why different passive microwave algorithms give different soil moisture retrievals

1X. Zhan, NOAA-NESDIS-STAR, IGARSS 2011, Vancouver, Canada, 24-27 July, 2011.

WHY DIFFERENT PASSIVE MICROWAVE WHY DIFFERENT PASSIVE MICROWAVE ALGORITHMS GIVE DIFFERENT SOIL MOISTURE ALGORITHMS GIVE DIFFERENT SOIL MOISTURE

RETRIEVALSRETRIEVALS

Xiwu Zhan, Jicheng LiuXiwu Zhan, Jicheng LiuNOAA-NESDIS Center for Satellite Applications and Research, Camp Springs, MDNOAA-NESDIS Center for Satellite Applications and Research, Camp Springs, MD

Thomas Holmes, Wade Crow, Tom JacksonThomas Holmes, Wade Crow, Tom Jackson USDA-ARS Hydrology and Remote Sensing Lab, Beltsville, MDUSDA-ARS Hydrology and Remote Sensing Lab, Beltsville, MD

Steven ChanSteven Chan NASA-JPL, Pasadena, CANASA-JPL, Pasadena, CA

IGARSS 2011, Vancouver, Canada, 24-27 July, 2011


OUTLINEOUTLINE

Current PM SM Data Products Current PM SM Data Products

Single-Channel vs Multi-Channel Single-Channel vs Multi-Channel AlgorithmsAlgorithms

Uncertainty Sensitivity AnalysisUncertainty Sensitivity Analysis

SummarySummary


GSFC SMMR (Owe et al, 2001)GSFC SMMR (Owe et al, 2001)

USDA TMI (Bindlish et al, 2003)USDA TMI (Bindlish et al, 2003)

Princeton TMI (Gao et al, 2006)Princeton TMI (Gao et al, 2006)

NASA AMSR-E (Njoku et al, 2003)NASA AMSR-E (Njoku et al, 2003)

USDA AMSR-E (Jackson et al, 2007)USDA AMSR-E (Jackson et al, 2007)

VUA AMSR-E (Owe et al, 2008)VUA AMSR-E (Owe et al, 2008)

USDA WindSat (Jackson et al, 2008)USDA WindSat (Jackson et al, 2008)

NRL WindSat (Li et al, 2008)NRL WindSat (Li et al, 2008)

Current Satellite Soil Moisture Data Products:Current Satellite Soil Moisture Data Products:


TB,icmp= Ts {er,i exp (-i/cos) +

(1 – ) [1 – exp (-i/cos)] [1 + (1-er,i)exp (-i/cos)]}

i = b *VWCer,i = f(es, h)

es = f(ε) -- Fresnel Equation

ε = f(SM) -- Mixing model (Dobson et al)

TB,iobs= TB06h , TB06v , TB10h , TB10v , TB18h , TB18v

}min{

26

1

,,2

i i

cmpiB

obsiB TT

Multi-channel Inversion (MCI) Algorithm :Multi-channel Inversion (MCI) Algorithm : (Njoku & Li, 1999)


Land Parameter Retrieval Model (LPRM) :Land Parameter Retrieval Model (LPRM) : (Owe, de Jeu & Holms, 2008)

TBhcmp= Ts {eh,r exp (-/cos) +

(1 – ) [1 – exp (-/cos)] [1 + (1- eh,r)exp (-/cos)]}

= f(MPDI) ,MPDI = (TBv-TBh)/(TBv+TBh)eh = f(es, h, Q)


ε = f(SM) -- Mixing model (Wang & Schmugge)

Ts = f(TB37v) or TsLSM

TBhobs= TB06h , TB10h or TB18h

}min{ cmpBh

obsBh TTdelta


Single Channel Retrieval Algorithm (SCA) :Single Channel Retrieval Algorithm (SCA) : (Jackson, 1993)

TB10h = Ts [1 –(1-er) exp (-2 /cos)]

= b * VWC, VWC = f(NDVI)eh = f(ev, h, Q)

es = f(ε) -- Fresnel Equationε = f(SM) -- Mixing model

Ts = f(TB37v) or TsLSM


Retrieval Results:Retrieval Results:

MCIMCI

LPRMLPRMSCRSCR

SMSM: : Aug 4, 2010Aug 4, 2010



MCIMCI

LPRMLPRMSCASCA

SMSM: : Aug 5, 2010Aug 5, 2010



MCIMCI

LPRMLPRMSCASCA

SMSM: : Aug 6, 2010Aug 6, 2010



MCIMCI

LPRMLPRMSCASCA

NDVI/VWC/tauNDVI/VWC/tau: : Aug 4, 2010Aug 4, 2010



MCIMCI

LPRMLPRMSCASCA



MCI and LPRM:MCI and LPRM:

1.1. LPRM converges while MCI sometimes not;LPRM converges while MCI sometimes not;

2.2. Remove tau=f(MPDI) from LPRM and use Remove tau=f(MPDI) from LPRM and use Ts = f(Tb37v) for MCI;Ts = f(Tb37v) for MCI;

3.3. Perturb Tb37v, Tbh & Tbv for LPRM and MCI Perturb Tb37v, Tbh & Tbv for LPRM and MCI to test how they are sensitive to their errors.to test how they are sensitive to their errors.

Uncertainty Sensitivity Analysis Procedure:Uncertainty Sensitivity Analysis Procedure:


Land Parameter Retrieval Model (LPRM) :Land Parameter Retrieval Model (LPRM) : (Owe, de Jeu & Holms, 2008)



= f(MPDI) ,MPDI = (TBv-TBh)/(TBv+TBh)eh = f(es, h, Q)



Ts = f(TB37v)

TBhobs= TB10h

}min{ cmpBh

obsBh TTdelta


Multi-channel Inversion with LPRM (MCI) :Multi-channel Inversion with LPRM (MCI) :



eh = f(es, h, Q)



Ts = f(TB37v)

TBiobs= TB10h and TB10v

}min{22

1,,

2

i

cmpiB

obsiB TT


Impact of Impact of Tau = f(MPDI) Tau = f(MPDI) onon SM SM Retrievals: Retrievals:

LPRM with tau = f(MPDI)

MCI without tau = f(MPDI)


Impact of Impact of 2K Ts error 2K Ts error on on LPRMLPRM//MCIMCI Retrievals: Retrievals:

Ts + 2K

Ts – 2K


No Ts errors

No Ts errors


Impact of Impact of 2K Tb error 2K Tb error on on LPRMLPRM//MCIMCI Retrievals: Retrievals:

Tbh + 2KTbv - 2K

Tbh - 2KTbv + 2K


No Tb errors

No Tb errors


SCA:SCA:

1.1. Use GLDAS SM inverse tau with SCA eqns;Use GLDAS SM inverse tau with SCA eqns;

2.2. Use the inversed tau to retrieve SM as reference;Use the inversed tau to retrieve SM as reference;

3.3. Perturb Tb37v, Tbh for SCA retrievals to testPerturb Tb37v, Tbh for SCA retrievals to testhow they are sensitive to these errors.how they are sensitive to these errors.

Uncertainty Sensitivity Analysis Procedure:Uncertainty Sensitivity Analysis Procedure:


Inversed Inversed SMSM and and Tau Tau usingusing SCA SCA equns: equns:

tau

SM


Impact of Impact of Tau error Tau error onon SCA SCA Retrievals: Retrievals:

Tau + 0.01

No Tau error



Tau + 0.05

No Tau error



Tau + 0.1

No Tau error


SUMMARYSUMMARY

The difference of current satellite soil moisture The difference of current satellite soil moisture products may confuse users.products may confuse users.

Single-Channel Algorithm relies heavily on accuracy of Single-Channel Algorithm relies heavily on accuracy of tau estimates.tau estimates.

LPRM algorithm uses a tau-MPDI relationship and TLPRM algorithm uses a tau-MPDI relationship and TB37vB37v

for Tfor Tss estimate to reduce iteration variable numbers in estimate to reduce iteration variable numbers in

solution procedure. Its sensitivity to Tsolution procedure. Its sensitivity to TBB calibration, T calibration, Tss

estimate and other parameter errors needs to be estimate and other parameter errors needs to be assessed.assessed.

Multi-channel Inversion algorithm is similar to LPRM Multi-channel Inversion algorithm is similar to LPRM algorithm when using the same Talgorithm when using the same Tss estimates. Thus, the estimates. Thus, the

tau-MPDI relationship may not be the key for the LPRM tau-MPDI relationship may not be the key for the LPRM success.success.

why different passive microwave algorithms give different soil moisture retrievals

Documents