Thresholds of Detection for Falling Snow from Satellite-Borne Active and Passive Sensors
1. Thresholds of Detection for Falling Snow from Satellite-Borne Active and Passive Sensors IGARSS 2011 Vancouver, Canada Gail Skofronick Jackson Benjamin Johnson Joe Munchak NASA Goddard Space Flight Center, Greenbelt, Maryland [email_address]
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3. Percentages from Surface , Snow , & Water Vapor Lake Effect 2-3km tops (0.5 to 1.0 IWP) Synoptic 5-7km tops (0.5 to 1.0 IWP) Blizzard ~10km tops (0.5 to 1.0 IWP) Blizzard ~10km tops (9 to 10 IWP) “ Surface and Atmospheric Contributions to Microwave Brightness Temperatures for Falling Snow Events,” by Gail Skofronick-Jackson and Benjamin Johnson, JGR-Atmos, published Jan 2011. (a) (b) (a) (b) Macro and microphysical cloud characteristics affect TB signal These use dendrite snowflakes
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5. (1) Surface Emissivity Part 1 Urban crop land deciduous evergreen/mixed water Surface Temperature Vegetation Type Snow Depth WRF Simulations Courtesy of W.-K. Tao & team Lake Effect Case Synoptic Snow Case IWP (Jan 20 0400UTC) IWP (Jan 22 0600UTC)
6. Radar Calculations W-Band (-26dBZ) Ka-Band (12dBZ) Ku-Band (18dBZ) Thresholds of Detection for Falling Snow from Satellite-borne Active and Passive Sensors by G. Skofronick-Jackson, et al., IEEE TGRS, submit 9/11 These use 3-bullet rosette snowflakes
12. Radiometer Thresholds Depend on Snow Vertical Structure and Surface Type Channel (GHz) Total Threshold Cutoff (rounded up) (in K) From 0.05 error in emissivity From 10 o C error in surface T From 10% change in Tprofile From 10% change in RHprof 10 25 14 10 0 0 19 25 14 10 0 0 23 25 14 10 0 0 37 25 13 10 0 0 89 25 13 9 0 0 166 20 11 8 1 1 183±3 5 1 2 1 1 183±7 15 5 6 0 1
13. Radiometer Thresholds Depend on Snow Vertical Structure and Surface Type Channel (GHz) Total Threshold Cutoff Average Detected IWP Lake Effect over Land Detected IWP Lake Effect over Lakes V-pol Detected IWP Lake Effect over Lakes H-pol Detected IWP Synoptic over Land Detected IWP Synoptic over Lakes V-pol Detected IWP Synoptic over Lakes H-pol 10 25 19 25 23 25 3.2 na na 37 25 1.2 2.0 1.1 89 25 0.4 0.5 1.5 0.5 0.6 0.8 166 20 0.2 0.2 0.2 0.3 0.3 0.3 183±3 5 1.8 na 1.1 1.1 na 183±7 15 0.4 0.4 na 0.6 0.6 na
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15. RGB Composite AMSU-B Emissivity Map Three Color Emissivity Map by Joe Munchak 89 GHz (red), 150 GHz (green), 183 GHz (blue) Darker colors indicate lower emissivities (more reflective) Missing data (black).
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18. Questions? Questions? IEEE Geoscience and Remote Sensing Society Administrative Committee (AdCom) Member Voting is open All GRSS members can vote for new AdCom members Please vote this week at the GRSS booth or online by Sept. 16, 2011
Editor's Notes
At 340GHz and higher, spheres were used instead of Liu non-spheres
A 1kg/m^2 threshold of detection for say 89 GHz means that if you distribute that 1kg/m^2 over a 5km cloud thickness (and if I did my math correctly) this means that one would need a surface LIQUID equivalent snow rate of ~3mm/hr (Hence the focus on the blizzard like events in the literature for passive snow events). For 0.5kg/m^2 the liquid equivalent is: 1.25mm/hr
A 1kg/m^2 threshold of detection for say 89 GHz means that if you distribute that 1kg/m^2 over a 5km cloud thickness (and if I did my math correctly) this means that one would need a surface LIQUID equivalent snow rate of ~3mm/hr (Hence the focus on the blizzard like events in the literature for passive snow events). For 0.5kg/m^2 the liquid equivalent is: 1.25mm/hr
dark=low emissivity, in this case from snow cover from blizzards in December 2006), why the oceans are blue (89=red,150=green,183=blue + emissivity increases with frequency = blue oceans), and why there is missing data (cloud cover or too much water vapor for all channels to "see" surface).
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