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xii | |
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xv | |
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xvii | |
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xix | |
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xx | |
Foreword |
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xxii | |
Acknowledgements |
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xxiv | |
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xxvi | |
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1 Health priorities in a changing climate |
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1 | (15) |
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1 | (1) |
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2 | (3) |
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1.3 Climate change and the global public health community |
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5 | (6) |
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1.3.1 Climate impacts on infectious diseases |
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5 | (1) |
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1.3.2 Climate impacts and disaster risk reduction |
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6 | (1) |
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1.3.3 Climate impacts on nutrition |
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7 | (1) |
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1.3.4 Impact of food systems on climate and health |
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7 | (1) |
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8 | (1) |
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1.3.6 Universal Health Coverage |
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8 | (1) |
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1.3.7 Climate shocks and conflict |
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9 | (1) |
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1.3.8 The Global Health Security Agenda |
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9 | (2) |
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1.3.9 Breaking down barriers to climate and health collaborations |
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11 | (1) |
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11 | (2) |
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13 | (3) |
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2 Climate impacts on disasters, infectious diseases and nutrition |
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16 | (26) |
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16 | (5) |
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2.2 Hydro-meteorological disasters |
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21 | (3) |
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24 | (3) |
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27 | (8) |
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2.5 Beyond the seasonal climate cycle to multiple timescales |
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35 | (2) |
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2.6 Population vulnerability |
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37 | (1) |
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37 | (5) |
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3 Connecting climate information with health outcomes |
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42 | (17) |
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42 | (1) |
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3.2 Climate information for use in health decision-making |
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43 | (2) |
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45 | (2) |
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3.4 Exploring relationships |
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47 | (3) |
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3.5 Linking climate to health outcomes |
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50 | (5) |
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50 | (3) |
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3.5.2 Mathematical models |
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53 | (2) |
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3.6 Working with uncertain forecasts |
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55 | (1) |
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56 | (3) |
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59 | (30) |
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59 | (1) |
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59 | (23) |
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62 | (4) |
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66 | (1) |
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67 | (4) |
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71 | (3) |
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74 | (1) |
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75 | (1) |
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4.2.7 Other important meteorological parameters |
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76 | (1) |
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76 | (1) |
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4.2.7.2 Geopotential heights |
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76 | (1) |
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77 | (1) |
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4.2.7.4 Sea, land and ice |
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77 | (1) |
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4.2.8 Hurricanes, typhoons and other storms |
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78 | (1) |
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4.2.8.1 Tropical cyclones |
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78 | (2) |
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4.2.8.2 Extratropical cyclones |
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80 | (2) |
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82 | (1) |
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4.3 How can climate be summarized? |
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82 | (5) |
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4.3.1 If weather is what we get, what should we expect? |
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82 | (1) |
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4.3.2 Aggregating weather data |
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83 | (1) |
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4.3.3 How hot is hot? When does dry mean drought? |
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84 | (3) |
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87 | (2) |
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5 Climate variability and trends: drivers |
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89 | (36) |
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89 | (1) |
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5.2 How does climate vary spatially? |
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89 | (16) |
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5.2.1 Climate and altitude |
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90 | (1) |
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5.2.1.1 Temperature and altitude |
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90 | (5) |
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5.2.1.2 Humidity and altitude |
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95 | (1) |
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5.2.1.3 Wind and altitude |
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95 | (1) |
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5.2.1.4 Rainfall and altitude |
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96 | (1) |
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5.2.2 Climate and latitude |
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96 | (1) |
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5.2.2.1 Rainfall and latitude |
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96 | (1) |
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5.2.2.2 Temperature and latitude |
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97 | (2) |
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5.2.3 The effects of land and sea |
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99 | (1) |
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5.2.3.1 Effects on temperature and the seasons |
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99 | (1) |
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5.2.3.2 Effects on humidity and rainfall |
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100 | (1) |
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5.2.4 The effects of land-surface type |
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101 | (1) |
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5.2.4.1 Urban heat islands |
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101 | (1) |
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102 | (1) |
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5.2.5 Climate and spatial scale: How big is a heat wave or, a drought? |
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102 | (1) |
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5.2.5.1 Spatial scales of temperature |
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103 | (1) |
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5.2.5.2 Spatial scales of rainfall |
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104 | (1) |
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5.3 How does climate vary temporally? |
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105 | (8) |
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5.3.1 How does the time of day affect the climate? |
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105 | (1) |
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105 | (1) |
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106 | (1) |
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106 | (1) |
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5.3.2 How long do weather patterns last? |
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107 | (1) |
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5.3.3 What causes the seasons? |
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108 | (1) |
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5.3.4 How do the seasons differ spatially? |
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109 | (1) |
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5.3.5 How much does climate vary? |
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110 | (3) |
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5.4 Why does climate vary temporally? |
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113 | (10) |
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5.4.1 Internal causes of climate variability |
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113 | (1) |
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5.4.1.1 Variability in earth's surface |
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114 | (6) |
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5.4.2 External causes of climate variability |
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120 | (1) |
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121 | (1) |
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5.4.2.2 Solar variability |
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121 | (1) |
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5.4.2.3 Atmospheric composition |
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122 | (1) |
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123 | (2) |
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6 Climate data: the past and present |
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125 | (22) |
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125 | (1) |
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6.2 How are global weather and climate data produced and shared? |
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126 | (4) |
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6.2.1 Global Observing System |
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126 | (2) |
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6.2.2 Global Telecommunication System |
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128 | (1) |
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6.2.3 Global Data Processing and Forecasting system |
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128 | (2) |
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6.2.4 Global Atmospheric Watch |
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130 | (1) |
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6.3 What types of meteorological data are available? |
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130 | (10) |
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6.3.1 Direct measurements from climate stations |
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130 | (1) |
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6.3.1.1 In situ station data |
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130 | (1) |
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6.3.1.2 Gridded station data |
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131 | (1) |
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132 | (1) |
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6.3.2 Indirect measurements of climate by proxy, including by remote sensing |
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133 | (1) |
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6.3.2.1 Historical proxy datasets |
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133 | (1) |
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133 | (1) |
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6.3.2.2.1 Satellite monitoring of rainfall |
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134 | (4) |
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6.3.2.2.2 Satellite monitoring of temperature |
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138 | (1) |
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138 | (1) |
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138 | (2) |
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6.4 What data and information are available? |
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140 | (4) |
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6.4.1 Availability of historical and real-time data |
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140 | (2) |
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6.4.2 Availability of historical and real-time information |
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142 | (2) |
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6.4.2.1 Drought monitoring |
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144 | (1) |
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6.4.2.2 Air chemistry and air quality monitoring |
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144 | (1) |
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144 | (3) |
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7 Weather forecasts: up to one week in advance |
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147 | (28) |
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Carlos Perez Garcia-Pando |
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147 | (1) |
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7.2 Why weather forecasts may be useful to the health community |
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148 | (11) |
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7.3 Why is it so hard to predict the weather beyond a few days? |
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159 | (1) |
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7.4 Given that it is hard, how do forecasters make predictions? |
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159 | (7) |
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162 | (1) |
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162 | (1) |
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163 | (1) |
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163 | (3) |
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166 | (1) |
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7.5 How accurate are weather forecasts? |
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166 | (4) |
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168 | (1) |
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168 | (1) |
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7.5.3 Tropical storms (cyclones, hurricanes and typhoons) |
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168 | (2) |
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7.6 What weather forecasts are available? |
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170 | (2) |
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7.6.1 Watches and warnings of hazardous and inhospitable conditions |
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170 | (1) |
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7.6.2 Forecasts of unhealthy weather |
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171 | (1) |
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7.6.3 Forecasts of suitable weather |
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171 | (1) |
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172 | (3) |
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8 Climate forecasts for early warning: up to six months in advance |
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175 | (24) |
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175 | (2) |
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8.2 How do forecasters predict the next few months? |
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177 | (12) |
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8.2.1 Why is the seasonal climate (sometimes) predictable? |
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178 | (1) |
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179 | (1) |
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8.2.1.1.1 Tropical Pacific Ocean |
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179 | (1) |
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8.2.1.1.2 Tropical Atlantic Ocean |
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180 | (1) |
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8.2.1.1.3 Tropical Indian Ocean |
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180 | (1) |
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8.2.1.1.4 Extratropical oceans |
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181 | (1) |
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181 | (1) |
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181 | (1) |
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8.2.2 How are seasonal forecasts made? |
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181 | (1) |
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8.2.2.1 Empirical prediction |
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182 | (1) |
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8.2.2.2 Dynamical prediction |
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183 | (1) |
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184 | (1) |
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185 | (1) |
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185 | (1) |
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186 | (1) |
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8.2.2.2.5 Post-processing |
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186 | (3) |
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8.3 What seasonal forecasts are available? |
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189 | (4) |
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8.3.1 Global Producing Centres of Long-Range Forecasts |
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189 | (2) |
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8.3.2 Regional Climate Centres and Regional Climate Outlook Forums |
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191 | (1) |
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8.3.3 National meteorological and hydrological services |
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192 | (1) |
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8.3.4 Additional global products |
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192 | (1) |
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8.4 Do seasonal forecasts work well? |
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193 | (2) |
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195 | (4) |
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9 Climate information for adaptation: from years to decades |
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199 | (20) |
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199 | (1) |
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9.2 How increasing concentrations of CO, can impact health |
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200 | (9) |
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9.2.1 Hydro-meteorological disasters |
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202 | (1) |
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9.2.2 Infectious diseases |
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203 | (2) |
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205 | (4) |
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9.3 How climate-change projections are made |
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209 | (4) |
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209 | (2) |
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9.3.2 Multi-annual to multi-decadal prediction |
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211 | (2) |
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9.4 How accurate are multi-annual to multi-decadal forecasts? |
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213 | (2) |
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9.4.1 Climate model errors |
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213 | (1) |
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9.4.2 How accurate are the predictions? |
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214 | (1) |
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215 | (4) |
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10 Climate information for public health action: challenges and opportunities |
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219 | (16) |
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219 | (1) |
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10.2 Climate services for health |
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220 | (4) |
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10.3 Advances in technology |
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224 | (4) |
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10.4 Institutional arrangements |
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228 | (2) |
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10.5 Education and training |
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230 | (3) |
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233 | (2) |
Index |
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