comparison of measured and modeled snow brightness temperature using various field techniques for...
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Comparison of Measured and Modeled Snow Brightness Temperature Using Various Field Techniques for Grain Size Measurement. Edward KIM NASA Goddard Space Flight Center Michael DURAND Ohio State University Noah MOLOTCH University of Colorado, Boulder - PowerPoint PPT PresentationTRANSCRIPT
Comparison of Measured and Modeled Snow Brightness Temperature Using Various Field Techniques
for Grain Size Measurement
Edward KIM NASA Goddard Space Flight CenterMichael DURAND Ohio State UniversityNoah MOLOTCH University of Colorado, BoulderDaniel F. BERISFORD Jet Propulsion LaboratorySteven MARGULIS University of California Los AngelesZoe COURVILLE Cold Regions Research and Engineering Laboratory
Outline
• Problem statement• Our approach• Description of snow field
measurements• EM models• Microwave radiometer• Tb comparison results• Summary & Conclusions
The Problem with Snow Remote Sensing and “Grain Size”
• For microwave remote sensing of snow, accurate grain size numbers are extremely important to have because…
• the microwave signature of snow is highly sensitive to grain size• Unfortunately “grain size” is not easy to quantify accurately,
especially in the field• So what is the “best” way to measure grain size in the field for
use in microwave snow emission models?
How to determine a “best” grain size field measurement technique?
• What do we really need?• What do we already have?• How do we compare (and will
anyone else believe our results)?– What are we going to use as “truth”?
• What is practical?
Our Approach• Field Measurements
– Small campaign: 6 days, 1 snow pit per day– Limited set of techniques; side-by-side– Stereology chosen as “truth”– Location: Storm Peak Lab, Steamboat, Colorado, USA
• Brightness Temperature Comparison– Try 2 EM models, both multi-layer– Grain size & stratigraphy info fed into EM models– Models output brightness temperatures (Tb)– Compare model Tb vs. observed Tb
Grain Size Measurement Techniques
• Hand lens• NIR photography• Spectroscopy– Contact– New probe
• Stereology
Hand lens grain size measurements
• Plenty of precedent (e.g., CLPX)• Non-repeatable (e.g., two pits one meter apart; different days, plus
user variations; ‘B’ pit was in the radiometer FOV)
Pex & Dmax related as inDurand, Kim, Margulis, 2008
Pit BPit A
NIR Camera grain size
• Repeatable (in theory)• Empirically-based (transferability?)
Matzl and Schneebeli, 2006
Mätzler, 2002
PackDepth ~1m
1m
Contact Spectroscopy
• Measures reflectance across entire VIS/IR range
• Reflectance varies with grain size (see plot at right)
• Vertical resolution ~2cm• Requires commercial
spectrometer ($$)• Requires dark tarp to block
unwanted background light
Spectral Profiler Probe Prototype• Sends an optical package
into a slotted sleeve inserted into the snowpack to perform contact spectroscopy in-situ, w/o snowpit.
• Black tarp not shown to block light at base.
Spectral Profiler Probe
• Send optics down hole• Lateral reflectance spectra• Fiber optic sends signal to
spectrometer on surface• No snowpit needed!
• Prototype unit; 1st field trial, so analysis still in progress
probe carrier body
drive tube
optical camera
spectral reflectance probe
nylon brush
aluminum sleeve
fiber optic to spectrometer
Stereology grain size (1/4)
• 3D cast of actual snow grain structure made with dimethyl phthalate• Frozen in field with dry ice (stop metamorphism)• Shipped to CRREL for processing in cold room• Relatively well-known technique, but logistically intensive
Perla & Davis, 1980’s & earlier references Matzl and Schneebeli, 2010
Stereology grain size (2/4)
Time consuming laboratory work to cut and photograph: 20 slices / sample
Red line = 1mm
Stereology grain size (3/4)
• Cycloids overlaid on image for estimating surface area• Time-consuming manual counting work• Yields SSA directly, but then need to convert to pex for MEMLS
Matzl and Schneebeli, 2010
Red line = 1mm
L=total length of cycloid linesI=# of intersections crossedv=ice volume fractionDo= optical equiv. grain size
Stereology grain size (4/4)
• Image is classified as air or ice• Draw line through image, compute autocorrelation, do for each vertical line• Exponential is fit to true autocorrelation function
Wiesmann et al., 1998
EM models
• MEMLS• Multi-layer HUT
MEMLS sensitivity of Tb to grain size
• Vertically averaged optical equivalent grain size from pit
• Run MEMLS• Sensitivity is the tangent
to the curve• For this grain size (vertical
line), sensitivity is similar for 19 & 37 GHz
• To achieve 5K Tb accuracy, need 10% grain size accuracy, so for typical grain size, this means
Radiometric measurements
• Brightness measured daily for three days at 19 and 37 GHz, v-pol
Results & Discussion
• Grain size & stratigraphy info fed into EM models
• Models output brightness temperatures (Tb)• Compare model Tb vs. observed Tb
MEMLS (pex) vs. observations
• Bias and mean absolute error < 5 K• No empirical tuning factors required!• Based on laboratory work
• 19v observed: 249 K• 19v modeled: 230 K
(similar for SPL5 and SPL6)
• • 37v observed: 230 K• 37v modeled: 153
K (similar for SPL5 and SPL6)
• • The 19v is off by 20 K, and
the 37v is off by 80 K. Averaged together, and you have 50 K.
Multi-layer HUT results
MEMLS results
Multi-layer HUT results
• Note: HUT is set up to use hand lens Dmax measurements, so we’ve compared that to MEMLS hand lens, and then to MEMLS stereology as a reference
Summary & Conclusions• Used hand lens, spectroscopy, NIR, & stereology methods to measure grain
size; stereology was our ‘truth’• Used the grain size/correlation length to drive EM models (MEMLS, multi-
layer HUT)• Compared EM model Tb’s vs. observed Tb’s (‘truth’)• Using lab-based methods, Tb errors are 5-8 K• Using field-based methods, Tb errors are ~10 K• For error <=5K, need grain size accurate to ~10% ==> 20-100um• Using pex directly from stereology, no tuning empirical factor is required• Using SSA, an empirical factor (0.74) is required to get the right Tb –
attested to in literature (Mätzler, 2002)• Need further examination of multi-layer HUT to understand apparent cold
bias