Skip to main content
Geosciences LibreTexts

9.1: Meteorological Reports and Observations

  • Page ID
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)

    One branch of the United Nations is the World Meteorological Organization (WMO). Weather-observation standards are set by the WMO. Also, the WMO works with most nations of the world to coordinate and synchronize weather observations. Such observations are made simultaneously at specified Coordinated Universal Times (UTC) to allow meteorologists to create a synoptic (snapshot) picture of the weather ( see Chapter 1).

    Most manual upper-air and surface synoptic observations are made at 00 and 12 UTC. Fewer countries make additional synoptic observations at 06 and 18 UTC.

    9.2.1. Weather Codes

    One of the great successes of the WMO is the international sharing of real-time weather data via the Global Telecommunication System (GTS). To enable this sharing, meteorologists in the world have agreed to speak the same weather language. This is accomplished by using Universal Observation Codes and abbreviations. Definitions of some of these codes are in:

    World Meteorological Organization: 1995 (revised 2015): Manual on Codes. International Codes Vol. 1.1 Part A - Alphanumeric Codes. WMO-No. 306. 466 pages.

    Federal Meteorological Handbook No. 1 (Sept 2005): Surface Weather Observations and Reports. FCM-H1-2005.

    Both manuals can be found with an online search.

    Sharing of real-time data across large distances became practical with the invention of the electric telegraph in the 1830s. Later developments included the teletype, phone modems, and the internet. Because weather codes in the early days were sent and received manually, they usually consisted of human-readable abbreviations and contractions.

    Modern table-driven code formats (TDCF) are increasingly used to share data. One is CREX (Character form for the Representation and EXchange of data). Computer binary codes include BUFR (Binary Universal Form for the Representation of meteorological data) and GRIB (Gridded Binary).

    However, there still are important sets of alphanumeric codes (letters & numbers) that are human writable and readable. Different alphanumeric codes exist for different types of weather observations and forecasts, as listed in Table 9-1. We will highlight one code here — the METAR.

    Sample Application

    Interpret the following METAR code:

    METAR KSJT 160151Z AUTO 10010KT 10SM TS FEW060 BKN075 28/18 A2980 RMK AO2 LTG DSNT ALQDS TSB25 SLP068 T02780178

    Hint: see the METAR section later in this chapter.

    Find the Answer:

    Weather conditions at KSJT (San Angelo, Texas, USA) observed at 0151 UTC on 16th of the current month by an automated station: Winds are from the 100° at 10 knots. Visibility is 10 statute miles or more. Weather is a thunderstorm. Clouds: few clouds at 6000 feet AGL, broken clouds at 7500 feet AGL. Temperature is 28°C and dewpoint is 18°C. Pressure (altimeter) is 29.80 inches Hg. REMARKS: Automated weather station type 2. Distant (> 10 statute miles) lightning in all quadrants. Thunderstorm began at 25 minutes past the hour. Sea-level pressure is 100.68 kPa. Temperature more precisely is 27.8°C, and dewpoint is 17.8°C.

    Exposition: As you can see, codes are very concise ways of reporting the weather. Namely, the 3 lines of METAR code give the same info as the 12 lines of plain-language interpretation.

    You can use online web sites to search for station IDs. More details on how to code or decode METARs are in the Federal Meteor. Handbook No. 1 (2005) and various online guides. The month and year of the observation are not included in the METAR, because the current month and year are implied.

    I am a pilot and flight instructor, and when I access METARs online, I usually select the option to have the computer give me the plain-language interpretation. Many pilots find this the easiest way to use METARs. After all, it is the weather described by the code that is important, not the code itself. However, meteorologists and aviation-weather briefers who use METARs every day on the job generally memorize the codes.

    Table 9-1. List of alphanumeric weather codes.
    Name Purpose
    SYNOP Report of surface observation from a fixed land station
    SHIP Report of surface observation from a sea station
    SYNOP MOBIL Report of surface observation from a mobile land station
    METAR Aviation routine weather report (with or without trend forecast)
    SPECI Aviation selected special weather report (with or without trend forecast)
    BUOY Report of a buoy observation
    RADOB Report of ground radar weather observation
    RADREP Radiological data report (monitored on a routine basis and/or in case of accident)
    PILOT Upper-wind report from a fixed land station
    PILOT SHIP Upper-wind report from a sea station
    PILOT MOBIL Upper-wind report from a mobile land station
    TEMP Upper-level pressure, temperature, humidity and wind report from a fixed land station
    TEMP SHIP Upper-level pressure, temperature, humidity and wind report from a sea station
    TEMP DROP Upper-level pressure, temperature, humidity and wind report from a dropsonde released by carrier balloons or aircraft
    TEMP MOBIL Upper-level pressure, temperature, humidity and wind report from a mobile land station
    ROCOB Upper-level temperature, wind and air density report from a land rocketsonde station
    ROCOB SHIP Upper-level temperature, wind and air density report from a rocketsonde station on a ship
    CODAR Upper-air report from an aircraft (other than weather reconnaissance aircraft)
    AMDAR Aircraft report (Aircraft Meteorological DAta Relay)
    ICEAN Ice analysis
    IAC Analysis in full form
    IAC FLEET Analysis in abbreviated form
    GRID Processed data in the form of grid-point values
    GRAF Processed data in the form of grid-point values (abbreviated code form)
    WINTEM Forecast upper wind and temperature for aviation
    TAF Aerodrome forecast
    ARFOR Area forecast for aviation
    ROFOR Route forecast for aviation
    RADOF Radiological trajectory dose forecast (defined time of arrival and location)
    MAFOR Forecast for shipping
    TRACKOB Report of marine surface observation along a ship’s track
    BATHY Report of bathythermal observation
    TESAC Temperature, salinity and current report from a sea station
    WAVEOB Report of spectral wave information from a sea station or from a remote platform (aircraft or satellite)
    HYDRA Report of hydrological observation from a hydrological station
    HYFOR Hydrological forecast
    CLIMAT Report of monthly values from a land station
    CLIMAT SHIP Report of monthly means and totals from an ocean weather station
    NACLI, CLINP, SPCLI, CLISA, INCLI Report of monthly means for an oceanic area
    CLIMAT TEMP Report of monthly aerological means from a land station
    CLIMAT TEMP SHIP Report of monthly aerological means from an ocean weather station
    SFAZI Synoptic report of bearings of sources of atmospherics (e.g., from lightning)
    SFLOC Synoptic report of the geographical location of sources of atmospherics
    SFAZU Detailed report of the distribution of sources of atmospherics by bearings for any period up to and including 24 hours
    SAREP Report of synoptic interpretation of cloud data obtained by a meteorological satellite
    SATEM Report of satellite remote upper-air soundings of pressure, temperature and humidity
    SARAD Report of satellite clear radiance observations
    SATOB Report of satellite observations of wind, surface temperature, cloud, humidity and radiation

    9.2.2. METAR and SPECI

    METAR stands for routine Meteorological Aerodrome Report. It contains hourly observations of surface weather made at a manual or automatic weather station at an airport. It is formatted as a text message using codes (abbreviations, and a specified ordering of the data blocks separated by spaces) that concisely describe the weather.

    Here is a brief summary on how to read METARs. Grey items below can be omitted if not needed.


    [METAR or SPECI] [corrected] [weather station ICAO code] [day, time] [report type] [wind direction, speed, gusts, units] [direction variability] [prevailing visibility, units] [minimum visibility, direction] [runway number, visual range] [current weather] [lowest altitude cloud coverage, altitude code] [higher-altitude cloud layers if present] [temperature/dewpoint] [units, sea-level pressure code] [supplementary] RMK [remarks].

    Example (with remarks removed): METAR KTTN 051853Z 04011G20KT 1 1/4SM R24/6200FT VCTS SN FZFG BKN003 OVC010 M02/M03 A3006 RMK...

    Interpretation of the Example Above

    Routine weather report for Trenton-Mercer Airport (NJ, USA) made on the 5th day of the current month at 1853 UTC. Wind is from 040° true at 11 gusting to 20 knots. Visibility is 1.25 statute miles. Runway visual range for runway 24 is 6200 feet. Nearby thunderstorms with snow and freezing fog. Clouds are broken at 300 feet agl, and overcast at 1000 ft agl. Temperature minus 2°C. Dewpoint minus 3°C. Altimeter setting is 30.06 in. Hg. Remarks...


    If the weather changes significantly from the last routine METAR report, then a special weather observation is taken, and is reported in an extra, unscheduled SPECI report. The SPECI has all the same data blocks as the METAR plus a plain language explanation of the special conditions.

    The criteria that trigger SPECI issuance are:

    Wind direction: changes >45° for speeds ≥ 10 kt.

    Visibility: changes across threshold: 3 miles, 2 miles, 1 mile, 0.5 mile or instrument approach minim.

    Runway visual range: changes across 2400 ft.

    Tornado, Waterspout: starts, ends, or is observed.

    Thunderstorm: starts or ends.

    Hail: starts or ends.

    Freezing precipitation: starts, changes, ends.

    Ceiling: changes across threshold: 3000, 1500, 1000, 500, 200 (or lowest approach minimum) feet.

    Clouds: when layer first appears below 1000 feet.

    Volcanic eruption: starts.

    Details of METAR / SPECI Data Blocks

    Corrected: COR if this is a corrected METAR.

    Weather Station ICAO Code is a 4-letter ID specified by the Internat. Civil Aviation Organization.

    Day, Time: 2-digit day within current month, 4-digit time, 1-letter time zone (Z = UTC. Chapter 1).

    Type: AUTO=automatic; (blank)=routine; NIL= missing.

    Wind: 3-digit direction (degrees relative to true north, rounded to nearest 10 degrees). VRB=variable. 2- to 3-digit speed. (000000=calm). G prefixes gust max speed. Units (KT=knots, KMH=kilometers per hour, MPS=meters per second).

    Direction Variability only if > 60°. Example: 010V090, means variable direction between 010° and 090°.

    Prevailing Visibility: 4 digits in whole meters if units left blank. If vis < 800 m, then round down to nearest 50 m. If 800 ≤ vis < 5000 m, then round down to nearest 100 m. If 5000 ≤ vis < 9999 m, then round down to nearest 1000 m. Else “9999” means vis ≥ 10 km. In USA: number & fraction, with SM=statute miles. NDV = no directional variations.

    Minimum Visibility: 4 digits in whole meters if units are blank & 1-digit (a point from an 8-point compass)

    Runway Visual Range (RVR): R, 2-digit runway identifier, (if parallel runways, then: L=left, C=center, R=right), / , 4-digit RVR. Units: blank=meters, FT=feet. If variable RVR, then append optional: 4 digits, V, 4 digits to span the range of values. Finally, append optional tendency code: U=up (increasing visibility), N=no change, D-down (decreasing visibility).

    Weather: see Tables in this chapter for codes. 0 to 3 groups of weather phenomena can be reported.

    Clouds: 3-letter coverage abbreviation (see Table 9- 10), 3-digit cloud-base height in hundreds of feet agl. TCU=towering cumulus congestus, CB = cumulonimbus. If no clouds, then whole cloud block replaced by CLR=clear or by SKC=sky clear. NSC= no significant clouds below 5000 ft (1500 m) with no thunderstorm and good visibility. NCD if no clouds detected by an automated system.

    Higher Cloud Layers if any: 2nd lowest clouds reported only if ≥ SCT. 3rd lowest only if ≥ BRN.

    Note: if visibility > 10 SM and no clouds below 5,000 ft (1500 m) agl and no precipitation and no storms, then the visibility, RVR, weather, & cloud blocks are omitted, and replaced with CAVOK, which means ceiling & visibility are OK (i.e., no problems for visual flight). (Not used in USA.)

    Temperature/Dew-point: rounded to whole °C. Prefix M=minus.

    Sea-level Pressure: 4 digits. Unit code prefix: A = altimeter setting in inches mercury, for which last 2 digits are hundredths. Q = whole hectoPascals hPa). Example: Q1016 = 1016 hPa = 101.6 kPa.

    Supplementary: Can include: RE recent weather; WS wind shear; W sea state; runway state (SNOCLO=airport closed due to snow); trend, significant forecast weather (NOSIG=no change in significant weather, NSW=no significant weather)

    Remarks: RMK. For details, see the manuals cited three pages earlier.

    Although you can read a METAR if you’ve memorized the codes, it is easier to use on-line computer programs to translate the report into plain language. Consult other resources and manuals to learn the fine details of creating or decoding METARs.

    9.2.3. Weather-Observation Locations

    Several large governmental centers around the world have computers that automatically collect, test data quality, organize, and store the vast weather data set of coded and binary weather reports. For example, Figs. 9.2 to 9.12 show locations of weather observations that were collected by the computers at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, for a sixhour period centered at 00 UTC on 30 Mar 2015.

    The volume of weather data is immense. There are many millions of locations (manual stations, automatic sites, and satellite obs) worldwide that report weather observations near 00 UTC. At ECMWF, many hundreds of gigabytes (GB) of weatherobservation data are processed and archived every day. The locations for some of the different types of weather-observation data are described next.

    Surface observations (Fig. 9.2) include manual ones from land (SYNOP) and ship (SHIP) at key synoptic hours. Many countries also make hourly observations at airports, reported as METARs.

    Surface automatic weather-observation systems make more frequent or nearly continuous reports. Examples of automatic surface weather stations are AWOS (Automated Weather Observing System), and ASOS (Automated Surface Observing System) in the USA. Those automatic reports that are near the synoptic hours are also included in Fig. 9.2.

    Screen Shot 2020-02-24 at 11.14.11 AM.png
    Figure 9.2 Surface data locations for observations of temperature, humidity, winds, clouds, precipitation, pressure, and visibility collected by synoptic weather stations on land and ship. Valid: 00 UTC on 30 Mar 2015. Number of observations: 36024 METAR (land) + 23742 SYNOP (land) + 376079 SHIP = 63526 surface obs. (From ECMWF. charts/monitoring/dcover )

    Both moored and drifting buoys (BUOY; Fig. 9.3) also measure near-surface weather and ocean-surface conditions, and relay this data via satellite.

    Screen Shot 2020-02-24 at 11.14.47 AM.png
    Figure 9.3 Surface data locations for temperature and winds collected by drifting and moored BUOYs. Valid: 00 UTC on 30 Mar 2015. Number of observations: 9114 drifters + 716 moored = 8830 buoys. (From ECMWF.)

    Small weather balloons (Fig. 9.4) can be launched manually or automatically from the surface to make upper-air soundings. As an expendable radiosonde package is carried aloft by the helium-filled latex balloon, and later as it descends by parachute, it measures temperature, humidity, and pressure. These radiosonde observations are called RAOBs.

    Screen Shot 2020-02-24 at 11.15.15 AM.png
    Figure 9.4 Upper-air sounding locations for temperature, pressure, and humidity collected by rawinsonde balloons launched from land and ship, and by dropsondes released from aircraft. Valid: 00 UTC on 30 Mar 2015. Number of observations: 596 land (TEMP) + 1 ship (TEMP SHIP) + 0 dropsondes (TEMP DROP) = 597 soundings. Extra dropsondes are often dropped over oceans at hurricanes, typhoons, and strong winter storms. (From ECMWF.)

    Some radiosondes include additional instruments to gather navigation information, such as from GPS (Global Positioning Satellites). These systems are called rawinsondes, because the winds can be inferred by the change in horizontal position of the sonde. When a version of the rawinsonde payload is dropped by parachute from an aircraft, it is called a dropsonde.

    Simpler weather balloons called PIBALs (Pilot Balloons) carry no instruments, but are tracked from the ground to estimate winds (Fig. 9.5). Most balloon soundings are made at 00 and 12 UTC.

    Screen Shot 2020-02-24 at 11.25.31 AM.png
    Figure 9.5 Upper-air data locations for winds collected by: PILOT balloons, ground-based wind profilers, and Doppler radars. Valid: 00 UTC on 30 Mar 2015. Number of observations: 324 pilot/ rawinsonde balloons + 3158 microwave wind profilers = 3482 wind soundings. (From ECMWF.)

    Remote sensors on the ground include weather radar such as the NEXRAD (Weather Surveillance Radar WSR-88D). Ground-based microwave wind profilers (Fig. 9.5) automatically measure a vertical profile of wind speed and direction. RASS (Radio Acoustic Sounding Systems) equipment uses both sound waves and microwaves to measure virtual temperature and wind soundings.

    Commercial aircraft (Fig. 9.6) provide manual weather observations called Aircraft Reports (AIREPS) at specified longitudes as they fly between airports. Many commercial aircraft have automatic meteorological reporting equipment such as ACARS (Aircraft Communication and Reporting System), AMDAR (Aircraft Meteorological Data Relay), & ASDAR (Aircraft to Satellite Data Relay).

    Screen Shot 2020-02-24 at 11.26.05 AM.png
    Figure 9.6 Upper-air data locations for temperature and winds collected by commercial aircraft: AIREP manual reports (black), and AMDAR & ACARS (grey) automated reports. Valid: 00 UTC on 30 Mar 2015. Number of observations: 2254 AIREP + 17661 AMDAR + 156136 ACARS = 176051 aircraft observations, most at their cruising altitude of 10 to 15 km above sea level. (From ECMWF.)

    Geostationary satellites are used to estimate tropospheric winds (Fig. 9.7) by tracking movement of clouds and water-vapor patterns. Surface winds over the ocean can be estimated from polar orbiting satellites using scatterometer systems (Fig. 9.8) that measure the scattering of microwaves off the sea surface. Rougher sea surface implies stronger winds.

    Screen Shot 2020-02-24 at 11.26.49 AM.png
    Figure 9.7 Upper-air data locations for winds collected by geostationary satellites (SATOB) from the USA (GOES), Europe (METEOSAT), and others around the world. Based atmospheric motion vectors (AMV) of IR cloud patterns. Similar satellite observations are made using water vapor and visible channels. Valid: 00 UTC on 30 Mar 2015. Number of observations: 442475. (From ECMWF.)
    Screen Shot 2020-02-24 at 11.35.59 AM.png
    Figure 9.8 Surface-wind estimate locations from microwave scatterometer measurements of sea-surface waves by the polar-orbiting satellites. Valid: 00 UTC on 30 Mar 2015. Number of observations: 526159. (From ECMWF.)

    Satellites radiometrically estimate air-temperature to provide remotely-sensed upper-air automatic data (Fig. 9.9). One system is the AMSU (Advanced Microwave Sounding Unit), currently flying on NOAA 15, 16, 17, 18, Aqua, and the European MetOp satellites.

    Screen Shot 2020-02-24 at 11.43.58 AM.png
    Figure 9.9 Temperature-sounding (SATEM) locations from radiation measurements by polar-orbiting satellites using the AMSU (Advanced Microwave Sounding Unit). Satellites: several NOAA satellites, Aqua, and MetOP. Valid: 00 UTC on 30 Mar 2015. Number of observations: 612703. (From ECMWF.)

    Higher spectral-resolution soundings (Fig. 9.10) are made with the HIRS (High-resolution Infrared Radiation Sounding) system on polar-orbiting satellites.

    Screen Shot 2020-02-24 at 11.45.02 AM.png
    Figure 9.10 Temperature-sounding (SATEM) locations from high-spectralresolution infrared radiation measurements by polar-orbiting satellites, using HIRS (High-resolution Infrared Radiation Sounder). Valid: 00 UTC on 30 Mar 2015. Number of observations: 5394127. (From ECMWF.)

    Estimates of air density can also be made as signals from Global Positioning System (GPS) satellites are bent as they pass through the atmosphere to other satellites (Fig. 9.11). Other techniques (not shown) use ground-based sensors to measure the refraction and delay of GPS signals.

    Screen Shot 2020-02-24 at 11.48.07 AM.png
    Figure 9.11 Air density estimates are made using Global Positioning System (GPS) Radio Occultation (GPS-RO). Valid: 00 UTC on 30 Mar 2015. Number of observations: 81236. (From ECMWF.)

    Polar orbiting satellites can also be used to estimate atmospheric motion vectors (AMV) from the movement of IR cloud patterns. These can give upper-air wind data over the Earth’s poles (Fig. 9.12) — regions not visible from geostationary satellites.

    Screen Shot 2020-02-24 at 11.48.58 AM.png
    Figure 9.12 Atmospheric motion vector (AMV) locations from IR observations by polar satellites, over the N. Pole. Valid: 00 UTC on 30 Mar 2015. Number of observations: 33171. (From ECMWF.)

    Many more satellite products are used, beyond the ones shown here. Radiance measurements from geostationary satellites are used to estimate temperature and humidity conditions for numerical forecast models via variational data assimilation in three or four dimensions (3DVar or 4DVar). Tropospheric precipitable water can be estimated by satellite from the amount of microwave or IR radiation emitted from the troposphere.

    These synoptically reported data give a snapshot of the weather, which can be analyzed on synoptic weather maps. The methods used to analyze the weather data to create such maps are discussed next.

    This page titled 9.1: Meteorological Reports and Observations is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Roland Stull via source content that was edited to the style and standards of the LibreTexts platform.