

contaminants, 322 



data bases, 197 



desert areas, Fig. IX-3, 291 



for tundra vegetation, 313, Fig. IX-16 



forest land, 205, 292, 300, 307 

 tropics, Fig. IX-10 



storage in rocks, 203 



tropical areas, 187, 188 

 Water use, 198, l°o-200 

 Water vapor 



as pollutant, 337 



disease carrier, Fig. X-21 



atmosphere-ocean system, 66, t>7, 71 



hail clouds, 152 



heat balance of the earth and, 287, 288 



hurricanes, 131 



in clouds, 331, 337 



in pure air, 329 



precipitation, Fig. VI-2 



storm forecasting, 138 



tornado models, 139 



urban area weather, 119 

 Watersheds 



forest areas, 20e, 209, 211, 212 



lakes, 273 



northern hardwood, 293-295 

 Waterspouts, 144, 147 

 Waves 



data, 78, 80 



hurricanes, 127, 128 



induced turbulence, 108-112, Fig. IV-10 



kinds 



gravity, 106, 111 

 Kelvin-Helmholtz, 109, 110, 111 

 Kelvin type, 255 



lakes, 254, 255, 256, 259 



models, 81 



ocean-surface, Fig. IV-2 

 Weasels 



in food chain, Fig. IX-6 



tundra ecosystem, Fig. IX-16 

 Weather, 62 



prescribed tire and, 311 



urban-induced change, 119 



see also Radar 

 Weather forecasting, Fig. IV-9 



anomalies, 87, 88 



climatology, 103 



data base, 90-92, 93, Fig. IV-7, Fig. IV-8, 

 98, 103 



extrapolation method, 93, 94, 95, 97 



for fishing industry, Fig. VIII— 7 



models, 93, 94, 95, 96, 97, 102 

 extended periods, 99, 105 



role of oceanography, 82, 100 



short-range, 94-96, 101-104 



tropical areas, 184, 189 



storms and hurricanes, 187 



urban-induced changes, 114, 115 

 Weather modification 



at airfields, 101 



environmental management, 283 



hail, 151 

 hurricanes, 126 

 lightning, 158, 190-161 

 tornado windspeed, 145, 146 

 urban-induced, 113-120, Fig. IV-11 

 see also Climate: control; Precipitation: 

 modification 

 Weather stations, 137, 138, 146 

 Weatherald, Richard T., 67, t>9 

 Weddell Sea, Antarctica, 84, 232 

 Weddell Seal, 232 

 Wegener, Alfred E., Fig. II-4 

 Well drilling, 203 

 Welland Canal, 261, 2c2 

 Weller, N., 139 

 Wells, Philip V., 73 

 West Germany, 181 

 West Indies, Lesser Antilles, 42, 134 

 West Virginia, 133 

 Western hemisphere 



dust from Africa and, 191 

 model of sea-level pressure, Fig. III-6 

 Whales, 232, 241 



in food chain, Fig. VIII-6 

 management of stocks, 245-24o 

 source of food, 240, 242 

 Wheat, 216, 217, 220, 289 

 White Mountains, Cal., el 

 White Mountains, N.H., 293 

 Whitefish 



food fish, 227 



Great Lakes, 261, 262, 263, 264 

 Lake Washington, 271 

 WHITETOP, Project, 170, 171, 172 

 WHO, see World Health Organization 

 Wilderness reserves 



see Isle Royale ecosystem 

 Williams, Roger J., 376 

 Wilmington, Cal., 203 

 Wind 



distribution 



in tornado vortices, 138 

 tornado models, 139 

 flow patterns 



atmospheric pollutants and, 335, 336, 



344, 360 

 climatic change and, 56, 100 

 drought, 165 



fog dispersal operations, 180 

 forecasting, 102, 104 

 hailstorms, 149 

 models, 89, 95 

 monsoons, 184 

 sea-surfaces and, 78, 86 

 severe storms, 125, 129, 130, 135, 138 

 tropical areas, 188 

 urbanization and, 113, 114, 116 

 water circulation, 254, Fig. VIII-12 

 weather modification systems, 174 

 shear, turbulence and, 108 

 speed 



atmospheric pollution, 347, Fig. X-10 



climatic records, 51 



cloud seeding, 176 



factor in plant growl: :. 



forest fires, 306, 310 



hailstorms, 149, 150, Fig. V-13 



hurricanes, 123, 127-128 



tornadoes, 137, 144-145, 14o 

 tunnels 



air pollution research, 334 



hail, 150 

 Wind River Basin, Wyo., 31 

 Winter 



dust transport, 191, 192, 193 

 forest fires, 310 

 monsoon winds, 184 

 temperatures, 56, 57, 114 

 Wisconsin, 257, 2o3, 269 

 Wisconsin, University of, 269 

 WIT (wave induced turbulence), 108, 109, 



110, 111, 112 

 WMO, sec World Meteorological 



Organization 

 Wolf, Timber, 302, 304-305 

 Woods, J. D., 106, 109 

 Woods Hole Oceanographic Institution, 



Mass., 3e>l 

 Work capacity, at high altitudes, Fig. XI-4, 



Fig XI-5, 382 

 World Data Centers (Wash., D. C; Moscow, 



U.S.S.R., etc.) : space data 



clearinghouse, 15 

 World Health Organization (WHO), 379, 



380, 385, 388 

 World Meteorological Organization 



(WMO), 91, 100, 185, 188, 340 

 see also Commission for Climatology 

 World Weather Program (WWP), 91 

 World Weather Watch (WWW), 59, 91, 



Fig. IV-7, 100, 101, 190 

 Wright, Sewall, 374 

 WWP, see World Weather Program 

 WWW, sec World Weather Watch 

 Wyoming, 29, 31 



XBT, see Expendable Bathy-Thermographs 

 X-rays, 4, 9, 10, 11, 15 



effects on humans, 325 



fluctuations, 55 



Yanomama Indians, Brazil, 374, Fig. XI-1, 



Fig. XI-2, 378, 379 

 Young's modulus, 203 

 Young, Thomas, 203 



Zinc, 193 



Zooplankton, Fig. VIII— 5 

 in food chain, 234, 237, 240 

 in lakes, 227, 228, Fig. VIII-2, 262 



421 



