Microwave Remote Sensing of Snowpack

Do-Hyuk “DK” Kang

Postdoctoral FellowNorthern Hydrometeorology Group (NHG)Environmental Science and Engineering

University of Northern BC

February 5th 2013

Northern Hydrometeorology Group, UNBC Discovery and Acceleration Fund

Outline Fundamentals of remote sensing Satellites and sensors Application of remote sensing Remote sensing of snow in the Cariboo

Mountains of BC (Jinjun Tong) Microwave Remote Sensing Results (DK and Déry)

Remote Sensing is a technology for sampling electromagnetic radiation to acquire and interpret non-immediate geospatial data from which to extract information about features, objects, and classes on the Earth's land surface, oceans, and atmosphere (and, where applicable, on the exteriors of other bodies in the solar system, or, in the broadest framework, celestial bodies such as stars and galaxies).

Energy Source or Illumination (A)

Radiation and the Atmosphere (B)

Interaction with the Target (C) Recording of Energy by the

Sensor (D) Transmission, Reception, and

Processing (E) Interpretation and Analysis (F) Application (G)

Electromagnetic Radiation

Interactions with the Atmosphere

Scattering Absorbing

Those areas of the spectrum which are not severely influenced by atmospheric absorption and thus, are useful to remote sensors, are called atmospheric windows

Target Interactions

Absorption (A) occurs when radiation (energy) is absorbed into the target while transmission (T) occurs when radiation passes through a target. Reflection (R) occurs when radiation "bounces" off the target and is redirected.

water and vegetation may reflect somewhat similarly in the visible wavelengths but are almost always separable in the infrared.

Passive vs. Active Remote Sensing

Passive Sensing Active Sensing

Satellites and Sensors In order for a sensor to collect and record energy

reflected or emitted from a target or surface, it must reside on a stable platform removed from the target or surface being observed. Platforms for remote sensors may be situated on the ground, on an aircraft or balloon (or some other platform within the Earth's atmosphere), or on a spacecraft or satellite outside of the Earth's atmosphere. Although ground-based and aircraft platforms may be used, satellites provide a great deal of the remote sensing imagery commonly used today.

Satellite Orbits

Geostationary orbits

Near-polar orbit

Ascending vs Descending

Weather Satellites/Sensors TIROS-1(launched in 1960 by the United States)

GOES (Geostationary Operational Environmental Satellite) -GOES-1 (launched 1975), GOES-8 (launched 1994)

Advanced Very High Resolution Radiometer(NOAA AVHRR)(sun-synchronous, near-polar orbits)

FengYun-1, FengYun-2, FengYun-3, FengYun-4 (China)

GMS (Japan)

Meteosat (European)

Land Observation Satellites/Sensors

Landsat (Landsat-1 was launched by NASA in 1972, near-polar, sun-synchronous orbits).

-Return Beam Vidicon (RBV), MultiSpectral Scanner (MSS), Thematic Mapper (TM)

SPOT(SPOT-1 was launched by France in 1986, sun-synchronous, near-polar orbits)

-Twin high resolution visible (HRV)

Multispectral Electro-optical Imaging Scanner(MEIS II) Compact Airborne Spectrographic Imager(CASI)(airborne

sensors)(Canada)

Canadian RADARSAT I and II - (Active Microwave Remote Sensing)

Data Reception, Transmission, and Processing

In Canada, CCRS operates two ground receiving stations - one at Cantley, Québec (GSS), just outside of Ottawa, and another one at Prince Albert, Saskatchewan (PASS)

Quiz

It is one of 13 main sub-basins in the Fraser River Basin, one of the world's most productive salmon river systems.

Snow plays a vital role in the energy and water budgets of these basins.

The Quesnel River Basin (QRB) in the Cariboo Mountains

Evaluation of MODIS data

Snow No snowSnow a b

No snow c d

GroundMODIS

a dAccuracya b c d

Accuracy of different MODIS snow data

Stations Elevation, m

MOD10A1, % MOD10A2, % SF, %

Horsefly Lake/Gruhs Lake 777 88.31 88.92 91.49

Barkerville 1265 85.95 86.69 87.89

Boss Mountain Mine 1460 71.14 81.25 82.72

Yanks Peak East 1670 62.17 73.85 74.15

The spatially filtered snow cover fraction (SCF) for different elevation bands (top) and aspects with slopes > 15o (bottom), 2000-2007.

ResultsSn

ow c

over

frac

tion

(%)

The mean elevational dependence of snow cover fraction (SCF) for the months of February to July, 2000-2007.

The annual snow cover duration (x3 days) in the QRB based on spatially filtered (SF) MODIS snow products, 2001-2007.

r = 0.96 d(SCD)/dz =

11.6 days (100 m)-1

400 800 1200 1600 2000 2400 28000

20406080

100120140

(Snow melt season)

SF MOD10A2

400 800 1200 1600 2000 2400 28000

20406080

100120140

(Snow accumulation season)

Sno

w c

over

dur

atio

n (d

ays)

400 800 1200 1600 2000 2400 28000

60120180240300360

(Entire year)

Elevation (m)

400 800 1200 1600 2000 2400 28000

0.51

1.52

2.53

(Snow melt season)

400 800 1200 1600 2000 2400 28000

0.5

1

1.5

2

2.5

(Snow accumulation season)

Sta

ndar

d de

viat

ion

(day

s)

400 800 1200 1600 2000 2400 28000

1

2

3

4

(Entire year)

Elevation (m)S

CD

(day

s)

Mean snow cover durations (SCD) for 10-m elevation

bands from the MOD10A2 (+) & SF (□) products, 2001-

2007.

Scatter plot between average air temperature and SCF50% (top) and scatter plot between SCF50% & R50% during spring for the QRB, 2000-2007 (bottom).

Quiz

Snow Microwave Sensors SMMR (scanning multichannel microwave radiometer) - It measured dual-polarized microwave radiances, at 6.63,

10.69, 18.0, 21.0, and 37.0 GHz, from the Earth's atmosphere and surface.

SSM/I (special sensor microwave/imager) -The instrument measures surface/atmospheric microwave

brightness temperature (TBs) at 19.35, 22.235, 37.0 and 85.5 GHz.

AMSR-E ( Advanced Microwave Scanning Radiometer-EOS). -12 channels and 6 frequencies ranging from 6.9 to 89.0

GHz. H-pol. and V-pol.

Energy Flux VS Intensity Energy flux is defined by the energy flow

with a given area [W/m2]

Intensity is defined by the energy flow per a given area, a given frequency, and a given solid angle [W/m2 Hz Steradian ] – a physically imaginary term but important for the interpretation in Remote Sensing

Fraser River Snow Dominant Watershed

1 mm grids, Salminen et al. 2009

Quiz

Passive vs. Active Sensing

Frolov and Marchert 1999, Hallikainen et al. 1986, TGRS

Key Words

Matzler and Wiesmann 1999 Devonec and Barros 2002

Tb

Ts

a

''n

b

pec s

'

s freq LWC

''

Brightness Temperature

Absorption Coeffi.

Scattering Coeffi.

Real Permittivity

Imaginary Permittivity

Schanda and Matzler1981

Willis et al. 2012 RS and Env

Kang et al. 2012Accepted in IEEE

Derksen et al. 2012 RS env

Derksen et al. 2005, Chang et al. 1987

Time series (left) and scatter plots (right) of the observed & retrieved SWE from algorithms using different AMSR-E channel combinations at Yanks Peak East from 2003-2005.

Conclusions Use Remote Sensing to cover global scale

monitoring of snowpack Visible and Microwave Remote Sensing of

Snowpack Reflectance and Microwave Radiometry Antenna Response Model VS Radiometry

observation Wave signatures VS Snow physical properties