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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. Motivation.
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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
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.
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.
7th IWW Review 500 mb Noise Filtered Retrievals 2580 targets Noise Filtered Retrievals 326 vectors
ATReC Q Loop at 343mb WRF RTRVL
ATReC (cont) Noise Filtered Retrievals 5536 targets 407 mb Noise Filtered Retrievals 316 vectors
ATReC (cont) Meters
ATReC (cont) IDV display of the retrieval winds illustrates the data density and vertical distribution. Meters
OceanWinds Q Loop at 729mb WRF RTRVL
OceanWinds (cont) Noise Filtered Retrievals 14414 targets Noise Filtered Retrievals QI 1912 vectors 729 mb
OceanWinds (cont) Meters
OceanWinds (cont) IDV display of the retrieval winds illustrates the data density and vertical distribution. Meters
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.