards to the frequency of tropical storms in future climate, models are strongly divergent. Several recent studies (e.g. Vecchi and Sodon, 2007; Bengtssen et al., 2007; Emanuel et al., 2008, Knutson et al., 2008) have indicated that the frequency of storms may decrease due to decreases in vertical wind shear in a warmer climate. In several of these studies, intensity of hurricanes still increases despite decreases in frequency (Emanuel et al., 2008; Knutson et al., 2008). In a recent study of the PRECIS regional climate model simulations for Central America and the Caribbean, Bezanilla et al., (2009) found that the frequency of ‘Tropical -Cyclone-like –Vortices’ increases on the Pacific coast of Central America, but decreases on the Atlantic coast and in the Caribbean. When interpreting the modelling experiments we should remember that our models remain relatively primitive with respect to the complex atmospheric processes that are involved in hurricane formation and development. Hurricanes are particularly sensitive to some of the elements of climate physics that these models are weakest at representing, and are often only included by statistical parameterisations. Comparison studies have demonstrated that the choice of parameterisation scheme can exert a strong influence on the results of the study (e.g. Yoshimura et al., 2006). We should also recognise that the El Niño Southern Oscillation (ENSO) is a strong and well established influence on Tropical Storm frequency in the North Atlantic, and explains a large proportion of inter-annual variability in hurricane frequency. This means that the future frequency of hurricanes in the North Atlantic is likely to be strongly dependent on whether the climate state becomes more ‘El-Niño-like’, or more ‘La-Niña-like’ – an issue upon which models are still strongly divided and suffer from significant deficiencies in simulating the fundamental features of ENSO variability (e.g. Collins et al., 2005). 29
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Caribbean Regional Headquarters Has
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4.3.4. Women and Youth in TCI Agric
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6.3. Energy Supply and Distribution
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Figure 5.8.2: Relationship status o
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Table 4.1.2: Availability of water
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ACKNOWLEDGEMENTS The CARIBSAVE Part
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The field work components of the re
Page 15 and 16: LIST OF ABBREVIATIONS AND ACRONYMS
Page 17 and 18: UKOT ----------------- United Kingd
Page 19 and 20: Overview Of Climate Change Issues I
Page 21 and 22: The field study sites include notab
Page 23 and 24: coastal infrastructure and settleme
Page 25 and 26: Perceptions of vulnerability in the
Page 27 and 28: Energy and Tourism Tourism is an in
Page 29 and 30: Reviewing and considering the feasi
Page 31 and 32: 4. Local watershed management: supp
Page 33 and 34: Given the importance of tourism to
Page 35 and 36: Marine and Terrestrial Biodiversity
Page 37 and 38: terrestrial habitats for the purpos
Page 39 and 40: 1. GLOBAL AND REGIONAL CONTEXT The
Page 41 and 42: damages from intense climatic condi
Page 43 and 44: 2. NATIONAL CIRCUMSTANCES 2.1. Geog
Page 45 and 46: Table 2.2.1: Gross Domestic Product
Page 47 and 48: Figure 2.2.1 shows a decline in per
Page 49 and 50: oom for expansion of the fin fisher
Page 51 and 52: The CPA points out that the all-inc
Page 53 and 54: Table 3.1.1: Earliest and latest ye
Page 55 and 56: GCM projections of future rainfall
Page 57 and 58: Table 3.3.4: GCM and RCM projected
Page 59 and 60: Relative humidity data has not been
Page 61 and 62: Table 3.6.1: Observed and GCM proje
Page 63 and 64: Annual Table 3.8.1: Observed and GC
Page 65: Annual DJF MAM JJA SON Annual DJF M
Page 69 and 70: thermal expansion, with only a cons
Page 71 and 72: particularly affected by higher wat
Page 73 and 74: Table 4.1.2: Availability of water
Page 75 and 76: 3). Factors which increase the vuln
Page 77 and 78: 4.2. Energy Supply and Distribution
Page 79 and 80: Intergovernmental Panel on Climate
Page 81 and 82: Table 4.2.3: Assessment of CO2 emis
Page 83 and 84: Figure 4.2.3: Evolution of electric
Page 85 and 86: - Reduce electricity costs and pric
Page 87 and 88: Figure 4.2.5: Crude oil prices 1869
Page 89 and 90: Climate policy Figure 4.2.6: Fuel c
Page 91 and 92: taxes can also be a highly transpar
Page 93 and 94: number of potential impacts of clim
Page 95 and 96: 4.3. Agriculture and Food Security
Page 97 and 98: Caicos Islands stems from the fact
Page 99 and 100: Table 4.4.1: Selected statistics re
Page 101 and 102: 2000). Thus, despite the fact that
Page 103 and 104: Table 4.4.3: Reported cases of gast
Page 105 and 106: 4.5. Marine and Terrestrial Biodive
Page 107 and 108: Table 4.5.1: Turks and Caicos Islan
Page 109 and 110: Status of wetlands Over half of the
Page 111 and 112: and enforcing adequate coastal setb
Page 113 and 114: Turtle fishery At least two species
Page 115 and 116: Vulnerability of coral reefs to cli
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Figure 4.5.4: Unusual amount of Sar
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Figure 4.6.1: Grand Turk, The Turks
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Table 4.6.1: Impacts associated wit
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to identify individual properties,
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Figure 4.6.6: Total beach and land
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the tourism sector as well, since t
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Hurricane Irene (2011) Figure 4.7.2
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4.7.3. Vulnerability of the tourism
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greater burden of care as poorer ho
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CLIMATE CHANGE EFFECTS DIRECT INDIR
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Partnership based on the establishe
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each gender group is of the opinion
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entity. One of the key resources ne
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5. ADAPTIVE CAPACITY PROFILE FOR TH
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The institutional and regulatory fr
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5.1.3. Technology Hydrological and
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equested a rate review to rebalance
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Table 5.2.1: Average weighted emiss
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agree that switching off air condit
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Note: Savings costs of energy effic
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Vast options exist to reduce energy
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5.4. Human Health 5.4.1. Policy The
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Table 5.4.1: Summary effects on the
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weaker social infrastructure. Conti
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end the Turks and Caicos Islands ar
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5.5.3. Technology A high degree of
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Table 5.6.1: Summary of adaptation
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5.6.2. Technology - Soft Engineerin
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5.7. Comprehensive Natural Disaster
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Table 5.7.1: Enhanced Comprehensive
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Related work in needs and vulnerabi
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Early Warning Systems (EWS) An EWS
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50% 45% 40% 35% 30% 25% 20% 15% 10%
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distributions based on the gender o
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significant differences in househol
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Table 5.8.13: Source of food supply
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45.0% 40.0% 35.0% 30.0% 25.0% 20.0%
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Social Protection Provision Table 5
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Table 5.8.24: Sample distribution b
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Subsistence Agricultural land (16%)
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Resource Importance River / Stream
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In the event of a hurricane, 90.3%
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Event Hurricane Flooding Storm Surg
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Table 5.8.37: Household Adaptation
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Assessments focussing on the links
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Provide gender disaggregated data a
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Short Term Actions Reassess water p
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Long Term Actions Pursue the concep
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Area Management Foundation (C-CAM)
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6.8. Comprehensive Natural Disaster
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The Fire Service is government-run,
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7. CONCLUSION 7.1. Climate Modellin
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7.3. Energy Supply and Distribution
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7.7. Sea Level Rise and Storm Surge
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REFERENCES Alcamo, J., Moreno, J. M
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CAREC. (2008a). Caribbean Epidemiol
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Contreras-Lisperguer, R., & de Cuba
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http://www.ey.com/Publication/vwLUA
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Government of the Turks and Caicos
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Hu, A., Meehl, G., Han, W., & Yin,
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Lime Turks & Caicos Islands. (2011)
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OECD (2010). Taxation, Innovation a
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Stern, N. (2006). The Economics of
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Wetherell, G. (2010). Third Quarter
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