Snow formation in the atmosphere: properties of snow and ice crystals

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Remote Sensing in Meteorology Applications for
Snow
Yildirim METE 110010231
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Topics in Remote Sensing of Snow

• Optics of Snow and Ice
• Remote Sensing Principles
• Applications
• Operational Remote Sensing

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FUNDAMENTALS OF REMOTE SENSING

1. Energy source
2. Atmospheric interactions
3. Target interactions
4. Sensor records energy
5. Transmission to receiving station
6. Interpretation
7. Application

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The EM Spectrum
Gamma Rays X rays Ultra-violet(UV) Visible
(400 - 700nm) Near Infrared (NIR) Infrared
(IR) Microwaves Weather radar Television,
FM radio Short wave radio
10-1nm 1 nm 10-2mm 10-1mm 1 mm 10
mm 100 mm 1 mm 1 cm 10 cm 1 m
102m
Violet Blue Green Yellow Orange Red
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C l v, where c is speed of light, l is
wavelength (m), And v is frequency (cycles per
second, Hz)
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WAVELENGTHS WE CAN USE MOST EFFECTIVELY
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Atmospheric absorptionand scattering
emission
absorption
scattering
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RADIATION CHOICES

• Absorbed
• Reflected
• Transmitted

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Properties of atmosphereand surface

• Conservation of energy radiation at a given
  wavelength is either
• reflected property of surface or medium is
  called reflectance or albedo (0-1)
• absorbed property is absorptance or emissivity
  (0-1)
• transmitted property is transmittance (0-1)

reflectance absorptance transmittance
1(for a surface, transmittance 0)
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PIXELS Minimum sampling area
One temperature brightness (Tb) value recorded
per pixel
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EM Wavelengths for Snow

• Snow on the ground
• Visible, near infrared, infrared
• Microwave
• Falling snow
• Long microwave, i.e., weather radar
• K (l 1cm)
• X (l 3 cm)
• C (l 5 cm)
• S (l 10 cm)

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Different Impacts in Different Regions of the
Spectrum

• Visible, near-infrared, and infrared
• Independent scattering
• Weak polarization
• Scalar radiative transfer
• Penetration near surface only
• ½ m in blue, few mm in NIR and IR
• Small dielectric contrast between ice and water

• Microwave and millimeter wavelength
• Extinction per unit volume
• Polarized signal
• Vector radiative transfer
• Large penetration in dry snow, many m
• Effects of microstructure and stratigraphy
• Small penetration in wet snow
• Large dielectric contrast between ice and water

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Visible, Near IR, IR
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Solar Radiation
Instrument records temperature brightness at
certain wavelengths
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Snow Spectral Reflectance
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General reflectance curves
from Klein, Hall and Riggs, 1998 Hydrological
Processes, 12, 1723 - 1744 with sources from
Clark et al. (1993) Salisbury and D'Aria (1992,
1994) Salisbury et al. (1994)
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Refractive Index of Light (m)

• m n ik
• The real part is n
• Spectral variation of n is small
• Little variation of n between ice and liquid

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Attenuation Coefficient

• Attenuation coefficient is the imaginary part of
  the index of refraction
• A measure of how likely a photon is to be
  absorbed
• Little difference between ice and liquid
• Varies over 7 orders of magnitude from 0.4 to 2.5
  uM

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ADVANCED VERY HIGH RESOLUTION RADIOMETER (AVHRR)

• 2,400 km swath
• Orbits earth 14 times per day, 833 km height
• 1 kilometer pixel size
• Spectral range
• Band 1 0.58-0.68 uM
• Band 2 0.72-1.00 uM
• Band 3 3.55-3.93 uM
• Band 4 10.5-11.5 uM

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Snow Measurement

• Satellite Hydrology Program

AVHRR and GOES Imaging Channels
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Snow Measurement

• Remote Sensing of Snow Cover

(NOAA 16)
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Snow Measurement

• NOAA-15 1.6 Micron Channel

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Mapping of snow extent

• Subpixel problem
• Snow mapping should estimate fraction of pixel
  covered
• Cloud cover
• Visible/near-infrared sensors cannot see through
  clouds
• Active microwave can, at resolution consistent
  with topography

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Analysis of Mixed Pixels

• Assuming linear mixing, the spectrum of a pixel
  is the area-weighted average of the spectra of
  the end-members
• For all wavelengths l,
• Solve for fn

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Subpixel Resolution Snow Mapping from AVHRR
May 26, 1995
(AVHRR has 1.1 km spatial resolution, 5 spectral
bands)
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AVHRR Fractional SCA Algorithm
Execute Sub-pixel snow cover algorithm using
reflectance Bands 1,2,3
Scene Evaluation Degree of Cloud Cover over
Study Basins
Snow Map Algorithm Output Mixed clouds, high
reflective bare ground, and Sub-pixel snow cover
Execute Atmospheric Corrections, Conversion to
engineering units
AVHRR Bands
AVHRR (HRPT FORMAT) Pre-Processed at
UCSB NOAA-12,14,16
Thermal Mask
Build Thermal Mask
Build Cloud Masks using several spectral-based
tests
Geographic Mask
Application of Cloud, Thermal, and Geographic
masks to raw AVTREE output
Composite Cloud Mask
Masked Fractional SCA Map
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Landsat Thematic Mapper (TM)

• 30 m spatial resolution
• 185 km FOV
• Spectral resolution
• 0.45-0.52 µm
• 0.52-0.60 µm
• 0.63-0.69 µm
• 0.76-0.90 µm
• 1.55-1.75 µm
• 10.4-12.5 µm
• 2.08-2.35 µm
• 16 day repeat pass

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Subpixel Resolution Snow Mapping from Landsat
Thematic Mapper
(Rosenthal Dozier, Water Resour. Res., 1996)
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Discrimination between Snow and Glacier Ice,
Ötztal Alps
Landsat TM, Aug 24, 1989
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AVIRIS CONCEPT

• 224 different detectors
• 380-2500 nm range
• 10 nm wavelength
• 20-meter pixel size
• Flight line 11-km wide
• Flies on ER-2
• Forerunner of MODIS

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AVIRIS spectra
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Spectra of Mixed Pixels
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Subpixel Resolution Snow Mapping from AVIRIS
(Painter et al., Remote Sens. Environ., 1998)
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GRAIN SIZE FROM SPACE
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EOS Terra MODIS

• Image Earths surface every 1 to 2 days
• 36 spectral bands covering VIS, NIR, thermal
• 1 km spatial resolution (29 bands)
• 500 m spatial resolution (5 bands)
• 250 m spatial resolution (2 bands)
• 2330 km swath

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Snow Water Equivalent

• SWE is usually more relevant than SCA, especially
  for alpine terrain
• Gamma radiation is successful over flat terrain
• Passive and active microwave are used
• Density, wetness, layers, etc. and vegetation
  affect radar signal, making problem more difficult

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SWE from Gamma

• There is a natural emission of Gamma from the
  soil (water and soil matrix)
• Measurement of Gamma to estimate soil moisture
• Difference in winter Gamma measurement and
  pre-snow measurement extinction of Gamma yields
  SWE
• PROBLEM currently only Airborne measurements
  (NOAA-NOHRSC)

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Snow Measurement

• Airborne Snow Survey Program

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Snow Measurement

• Airborne SWE Measurement Theory
• Airborne SWE measurements are made using the
  following relationship

Where C and C0 Uncollided terrestrial gamma
count rates over snow and
dry, snow-free soil, M and M0 Percent soil
moisture over snow and dry, snow-free soil, A
Radiation attenuation coefficient in water,
(cm2/g)
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Snow Measurement

• Airborne SWE Accuracy and Bias

Airborne measurements include ice and standing
water that ground measurements generally miss.
RMS Agricultural Areas 0.81 cm RMS Forested
Areas 2.31 cm
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Airborne Snow Survey Products
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Microwave Wavelengths
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Frequency Variation for Dielectric Function and
Extinction Properties

• Variation in dielectric properties of ice and
  water at microwave wavelengths
• Different albedo and penetration depth for wet
  vs. dry snow, varying with microwave wavelength
• NOTE typically satellite microwave radiation
  defined by its frequency (and not wavelength)

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Dielectric Properties of Snow

• Propagation and absorption of microwaves and
  radar in snow are a function of their dielectric
  constant

• Instrumentation Denoth Meter, Finnish Snow
  Fork, TDR
• e m2 and also has a real and an imaginary
  component

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Modeling electromagnetic scattering and absorption
Snow
Soil
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Volume Scattering

• Volume scattering is the multiple bounces radar
  may take inside the medium
• Volume scattering may decrease or increase image
  brightness
• In snow, volume scattering is a function of
  density

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SURFACE ROUGHNESS

• Refers to the average height variations of the
  surface (snow) relative to a smooth plane
• Generally on the order of cms
• Varies with wavelength and incidence angle

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SURFACE ROUGHNESS

• A surface is smooth if surface height
  variations small relative to wavelength
• Smooth surface much of energy goes away from
  sensor, appears dark
• Rough surface has a lot of back scatter, appears
  lighter