IGARSS July 2011 1

Thresholds of Detection for Falling Snow from Satellite-Borne Active and Passive Sensors

IGARSS 2011 Vancouver, Canada

Gail Skofronick JacksonBenjamin Johnson

Joe MunchakNASA Goddard Space Flight Center,

Greenbelt, MarylandGail.S.Jackson@nasa.gov

IGARSS July 2011 2

Presentation Outline

(1) Contributions to Brightness Temperatures

(2) Falling Snow Detection Thresholds• Analysis framework• Active thresholds based on instrument sensitivity• Passive thresholds• Comparison between active and passive• Future improvements

(3) Snow Field Campaign (Jan – Feb 2012)

(4) Summary

IGARSS July 2011 3

Percentages from Surface, Snow, & Water VaporL

ake

Eff

ect

2-3k

m t

op

s (0

.5 t

o 1

.0 I

WP

)S

yno

pti

c 5-

7km

to

ps

(0.5

to

1.0

IW

P)

Bli

zzar

d ~

10km

to

ps

(0.5

to

1.0

IW

P)

Bli

zzar

d ~

10km

to

ps

(9 t

o 1

0 IW

P)

“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 usedendrite snowflakes

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Falling Snow Detection Thresholds

What are the thresholds of detection in terms of IWP or IWC of falling snow?

Analysis Approach:• Use WRF models of Lake Effect and Synoptic snow

•Vertical profiles: IWC, temperature, water vapor profiles•Surface: temperature, land classification, snow depth

• Joint active and passive computations of Z and TB•Use Liu’s 2004 DDA tables for abs, scat, asymmetry, & backscatter

• 11 non-spherical snowflake shapes•Adjust N0 to integrate Liu’s min-max DDA sizes to ensure WRF IWC is preserved

IGARSS July 2011 5

(1) Surface Emissivity Part 1

Urban cropland deciduous evergreen/mixed water

Surface Temperature Vegetation Type Snow Depth

WRF Simulations

Courtesy of W.-K. Tao & team

IWP

(Ja

n 2

0 04

00U

TC

)

IWP

(Ja

n 2

2 06

00U

TC

)

Lake Effect Case Synoptic Snow Case

IGARSS July 2011 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

IGARSS July 2011 7

Reflectivities Depend on Particle Shape

W-Band

Ka-Band Ku-Band

IGARSS July 2011 8

Reflectivities Depend on Particle Shape

W-Band

Ka-Band Ku-Band

Ka

IGARSS July 2011 9

Z-Thresholds Depend on Particle Shape Average IWC Detected at Surface

Assumed minimum instrument Z:Ku: 18 dBZKa: 12 dBZW: -15 dBZ

±One std dev of variability over 11 shapes is plotted

Snowflake Shape (#) Ku-Band Ka-Band W-BandLong Hex Col. (0) 0.037 0.020 0.0020Short Hex Col. (1) 0.037 0.020 0.0019

Block Hexag. Col. (2) 0.039 0.020 0.0020Thick Hex Plate (3) 0.035 0.019 0.0019Thin Hex Plate (4) 0.033 0.018 0.00223-Bullet Rosette (5) 0.062 0.038 0.00184-Bullet Rosette (6) 0.065 0.052 0.00265-Bullet Rosette (7) 0.062 0.047 0.0022

Six Bullet Rosette (8) 0.063 0.101 0.0023Sector Snowflake (9) 0.077 0.049 0.0018Dendrite Snow (10) 0.079 0.145 0.0032

IGARSS July 2011 10

Radiometer Threshold ProcedureY-Axis: TBhydr – TBclearair (with perfect surface, etc knowledge)

X-Axis: IWP (max of 6 kg/m2)3-Bullet Rosette Shape: Red Line = Land surfaces, Blue line = Water Surfaces

10V

183±3V 166V

89V 37V

183±7V

These use 3-bullet rosette snowflakes

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Radiometer Thresholds Depend on Shape

89V

166V

166V 166H

183±3V 183±7V 166V22 Jan

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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 10oC

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

IGARSS July 2011 13

Radiometer Thresholds Depend on Snow Vertical Structure and Surface Type

Channel (GHz)

TotalThreshold

Cutoff

Average Detected

IWPLake Effect over Land

DetectedIWPLake Effect over LakesV-pol

DetectedIWPLake Effect over

Lakes H-pol

DetectedIWP

Synoptic over Land

DetectedIWP

Synoptic over

Lakes V-pol

DetectedIWP

Synoptic over LakesH-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

IGARSS July 2011 14

Active Versus Passive Snow Detection

Thresholds of Detection for Falling Snow from Satellite-borne Active and Passive Sensors by G. Skofronick-Jackson, et al., IEEE TGRS, submit 9/11

ActiveAvg. Surface IWC Detected: Ku Ka W Units

0.08 0.07 0.004 g m-3

Simple falling snow conversion (melted snow rate)1.01 0.93 0.027 mm hr-1

Passive over landAvg. Columnar IWP Detected: 89 166 183±3 183±7 Units Land V-Pol Lake Effect 0.43 0.16 1.85 0.37 kg m-2

Land V-Pol Synoptic 0.53 0.26 1.10 0.63 kg m-2

Simple IWC conversion (correct assumption????)Lake Effect (3 km clouds) 0.14 0.05 0.62 0.12 g m-3

Synoptic (6 km clouds) 0.09 0.04 0.18 0.11 g m-3

Simple falling snow conversion (melted snow rate)Lake Effect (3 km clouds) 1.97 0.61 11.19 1.65 mm hr-1

Synoptic (6 km clouds) 1.11 0.47 2.64 1.36 mm hr-1

Thresholds for passive could be improved with additional information

IGARSS July 2011 15

RGB Composite AMSU-B Emissivity MapThree Color Emissivity Map by Joe Munchak89 GHz (red), 150 GHz (green), 183 GHz (blue)

Darker colors indicate lower emissivities (more reflective) Missing data (black).

16IWSSM March 2011

GCPEx Snowfall Campaign (Near Toronto, Canada Jan.-Feb. 2012)GV Science

1. Radiometer/DPR Snowfall measurement sensitivities to snow type, rate, surface and tropospheric characteristics

2. Physics of snowfall in the column and relation to extinction characteristics3. Model databases for forward modeling and retrieval development.

Approach: •DFIR instrument clusters (account for measurement uncertainty, mitigate wind, complimentary physics) centered around X/W/Ka-KU/MRR radars and a ground-staring radiometer at CARE site.•Clusters located under C-band/D3R multi-freq/dual-pol radar umbrella; D3R V-point with W and X-bands or cover clusters in scanning/RHI/spectral sampling modes. •Overfly in-situ aircraft in coordination with DC-8 (APR-2 and CoSMIR radiometer);•Pre and post land surface radiative measurements by Ka-Ku and radiometers.

O (60 km)O (10 km)

7-8 km

0.4-0.8 km

Ht.

King City C-band Dual-pol

DFIR Clusters

xGeorgian Bay

CARE D3R

PSD: 2DVD, Parsivel, POSS,SVI

Radar: Ka/Ku,X,W(2),MRR

SWER: Pluvio, Hot Plate

SWE/Depth L-Band + -sensor

(Land/Snow) 10-89 GHz Radiometer

Aircraft: DC-8, Citation

x

IGARSS July 2011 17

Today’s Messages

(1) Falling snow retrievals are complex

Challenges being addressed:• non-spherical particles• surface emissivity

(2) Thresholds of Detection• Theoretical thresholds of detection are promising• Differences between active and passive detection thresholds• Thresholds for passive could be improved with additional

constraints

(3) What matters? IWP, cloud thickness, surface underneath, snow particle shapes and PSD limits, and more

(4) The GCPEx Field Campaign in 2012 will provide data to help address challenges and finalize algorithms.

IGARSS July 2011 18

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