Multi-Satellite 3D Winds Land/Atmosphere Requirements

Transcription

1 Multi-Satellite 3D Winds Land/Atmosphere Requirements James L Carr* Carr Astronautics 6404 Ivy Lane, #333 Greenbelt, MD August 22-23, 2017 NOAA Workshop *jcarr@carrastro.com

2 Multi-Satellite 3D Winds Capability Name: Multi-Satellite 3D-Winds Capability Developer (NOAA funding organization): Self Partnerships in Development: CIMSS Capability Brief Description/Status: Optical flow of cloud/moisture tracers with parallax from multiple satellites enables retrievals of wind vectors with heights. Algorithm has been prototyped and tested. As presented at the 2017 NOAA Workshop 2

3 Multi-Satellite 3D Winds Derived Motion Wind height assignments are as important as the wind vectors themselves. Accurate and reliable height assignments can now be derived from parallax observations thanks to the high-quality Image Navigation and Registration (INR) now being achieved across the GOES constellation. We have a prototype 3D-Wind product and have crosscompared our parallax heights against CLAVR-x and CALIPSO with good results. As presented at the 2017 NOAA Workshop 3

4 Multi-Satellite 3D Winds What RFI gap can capability address? 2d How will capability complement or replace existing capabilities? Improves on wind height assignments by directly assigning heights to optical tracers used to derive wind vectors from first principles. What cost efficiencies are inherent to the capability? Extends on an existing GOES L2 Product (Derived Motion Winds) while using existing observing assets. True Enterprise Algorithm. As presented at the 2017 NOAA Workshop 4

5 Initial Work with Cloud-Top Heights Initial work was directed at Cloud-Top Height (CTH) maps using stereo methods with GOES-13, 14 & 15 while GOES-14 operated during Hurricane Sandy Use VIS Channel for fine resolution As presented at the 2017 NOAA Workshop 5

6 CLAVR-x Comparison Comparison with radiometric CLAVR-x algorithm shows anomalies probably because high thin layer makes assignment, but wind tracers are optically thick Some improvements since in radiometric methods to accommodate layering (Yue Li, et. al NOAA Satellite Conference). As presented at the 2017 NOAA Workshop 6

7 CALIPSO Comparison As presented at the 2017 NOAA Workshop 7

8 3D-Wind Prototype Algorithm We work with G-16 ABI Band 2 and the VIS Bands from the G-13 and G-15 Imagers Multi-satellite pairs/triplets provide height information from parallax Multi-temporal triplets provide optical flow of cloud motion 3D-geometric model solution provides wind vector with a height assignment Simultaneity correction improves accuracy of height assignments As presented at the 2017 NOAA Workshop 8

9 Multi-Temporal/Satellite Triplets G-16 Time G-15 Remapped into G-16 Fixed Grid + 5 minutes G-13 Remapped into G-16 Fixed Grid Longitude longitude = longitude = minutes G-16 As presented at the 2017 NOAA Workshop 9

10 Multi-Temporal Triplet RGB Composite Color separation shows motion Same clouds seen from same satellite at three times As presented at the 2017 NOAA Workshop 10

11 Multi-Satellite Triplet RGB Composite Color separation shows height Nearly Simultaneous Three-Satellite Composite Two Satellites Used Two Satellites Used Three Satellites Used Same cloud seen from the East, Center, West Satellite As presented at the 2017 NOAA Workshop Same cloud seen from the East, Center Satellite 11

12 Feature Matching for Tracers We measure feature correspondence with Normalized Cross Correlation (NCC) Interpolate on correlation surface for subpixel precision on relative shift As presented at the 2017 NOAA Workshop 12

13 Autocorrelation Screens for Valid Tracers If autocorrelation doesn t work, cross-correlation won t As presented at the 2017 NOAA Workshop 13

14 Adjustment for Non-Simultaneity Tracer motion can falsely look like parallax if multisatellite images are not simultaneous. As presented at the 2017 NOAA Workshop 14

15 Calibration of Height Assignments Calibrate clear sky over land three-satellite heights versus GLOBE terrain to remove any biases due to relative INR errors which tend to be slowly varying Calibrate two-satellite heights against three-satellite heights for the same slope and bias Over Terrain As presented at the 2017 NOAA Workshop 15

16 Prototype 3D-Winds Product As presented at the 2017 NOAA Workshop 16

17 Constellations for Enterprise 3D-Winds TEMPO GOES-R + S + EPIC + VIIRS As presented at the 2017 NOAA Workshop 17

18 Future Plans Work with GOES-S once it enters Post-Launch Testing Extend to IR & WV winds Experiment with LEO+GEO combinations Collaborate with CIMSS for more validation and comparison against operational products Participate in Cloud & Winds community meetings and exercises Exploit coverage by TEMPO once in orbit Our Goal: Introduce as a real capability within the NOAA weather enterprise. As presented at the 2017 NOAA Workshop 18

19 Multi-Satellite 3D Winds Additional Information: Inter-Comparisons between Radiometric and Geometric Cloud Top Height Products, H. Madani, J. Carr, Andrew Heidinger, and Steve Wanzong, American Geophysical Union, December Stereo Cloud Top Height Products for the GOES-R Era, H. Madani, and J. Carr, NOAA Satellite Conference, April As presented at the 2017 NOAA Workshop 19