Modeling Surface Energy Balance Using the MEP Method

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Modeling Surface Energy Balance Using the MEP Method Jingfeng Wang 1 and Rafael L. Bras 1,2 1 University of California at Irvine 2 Georgia Institute of Technology 5 th Interagency Surface Dynamics Working Group Meeting 1 - 3 March 2011 USDA Southwest Watershed Research Center, Tucson, AZ

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Modeling Surface Energy Balance Using the MEP Method. Jingfeng Wang 1 and Rafael L. Bras 1,2 1 University of California at Irvine 2 Georgia Institute of Technology 5 th Interagency Surface Dynamics Working Group Meeting 1 - 3 March 2011 - PowerPoint PPT Presentation

Transcript of Modeling Surface Energy Balance Using the MEP Method

Page 1: Modeling Surface Energy Balance Using the MEP Method

Modeling Surface Energy Balance Using the MEP Method

Jingfeng Wang1 and Rafael L. Bras1,2

1University of California at Irvine2Georgia Institute of Technology

5th Interagency Surface Dynamics Working Group Meeting 1 - 3 March 2011

USDA Southwest Watershed Research Center, Tucson, AZ

Page 2: Modeling Surface Energy Balance Using the MEP Method

Rn = E + H + G

Land Surface Energy Budget

Partition of net radiation Rn into the fluxes of latent heat E, sensible heat H and ground heat G.

Page 3: Modeling Surface Energy Balance Using the MEP Method

MEP Theory

• Maximum Entropy Production Principle (MEP): an application of MaxEnt to non-equilibrium systems with macroscopic transport of energy and matter.

• Maximum Entropy Principle (MaxEnt): a general method to assign probability distribution. The concept of entropy is introduced as a quantitative measure of information (or lack of it).

Page 4: Modeling Surface Energy Balance Using the MEP Method

MaxEnt Formalism

mk

k

m

kikk

mikI

k

n

iiki

n

iiiI

ZF

xfZ

pmkFSMax

nmkFxfp

ppS

,...,ln

)(exp),...,(

1}1,{

);(1,

,ln

1

11

1

1

Assigning probabilities pi of xi by maximizing the information entropy SI under generic constraints Fk,

Page 5: Modeling Surface Energy Balance Using the MEP Method

,21

m

kkk FD

Dissipation function or entropy production function, D, is defined as,

satisfying the orthogonality condition, according to MaxEnt,

.1,4 mkFD

kk

Page 6: Modeling Surface Energy Balance Using the MEP Method

• D is maximized under a (nonlinear) constraint,

m

kkk

m

F

FFD

1

*

1

2

,,

• D is minimized under a (linear) constraint,

*

1

*2 cFm

kkk

Page 7: Modeling Surface Energy Balance Using the MEP Method

MEP Method

1. Formulate a dissipation function or entropy production function in terms of the heat fluxes,

2. Find the stationary point of the dissipation function under the constraint of conservation of energy,

3. Solve the heat fluxes.

Page 8: Modeling Surface Energy Balance Using the MEP Method

An Example

I1

I2

I0 = I1+I2

R1

R2

1. Formulate the dissipation function of the system in terms of the electric currents,

12

22

11

21

21 ),( RI

RIIID

Page 9: Modeling Surface Energy Balance Using the MEP Method

2. Find the stationary point of the dissipation function under the constraint of conservation of electric charges,

12

21

1

1

02121,min

RI

RI

IIIIID

3. Solve the currents,

012

11

12

2

012

11

11

1 ,

IRR

RI

IRR

RI

Lagrangian multiplier

Page 10: Modeling Surface Energy Balance Using the MEP Method

Physical Meaning of D

,

,),(

,),(

2

222

1

12

121

2221

2121

TRI

TRIIID

RIRIIID

thermal dissipation

thermodynamic entropy production

Voltage

Page 11: Modeling Surface Energy Balance Using the MEP Method

MEP Formalism of Heat Fluxes

A dissipation function or entropy production function is formulated as [Wang and Bras, 2011];,

sae IG

IH

IEGHED

222

),,(

Is=thermal inertia of conduction = Ia=thermal inertia of sensible heat transfer =Ie=thermal inertia of latent heat transfer (to be defined)

sssc Hpac

Page 12: Modeling Surface Energy Balance Using the MEP Method

Formulation of Ia

Based on the Monin-Obukhov similarity theory [Wang and Bras, 2010];,

a,b,g2 are universal empirical constants[Businger et al, 1971].

bgaa

22/)21/(2/3,

22

1

61

0210

CC

stableunstable

TczgCzCcI

papa

61

0 HIIa

Page 13: Modeling Surface Energy Balance Using the MEP Method

Formulation of Ie

1. Ie is related to Ia due to the same turbulent transport mechanism for heat and water vapor;

2. Ie is a function of surface soil temperature and soil moisture as E depends on the two variables;

3. Water vapor right above the evaporating surface is in equilibrium with the liquid water at the soil surface.

Page 14: Modeling Surface Energy Balance Using the MEP Method

Ie is postulated based on the above propositions:

ae II

Ts = surface (skin) soil temperature,qs = surface (skin) specific humidity, = latent heat of vaporization,cp = specific heat of air at constant pressure,Rv = gas constant of water vapor,

,2

2

s

s

vp Tq

Rc

Page 15: Modeling Surface Energy Balance Using the MEP Method

MEP Model of E, H, G

2

2

61

0

,1361116

,,

)(

),,(,,

min

s

s

vp

n

s

n

Tq

RcB

GHERGHEHBE

HHIIBG

RGHEGHEDGHE

Page 16: Modeling Surface Energy Balance Using the MEP Method

Input of the MEP Model

Rn, Ts, qs or qs

E, H, G

net radiationsurface temperature

surface humidity

surface soil moisture

Page 17: Modeling Surface Energy Balance Using the MEP Method

Properties of the MEP Model Over a dry soil ( = 0, hence E = 0), the MEP model for the dry case is retrieved [Wang and Bras, 2009];

Over a saturated soil, the MEP Bowen ratio, B-1(), reduces to the classical equation [Priestley, 1959, p.116],

Page 18: Modeling Surface Energy Balance Using the MEP Method

Lucky Hills site of the Walnut Gulch Experimental Watershed during 11/16 – 12/26, 2007.

Page 19: Modeling Surface Energy Balance Using the MEP Method

MEP Model of Transpiration

Over a canopy when Is=0 (hence G=0), the MEP model gives explicit expressions of transpiration Ev and H,

)(1

)(1 1

BRH

BRE

n

nv

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Harvard Forest site during 19 August - 18 September 1994.

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• MODIS-Terra for Sept., 2006•

Remote Sensing Application

September 2006

Remotely sensed MEP model input Rn, Ts, and qs (Td) from MODIS on Terra satellite over Oklahoma [Bisht and Bras, 2010]. The heat fluxes are in W m-2 and time in hours.

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Conclusion

The MEP model provides an effective tool to estimate evapotranspiration (together with sensible and ground heat fluxes) using field and remotely sensed surface variables as model input.

Acknowledgment: This study is sponsored by ARO grant W911NF-10-1-0236 and NSF grant EAR-0943356.

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References• Bisht, G., and R. L. Bras (2010), Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study, Remote Sens. Environ., 114, 1522-1534.

• Businger, J. A., J. C. Wyngaard, Y. Izumi, and E. F. Bradle (1971), Flux-profile relationships in the atmosphere surface layer, J. Atmos. Sci., 28, 181-189.

• Dewar, R. C. (2005), Maximum entropy production and fluctuation theorem, J. Phys. A: Math Gen., 36, L371-L381.

• Priestley, C. H. B. (1959), Turbulent Transfer in the Lower, The University of Chicago Press, Chicago, 130pp.

• Wang, J., and R. L. Bras (2009), A model of surface heat fluxes based on the theory of maximum entropy production, Water. Resour. Res., 45, W11422.

•Wang, J., and R. L. Bras (2010), An extremum solution of the Monin-Obukhov similarity equations, J. Atmos. Sci. 67(2), 485-499. • Wang, J., and R. L. Bras (2011), A model of evapotranspiration based on the theory of maximum entropy production, Water. Resour. Res., in press.