The ICESat 2 Mission: Objectives, concept, and opportunities for snow

Transcription

1 The ICESat 2 Mission: Objectives, concept, and opportunities for snow M. Jasinski and T. Neumann NASA Goddard Space Flight Center NASA Snow Remote Sens Workshop CIRES August 14, 2013

2 Science Team Thorsten Markus: NASA GSFC/Project Scientist Thomas Neumann: NASA GSFC/Deputy Project Scientist Science Definition Team Beata Csatho, Univ. at Buffalo: ice sheets, SDT Leader Sinead Farrell, ESSIC, UMD: sea ice Helen Fricker, Scripps Institution of Oceanography: ice sheets Dave Harding, NASA GSFC: solid earth Mike Jasinski, NASA GSFC: inland lake elevation and snow depth Ron Kwok, JPL: sea ice Michael Lefsky, Colorado State Univ.: vegetation Dan Lubin, Scripps Institution of Oceanography: atmospheric science James Morison, Univ. of Washington: Arctic oceans Ross Nelson, NASA/GSFC: vegetation Amy Neuenschwander, Univ. of Texas: vegetation Steve Palm, SSAI: atmospheric science Bob Schutz, Univ. of Texas: geodesy CK Shum, Ohio State Univ.: ice sheets Ben Smith, Univ. of Washington: ice sheets incl snow Jay Zwally, NASA GSFC: ice sheets

3 Level 1 Baseline Science Requirements 1. Elevation changes of Greenland and Antarctica ice sheet elevation change rates to an accuracy of less than or equal to to 0.4 cm/yr on an annual basis. annual surface elevation change rates on outlet glaciers to an accuracy of less than or equal to 0.25 m/yr over areas of 100 km 2 for year to year averages. surface elevation change rates for dynamic ice features that are intersected by its set of repeated ground tracks to an accuracy of less than or equal to 0.4 m/yr along 1km track segments. resolution of winter (accumulation) and summer (ablation) ice sheet elevation change to 10 cm at 25 sq km scale. 2. Thickness of the polar ocean sea ice monthly surface elevation products of sea ice freeboard to an uncertainty of less than or equal to 3 cm along 25 km segments for the Arctic and Southern Oceans; the track spacing should be less than or equal to 35 km at 70 degrees latitude on a monthly basis. 3. Global vegetation height, inland and ocean elevation elevation measurements, that enable determination of global vegetation height, with a ground track spacing of less than 2 km over a 2 year period. 4. Elevation measurements for a minimum three year duration.

4 Advanced Topographic Laser Altimeter System (ATLAS) Single micro pulse, multi beam hi res, photon counting laser. Current launch date: mid 2016 flight direction flight direction 3 km 90 m 3 km 3 km 3 km Footprint size: 12 m PRF: 10 khz (0.7 m) 3 km spacing between pairs provides spatial coverage 90 m pair spacing for slope determination. High/low energy beams (~100/25 J) for better performance over low/high reflectance targets. Pointing: center of footprint known to ~6.5m

5 Mapping and Repeat Coverage Observation Zones Exact Repeat Mapping

6 ICESat 2 Mapping Scenario Mapping Operations: vegetation mapping requirement calls for two years off points to fill in veg. tracks After 2 years, we have 8 passes, reducing gaps to ~30/8 = ~3.75km. With 3 strong beams per pass, reduces to ~1.25km spacing km 7 7 pass pass 1 3 Large cross over database w/time

7 ICESat 1 Snow Depth Feasibility Study Stoll et al. AGU Fall Mtg, Dec. 2012

8 MABEL: ICESat 2 airborne simulator photon counting detection dual wavelength (532, 1064nm) small footprint (2m) high rep rate (typically 5 khz) mounted in nose of NASA s ER 2 aircraft (20 km altitude) 105 fibers in each row select up to 16 active channels at 532 nm and 8 at 1064nm flight direction

9 Photon counting philosophy ICESat 2 10 m 50 m 100 m MABEL data

10 Data Products for Seasonal Snow ATL03 Global Geolocated Photon Cloud. Provides latitude, longitude, and elevation for every returned photon (background and signal). Organized by beam. Provides coarse signal finding: +/ 5m vertically. HDF5 format. MABEL, Greenland April km ATL08 Land Elevation. Provides latitude, longitude, and elevation of ground and canopy top posted every 25 m along track. End user friendly data product. HDF5 format.

11 ICESat 2 Details for Consideration Radiometry: For fresh snow surfaces (albedo ~0.9), expect ~8 signal photons/shot for strong beam, 2 for weak beam. For non snowy surfaces, return depends (mainly) on albedo at 532nm. snow covered times of year will have better signal to noise. Total Ranging Precision: Driven by geolocation uncertainty, radiometry, surface algorithm. With more signal photons, surface is easier to identify. Approximate strong beam ranging precision; smooth surface Winter: fresh snow (albedo ~ 0.8) geoloc (cm) 100 shot ranging (cm) big Summer: bare ground (albedo ~ 0.2) geoloc (cm) 100 shot ranging (cm) biggest Spring: aged snow (albedo ~ 0.6) geoloc (cm) 100 shot ranging (cm) bigger

12 1. Imnavait Region SnowNet1km x 1km area centered at 68 36'43.40"N, '28.57"W Snow Depth Intensive section of test area Aircraft operated out of here Chris Hiemstra, CRREL, Fairbanks Jasinski & Neumann, Snow RS Ground Wkshp, LiDAR Aug 14, 2013

13 ICESat 2 Possible Seasonal Snow Sampling 2. Joe Wright Snotel site monitored by S. Fassnacht, CSU 1 km by 1km area centered at N, W First 2 years of tracks shown (8 cycles of 91 days) pairs of beams = 4 cross over points over ~100m x 100m area 6 beams crossing 6 beams = super cross over several km^2 area.

14 ICESat 2 Early Adopter Program (opportunity for cal val sites?) ov.php

15 Potential contributions of satellite lidar altimetry to 15 year snow remote sensing vision High spatial O[10m] and vertical 0[0.1 m] resolution Utility for snow within moderate density forest canopies Utility for other land and water targets Complements microwave retrievals of swe and vis/ir cover Multi frequency lidar offers greater potential.