Facility for Atmospheric Remote Sensing (FARS) Ruby LIDAR Data Archive Instruction 1. Location: Salt Lake City, Utah Latitude: 40¡ 46' 00' N Longitude: 111¡ 49' 38'' W Elevation: 1520 meters above sea level 2. Instrument: Ground based Polarization Cloud Ruby LIDAR 3. Specifications: 2 channels vertical polarization transmitted manually "tiltable" +/- 5 degrees from zenith 0.1 Hz PRF, 7.5 meter maximum range resolution 1-3 mrad receiver beamwidths 25 cm diameter telescope 0.694 micron wavelength 4. Operating Procedure and Measurements: Data is recorded with the FARS Ruby LIDAR system when cirrus clouds are present overhead. Observations usually begin several minutes before the cirrus arrives and is concluded several minutes after the cirrus passes. Data collection normally occurs in periods of 1-3-h in support of the local overpass times of polar-orbiting satellites. The LIDAR is primarily operated in the zenith direction. When conditions are suitable, the instrument is tilted +/- 5 degrees off the zenith to test for horizontally oriented plate crystals. Raw LIDAR backscattered return is recorded for 2 channels containing parallel and orthogonal polarized signals. The time is recorded in Universal Time Coordinate (UTC). 5. Data Processing: Raw LIDAR backscattered return has been processed using system constants to calculate LIDAR relative returned parallel polarized signal (backscatter). The original data set is recorded at a maximum resolution of 0.1 Hz PRF (1 shot per 10 seconds) and 7.5m resolution. 6. Data Recording Errors: Three types of checks were performed to remove data recording errors and assure data quality. I. Background checks - The background is a prepulse that is fired before the main LIDAR signal pulse. The raw background signal is a number between -128 and +127 and consists of 100 points. Three types of background checks are performed. A. Offscale setting - If more than 5 background points are equal to -128 or more than 5 points equal to +127, the signal is considered offscale and the shot is rejected. B. Pretrigger - An average of every 10 background points, up to 80 points, is calculated. If the largest average value is greater than or equal to 1.1 times the smallest average, the shot is rejected. C. Noisy signal - The standard deviation of the first 75 background points is calculated. If the standard deviation is greater than 10.0, the shot is rejected. II. Signal checks - Sometimes there are errors in the signal that are not detected in the background checks. A. No data recorded - The standard deviation of the entire signal is calculated. If the standard deviation is less than 1.0, the shot is rejected. B. Oscilloscope false trigger - This error is detected by finding a fluctuating signal in the first 10 to 20 points of the LIDAR profile. If the signal oscillates several times between positive and negative values and then becomes a straight line, the shot is rejected. III. LIDAR system checks A. Valid power out - If the recorded laser power output is less than 0.5 Joules the shot is rejected. B. Valid photo-multiplier tube (PMT) - If the PMT voltage is less than 0.5 Joules the shot is rejected. 7. Data Format: The data set consists of 9 ASCII data files arranged in chronological order. The file names reflect the date and start and stop times for each file. An example of a file name is: rb92_01010000_0100.1min rbYY_MMDDH1M1_H2M2.1min where YY: year MM: month DD: day H1M1: hour and minute of start time H2M2: hour and minute of stop time Each file contains 10 second LIDAR relative returned backscatter signal (perpendicular channel and parallel channel) at 7.5 meter resolution. The time is recorded in UTC. The format (in ASCII) of file is two parts, first header information, second data information. many shots form the data information. the structure of shot is as following. header info: pmt_ratio Phi base-height high resolution structure of shot: year month day hour minute second (start time of average) year month day hour minute second (end time of average) shot_avg total_shots n_vertical n_angle perpendicular_polarizd_data (n_vertical points) parallel_polarized_data (n_vertical points) where shot_avg: number of shots in the 1 minute average total_shots: total number of shots tested for errors in the 1 minute interval n_vertical: number of points in the vertical n_angle:number of shots in average where the LIDAR axis is tilted off the zenith perpendicular _polarized_data: n_vertical points of data of perpendicular channel where the first point is 7.5 meters above ground level (AGL) and the vertical resolution is 7.5 meters, or since the site is 1520 meters above sea level, the first data point would be 1527.5 meters Mean Sea Level (MSL). parallel_polarized_data: n_vertical points of data of parallel channel where the first point is 7.5 meters above ground level (AGL) and the vertical resolution is 7.5 meters, or since the site is 1520 meters above sea level, the first data point would be 1527.5 meters Mean Sea Level (MSL). NOTE: calculation LDR we use ldr = pmt_ratio*powrofperdicular/powerofparallel ldr =1./ldr -1. ldr = (1.-ldr*phi)/(ldr*(1.+phi)+1.) to calculate linear depolarization ratio we use following data process to get the gif file. 1. use range calibration, that powerof parallel channel*r^2. power1 2. get the maximun valune of whole range calibrated power. maxv=max(power1) 3. power2 = power1/maxv 4. power3 = log(power2), for the non-sense points, power3(i,j)=-40 5. from -40~0, convert into gray scale, then plot we use idl to finish above process ------------------------------------------------------------------------ 8. An example of 1 LIDAR shot, including the header information is: 0.770000 7.00000E-02 1520.00 7.50000 1992 9 8 17 32 16 1992 9 8 17 32 16 1 1 1948 0 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 796 787 793 796 767 752 720 672 637 637 627 611 564 560 551 551 459 494 494 427 487 430 414 446 404 382 347 369 382 341 341 337 344 344 293 331 277 271 296 271 255 283 283 252 261 252 220 213 239 216 204 204 188 178 194 175 197 150 159 169 143 127 162 137 153 143 153 137 143 121 146 140 108 102 121 150 130 143 121 111 102 124 115 92 105 99 108 89 80 102 95 86 95 95 108 83 99 99 86 99 76 86 64 86 73 92 70 86 73 73 80 64 73 60 60 70 76 45 64 48 80 54 67 67 67 51 51 45 67 76 54 35 73 45 57 57 38 57 38 45 41 32 41 51 45 41 45 38 32 51 51 35 45 41 41 54 51 35 35 29 45 35 38 35 35 48 41 35 41 35 41 32 38 45 32 41 22 25 25 22 38 25 32 29 32 25 32 19 19 25 35 38 16 25 22 32 19 35 35 16 29 35 32 29 22 25 16 22 25 22 16 22 29 19 22 29 19 25 25 25 19 32 19 19 19 13 25 13 29 16 16 25 9 16 16 16 16 9 25 13 13 22 16 16 25 25 13 13 13 19 6 9 6 9 16 16 9 13 9 13 9 16 16 6 6 13 9 6 32 25 32 22 22 22 38 48 45 51 38 51 29 25 35 35 41 32 48 35 38 38 51 22 38 35 41 9 19 25 22 25 16 29 22 22 22 6 19 9 13 16 9 6 9 13 9 19 9 19 16 13 13 13 6 13 13 6 9 13 13 9 13 19 3 13 9 9 19 6 16 16 9 19 9 9 9 9 13 13 3 13 9 9 13 13 9 3 9 6 29 22 16 13 13 9 29 32 19 19 13 19 19 16 13 9 13 3 6 13 3 6 3 3 9 3 6 3 3 -6 3 0 3 3 6 0 -3 3 9 -3 9 -6 3 3 13 6 0 3 6 9 6 9 3 6 0 0 -6 3 0 9 -3 3 13 0 6 3 3 0 0 9 0 -3 3 9 9 9 9 0 3 3 16 0 3 6 6 3 6 3 -3 6 -3 13 0 0 9 9 0 -3 -3 3 9 0 0 3 0 9 3 -3 6 -3 3 -3 0 16 3 0 3 0 -3 6 6 0 16 6 0 3 6 3 3 0 6 -6 13 6 6 13 3 3 0 3 3 -3 0 -3 0 0 0 3 6 9 -6 3 6 3 -6 6 0 6 6 -3 0 9 -10 0 6 6 0 6 6 -6 3 -6 3 0 0 3 -6 9 0 3 16 0 0 -3 -3 0 6 3 9 0 0 9 -3 6 3 6 0 -6 -3 0 0 16 6 -10 9 0 -3 -3 -3 6 3 3 0 6 -6 0 0 -3 0 9 6 3 0 -3 3 -6 0 6 6 3 3 -6 -3 0 0 6 3 3 0 3 0 -3 9 0 3 6 -6 -3 0 6 -3 0 9 0 3 -6 13 -3 0 3 0 9 0 3 3 0 0 -3 0 -3 -3 -3 0 -3 -3 -3 3 3 -3 -3 6 -3 -3 0 -6 9 -3 -3 3 -3 -3 3 0 0 6 -3 13 3 0 9 6 6 0 -3 -6 6 -6 0 6 -3 0 3 0 -3 9 0 0 3 -3 -3 3 9 0 0 0 0 3 -3 0 0 -3 -3 3 -3 3 -3 3 3 -3 0 0 -3 0 -3 0 0 0 -6 3 3 0 0 6 -3 6 0 6 0 -3 3 3 13 -6 6 0 6 0 3 -3 6 -3 -3 3 0 0 0 0 9 -3 -3 -10 -3 0 3 0 0 0 3 6 -6 -3 0 -6 0 0 -3 3 -3 3 -6 0 9 3 0 0 3 -10 3 3 -3 -3 -3 -3 0 3 0 3 3 -10 0 9 -3 -3 0 0 0 -3 -3 -3 0 0 0 3 0 -3 -3 3 -10 -3 3 3 0 0 0 -6 0 -6 3 3 0 -3 3 -6 6 -3 -3 -3 3 -3 -6 0 0 9 0 0 3 -3 9 -3 -3 -3 0 6 -10 0 0 -3 -3 6 -3 -6 0 -6 -6 -3 3 0 0 0 -3 0 6 3 -3 -6 -3 -3 3 0 -6 3 -3 -3 9 0 3 6 -3 -3 6 3 3 -3 -3 0 6 3 -6 3 0 0 -3 -3 -3 -3 3 6 0 0 0 0 -3 0 6 -3 -3 -3 3 9 -6 0 -3 0 -3 -3 0 9 3 -6 9 -6 -3 -10 0 3 -6 3 3 -6 6 3 6 3 3 -3 0 3 3 3 9 -3 3 9 0 -3 -6 3 0 -3 3 6 0 6 -3 9 -3 -3 13 0 6 0 0 0 6 0 0 -3 -6 -6 0 3 0 6 3 0 13 3 -6 0 -3 3 3 3 3 -3 -3 3 0 9 0 0 3 6 3 0 -3 3 0 9 6 3 0 -6 -3 0 3 0 3 -3 -3 9 -6 3 3 0 -3 -6 3 0 6 3 9999 0 3 -3 -3 0 0 0 -3 -3 0 0 -3 9999 -3 3 -3 9 9 -6 3 0 0 3 -3 9 0 -6 3 -3 0 0 -6 -3 6 0 3 0 6 0 6 -3 -6 -3 0 3 -3 6 -3 -6 -6 3 6 0 -6 6 -6 0 0 0 -3 3 3 0 -3 3 0 0 -3 3 -6 3 0 3 -3 -3 0 0 -3 0 0 0 3 -3 -3 0 -6 -6 3 3 3 -3 -6 3 3 6 -3 0 0 -3 0 0 6 -3 3 -3 0 0 0 -6 -6 -3 3 -6 9 -3 -3 -6 3 9 -3 -3 0 3 -3 3 -3 3 0 6 6 0 0 3 0 3 3 0 0 0 -6 -10 0 -3 6 9999 3 -3 6 3 -6 -3 3 3 -3 -3 0 3 3 0 3 -3 0 3 3 -3 0 3 3 3 -6 -6 9 -3 9 -3 0 -3 -6 -3 -3 -6 9 -6 6 0 3 0 0 0 -6 3 -6 -3 0 0 -3 0 13 -3 9 0 -6 -3 -3 -3 -3 6 6 0 0 9999 -3 -6 0 -6 0 -6 -3 0 0 0 3 -3 -3 -3 0 6 0 -6 -3 6 6 3 -3 -3 -3 -3 6 -3 0 9 3 -3 0 -6 3 0 -3 9 -6 -3 -3 -3 -3 -3 -6 0 0 -3 0 6 3 3 0 6 0 -6 9 0 6 -3 -3 0 -6 0 6 3 0 0 0 6 0 0 6 0 -3 6 3 -6 0 -3 -6 -3 3 -6 -6 -3 0 3 3 3 0 0 -3 6 3 -3 -3 9999 -3 -3 6 0 0 0 -3 0 -3 0 0 -10 0 0 -3 6 6 3 -3 -3 -3 0 -3 0 6 0 -6 -3 13 -6 3 -3 13 0 3 3 0 -3 0 0 -3 -6 9999 -3 -6 0 3 0 -3 -6 -3 6 -3 -3 6 3 0 0 -3 -3 6 -3 -3 0 0 0 0 9 0 0 3 -3 3 0 0 0 -6 0 3 0 0 0 -3 6 0 -6 -6 6 3 -3 16 -6 3 3 -10 -3 6 0 0 0 0 -3 -6 9999 -6 6 -6 3 9 -3 -3 3 0 -3 -3 0 0 0 0 9 -6 9999 -3 -3 -3 -6 0 -3 -13 -3 -3 6 3 -6 9999 0 0 3 -3 0 -6 0 0 -13 9 -3 9999 3 -3 3 3 0 -3 6 -3 -3 0 3 -3 3 3 -3 -3 3 3 -3 -6 0 0 6 0 -6 -10 0 -3 6 3 0 -6 0 -3 -3 0 6 -3 -10 -3 3 -3 0 -3 -3 3 -6 -6 3 0 3 -3 9999 -3 -3 3 0 0 -6 9999 -6 -3 9999 -3 -3 0 0 -3 9 9 0 0 0 0 -3 -6 3 -6 -3 -6 -3 -3 -3 0 -6 6 3 -6 -6 3 0 3 -3 -3 3 -3 -3 0 -3 -3 0 9 -3 0 0 6 3 3 -3 6 0 -3 6 3 9999 9 -3 -3 3 0 -3 0 -3 -3 0 -3 3 -3 3 -6 -6 0 3 6 -6 -3 -6 -3 9 0 6 6 -6 -3 9999 0 0 -3 -3 3 0 3 3 -10 3 0 3 0 0 -3 -3 3 0 -3 0 -3 3 9 0 -3 0 -3 3 -6 0 6 0 -3 0 3 0 -3 -3 -6 0 -3 -3 6 0 0 6 -3 3 3 3 -3 -3 0 -3 -6 3 -6 0 0 0 -3 -3 9 -3 0 0 0 -3 -6 0 -3 3 3 3 3 6 -6 9 -3 3 -6 -6 3 -6 9999 9999 6 -3 -3 -3 6 -3 3 -6 0 0 -3 0 3 -3 3 -6 3 -3 -6 -6 -3 -3 0 3 -10 3 0 -6 -6 3 0 -6 -3 0 3 -6 -3 3 -6 -6 0 0 0 -3 -6 0 -6 -3 -3 13 6 -6 0 0 6 -3 9999 -3 -3 0 9999 0 3 -3 -3 -3 0 3 0 -3 3 -3 6 -10 -3 0 -3 -6 -6 0 -3 6 -6 0 0 -3 9 0 0 3 -6 9999 9999 0 -3 0 0 6 -3 -3 9 3 3 3 -3 -10 6 0 -3 -3 0 9 -6 0 -3 -3 3 -3 -3 0 3 -3 -3 6 6 -6 6 -3 0 0 -10 -3 0 0 3 -3 -3 9 9 3 -3 -3 0 -6 3 -3 -3 3 0 3 3 -6 -6 -3 -3 -3 -3 3 0 0 -6 0 0 -6 0 0 3 -3 -6 3 0 0 -6 -3 0 13 0 -3 -10 -3 3 -3 3 3 -6 0 0 -3 6 -6 0 3 -6 -3 6 -3 0 0 0 6 3 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 798 795 798 788 779 750 709 744 687 690 667 687 620 661 674 655 610 620 591 610 591 575 524 591 594 530 556 530 543 553 492 511 445 464 457 502 483 464 454 422 464 422 460 441 445 432 413 406 425 394 394 397 371 384 368 378 362 397 355 365 336 352 371 320 333 327 336 304 320 311 314 320 298 308 295 285 282 298 288 266 308 257 222 276 266 279 244 237 244 244 253 228 260 237 228 202 222 244 202 209 241 231 253 202 209 222 199 222 190 187 199 193 199 190 190 180 209 196 167 177 190 215 180 161 180 177 167 164 171 174 155 155 171 155 171 161 161 155 161 167 158 136 148 187 142 120 136 142 155 123 136 148 152 139 152 132 132 120 139 132 123 126 129 123 116 126 142 116 126 120 116 113 126 123 123 132 104 94 110 97 91 97 97 75 101 94 101 91 88 107 81 88 88 85 91 78 72 91 91 69 78 97 110 120 142 148 148 164 183 237 346 323 285 343 292 263 266 257 225 237 244 247 218 228 183 187 193 187 174 145 139 113 116 142 110 126 97 116 107 107 113 91 104 85 66 85 88 85 91 88 78 78 78 85 75 72 85 78 78 62 62 81 81 69 75 59 59 59 75 66 81 81 81 75 59 69 66 50 85 78 81 69 69 69 62 59 66 75 59 85 78 69 59 75 66 91 78 66 126 193 167 199 167 145 152 132 113 107 101 72 62 59 59 37 37 43 34 30 34 30 30 27 34 34 37 37 30 30 34 46 34 40 30 40 30 37 34 34 27 34 34 30 30 24 21 34 30 30 30 34 34 34 40 30 24 24 37 30 30 34 24 24 34 34 30 40 40 30 24 24 21 27 40 24 30 30 24 27 27 24 27 27 30 24 24 24 37 18 30 30 27 24 24 30 27 27 27 18 18 24 27 21 27 34 21 21 27 21 18 24 24 24 30 24 27 18 27 15 18 30 21 27 30 24 24 30 21 24 34 24 24 24 30 21 18 24 27 34 24 21 18 21 21 15 18 24 18 8 27 21 21 15 27 24 18 18 18 18 24 21 27 27 11 21 18 24 24 18 8 21 21 27 21 24 15 18 24 15 11 24 15 21 21 24 15 15 15 18 15 18 21 18 18 24 24 15 15 15 15 8 11 11 8 24 15 15 11 15 15 15 18 18 15 15 15 8 11 8 15 11 11 18 21 21 18 15 8 15 15 11 18 11 2 15 15 18 11 21 11 11 24 21 8 15 11 18 15 11 15 11 11 21 18 21 11 8 15 8 15 15 21 11 15 18 11 15 15 18 15 15 15 15 18 11 11 8 11 11 11 15 21 15 11 18 8 18 15 11 8 11 11 18 15 15 11 8 15 15 8 8 8 8 11 15 15 8 15 18 8 15 11 8 5 15 15 5 5 11 11 15 8 8 5 11 8 8 5 5 5 5 5 11 8 8 5 8 5 11 11 8 8 15 5 11 11 15 5 5 8 15 15 5 8 5 5 11 11 8 18 5 8 11 11 8 15 5 11 8 8 8 8 5 11 5 8 8 5 8 8 2 11 11 5 5 5 2 11 8 8 5 2 8 8 15 8 8 5 5 8 11 5 5 5 11 5 8 8 5 5 5 5 5 5 5 5 8 8 8 11 8 5 5 2 8 5 5 8 8 5 11 11 8 5 5 5 11 5 2 5 11 15 5 8 8 8 8 5 5 11 5 11 5 8 5 2 5 5 5 5 11 2 5 5 5 5 8 5 5 5 5 2 2 11 5 2 5 5 2 5 5 5 5 5 5 5 5 5 5 5 5 2 2 5 5 2 5 5 2 11 8 8 5 8 2 8 5 5 8 5 5 5 5 5 18 5 11 8 8 5 5 15 2 5 5 11 2 5 5 2 2 5 8 8 5 2 2 2 -1 2 8 8 5 5 11 5 8 2 2 8 5 15 2 8 8 2 2 2 2 2 5 5 5 5 8 -1 5 8 5 5 5 5 2 8 5 -1 2 15 2 5 -1 11 2 5 5 2 5 8 2 5 15 8 -1 5 2 5 8 5 5 2 8 8 5 5 5 5 5 5 5 5 5 5 -1 8 5 5 2 11 5 2 2 8 2 2 5 8 5 2 2 8 2 2 2 5 2 2 8 5 2 11 5 5 2 5 5 9999 2 2 2 2 5 5 -1 5 8 5 8 5 9999 5 5 2 5 5 2 5 5 5 2 5 5 2 5 5 5 8 -1 5 5 2 2 5 5 8 2 5 2 5 2 8 5 8 5 2 5 -1 8 2 8 8 2 2 2 2 2 2 11 5 2 5 5 2 -1 -1 5 5 2 2 2 2 2 2 2 2 2 2 5 2 2 2 -1 5 2 2 2 5 -1 -1 2 -1 2 5 2 2 2 2 2 5 5 2 2 -1 -1 2 2 2 5 -1 5 -1 2 2 2 5 2 2 11 2 2 8 2 2 -1 2 5 2 2 5 2 2 2 2 2 5 2 5 -1 -1 2 2 9999 5 5 -1 -1 -1 2 2 2 8 2 -1 -1 -1 2 -1 2 2 2 5 2 2 2 5 5 2 2 2 5 5 5 8 5 2 -1 5 -1 -1 2 2 2 5 2 -1 -1 2 5 -1 2 2 5 5 5 -1 -1 2 2 5 2 2 2 2 -1 2 5 5 9999 2 2 2 5 5 8 5 2 2 2 5 -1 2 2 2 2 2 2 5 5 5 5 2 2 -1 2 -1 8 5 -1 2 2 -1 2 5 5 2 2 -1 2 5 -1 5 5 5 2 2 -1 5 5 2 2 -1 2 2 -1 -1 11 -1 5 2 2 2 8 -1 2 2 2 2 5 2 -1 -1 2 2 5 -1 5 2 2 2 -1 2 2 2 2 2 2 2 5 2 2 2 2 -1 2 2 9999 5 -1 5 -1 2 2 2 5 5 5 5 2 2 -1 -1 2 2 5 2 2 2 2 2 -1 2 2 2 -1 -1 -1 8 -1 -1 2 2 2 5 -1 2 2 2 2 9999 2 2 -1 -1 2 2 -1 2 2 -1 2 2 2 2 2 2 2 2 2 5 2 2 5 2 8 2 11 5 8 5 2 8 5 2 2 -1 5 5 2 2 -1 5 -1 -1 -1 5 5 5 2 5 -1 -1 2 2 2 -1 -1 -1 2 -1 9999 2 2 5 2 2 5 -1 5 -1 -1 2 5 2 5 2 2 2 9999 8 2 -1 2 5 5 2 2 2 2 2 5 9999 2 2 -1 2 5 2 8 2 -1 2 2 9999 2 -1 -1 -1 2 2 -1 -1 2 2 2 2 -1 5 2 5 2 2 -1 2 8 2 2 2 2 -1 2 2 2 2 2 -1 2 2 5 2 2 5 2 2 2 2 5 2 2 -1 5 2 5 2 2 2 9999 2 8 5 -1 -1 2 9999 2 2 9999 2 2 -1 -1 5 -1 2 5 2 5 2 -1 -1 2 2 8 -1 2 2 2 2 2 2 -1 5 -1 2 5 2 8 2 5 5 2 2 2 5 2 2 2 -1 2 2 2 -1 -1 2 2 -1 5 2 9999 -1 5 2 5 5 2 5 2 5 -1 2 5 -1 8 2 2 -1 2 2 2 -1 5 5 8 2 5 -1 -1 -1 9999 -1 2 2 2 2 2 2 2 5 2 2 2 2 2 2 2 2 -1 2 -1 -1 -1 2 -1 2 5 2 2 8 -1 2 5 2 8 -1 2 -1 -1 5 2 2 5 2 2 -1 2 5 2 2 -1 11 2 5 2 2 2 2 5 -1 -1 -1 -1 2 5 2 2 5 -1 5 -1 5 2 2 2 -1 8 2 -1 2 2 2 2 2 2 9999 9999 5 -1 2 5 2 2 5 2 8 -1 -1 -1 5 -1 2 -1 5 5 5 2 2 5 2 2 2 -1 -1 2 -1 5 2 2 5 8 5 2 2 -1 5 2 -1 2 -1 -1 -1 2 -1 -1 -1 2 2 2 -1 8 5 5 9999 2 -1 5 9999 2 2 5 -1 -1 2 5 5 2 2 2 2 -1 2 2 2 2 -1 2 2 -1 -1 -1 -1 -1 2 2 -1 2 2 9999 9999 -1 5 -1 -1 2 2 2 2 2 2 5 -1 2 2 2 2 2 5 -1 -1 -1 2 2 -1 2 2 2 2 5 5 2 -1 2 8 -1 5 5 2 2 -1 2 5 5 -1 2 2 2 2 -1 -1 2 -1 2 5 8 8 2 -1 2 2 5 2 -1 5 2 2 2 5 -1 2 2 2 2 -1 2 5 5 2 2 5 2 -1 -1 5 2 2 2 5 2 -1 5 5 5 2 2 2 2 5 2 8 2 2 2 5 5 5 2 -1 9. Sample read archive file fortran program 'arcread_1min.f' ********************************************************************************** c arcread.f reads in FARS Polarization Cloud Lidar Archive Data c explanation of variables: c time1: 2 minute average start time, 6 integers including c year,month,day,hour,minute,second c time2: 2 minute average end time, 6 integers including c year,month,day,hour,minute,second c shot_avg: number of shots in 2 minute average c totnum: total number of shots in 2 minute average if no shots c are rejected due to data recording errors c nvert: number of points in the vertical, used to read in c the backscatter data c nangle: number of shots in 2 minute average that the lidar c was tilted off the zenith position c dataB: relative backscatter data, 2 minute average with nvert c points in the vertical c c COMPILING: on a UNIX based machine, type: c f77 arcread.f c this will compile and create the executable: a.out c c To run the program, type: a.out c----------------------------------------------------------------------- program arcread integer*2 time1(1000,6),time2(1000,6),shot_avg(1000), : nvert(1000),nangle(1000),dataA(1000,250),dataB(1000,250),totnum(1000) character*80 infile character filestr(80) real*4 pmt_ratio,phi,baselev,h_res equivalence(infile,filestr) print *,'arcread.f - This program will read in FARS Ruby', : 'Lidar Data into arrays and print the header information ', : 'to the screen.' print *,'Input filename to read (Press "E" to exit):' read(5,2)infile 2 format(a80) if (filestr(1) .eq. 'e' .or. filestr(1) .eq. 'E') then stop else open(unit=1,file=infile,status='old') end if c read in header info read(1,*) pmt_ratio, phi read(1,*) baselev, h_res c read in each shot nshots = 1 5 read(1,*,end=10)time1(nshots,1),time1(nshots,2),time1(nshots,3), : time1(nshots,4),time1(nshots,5),time1(nshots,6) read(1,*)time2(nshots,1),time2(nshots,2),time2(nshots,3), : time2(nshots,4),time2(nshots,5),time2(nshots,6) read(1,*)shot_avg(nshots),totnum(nshots),nvert(nshots) read(1,*)nangle(nshots) read(1,*)(dataA(nshots,i),i=1,nvert(nshots)) read(1,*)(dataB(nshots,i),i=1,nvert(nshots)) print*,time1(nshots,1),time1(nshots,2),time1(nshots,3), : time1(nshots,4),time1(nshots,5),time1(nshots,6) print *,time2(nshots,1),time2(nshots,2),time2(nshots,3), : time2(nshots,4),time2(nshots,5),time2(nshots,6) print *,shot_avg(nshots),totnum(nshots),nvert(nshots) print *,nangle(nshots) nshots = nshots + 1 go to 5 10 close(unit=1) nshots = nshots - 1 print *,'Number of lidar shots read: ',nshots stop end *************************************************************************************