1. RECENT INNOVATIONS IN DERIVING ATMOSPHERIC MOTION VECTORS AT CIMSS
PART 1: AMV CALCULATIONS USING HYPERSPECTRAL SATELLITE RETRIEVALS
Steve Wanzong, Chris Velden, Dave Santek, Jun Li, Erik Olson, Jason Otkin
SSEC/CIMSS Seminar
28 June 2006

2. Motivation
Track constant-level sequential moisture analyses from hyperspectral soundings.
Reduce the height assignment errors.
Vertical profiles of winds.
Part of GOES-R risk reduction program.
CIMSS is involved in the GOES-R risk reduction. Falls under the Winds component of the Algorithm Working Group (AWG) to test algorithm developments for the HES instrument using GIFTS specifications.
Current method only provides clear sky upper-tropspheric winds from 3 water vapor channels. 1 imager (6.5), 2 sounder (7.0 and 7.4).
Future slides will show the vertical nature of the winds.

3. Methodology
Employ high resolution mesoscale models to generate simulated atmospheres.
Calculate Top of Atmosphere (TOA) radiances from the mesoscale model simulations using the GIFTS forward radiative transfer model.
Generate single-field-of view water vapor retrievals (vertical profiles) from the TOA radiances.
Target and track clear-sky Atmospheric Motion Vectors (AMV) using constant-pressure (altitude) analyses derived from the water vapor retrievals and model mixing ratios.
Weather Research and Forecasting model. WRF. ARW Core. Advanced Research WRF.
A fast model takes the output from the wrf model and calculates the TOA radiances. Gifts instrument model which includes optics and detector effects modify the TOA.
Statistical retrieval only at this point. Moisture retrievals are used as input to our software.
McIDAS is used to create GRID files from the binary output of the retrievals. Then converted to McIDAS AREA files for our code.

4. 7th IWW Review 500 mb Noise Filtered Retrievals 2580 targets
Noise Filtered Retrievals vectors

5. ATReC Q Loop at 343mb WRF RTRVL
Hourly images. Tracked both the WRF and RTRVL image triplets.
Clouds are masked as black. Lighter color is higher moisture values.

6. ATReC (cont) Noise Filtered Retrievals 5536 targets 407 mb
WRF model Q and RTRVL were run through windco. 343mb down to Every 33 or 34mb was processed. AE was not used. QI was. Looking at good flagged winds greater the 3m/s. QI >=50.
Noise Filtered Retrievals targets
407 mb
Noise Filtered Retrievals vectors

7. ATReC (cont)
Meters

8. ATReC (cont)
IDV display of the retrieval winds illustrates the data density and vertical distribution.
931mb to 343mb.
Meters

9. OceanWinds Q Loop at 729mb WRF RTRVL
Very similar domain as the AtREC case.
Part of a larger simulation that will be shown later.

10. OceanWinds (cont) Noise Filtered Retrievals 14414 targets
Winds have been plotted with spd >= 3m/s. QI >=70. Winds calculated from 683mb to 986mb at 13mb differences.
Noise Filtered Retrievals targets
Noise Filtered Retrievals QI vectors
729 mb

11. OceanWinds (cont)
Meters

12. OceanWinds (cont)
IDV display of the retrieval winds illustrates the data density and vertical distribution.
Meters

13. FULLDISK Case

14. Polar Retrievals
AIRS Moisture Retrieval Targets and Winds (unedited) at 400 hPa
The moisture features are tracked in an area that is inscribed by 3 successive, overlapping passes in the polar region. See below.