Canopy Radiation Processes EAS 8803. Background Absorption of solar radiation drives climate system exchanges of energy, moisture, and carbon. Absorption.

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Presentation transcript:

Canopy Radiation Processes EAS 8803

Background Absorption of solar radiation drives climate system exchanges of energy, moisture, and carbon. Absorption of solar radiation drives climate system exchanges of energy, moisture, and carbon. What needed for climate modeling? What needed for climate modeling? Issue of scaling from small scale to scale of climate model-substantial room for improvement in quantification Issue of scaling from small scale to scale of climate model-substantial room for improvement in quantification

Ref. Dickinson 1983

Controls on Canopy Radiation Controls on Canopy Radiation Leaf orientation Leaf orientation Leaf optical properties Leaf optical properties LAI LAI Stems also commonly included but yet not constrained by any observations – leave out here Stems also commonly included but yet not constrained by any observations – leave out here Canopy geometry Canopy geometry Interaction with underlying soil or under-story vegetation Interaction with underlying soil or under-story vegetation

Leaf Orientation (ref. Dickinson, 1983)

Leaf orientation geometry: sun at an angle θ s whose cosine is µ s and leaf oriented with normal vector θ s, λ (i.e. zenith and azimuth ) and µ L = cos θ s Fraction of incident light intercepted per unit leaf area is : Fraction of incident light intercepted per unit leaf area is : cos (θ s - θ L ) = µ L µ L + sqrt[( 1- µ L 2 )(1- µ L 2 )]cos φ Where the two terms cancel, cos( ) = 0, switch from sunlight to shaded leaf upward. Happens when leaf normal + sun direction > 180 deg. Integrate over φ to describe the contributions of sunlight and shaded. Expressions too complicated to use for integrations over leaf angle –need to approximate. Where the two terms cancel, cos( ) = 0, switch from sunlight to shaded leaf upward. Happens when leaf normal + sun direction > 180 deg. Integrate over φ to describe the contributions of sunlight and shaded. Expressions too complicated to use for integrations over leaf angle –need to approximate. Easy to determine upward scattering for vertically or horizontally incident sun, so weighted average over these two terms, W = µ s 2 Easy to determine upward scattering for vertically or horizontally incident sun, so weighted average over these two terms, W = µ s 2

Leaf Orientation Distribution Numerous suggestions: easiest is to expand arbitrary orientation in even polynomials of µ L to obtain a distribution F(µ L ) = w (1. + b µ L 2 ) where w = 1/(1. + 1/3 b). Set b = 2 a/(1 -a), then observed orientations from a = -1, b = -1 to a = 1, b = ∞ Numerous suggestions: easiest is to expand arbitrary orientation in even polynomials of µ L to obtain a distribution F(µ L ) = w (1. + b µ L 2 ) where w = 1/(1. + 1/3 b). Set b = 2 a/(1 -a), then observed orientations from a = -1, b = -1 to a = 1, b = ∞ Overhead sun – all backward reflection r Overhead sun – all backward reflection r Sun on horizontal, upward scattering sees equal area of sunlight and shaded leaves. Sun on horizontal, upward scattering sees equal area of sunlight and shaded leaves. Sideways scattering = Ω/2 = (r+t) 2, where t is leaf transmission, Ω is single scattering albedo Sideways scattering = Ω/2 = (r+t) 2, where t is leaf transmission, Ω is single scattering albedo

Spectral leaf optical properties Observations – Observations – spectral dimension – r versus t, need to divide into 3 regions? spectral dimension – r versus t, need to divide into 3 regions? Scattering includes specular term with magnitude depending on structure of leaf surface. Scattering includes specular term with magnitude depending on structure of leaf surface. Models Models Describe structure in detail use Monte-Carlo statistical simulation Describe structure in detail use Monte-Carlo statistical simulation RT through flat plates- PROSPECT model( Jacquemoud) RT through flat plates- PROSPECT model( Jacquemoud) Parameterization simple enough for climate model- Parameterization simple enough for climate model-

Spectral properties- upper versus lower?- Hume et al technical report

Scattering phase function – diffuse + specular ( Greiner et al., 2007 )

Schematic Yves Govaerts et al.

Mechanistic Leaf Models (Jacquemoud & Ustin

Simple Parameterization for Leaf Scattering ( Lewis/Disney) W leaf = exp[ -a(n) A(λ)] W leaf = exp[ -a(n) A(λ)] a is O(1), depends on refractive index n a is O(1), depends on refractive index n A(λ) is the bulk absorption averaged over leaf materials at wavelength λ (i.e,, water and dry matter at all wavelengths, chlorophyll and cartinoids in visible). A(λ) is the bulk absorption averaged over leaf materials at wavelength λ (i.e,, water and dry matter at all wavelengths, chlorophyll and cartinoids in visible).

Leaf Area (LAI) From remote sensing, get pixel average. From remote sensing, get pixel average. Because of non-linearities, need details about spatial distribution Because of non-linearities, need details about spatial distribution How are these currently estimated? How are these currently estimated? Ignore – view LAI /canopies as applied to model grid square Ignore – view LAI /canopies as applied to model grid square Use concept of fractional cover of a pft – LAI a constant for a given pft –covers some fraction of model grid-square. Use concept of fractional cover of a pft – LAI a constant for a given pft –covers some fraction of model grid-square.

Canopy Geometric Structure. Climate models have only used plane parallel RT models Climate models have only used plane parallel RT models Uniform versus fractional cover f c of pft. Uniform versus fractional cover f c of pft. Transmission of sunlight T = fraction of area covered by sun or sun-flecks. Transmission of sunlight T = fraction of area covered by sun or sun-flecks. Compare: (1.- f c ) + f c exp ( - ½ LAI/ f c ) versus exp( - ½ LAI ) Compare: (1.- f c ) + f c exp ( - ½ LAI/ f c ) versus exp( - ½ LAI ) Both 1 – ½ LAI for small LAI, but (1.-fc) versus 0 for large LAI – non-vegetated fraction a canopy “gap” Both 1 – ½ LAI for small LAI, but (1.-fc) versus 0 for large LAI – non-vegetated fraction a canopy “gap”

Remote Sensing Community Ideas Geometry recognized as important contributor to reflected radiation Geometry recognized as important contributor to reflected radiation Strahler/Li – geometric shape/shadowing effects, add numerical treatment of canopy RT (GORT). Strahler/Li – geometric shape/shadowing effects, add numerical treatment of canopy RT (GORT). Quite a few simpler /more approximate approaches: e.g. GEOSAIL apparently developed for FIFE –idea is to use plane parallel RT model over sunlight canopy, and add in reflectance's from sunlight background, and shaded canopy and background. Quite a few simpler /more approximate approaches: e.g. GEOSAIL apparently developed for FIFE –idea is to use plane parallel RT model over sunlight canopy, and add in reflectance's from sunlight background, and shaded canopy and background.

Where canopy, LAI, hence optical path lengths, depend on location in space. Radiation decay as : exp (- ½ LAI(x,y) ) Radiation decay as : exp (- ½ LAI(x,y) ) Average transmission, an area average-can simplify by use of distribution, e.g. x a scaling parameter, 0 ≤ x ≤ 1.0, LAI = x LAI max and D(x) the fractional area where LAI/LAI max between x and x+ dx, then T = ∫ 1 0 dx D(x) exp ( - ½ x LAX max ). Integrates analytically if D(x) simple enough. Average transmission, an area average-can simplify by use of distribution, e.g. x a scaling parameter, 0 ≤ x ≤ 1.0, LAI = x LAI max and D(x) the fractional area where LAI/LAI max between x and x+ dx, then T = ∫ 1 0 dx D(x) exp ( - ½ x LAX max ). Integrates analytically if D(x) simple enough. Can fit T to exponentials and infer effective leaf parameters (approach of Pinty et al.) Can fit T to exponentials and infer effective leaf parameters (approach of Pinty et al.)

Use of distributions depends on canopy geometry Suppose canopy symmetric about some vertical axis, i.e LAI = LAI(r) depends on radial distance from this axis. Then Suppose canopy symmetric about some vertical axis, i.e LAI = LAI(r) depends on radial distance from this axis. Then T = 2∫rdr exp ( - ½ LAI(r) ). LAI = LAI max f(x), where x = (1.-r 2 ), f(x) = x ν 0 ≤ ν ≤ 1, ν = ½ or 1 gives half-sphere or rotated parabola. LAI = LAI max f(x), where x = (1.-r 2 ), f(x) = x ν 0 ≤ ν ≤ 1, ν = ½ or 1 gives half-sphere or rotated parabola.

Analysis of Spherical Bush Note: if distribution for transmission has analytic integral, so does that for forward and backward single scattering Note: if distribution for transmission has analytic integral, so does that for forward and backward single scattering Single scattering in arbitrary direction (for sphere at least) simply related to forward and backward scattering. Single scattering in arbitrary direction (for sphere at least) simply related to forward and backward scattering.

Spherical/spheroidal Bush Scattering ( Dickinson et al., in review Dickinson – in press ) To be multiplied by ω/(4π)To be multiplied by ω 2 /(4π)

Clustering If clustered at a higher level of organization, predominant effect is to multiply leaf optical properties by probability of a photon escape p e from cluster (can be directional): If clustered at a higher level of organization, predominant effect is to multiply leaf optical properties by probability of a photon escape p e from cluster (can be directional): In general, for p e a constant, p a = 1. – p e, In general, for p e a constant, p a = 1. – p e, ω cluster = ω leaf p e /( 1. – ω leaf p a ). Works for LAI of cluster out to 1. Spherical bush solutions and observational studies suggest maybe useful approximation for all expected LAI. Works for LAI of cluster out to 1. Spherical bush solutions and observational studies suggest maybe useful approximation for all expected LAI.

Overlapping Shadows Many statistical models can be used to fit spatial distribution of individual plant elements and hence the fractional area covered by shadows Many statistical models can be used to fit spatial distribution of individual plant elements and hence the fractional area covered by shadows Simplest default (random) model for shadows is fraction of shadow f s = (1. – exp( -f c S)) where f c is fractional area covered by vertically projected vegetation, and S is the area of an individual plants shadow relative to it projected area, eg. 1/ µ for sphere. Besides sun shadow, reflected radiation sees sky- shadow. Simplest default (random) model for shadows is fraction of shadow f s = (1. – exp( -f c S)) where f c is fractional area covered by vertically projected vegetation, and S is the area of an individual plants shadow relative to it projected area, eg. 1/ µ for sphere. Besides sun shadow, reflected radiation sees sky- shadow.

Shadow determines fraction of incident solar radiation intecepted by canopy For overlapping shadow, reduction of shadow area from nonoverlap requires addition of some distribution of LAI to canopy. Simplest is as a uniform layer above individual objects but other assumptions are feasible. For overlapping shadow, reduction of shadow area from nonoverlap requires addition of some distribution of LAI to canopy. Simplest is as a uniform layer above individual objects but other assumptions are feasible.

Combining with Underlying Surface Climate model does not use “albedo a” but how much radiation per unit incident sun absorbed by canopy A c and by ground A g. Climate model does not use “albedo a” but how much radiation per unit incident sun absorbed by canopy A c and by ground A g. A g = (1. – f s (1. – T c )) (1. – a g ) A c = f s (1 – a c ) + reflected by soil into canopy sky shadow (shadow overlap?)

Climate Consequences

Replacing Larch with Evergreen Conifers has an effect on albedo in winter that is analogous to growing trees. Siberian pine regeneration under a Larch canopy