Long-Term Passive Microwave Observations of Soil and Vegetation Water Variability Eni Njoku

Long-Term Passive Microwave Observations of Soil and Vegetation Water Variability

Eni Njoku

Jet Propulsion LaboratoryPasadena, CA

WCRP/GEWEX LandFlux WorkshopToulouse, FranceMay 28-31, 2007

Satellite microwave radiometers viewing Earth have operated in space since the early 1970s

Only recently have they been designed specifically for soil moisture sensing (SMOS, HYDROS)

* Radiometer and radar

Relevant Spaceborne Microwave Sensors (Global Coverage)

**Status as of 2004**

Instrument Lowest

Frequency (GHz)

Resolution at Lowest Freq.

(km)

Year of Launch

ESMR (Nimbus-5) 19.3 25 1972 S-193* (Skylab) 13.9 16 1973 S-194 (Skylab) 1.41 115 1973 ESMR (Nimbus-6) 37 20 1975 SMMR (Seasat) 6.6 48.8 1978 SMMR (Nimbus-7) 6.6 50.3 1978 SSM/I (DMSP) 19.3 53.1 1987–> Mir-Priroda 13.0 1996 TMI 10.7 53.1 1997 MSMR 6.6 49.7 1999 Okean-O 6.9 1999 AMSR-E (Aqua) 6.9 55 2002 AMSR (ADEOS-II) 6.9 55 2002 SSMI/S 19.3 53.1 2003–> Windsat (Coriolis) 6.8 55 2003 GPM-Core 10.7 TBD 2007 SMOS 1.41 30-50 2007 CMIS (NPOESS) 6.8 56 2010–> HYDROS* 1.26, 1.41 1-3, 40 2010

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Earth Science Decadal Survey Reporthttp://www.nap.edu/catalog/11820.html

Missions Recommended for NASA(2016-2019 time-frame not shown)

L-Band1.4 GHzCMIS

AMSR6.0 GHzSSM/I

19 GHz

= Wavelengthn’’ = Im {Refractive Index}Power Attenuates as e-z/d

d = 4 π n’’

Vegetation attenuation increases with increasing measurement frequency

1.4 GHz

6.0 GHz

10.0 GHz

Effective sensing depth decreases with increasing measurement frequency

L-band provides significant improvements in soil moisture sensing capability over C- to K-band (SSM/I, TMI, AMSR-E)

Subscripts p, q : polarization (h or v)

Lpq, Lp : one-way vegetation attenuation factor, exp(-o / cos

Superscripts t, s, v, and sv indicate total, soil, vegetation, and soil-vegetation interaction terms, respectively

Emission(Radiometer)

Backscatter(Radar)

€

TBpt =TBp

s Lp +TBpv +TBp

sv

€

σ pqt =σ pq

s Lpq2 +σ pq

v +σ pqsv

(Emission)

(Backscatter)

Ionosphere, Atmosphere

Surface(Composite soil/vegetation)

Soil-Vegetation Surface Microwave Modeling

AMSR-E Observations

Means and standard deviations of TB spectral differences have been investigated to identify 'strong' RFI RFI spectral difference Indices:

TB6.9 – TB10.7 TB10.7 – TB18.7 etc.

These indices are not robust for identifying 'weak' RFI Caution is needed in using 6.9 GHz data

(and 10.7 GHz in some locations)

TB6.9 H-pol

TB6.9 –TB10.7

H-pol

TB (K): June 2004 (Mean, Descending)

Radio-Frequency Interference Effects

Reduction in Soil Moisture Sensitivity From C-to Ka-band(Can we do without C-band?)

Sensitivity to moisture in time series spanning a storm event (San Antonio, TX)

Sensitivity is greatest at 6.9 GHz, but RFI contamination is evident

10.7 GHz provides the best/most usable signal response

QuikScat

TMI

In Situ

Active and Passive Microwave Signatures vs. In Situ Soil Moisture

TB (K) 10.7 GHz (H-pol) June 1-3, 2003

190 310

0.0 0.3

Soil Moisture (g cm-3) June 1-3, 2003

Vegetation/Roughness (kg m-2) June 1-3, 2003

0 8

AMSR-E Soil Moisture Retrievals

Initial soil moisture algorithm used a 6.9 to 18 GHz multichannel forward-model iterative method

To avoid the RFI problem an alternate approach was implemented using primarily the 10.7 and 18.7 GHz channels

This approach retrieves a vegetation/ roughness “correction” parameter g, and the soil moisture mv

AMSR-E Retrieval Flag Classification

10 - Permanent Ice/Snow

20 - Mountainous

30 - Snow

40 - Frozen ground

50 - Precipitation

60 - RFI

70 - Dense vegetation

80 - Moderate vegetation

90 - Low vegetation

Jan 2003

July 2003

AMSR-E Flood Extent Mapping

Thunderstorms occurred from central Kansas to northern Texas in early March 2004

Analysis of the AMSR-E PR change from dry conditions indicates the daily spatial extent of elevated soil moisture (06 March 2004 image at left)

The image shows the observed maximum extent of retrieved soil moisture greater than 20% (vol)

Courtesy of NOAA Severe Storms Laboratory

AMSR-E Daily (Interpolated) Soil Moisture Extent(March 2004 Texas/Oklahoma Storm)

Precip (CPC) vs.

Soil Moisture (NARR)

Soil Moisture( AMSR-E vs.

NARR)

Except for a scaling factor, AMSR-E Soil Moistures show consistency with reanalysis data (NARR) in time series at some locations.

However, spatial patterns of the soil moisture are often not in good agreement between AMSR-E and NARR

AMSR-E Comparisons with Reanalysis Data (NARR)

K.-W. Jin

AMSR-E Monthly Soil Moisture (September 2002)

NASA Catchment Land Surface Model Soil Moisture(Koster, Reichle et al.)

Top two layers are 2 cm and 1 m

2-cm layer soil moisture

AMSR-E and NASA Catchment Model Soil Moisture Annual Statistics (2004)

Global maps of annual means and standard deviations of soil moisture were generated for AMSR-E and Catchment Model data

PDFs of the spatial distributions were computed for each map

(a) Top Panel: PDFs of annual mean soil moisture (2004)

(b) Bottom Panel: PDFs of annual standard deviation of soil moisture (2004)

AMSR-E retrievals show much less spread than modeled values in the annual mean and seasonal variability of soil moisture across the globe

(a) Annual Mean

(b) Annual Standard Deviation

Evolution of Soil Moisture Statistics with Changing Spatial Scale Using SWAP model (SMEX02,03,04)

Mohanty et al.

Evolution of Soil Moisture Statistics with Changing Spatial Scale Using SWAP model (Arizona)

1 cm depth

Mohanty et al.

10 cm depth10 cm depth

Evolution of Soil Moisture Statistics with Changing Spatial Scale Using SWAP model (Arizona)

Mohanty et al.

1 cm depth

Evolution of Soil Moisture Statistics with Changing Spatial Scale Using SWAP model (Iowa)

Mohanty et al.

10 cm depth

Evolution of Soil Moisture Statistics with Changing Spatial Scale Using SWAP model (Iowa)

Mohanty et al.

Sensor Intercalibration

Conical Scan Passive Microwave Sensor Data

SMMR (Nimbus-7)

SSM/I (DMSP-F08)

SSM/I (DMSP-F11)

SSM/I (DMSP-F13)

AMSR-E (Eos Aqua)

Center freq. (GHz) 6.6, 10.7, 18.0, 21.0,

37.0

19.35, 22.235(V), 37.0, 85.5

19.35, 22.235(V), 37.0, 85.5

19.35, 22.235(V), 37.0, 85.5

6.9, 10.7, 18.7, 23.8, 36.5, 89.0

Inc. Angle (deg) 50.3 53.1 53.1 53.1 54.8

3-dB footprint at 37 GHz (km)

27x18 37x29 37x29 37x29 14x8

Altitude (km) 955 832-851 841-878 844-856 705

Swath width (km) 780 (and 50% duty cycle)

1400 1400 1400 1445

Orbit; asc. node crossing

Polar, sun-sync;

12:00 noon

Polar, sun-sync;

6:15 am

Polar, sun-sync;

6:11 pm

Polar, sun-sync;

5:42 pm

Polar, sun-sync;

1:30pm

EASE-Grid Data period

Oct. 1978 - Aug. 1987

Jul. 1987 - Dec. 1991

Dec. 1991 - May 1995

May 1995 - present

May 2002 - present

Data from the SMMR, SSM/I, and AMSR-E are available in common gridded format from NSIDC

Cover period from 1978 through the present - though not all channels - and instruments have different frequencies, incidence angles, diurnal sampling, spatial resolution, and revisit intervals

Brig

htne

ss T

empe

ratu

re (

K)

Brig

htne

ss T

empe

ratu

re (

K)

Tropical Forest

Ice Sheet

Ocean

Tropical Forest

Ice Sheet

Ocean

SSM/I SSM/I SSM/I(a) 10 GHz Vertical

(b) 37 GHz Vertical

Single Grid Point Time-Series Data

Single-point data time series are from 10V and 37V ‘cold’ passes of SMMR, SSM/I (F08, F11, F13) and AMSR-E

Locations: Tropical Forest - Salonga, Zaire Ice Sheet - Dome C, Antarctica Ocean - Indian Ocean (35°S, 90°E)

Calibration anomalies are apparent, but are mixed with geophysical effects arising from seasonal and interannual trends at the point locations

Radiative transfer modeling and in-situ data are needed to indicate how much of the observed offsets are explainable by sensor observation configuration differences

Ocean-Average Time-Series Data

Six-day ocean-average brightness temperatures were generated daily, with filtering of land (~125 km from coast), sea-ice (<44°N & S), and ‘outlier’ data (95th percentile)

Shown plotted as deviations from long-term mean at 6.6/6.9 GHz and 37/36.5 GHz (SMMR/AMSR-E)

Geophysical variability (seasonal and interannual) is reduced by averaging; residual seasonal cycle can be filtered out

Calibration drifts of as little as several tenths of Kelvin can be detected against the stable ocean-average Tb background

Bri

ghtn

ess

Tem

pera

ture

(K

)B

righ

tnes

s T

empe

ratu

re (

K)

First-Order SMMR TB Correction Model(Adjusting to Mean AMSR-E Levels)

where hi( f )’s and vi( f )’s are to be determined for f = 6.6, 10.7, and 18.0 GHz

Establish common “tie points” between the two datasets

Compute coefficient matrices

T*Bh( f ) = h1( f ) TBh( f ) + h2( f ) TBv( f ) + h0( f )

T*Bv( f ) = v1( f ) TBv( f ) + v2( f ) TBh( f ) + v0( f )

Modeled relationship between AMSR-E TB and SMMR TB:

Comparison between AMSR-E and corrected SMMR:

S. Chan

Site 01: Tropical forest: Boumba in S.E. Cameroon (3.5N,14.5E)

Site 02: Tropical forest: Salonga in Central Zaire (1.5S,21.5E)

Site 03: Tropical forest: Mitu in Colombia/Brazil (1.5N,69.5W)

Site 04: Tropical forest: Curua in Central Brazil (8.5S,54.5W)

Site 05: Desert: Simpson Desert in Central Australia (24.5S,137.0W)

Site 06: Desert: Kalahari Desert in S.W. Botswana (24.5S,21.0E)

Site 07: Desert: Western Desert in W. Egypt (26.5N,26.5E)

Site 08: Desert: Erg Chech Desert in W. Algeria (26.5N,2.5W)

Site 09: Boreal forest: Boreas SSA in Saskatchewan, Canada (54.0N,104.0W)

Site 10: Boreal forest: Boreas NSA in Manitoba, Canada (56.0N,98.0W)

Site 11: Boreal forest: Bonanza Creek in N. Central Alaska (64.5N,148.0W)

Site 12: Sahel: Bilma in E. Niger (18.5N,13.5E)

Site 13: Sahel: Tahoua in S.W. Niger (14.0N,5.0E)

Site 14: Sahel: Kayes in Mali/Senegal (15.0N,12.0W)

Site 15: Grassland: Little Washita SGP in Oklahoma (36.0N,97.5W)

Site 16: Grassland: Lonoke Farm SCAN in Arkansas (34.9N,91.9W)

Site 17: Steppe: Mongolian Plateau in S.E. Mongolia (44.5N,108.0E)

Site 18: Tundra: Toolic Lake in N. Central Alaska (68.5N,149.5W)

Site 19: Ocean: N. Pacific Ocean (40.0N,160.0W)

Site 20: Ocean: S. Pacific Ocean (40.0S,160.0W)

Site 21: Ocean: N. Atlantic Ocean (40.0N,40.0W)

Site 22: Ocean: S. Atlantic Ocean (40.0S,40.0W)

Site 23: Ocean: Indian Ocean (20.0S,80.0E)

Site 24: Permanent Ice: Dome C, Antarctica (75.00S,123.0E)

End