Seasonal change of water content in the atmosphere over the West Siberia on the basis of remote sensing using ENVISAT (ESA) D. Trochkine, V. Pavlov, I. Sutorikhin, A. Romanov, N. Bezuglova, G. Zinchenko Institute for water and environmental problem SB RAS Russia, 656038, Barnaul, Molodezhnaya st., 1, e-mail: dtroshkin@iwep.asu.ru This work was supported by European Space Agency (ESA) provided access to MERIS (ENVISAT) data under the grant #4747.
ENVISAT 2
Instruments onboard ENVISAT 3
MERIS overview The Medium Resolution Imaging Spectrometer (MERIS) instrument produces multispectral images (in 15 selected spectral bands between 390 nm and 1040 nm) obtained in a downward viewing pushbroom imaging gmanner. The 15 bands acquire radiance in the visible and near infra-red bands. MERIS measurement data are used to derive information including: ocean color parameters in open waters such as chlorophyll and coastal waters parameters such as chlorophyll, dissolved organic matter, and suspended solid matter concentrations, characteristics of clouds, such as top pressure and optical thickness, the presence of vegetation and derived indices to characterize vegetation vigor, and atmosphere parameters such as aerosol optical thickness, aerosol type, and water vapor column contents. 4
MERIS Instrument Characteristics (wavelengths) Centre (nm) Bandwidth (nm) Use 412.5 10 Yellow substance and detrital pigments 442.5 10 Chlorophyll absorption maximum 490 10 Chlorophyll and other pigments 510 10 Suspended sediment, red tides 560 10 Chlorophyll absorption minimum 620 10 Suspended sediment 665 10 Chlorophyll absorption and fluo. reference 681.25 7.5 Chlorophyll fluorescence peak 705 10 Fluo. reference, atmospheric corrections 753.75 7.5 Vegetation, cloud 760.625 3.75 O 2 R-branch absorption band 775 15 Atmosphere corrections 865 20 Vegetation, water vapour reference 885 10 Atmosphere corrections 900 10 Water vapour, land 5
Geolocation and connections with meteo parameters Clouds and water vapor set (Low resolution) Geolocation 6
Basis for studying of clouds water content For studying water content of clouds we analyzed distribution of cloud optical thickness on the number of pixels with clouds. Water content LWP depends on optical thickness of clouds directly by equation τ=3lwp/2ρr ef, where ρ - water density, and r ef -effective radii of cloud droplets. For the LWP estimations common value of = 13 μm were used (revised value 12 μm). Preliminary type of the distribution function over the West Siberia (limited by 66 0-87 0 E longitude, and 52 0-72 0 N latitude) were established. 7
Example of LWP over West Siberia on August 10, 2008 Latitude 72 69 Салехард 65 61 Ханты-Мансийск Александровское 1-65 65-130 130-195195 195-260 260-347 347-433 433-563 563-737 737-910 >910 57 53 66 Омск Томск Новосибирск Барнаул 71 76 81 86 Longitude 8
Data selection 9
Study of spatial characteristics 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 1 1 2 2 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 11 8 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 10
Example of selection of area with different distribution ib i of Clouds Optical Thickness 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 87 88 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 97 98 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 11
Distribution of Cloud Optical Thickness logarithm on the number of pixels with clouds 0.50 N 0.40 0.30 4x4_point_24 Total 4x4_point_5 4x4_point_44 4 0.20 010 0.10 0.00 Lg(τ) 0.00 0.50 1.00 1.50 2.00 2.50-0.10 12
Comparison of 4 x4 area distribution with 4 included 2 x2 distributions 0.40 N 0.35 0.30 0.25 4x4 87 88 97 98 0.20 0.15 0.10 0 0.05 000 0.00 Lg(τ) 0.00 0.50 1.00 1.50 2.00 2.50-0.05 13
0.50 N 0.40 0.30 Comparison of 4 x4 area distribution with 16 included 1 x1 distributions 0.20 416 4x4 350 351 352 353 371 372 373 374 392 393 394 395 413 414 415 0.10 0.00 Lg(τ) 000 0.00 050 0.50 100 1.00 150 1.50 200 2.00 250 2.50-0.10 14
Study of temporal characteristics 1 N Portion of Cloud-free pixels 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 2008_04_08 2008_04_17 15
Monthly averaged portion of cloud- free pixels over West Siberia N 07 0.7 0.6 05 0.5 0.4 03 0.3 0.2 01 0.1 0 16
Distribution of Water Vapor Content logarithm on the number of pixels without ih clouds 0.7 april N may 0.6 june july august 05 0.5 september 0.4 0.3 0.2 0.1 January Jl July october november december january february march april may june 0 Lg(W) 0 0.5 1 1.5 2 2.5 17
Variation of water vapor content (W, g/m 2 ) over the West Siberia 2.5 Averaged lg(w) Averaged Lg(W) Averaged W 2 1.5 60 Averaged Water vapour content W(g/m 2 ) 50 40 30 1 20 0.5 0 Month 10 0 18
Distribution of Cloud Optical Thickness logarithm on the number of pixels with clouds 0.25 april may N june july august september 0.2 october november december january february march april may 0.15 june 0.1 0.05 0 Lg(τ) 0 0.5 1 1.5 2 2.5 19
Variation of Cloud Optical Thickness (τ) over the West Siberia 80 τ Averaged τ Averaged Lg(τ) 70 60 50 40 30 20 2.6 Lg(τ) 2.4 2.2 2 18 1.8 1.6 1.4 1.2 1 20
Reproducibility of Clouds Optical Thickness Distribution 0.25 0.2 June 08 June 09 0.25 0.2 May 08 May 09 May 09(14 31) 0.15 0.15 0.1 0.1 0.05 0.05 0 0 0.5 1 1.5 2 2.5 0 0 0.5 1 1.5 2 2.5 21
Seasonal change of water content in the atmosphere over the West Siberia g/m2 700 600 av LWP av W Total 500 400 300 200 100 0 Total content is considering portions of Cloud and Cloud-free Pixels!!! 22