ABI: Vertical Res km Horizontal Res. 2-km. Horizontal Res. 14-km Time Res min. Time Res. 1-7 hr.
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1 Combining Polar Hyper-spectral and Geostationary Multi-spectral Sounding Data A Method to Optimize Sounding Spatial and Temporal Resolution W. L. Smith!,2, E. Weisz 1, and J. McNabb 2 1 University of Wisconsin, Madison WI, USA ; 2 Hampton University, Hampton VA, USA ABI: Vertical Res km AIRS, PHS: IASI, CrIS: Vertical Vertical Res. 1-4 Res. km1-4 km Horizontal Res. 2-km Horizontal Res. 14-km Time Res min. Time Res. 1-7 hr.
2 HU CARE Hampton
3
4 Polar-Orbiting Ultra-Spectral & Geostationary Sounders GOES-16 ABI ABI GOES-16 Radiometer GOES cm μm 16 / / km 2016
5 PHS (CrIS/IASI) + ABI Sounding ABI/PHS = ABI (x,y,t) + [PHS (x o,y o,t o )- ABI (x o,y o,t o )] ABI (x,y,t): ABI retrieval value at location and time (x, y, t) PHS (x o,y o,t o ): Mean of 5 reference PHS values closest to ABI location and time (x, y, t) ABI (x o,y o,t o ): Mean of 5 reference PHS Field-of-View average ABI retrieval values closest to the ABI location and time (x, y, t) Implicit Assumption: The vertical resolution induced error of multi-spectral ABI retrievals is persistent over the time interval between the acquisition times of the high vertical resolution polar hyperspectral soundings and over the spatial scale (i.e., 14-km) of the hyperspectral sounding data.
6 Combining 500 hpa ABI with PHS 15:00 UTC
7 Combining ABI with PHS 17:55 UTC
8 CrIS + ABI Vs Radiosondes (May 19, 2017) ABI (18 UTC) IASI (14 UTC)+ABI CrIS (18 UTC)+ABI ABI (18 UTC) IASI (14 UTC)+ABI CrIS (18 UTC)+ABI
9 IASI + ABI Predicted CrIS + ABI IASI + ABI Predicted CrIS + ABI IASI + ABI Predicted CrIS + ABI
10 PHS+ABI Time Series (MOVIE)
11 IASI-A +ABI
12 IASI-A +ABI
13 IASI-A +ABI
14 IASI-B +ABI
15 IASI-B +ABI
16 IASI-B +ABI IASI-B +ABI IASI-B +ABI
17 IASI-B +ABI
18 IASI-B +ABI
19 CrIS +ABI
20 CrIS +ABI
21 Atmospheric Stability Change
22 HR Severe Weather Not Predicted by NWS (May 19, 2017) Day 1 Risk Area (sq. mi.) Area Pop. Some Larger Population Centers in Risk Area ENHANCED 48,447 7,656,120 Dallas, TX...Fort Worth, TX...Arlington, TX...Plano, TX...Garland, TX... SLIGHT 194,795 19,485,383 Columbus, OH...Oklahoma City, OK...Kansas City, MO...Tulsa, OK...Wichita, KS... MARGINAL 294,539 67,316,656 New York, NY...Philadelphia, PA...Indianapolis, IN...Austin, TX...Baltimore, MD... Probabilistic Tornado Graphic
23 HR Severe Weather Predicted by NWS ( May 22, 2017)
24 Summary and Conclusions Profile Retrievals from Polar Hyperspectral Sounders and Geostationary Multi-spectral Instruments to Optimize the Vertical, Horizontal, and Temporal resolution of the Satellite Sounding Product Improving low altitude sounding coverage in partly cloudy areas Observe spatial mesoscale details important for intense weather prediction Provide high temporal resolution for predicting the onset of severe convection Provide altitude-resolved water vapor imagery time sequences potentially useful for estimating 4-d wind profiles for NWP applications Technique Can Provide Near-Global Coverage Using be Polar Satellite Hyperspectral Sounders (e.g., IASI, CrIS, HIRAS) Data Obtained Using the International Network of Direct Broadcast Systems (e.g., DBnet) and Geostationary Satellite Multi-spectral Instruments (e.g., ABI, AHI, AMI, and SEVIRI) PHS + ABI is NOT a replacement for the Geo-Hyperspectral Sounder
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