AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the...

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AT737 Winds

Transcript of AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the...

Page 1: AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the humidity field, and the flow field. The first two were.

AT737

Winds

Page 2: AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the humidity field, and the flow field. The first two were.

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Importance

To forecast the weather, one must know the mass field, the humidity field, and the flow field. The first two were covered in the last two lectures. Winds are the topic of this lecture.

Page 3: AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the humidity field, and the flow field. The first two were.

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Outline

Winds from soundingsCloud and vapor trackingOcean surface winds Scatterometers Passive microwave winds Tropical cyclone winds

Doppler winds Passive stratospheric techniques Lidar tropospheric techniques

Page 4: AT737 Winds. AT737 Winds2 Importance To forecast the weather, one must know the mass field, the humidity field, and the flow field. The first two were.

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Winds from Soundings

In the mid and high latitudes, the flow field adjusts to the mass field. Therefore, soundings (temperature and humidity) provide information on winds; for example, the geostrophic wind. Data assimilation schemes are designed to do this.

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Cloud TrackingIf you can locate a cloud in two successive satellite images, you can calculate the horizontal wind.

Manual tracking is extremely tedious!

Wind vectors only where there are clouds

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Automatic Tracking

• Cross-correlations are utilized

• Assumes the clouds are translating but not changing

• Used for operational wind retrievals

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Operational High-Density Winds

From the NOAA Geostationary Satellite Server

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MODIS Polar Winds 24-hr Loop

Routine production of MODIS winds began in 2002Courtesy of Jeff Key/CIMSS

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Model impact studies have shown that the polar winds have a positive impact on weather forecasts not just in the polar regions, but globally.

Figure: Anomaly correlations as a function of forecast range for the 500 hPa geopotential over the Northern Hemisphere extratropics (north of 20 degrees latitude). The study period is 5-29 March 2001. Including the MODIS winds in the model (red line) extends the 5-day forecast at a given accuracy by 3-6 hrs. (Figure courtesy of ECMWF)

Courtesy of Jeff Key/CIMSS

Model Impact Studies

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MODIS Winds in NWPCurrent Operational Users:

• European Centre for Medium-Range Weather Forecasts (ECMWF) - since Jan 2003.

• NASA Global Modeling and Assimilation Office (GMAO) - since 2003.• Deutscher Wetterdienst (DWD) – since Nov 2003.• Japan Meteorological Agency (JMA), Arctic only - since May 2004.• Canadian Meteorological Centre (CMC) – since Sept 2004.• US Navy, Fleet Numerical Meteorology and Oceanography Center

(FNMOC) –since Oct 2004.• UK Met Office – since Feb 2005.• National Centers for Environmental Prediction (NCEP) and the Joint

Center for Satellite Data Assimilation - since Nov 2005.• MeteoFrance - since June 2006.• National Center for Atmospheric Research (NCAR) - in AMPS model

since October 2006.

Courtesy of Jeff Key/CIMSS

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Water Vapor Winds

• Track water vapor features (and high clouds)

• Complement cloud track winds because they are mostly mid-level winds, where there are few clouds

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Water Vapor Winds

From the NOAA Geostationary Satellite Server

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Height Assignment

After one estimates the wind vector, one needs to assign a height to it. One way to do this is by comparing the temperature of the cloud with a sounding or a model grid field, but this is accurate to within, perhaps, 100 mb. Height assignment, not wind vector calculation, constitutes the major error in cloud and vapor track winds.

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Scatterometers• Came about from

watching “sea clutter” with early radars

• Measure backscatter from ocean surface

SeaWinds on QuikSCAT

Instrument Description

• Radar: 13.4 gigahertz; 110-watt pulse at 189-hertz pulse repetition frequency (PRF)

• Antenna: 1-meter-diameter rotating dish that produces two spot beams, sweeping in a circular pattern

• Mass: 200 kilograms

• Power: 220 watts

• Average Data Rate: 40 kilobits per second

SOURCE: http://winds.jpl.nasa.gov

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Wind Retrieval

From SeaSat

Possible Solutions (“Aliases”)• Two observations of

backscatter produce two profiles of wind speed/wind direction.

• Possible solutions exist where the two curves intersect

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QuikSCAT Winds

3 Jan 2005 1758 UTC

SOURCE: http://winds.jpl.nasa.gov

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More QuikSCAT Winds

SOURCE: http://www.nrlmry.navy.mil/sat-bin/scatt_winds.cgi

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Passive Microwave Winds• Goodberlet and Swift algorithm using SSM/I data

WS = 147.90 + 1.0969*TB19V - 0.4555*TB22V

-1.7600*TB37V + 0.7860*TB37H

• Wind speed only

• Must have polarization measurements to do this. Cross-track microwave sounders like AMSU can’t do it.

Wind Speed Signal

Cloud Liquid Correction

SST Correction Water Vapor Correction

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SSM/I Wind Speed

SOURCE: http://manati.orbit.nesdis.noaa.gov/doc/ssmiwinds.html

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WindSat/CoriolisWindSat is the primary payload on the Air Force Coriolis satellite, which was launched on 6 January 2003. It is in an 840 km circular sun-synchronous orbit. The WindSat payload is performing well and is currently undergoing rigorous calibration and validation to verify mission success. The WindSat radiometer has polarimetric channels at 10.7, 18.7 and 37.0 GHz. Dual-polarization channels at 6.8 and 23.8 GHz provide key data sea surface temperature and atmospheric water vapor. The WindSat design and ground processing focus on the primary mission of measuring the ocean surface wind vector.

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CLW Retrievals

18.7,28.8 and 37GHz

WV Retrievals

18.7,23.8 and 37GHz

Wind Speed Retrievals

10.7,18.7,23.8 and 37GHz

SST Retrievals

10.7GHz

Wind Direction Retrievals

10.7, 18.7 and 37GHz3rd and 4th Stokes

biclwi TaL

biwvi Tav

biui Tau

bisstisst TaT

5

1 ,

2mod,,

)(

))((

imeasViU

VUmeasViU

TVar

TTJ

Ambiguity Removal•4 possible solution•GDAS initialization•Median filter•3 passes

NOAA WindSat Wind Vector Retrieval Algorithm – Ver 1

)2cos()cos( 21 aauu

SOURCE

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Tropical Cyclone Winds

Dvorak Technique:

• Tropical cyclones undergo a predictable life cycle

• Wind speed is associated with the stage in a storm’s life

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Dvorak Technique

• Subjective

• Not easily learned

• In use around the world

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TC Microwave Temp Anomalies

SOURCE

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Doppler Winds

The Doppler effect can be used to measure winds toward or away from the satellite.

• Passive stratospheric winds

• Active tropospheric winds

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High Resolution Doppler Imager (HRDI)Wind Imaging Interferometer (WINDII)

Flew on board NASA’s Upper Atmosphere Research Satellite (UARS). The satellite was launched on 12 September 1991. Both instruments observe emission and absorption lines of molecular oxygen (and other atmospheric components) in small volumes (4 km in height by 50 km in width) above the limb of the Earth. From the Doppler shift of the lines, the horizontal winds in the mesosphere and stratosphere can be determined, while the line shapes and strengths yield information about the temperature and atmospheric species make-up.

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Laser Atmospheric Wind Sounder (LAWS)

• Never flew

• Proposed as part of the Earth Observing System (EOS)

• A 1-meter diameter mirror was to rotate in a conical pattern

• CO2 (9 µm) Doppler lidar return from aerosols was supposed to yield wind direction and speed by utilizing multiple looks

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Atmospheric Dynamics Mission (ADM-Aeolus)

• ESA mission with target launch date in 2007

• 355 nm (eye-safe) lidar

• Measures radial velocities at 35º in the antisolar direction to minimize solar contamination and spacecraft motion contamination

• 3000 observations per day

• SOURCE: Stoffelen et al. (2005), BAMS, 73-87.

• Web Site: http://www.esa.int/esaLP/ESAES62VMOC_LPadmaeolus_0.html