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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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Presentation on theme: "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."— Presentation transcript:

1 AT737 Winds

2 AT737 Winds2 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.

3 AT737 Winds3 Outline Winds from soundings Cloud and vapor tracking Ocean surface winds Scatterometers Passive microwave winds Tropical cyclone winds Doppler winds Passive stratospheric techniques Lidar tropospheric techniques

4 AT737 Winds4 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.

5 AT737 Winds5 Cloud Tracking If 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

6 AT737 Winds6 Automatic Tracking Cross-correlations are utilized Assumes the clouds are translating but not changing Used for operational wind retrievals

7 AT737 Winds7 Operational High-Density Winds From the NOAA Geostationary Satellite ServerNOAA Geostationary Satellite Server

8 AT737 Winds8 MODIS Polar Winds 24-hr Loop Routine production of MODIS winds began in 2002 Courtesy of Jeff Key/CIMSS

9 AT737 Winds9 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

10 AT737 Winds10 MODIS Winds in NWP Current 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

11 AT737 Winds11 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

12 AT737 Winds12 Water Vapor Winds From the NOAA Geostationary Satellite ServerNOAA Geostationary Satellite Server

13 AT737 Winds13 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.

14 AT737 Winds14 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

15 AT737 Winds15 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

16 AT737 Winds16 QuikSCAT Winds 3 Jan 2005 1758 UTC SOURCE: http://winds.jpl.nasa.gov

17 AT737 Winds17 More QuikSCAT Winds SOURCE:

18 AT737 Winds18 Passive Microwave Winds Goodberlet and Swift algorithm using SSM/I data WS = 147.90 + 1.0969*TB 19V - 0.4555*TB 22V -1.7600*TB 37V + 0.7860*TB 37H Wind speed only Must have polarization measurements to do this. Cross-track microwave sounders like AMSU can’t do it. Wind Speed SignalCloud Liquid Correction SST CorrectionWater Vapor Correction

19 AT737 Winds19 SSM/I Wind Speed SOURCE:

20 AT737 Winds20 WindSat/Coriolis WindSat 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.

21 AT737 Winds21 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 37GHz 3 rd and 4 th Stokes Ambiguity Removal 4 possible solution GDAS initialization Median filter 3 passes NOAA WindSat Wind Vector Retrieval Algorithm – Ver 1 SOURCE

22 AT737 Winds22 Tropical Cyclone Winds Dvorak Technique: Tropical cyclones undergo a predictable life cycle Wind speed is associated with the stage in a storm’s life

23 AT737 Winds23 Dvorak Technique Subjective Not easily learned In use around the world

24 AT737 Winds24 TC Microwave Temp Anomalies SOURCE

25 AT737 Winds25 Doppler Winds The Doppler effect can be used to measure winds toward or away from the satellite. Passive stratospheric winds Active tropospheric winds

26 AT737 Winds26 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.

27 AT737 Winds27 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 CO 2 (9 µm) Doppler lidar return from aerosols was supposed to yield wind direction and speed by utilizing multiple looks

28 AT737 Winds28 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: 2VMOC_LPadmaeolus_0.html 2VMOC_LPadmaeolus_0.html

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