Knowledge (XXG)

Atmospheric sounding

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since these cannot measure the quantity of interest, such as temperature, pressure, humidity etc., directly. By understanding emission and absorption processes, we can figure out what the instrument is looking at between the layers of atmosphere. While this type of instrument can also be operated
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that only detect what is already there. There can be a variety of sources for a passive instrument, including scattered radiation, light emitted directly from the sun, moon or stars—both more appropriate in the visual or ultra-violet range—as well light emitted from warm objects, which is more
627:. These can be generated either from models—e.g. state vectors from dynamical models and measurement vectors from radiative transfer or similar forward models—or from direct, empirical measurement. Other times when a statistical method might be more appropriate include highly 428:
instruments do not measure the relevant physical properties, that is the state, but rather the amount of radiation emitted in a particular direction, at a particular frequency. It is usually easy to go from the state space to the measurement space—for instance with
317:. The state vector could be temperatures, ozone number densities, humidities etc. The measurement vector is typically counts, radiances or brightness temperatures from a radiometer or similar detector but could include any other quantity germane to the problem. The 208:
looks at the edge of the atmosphere where it is visible above the Earth. It does this in one of two ways: either it tracks the sun, moon, a star, or another transmitting satellite through the limb as the source gets
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from ground stations or vehicles—optical methods can also be used inside in situ instruments—satellite instruments are particularly important because of their extensive, regular coverage. The
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Sensors that measure atmospheric constituents directly, such as thermometers, barometers, and humidity sensors, can be sent aloft on balloons, rockets or
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Sometimes the physics is too complicated to model accurately or the forward model too slow to be used effectively in the inverse method. In this case,
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behind the Earth, or it looks towards empty space, collecting radiation that is scattered from one of these sources. In contrast, a
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satellites, for instance, can sample the entire globe at better than one degree resolution in less than a day.
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concentration, pollution, and other properties. Such measurements are performed in a variety of ways including
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The following applies mainly to passive sensors, but has some applicability to active sensors.
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The more challenging case involves sensors, primarily satellite-mounted, such as
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Typically, there is a vector of values of the quantity to be retrieved,
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is a measurement of vertical distribution of physical properties of the
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we can use some type of matrix inverse method—often the problem is
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Inverse Methods for Atmospheric Sounding: Theory and Practice
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observation of atmospheres on different planets, such as the
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We can distinguish between two broad classes of sensor:
620:{\displaystyle \lbrace {\vec {x}}:{\vec {y}}\rbrace } 583: 481: 446: 397: 332: 294: 261: 225:instrument operates in all three of these modes. A 619: 506: 461: 412: 380: 309: 276: 381:{\displaystyle {\vec {y}}={\vec {f}}({\vec {x}})} 323:maps the state vector to the measurement vector: 77:Remote sensing soundings generally use passive 695:Egbert Boeker and Rienk van Grondelle (2000). 95:Earth-observing satellite instruments such as 221:) through the atmosphere at the surface. The 8: 614: 584: 732:University of Wyoming Atmospheric Soundings 196:appropriate in the microwave and infrared. 603: 602: 588: 587: 582: 495: 484: 483: 480: 448: 447: 445: 399: 398: 396: 364: 363: 349: 348: 334: 333: 331: 296: 295: 293: 263: 262: 260: 62:The most common in situ sounding is a 538:it: good, simple methods include the 7: 641:Differential absorption spectroscopy 191:, that have their own source, and 14: 719: 233:) from a ground-based location. 507:{\displaystyle {\vec {f}}^{-1}} 608: 593: 489: 453: 404: 375: 369: 360: 354: 339: 301: 288:and a vector of measurements, 268: 1: 663:Collocation (remote sensing) 544:singular value decomposition 237:Atmospheric inverse problem 111:Mars Reconnaissance Orbiter 765: 571:statistical classification 462:{\displaystyle {\vec {f}}} 413:{\displaystyle {\vec {f}}} 310:{\displaystyle {\vec {y}}} 277:{\displaystyle {\vec {x}}} 240: 136: 704:Clive D. Rodgers (2000). 47:), liquid water content, 248:Statement of the problem 699:(2nd ed.). Wiley. 683:Thermodynamic diagrams 621: 508: 463: 414: 382: 311: 278: 697:Environmental Physics 673:Satellite meteorology 622: 509: 464: 415: 391:Usually the mapping, 383: 312: 279: 241:Further information: 172:instruments on three 137:Further information: 83:microwave radiometers 66:, which usually is a 21:atmospheric profiling 747:Atmospheric sounding 728:at Wikimedia Commons 726:Atmospheric sounding 678:Skew-T log-P diagram 581: 550:may be appropriate. 479: 444: 395: 330: 292: 259: 107:Mars climate sounder 89:airborne instruments 70:, but can also be a 17:Atmospheric sounding 708:. World Scientific. 534:so we will need to 518:Methods of solution 151:, optical sensors, 651:Optimal estimation 617: 522:If the problem is 504: 469:or of finding the 459: 435:radiative transfer 410: 378: 307: 274: 724:Media related to 646:Isoline retrieval 611: 596: 575:kernel estimation 563:linear regression 492: 456: 407: 372: 357: 342: 304: 271: 139:Atmospheric lidar 754: 723: 709: 700: 668:Inverse problems 626: 624: 623: 618: 613: 612: 604: 598: 597: 589: 561:methods such as 559:machine learning 513: 511: 510: 505: 503: 502: 494: 493: 485: 468: 466: 465: 460: 458: 457: 449: 419: 417: 416: 411: 409: 408: 400: 387: 385: 384: 379: 374: 373: 365: 359: 358: 350: 344: 343: 335: 316: 314: 313: 308: 306: 305: 297: 283: 281: 280: 275: 273: 272: 264: 200:Viewing geometry 133:Indirect methods 92:surface stations 764: 763: 757: 756: 755: 753: 752: 751: 737: 736: 716: 703: 694: 691: 659: 637: 635:List of methods 579: 578: 567:neural networks 540:normal equation 520: 482: 477: 476: 442: 441: 393: 392: 328: 327: 290: 289: 257: 256: 250: 245: 243:Inverse problem 239: 217:looks down (at 202: 145: 135: 119: 68:weather balloon 43:(thus deriving 27:column such as 12: 11: 5: 762: 761: 758: 750: 749: 739: 738: 735: 734: 729: 715: 714:External links 712: 711: 710: 701: 690: 687: 686: 685: 680: 675: 670: 665: 658: 655: 654: 653: 648: 643: 636: 633: 616: 610: 607: 601: 595: 592: 586: 548:Newton–Raphson 519: 516: 501: 498: 491: 488: 455: 452: 426:remote sensing 406: 403: 389: 388: 377: 371: 368: 362: 356: 353: 347: 341: 338: 303: 300: 270: 267: 249: 246: 238: 235: 227:zenith sounder 201: 198: 134: 131: 118: 117:Direct methods 115: 114: 113: 103: 93: 90: 59:observations. 53:remote sensing 41:wind direction 13: 10: 9: 6: 4: 3: 2: 760: 759: 748: 745: 744: 742: 733: 730: 727: 722: 718: 717: 713: 707: 702: 698: 693: 692: 688: 684: 681: 679: 676: 674: 671: 669: 666: 664: 661: 660: 656: 652: 649: 647: 644: 642: 639: 638: 634: 632: 630: 605: 599: 590: 576: 572: 568: 564: 560: 556: 551: 549: 545: 541: 537: 533: 529: 525: 517: 515: 499: 496: 486: 474: 473: 472:inverse model 450: 440: 436: 432: 427: 423: 401: 366: 351: 345: 336: 326: 325: 324: 322: 321: 320:forward model 298: 287: 284:, called the 265: 253: 247: 244: 236: 234: 232: 229:looks up (at 228: 224: 220: 216: 215:nadir sounder 212: 207: 199: 197: 194: 190: 186: 181: 179: 175: 171: 166: 162: 158: 154: 150: 144: 143:Weather radar 140: 132: 130: 128: 124: 116: 112: 108: 104: 102: 98: 94: 91: 88: 87: 86: 84: 80: 75: 73: 69: 65: 60: 58: 54: 50: 46: 42: 38: 34: 30: 26: 22: 18: 705: 696: 552: 521: 470: 390: 318: 286:state vector 285: 254: 251: 226: 214: 206:limb sounder 205: 203: 192: 184: 182: 146: 127:transponders 120: 76: 61: 20: 16: 15: 555:statistical 422:empirically 163:as well as 149:radiometers 72:rocketsonde 33:temperature 25:atmospheric 689:References 631:problems. 536:regularize 431:Beer's law 211:occultated 187:, such as 161:ceilometer 123:dropsondes 64:radiosonde 45:wind shear 37:wind speed 629:nonlinear 609:→ 594:→ 528:ill-posed 497:− 490:→ 454:→ 439:inverting 405:→ 370:→ 355:→ 340:→ 302:→ 269:→ 223:SCIAMACHY 741:Category 657:See also 532:unstable 178:EUMETSAT 176:and two 79:infrared 29:pressure 193:passive 109:on the 57:in situ 524:linear 231:zenith 185:active 219:nadir 189:radar 165:sodar 157:lidar 153:radar 49:ozone 174:NOAA 170:AMSU 159:and 141:and 101:AMSU 99:and 97:AIRS 81:and 55:and 39:and 557:or 542:or 530:or 433:or 19:or 743:: 573:, 569:, 565:, 514:. 475:, 204:A 155:, 129:. 85:: 74:. 35:, 31:, 615:} 606:y 600:: 591:x 585:{ 500:1 487:f 451:f 402:f 376:) 367:x 361:( 352:f 346:= 337:y 299:y 266:x

Index

atmospheric
pressure
temperature
wind speed
wind direction
wind shear
ozone
remote sensing
in situ
radiosonde
weather balloon
rocketsonde
infrared
microwave radiometers
AIRS
AMSU
Mars climate sounder
Mars Reconnaissance Orbiter
dropsondes
transponders
Atmospheric lidar
Weather radar
radiometers
radar
lidar
ceilometer
sodar
AMSU
NOAA
EUMETSAT

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