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Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer . Marco Matricardi, ECMWF 26 April - 27 April 2011.

Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

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Page 1: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Training Course Module DA.

Data assimilation and use of satellite data.

Introduction to infrared radiative transfer.

Marco Matricardi, ECMWF

26 April - 27 April 2011.

Page 2: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Why learn about radiative transfer

The exploitation of radiance data from satellite sounders requires the availability of a radiative transfer model (usually called the observation

operator) to predict a first guess radiance from the NWP model fields corresponding to every measured radiance.

The radiative transfer model (and its adjoint) are therefore a key component in the assimilation of satellite radiance in a NWP system.

Page 3: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Electromagnetic radiationat the top of the atmosphere

The forward model simulates the observed radiances using the equation of radiative transfer

Page 4: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Liou (2002)

Near Infrared

Far infrared

Spectrum of electromagnetic radiation

Page 5: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Liou (2002)

Pencil of radiation

Differential area, dA

Normal to dA

Radiance

The monochromatic radiance, Lν, is defined as the amount of energy crossing, in a time interval dt and in the frequency interval to , a differential area dA at an angle θ to the normal to dA, the pencil of radiation being confined to a solid angle dΩ.

][)cos( 12

ssrm

W

dddtdA

dEL

A fundamental quantity associated to a radiation field is the intensity of the radiation field or radiance.

The radiance can also be defined for a unit wavelength, λ, or wave number, , interval. If, c, is the speed of light in vacuum, the relation between these quantities is:

1c

~

d

(2)

(1)

Wavelengths are usually expressed in units of microns (1µm=10-6 m) whereas wave numbers are expressed in units of cm-1.

Page 6: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

To represent the outgoing radiance as viewed by a radiometer, the spectrum of monochromatic radiance must be convolved with the appropriate instrument response function. This yields to so-called polychromatic or channel radiance.

Radiance

Satellite radiometers make measurements over a finite spectral interval. They respond to radiation in a non-uniform way as a function of frequency (or wave

number).

AIRS: Atmospheric Infrared Sounder

The channel radiance is defined as:

Where is the normalised instrument response function and ^ over the symbol denotes convolution. Here is the central frequency of the channel.

2

1

*

~

~

*~~~)~~(ˆ

dfLL

*~)~~( * f

(3)

Monochromatic radiance

Page 7: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Blackbody radiation

If we consider a gas in thermodynamic equilibrium inside an isothermal enclosure at temperature T, the radiance inside the enclosure is expressed by the Planck’s function:

where h is the Planck’s constant and k is the Boltzman constant. Note that depends only on the temperature of the enclosure (for a fixed frequency).

The radiance inside an isothermal enclosure is the

same as the radiance emitted by a blackbody at the

same temperature. A blackbody is a body which

absorbs all the radiation incident on it.

Bν(T) is also known an blackbody function and the radiation inside the enclosure is called blackbody radiation.

)1(

2)(

)(2

3

kT

h

ec

hTB

(4)

Large cavity with absorbing walls

)(TB

A small hole in a large cavity is a very close approximationto an ideal blackbody if the wavelength of the incident radiation is shorter than the diameter of the hole.

Note that for a finite-size cavity, the radianceinside the cavity can be expressed by the Planck’s function only if the wavelengthof the radiation is smaller than the size of the cavity.

Page 8: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Blackbody radiation

If we define c1=2πhc2 and c2=hc/k as the first and second radiation constant, we can give an equivalent black body function in terms of radiance per unit wavelength:

(5)

for

for

)1(

)()(

51

2

T

c

e

cTB

2

2

20 or , ( )

kTB T

c

3

2

2or 0, ( )

hv

kThB T e

c

This is known as Rayleigh-Jeans Distribution

This is known an Wien distribution

Page 9: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Valley (1965)

Blackbody radiation curves for different temperatures

The peak of the blackbodycurve shifts to shorter wavelengths as the temperature of the blackbodyincreases. The peak is given byWien’s displacement law:

λ=2.7 103/T [µm]

Page 10: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Brightness temperature

In many applications, the radiance, L(ν), is expressed in units of equivalent brightness temperature, Tb(ν).

For a given frequency, the brightness temperature is the temperature (in Kelvin) that a black body would need to have to emit the observed (or simulated) radiance. The brightness temperature can be computed

by inverting Planck’s function (equation (4) ).

Page 11: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Electromagnetic radiation in the atmosphere interacts with molecules and aerosol/cloud particles. This interaction can increase or decrease the intensity of the radiation field. The decrease of the intensity is called extinction whereas the increase of the intensity is called emission.

In general, the extinction of radiation is the sum of two different mechanisms: absorption and scattering. In the infrared, atmospheric scattering occurs in presence of aerosol and cloud particles.

Transmittance and optical depth

After McCartney (1983)

When we have absorption, the intensity of the radiation field decreases because radiant energy is converted into other forms of energy (e.g. kinetic energy of the medium).

When we have scattering, there is no conversion of the radiant energy to other forms of energy. The intensity of the radiation field decreases because radiant energy is redirected from its original direction.

Scattering mediumAbsorbing medium

•Scattering particles

Page 12: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Transmittance and optical depth

ds

s

The attenuation of intensity along a path ds is thus:

(6)dsskLdL e )(

The extinction coefficient can be written as the sum of the absorption coefficient, , and the scattering coefficient, .ak

sk

Density of the medium [Kg m-3]Mass extinction coefficient [m2Kg-1]

The process of extinction is governed by the Beer-Bouguer-Lambert law. It states that extinction is linear in the amount of matter and in the

intensity of radiation.

Page 13: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The integration of Eq. (6) between points s1 and s2=s1+s yields :

(7)

Transmittance and opical depth

2

1

)(exp()()( 12

s

s

e dssksLsL

The optical depth of the medium between points s1 and s2 is defined as:

(8)2

1

)(s

s

e dssk

The transmittance of the medium between points s1 and s2 is defined as:

(9)2

1

)(exp(s

s

e dssk

Page 14: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer

If we assume that the emission process is linear in the amount of matter, the change of intensity can be written as:

(10)

Eq. (10) is the equation of radiative transfer (Schwarzchild’s equation).

dskJdskLdL ee )()()( sss

is called the source function. It consists, in general, of two parts:

(11)

)(sJ

The change of intensity resulting from the interaction between radiation and matter is the sum of the contribution due to extinction and

emission.

e

sscattering

e

athermal

k

kJ

k

kJJ

)()()( sss

Page 15: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer: the scattering source function

Scattering is a source of emission in a given direction because it canredirect radiant energy from other directions into the actual direction.

In absence of solar radiation, the scattering source function can be written as:

(12)

d

dscattering dLPJ

)(),(

4

1)( dsds

is known as the phase function. It describes the angular distribution of the scattered energy.

),( sdP

••

Scattering particles

Page 16: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer: the thermal source function

Below the altitude of ~70 km, emissions from localized volumes of the Earth’s atmosphere are said to be in Local Thermodynamic Equilibrium (LTE).

Under LTE conditions, a volume of gas behaves like a blackbody.

In LTE conditions, the thermal source function of the emission from a local volume of the atmosphere is equal to the Planck’s function computed at the local kinetic temperature:

(13)))(()( ss TBJ thermal

Page 17: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer

In presence of scattering, the radiative transfer equation cannot be solved analytically.

An “exact” solution for the scattering radiative transfer equation can only be obtained using numerical techniques (e.g. discrete-ordinate, doubling-adding, Monte-Carlo).

An analytical solution, however, can be sought if approximate methods are used (e.g. two/four-stream approximation, Eddington/Delta-Eddington approximation, single scattering approximation, etc.)

Page 18: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer for a plane-parallel atmosphere

sz

Z

θ

Localized portion of the Atmosphere

We can solve the radiative transfer equation assuming that in localized portions the atmosphere is plane-parallel.

In a plane-parallel atmosphere variations in the radiance and atmospheric parameters depend only on the vertical direction, and distances can be measured along the normal Z to the plane of stratification of the atmosphere.

Page 19: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer for a plane-parallel atmosphere

In absence of scattering, the radiative transfer equation for a plane-parallel atmosphere can be written as:

(14)dzkzTBdzkzLzdL aa ))((),(),(

Eq. (14) can be rewritten in terms of the optical depth coordinate:

(15) dTBdLdL ))((),(),(

)cos(

Page 20: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer for a plane-parallel atmosphere

Eq. (15) can be solved for the upward and downward radiances in a homogeneous atmospheric layer applying the appropriate boundary

conditions at the top and at the bottom of the layer.

If we divide the atmosphere into N homogeneous layers (N=1 is the top layer) bounded by N+1 pressure levels, the upward radiance at the top of the atmosphere and the and downward radiance at the surface can be written respectively as:

(16)

(17)

N

jjvjvjvs

TBsurfLL1

1,,,))(()(

N

jjj

jjs

jvsTBtopLL

11,,

1,,,

,

)()()(

Radiance emitted by the surface

Transmittance from the surface to the top of the atmosphere

Transmittance from pressure level j to the top of the atmosphere

Average temperature in the layer

Radiance coming from the top of the atmosphere. In the infrared this term can be omitted.

Page 21: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The equation of radiative transfer for a plane-parallel atmosphere

The radiance emitted by the surface can be written as:

(18) LTBsurfLs

)1()()(

Spectral emissivity of the surface Surface temperature

Emissivity of sea water: nadir view and zero wind speed

Wave number (cm-1)

A blackbody as an emissivity of 1 at any frequency

The second term of Eq.(18) is valid under the assumption that the reflectionfrom the surface is quasi-specular.

The downward radiance is reflected upward by the surface

Page 22: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Hanel (1971)

Top of the atmosphere radiance spectrum

Page 23: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Mechanism for gaseous absorption

Radiance spectra measured at the top of the atmosphere show large variations in energy emitted upwards. These variations are due to complex interactions between molecules and the atmospheric radiation field.

For interaction to take place, a force must act on a molecule in the presence of an external electromagnetic field. For such a force to exist, the molecule must possess an electric or magnetic dipole moment.

Asymmetric molecules as CO, N20, H2O and O3 possess a permanent dipole moment. Symmetric molecules as N2, O2, CO2 and CH4 do not.

For symmetric molecules, however, molecular vibrations and interactions with other molecules can generate a temporary dipole moment and an interaction can take place.

Page 24: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Mechanism for gaseous absorption

When a molecule interacts with electromagnetic radiation having a frequency , a quantum of energy is extracted from (absorption process) or added

(emission process) to the external field and the molecule undergoes a transition between two different energy levels. When either process occurs, we say we

are in presence of an absorption/emission line.

The basic relation holds: (19)

where and are the final and initial energy level of the molecule.

In general: (20)

oh

/E //E

o

ohEE ///

rotvibelecEEEEE ///

Page 25: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Mechanism for gaseous absorption

involves changes in the molecule electron energy levels and result in absorption/emission at U.V. and visible wavelengths.

involves changes in the molecule vibrational energy levels and result in absorption/emission at near-infrared wavelengths.

involves changes in the molecule rotational energy levels and result in absorption/emission at microwave and far-infrared wavelengths.

elecE

rotE

vibE

Vibrational transitions are generally accompanied by rotational transitions. The associated absorption/emission lines form what is known as a vibration-

rotation band.

Page 26: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

For an ideal monochromatic absorption line, the molecular absorption coefficient can be expressed as:

(21)

where S is known as the line strength and is the delta Dirac function.

Gaseous absorption: line shape and absorption coefficient

Mak

)( o

In a real atmosphere, however, the absorption line is broadened by three physical phenomena:

1)Natural broadening2)Collision broadening3)Doppler broadening

Delta Dirac function

S

νo

)(o

M

aSk

Page 27: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Gaseous absorption: line shape and absorption coefficient

Natural broadening:

It is caused by smearing of the energy levels involved in the transition. In quantum mechanical terms it is due to the uncertainty principle and depends on the finite duration of each transition. It can be shown that the appropriate line shape to describe natural broadening is the Lorentz line shape:

(22)

where S is the line strength and is the line half width. The line half width is independent of frequency and its value is of the order of 10-5 nm.

n

dkSS

kno

nM

a)(,

)( 22

Page 28: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Gaseous absorption: line shape and absorption coefficient

Doppler broadening:

It is caused by a Doppler shift in the frequency of the emitted and absorbed radiation. The Doppler shift is due to the molecular velocity component along the direction of propagation of the radiation. The absorption coefficient is:

(23)

(24)

where is the molecular mass.aM

a

od

d

o

d

M

a

MT

Sk

7

2

2

1058.3

)(exp[

Page 29: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Gaseous absorption: line shape and absorption coefficient

Collisional broadening:

It is due to the modification of molecular potentials, and hence the energy levels, which take place during each emission (absorption) process. The modification of the molecular potentials is caused by inelastic as well as elastic collision between the molecules.

The shape of the line is Lorentzian, as for natural broadening, but the half width is several order of magnitudes greater, and is inversely proportional to the mean free path between collisions, which indicates that the half width will vary depending on pressure p and temperature T of the gas.

When the partial pressure of the absorbing gas is a small fraction of the total gas pressure we can write:

(25)

where ps and Ts are reference values.

TT

pp

s

s

scc ,

Page 30: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Levi (1968)

Doppler (a) and collisional (b) line shape

Page 31: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Gaseous absorption: line shape and absorption coefficient

Collisions are the major cause of broadening in the troposphere while Doppler broadening is the dominant effect in the stratosphere.

There is, however, an intermediate region where neither of the two shapes is satisfactory since both processes are active at once. Assuming the collisional and Doppler broadening are independent, the collision broadened line shape can be Doppler shifted and averaged over a Maxwell velocity distribution to obtain what is known as the Voigt line shape.

The Voigt line shape includes the Gaussian and Lorentzian line shapes as limiting cases. It cannot be evaluated analytically. For its computation, fast numerical algorithms are available.

Page 32: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The comparison of accurate calculations and measurements taken by high spectral resolution instruments have shown the importance

of the finer details of line shape.

Gaseous absorption: continuum type absorption

For water vapour in particular, measurements show that there is a componentof the absorption that varies slowly with frequency. This component cannot be explained by a spectrum computed using Lorentzian line shapes based oncollision broadening theory.

To reconcile measurements and simulations, in addition to spectral lines weintroduce a continuum type absorption.

Page 33: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Gaseous absorption: continuum type absorption

Mechanism: the exact mechanism for the continuum absorption continues to be a matter of debate. There are two main theories:

(1) the continuum is due to inadequate description of line shape away from line centres

(2) the continuum is due to molecular polymers (e.g. water vapour dimers).

Formulation: empirical algorithms based on laboratory and field measurements are available that provide an estimate of the continuum absorption for any atmospheric path. The problem is that most of the measurements have to extrapolated to atmospheric paths that are colder than the warm paths used in the

laboratory.

Page 34: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Scattering and absorption by aerosol and cloud particles

Particulates contained in the Earth’s atmosphere vary from aerosols, to water droplets and ice crystals.

The range of shapes for aerosols vary from quasi-spherical to highly irregular with a size typically less than 1 μm.

Small water droplets are by their nature spherical in shape with a size typically less than 10 μm.

Ice crystals are mainly present in cirrus clouds. The shape of ice crystals vary greatly with a size typically less than 100 μm. Their shape include solid and hollow columns, prisms, plates, aggregates and branched particles, and, hexagonal columns.

Page 35: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Scattering and absorption by aerosol and cloud particles

The computation of the absorption/scattering coefficient (and phase function) for particles with a spherical shape can be performed by using the exact Lorentz-Mie theory for any practical size. This is the approach usually followed for aerosols and water droplets.

For nonspherical ice crystals, an exact solution that covers the whole range of shapes and sizes observed in the Earth’s atmosphere is not available in practice.

Page 36: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Scattering and absorption by aerosol and cloud particles

If the size of an ice crystal is much larger than the wavelength of the incident radiation, the geometric optics approach can then be used.

The geometric optics approach is based on the assumption that a light beam can be considered to be made of a bundle of separate parallel rays that undergo reflection and refraction outside and inside the crystal. This is the only practical method to compute optical parameters for large non-spherical particles.

For smaller sizes, other techniques have to be employed such as the Finite-Difference Time Domain Method, the T-Matrix method and the Direct Dipole Approximation Method.

Page 37: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Computation of the total extinction coefficient

In the most general case where absorption and scattering take place, the total extinction coefficient can be written as:

)()()()()()()( cld

s

cld

a

aer

s

aer

a

cont

a

M

a

tot

e kkkkkkk

absorptionLinek M

a )(absorptionContinuumk cont

a )(

absorptionAerosolk aer

a )(

scatteringAerosolk aer

s )(absorptionCloudk cld

a )(

ScatteringCloudk cld

s )(

(26)

Page 38: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Line-by-line models

For a given frequency, the line absorption coefficient for a combination of J different molecules is computed by performing the sum of the

absorption coefficient evaluated for each single molecule and each single i absorption line.

]),([)( , jijjijgasesallilinesall

M

a gSk

Line strength adjusted to the path conditions (e.g. the linestrength is temperature dependent) Normalized line shape

function

Gas density

The models used to compute the gaseous line absorption coefficients are called line-by-line models (e.g. GENLN2, LBLRTM, HARTCODE, RFM).

(27)

Page 39: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

In addition to the computation of the line absorption coefficient, line-by-line models also perform the computation of the continuum absorption. They can

then be used to compute monochromatic radiance at the top of the atmosphere using the radiative transfer equation.

Line-by-line models

The accuracy of the line-by-line calculations is mainly controlled by the accuracy of line shape and line parameters (e.g. line strength and line width).

Monochromatic radiances must be convolved with the appropriate channel response functions.

Page 40: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -
Page 41: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

After Valley (1965)

Absorption by different molecules

Page 42: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Pseudo line-by-line models

Line-by-line models are computationally expensive both in CPU and disk space.

Efforts to alleviate this have lead to the development of pseudo line-by-line models (e.g. 4A, K-carta) that use absorption coefficients stored in a look-up-table.

Because the monochromatic absorption coefficient varies slowly with temperature and is directly proportional to the absorber amount, the monochromatic optical depths stored in the look-up table can be interpolated in temperature and modified for changes in absorber amount to give the most appropriate optical depths for a given profile.

Page 43: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Fast radiative transfer model for use in NWP

Line-by-line and pseudo line-by-line models are too slow to be used operationally in NWP (note that operational forward models must also be capable of performing gradient computations, e.g. tangent linear

and adjoint).

To cope with the operational processing of observations in near real-time, fast radiative transfer models have been developed. These models are very computationally efficient and also accurate (i.e. they can reproduce line-by-line “exact” calculations very closely).

Page 44: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Fast radiative transfer model for use in NWP

There are several types of fast radiative transfer models, in use or

under development, which are relevant to infrared radiance

assimilation.

The various models can be categorised into:

1) Regression based fast models

2) Physical models

3) Neural network based models

4) Principal component based models

Page 45: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The RTTOV fast radiative transfer model

The fast model used at ECMWF (and in many others NPW centres) is called RTTOV. RTTOV is a regression based fast model that computes

channel optical depths using profile dependent predictors that are functions of temperature, absorber amount, pressure and viewing angle.

In RTTOV, the atmosphere is divided into N homogeneous layers bounded by N+1 fixed pressure levels. The channel optical depth for layer j is written as:

(28)

where M is the number of predictors and the functions constitute the profile-dependent predictors of the fast transmittance model.

jkX ,

M

kjkkjj

Xa1

,,,, **ˆ

Page 46: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The RTTOV fast radiative transfer model

To compute the expansion coefficients , a line-by-line model is used to compute accurate channel averaged optical depths for a diverse set of temperature and atmospheric constituent (typically water vapour

and ozone) profiles.

*,, kja

These atmospheric profiles are chosen to be representative of widely differing atmospheric situations.

The line-by-line optical depths are then used to compute the expansion coefficients by linear regression against the predictor values calculated from the profile variables for each profile at several viewing angles.

The expansion coefficients can then be used by the model to compute optical depths for any other input profile.

Page 47: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The RTTOV fast radiative transfer model

The functional dependence of the predictors used to parameterise the optical depth depends mainly on factors such as the absorbing gas, the

spectral response function and the spectral region although also the layer thickness can be important.

The basic predictors are defined from the layer temperature and the absorber amount of the gas.

Since we are predicting channel averaged optical depths (polychromatic regime) a number of predictors have to be included that in general depend on pressure-weighted quantities above the layer.

Page 48: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Water vapour sounding channel of the HIRS instrument

Water vapour sounding channel of the IASI instrument

Squares denote the line-by-line optical depths

Stars denote the fast model optical depthsWater vapour amount in the path

Optical depth of the path

The ability of RTTOV to reproduce line-by-line optical depths

HIRS: High resolution Infrared Radiation Sounder (wheel radiometer with broad channels)

IASI: Infrared Atmospheric Sounding Interferometer(hyperspectral sensor with very narrow channels)

Page 49: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The RTTOV fast radiative transfer model

The error introduced by the parameterisation of the optical depths can be assessed by comparing fast model and line-by-line computed

radiances.

The largest errors are usually associated with water vapour channels. In general, however, RTTOV can reproduce the line-by-line radiances to an accuracy typically below the instrument noise.

Note that to characterize the total RTTOV error we must include the error contribution from the underlying line-by-line model.

It should be stressed that RTTOV comes with associated gradient routines. This is a prerequisite for a fast model to be used in NWP assimilation.

Page 50: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

HIRS: High Resolution Sounder AIRS: Atmospheric Infrared Sounder

The ability of RTTOV to reproduce line-by-line radiances

The statistic of the error has been obtained from the difference betweenRTTOV and line-by-line radiances computed or 82 profiles and six different

viewing angles.

Page 51: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The parametrization of scattering in RTTOV

The computational efficiency of a fast radiative transfer model can be

seriously degraded if explicit calculations of multiple scattering are to be

introduced.

In RTTOV we have introduced parameterization of multiple scattering that

allows to write the radiative transfer equation in a form that is identical to that in

clear sky conditions.

Page 52: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The parametrization of scattering in RTTOV

The scattering parameterization used in RTTOV (scaling approximation) rests

on the hypothesis that the diffuse radiance field is isotropic and can be

approximated by the Planck function.

In the scaling approximation the absorption optical depth, , is replaced by an

effective extinction optical depth, , defined as:

(29)

ae

saeb ~

is the scattering optical depth b is the integrated fraction of energy scattered backward for radiation incident either from above or from below

s

If is the azimuthally averaged phase function, the scaling factor b can be written in the form:

(30)

),( /P

0

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Page 53: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

The black line denotes the difference between clear sky and exact scattering computations performed introducing either aerosol or ice crystal particles.

The red line denotes the difference between approximate (RTTOV) and exact scattering computations

Page 54: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Fast radiative transfer model:regression model on layers of equal absorber amount

This approach (known as the Optical Path Transmittance (OPTRAN) method) is similar to the one used in the fast models that use fixed

pressure levels (e.g. RTTOV) but uses layers of equal absorber amount instead.

In OPTRAN the atmosphere is sliced into layers according to layer-to-space absorber amount rather than atmospheric pressure.

This can be advantageous for gases like water vapour where the path absorber amounts are not simple functions of pressure.

In fact, in the OPTRAN approach the layer absorber amount is constant across the layer and pressure becomes a predictor.

Page 55: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Fast radiative transfer model:optimal spectral sampling (OSS) method

The Optimal spectral sampling method (OSS) uses a few representative monochromatic transmittances to derive narrowband

or moderate-to-high spectral resolution channel transmittances.

In the OSS method, top of the atmosphere channel radiances are computed by statistically selecting top of the atmosphere monochromatic radiances.

The OSS approach has the advantage that, for instance, accurate scattering computations can be easily incorporated in these models.

Page 56: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Physical fast radiative transfer models

This approach averages the spectroscopic parameters for each channel and uses these to compute layer optical depths.

The advantages of this approach are:

1)More accurate computations for some gases

2)Any vertical co-ordinate grid can be used

3)It is easy to modify if the spectroscopic parameters change

However, to date, these models are a factor 2-5 slower than the regression based ones which is significant for assimilation purposes.

Page 57: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Neural networks based fast radiative transfer models

Fast radiative transfer models using neural networks have been developed and may provide even faster means to compute radiances.

A limitation of neural network based models is that accurate gradient versions of the models are proving difficult to develop.

Page 58: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Principal components based fast radiative transfer models

Principal component (PC) based fast models have been developed for hyperspectral (i.e. for sensors with many thousand channels) remote

sensing applications.

PC based fast models compute the PC scores of the radiance spectrum. The PC scores have much smaller dimensions as compared to the number of channels.

This optimizations results in a significant decrease of the computational time without affecting the accuracy of the results.

Page 59: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Many of the aspects of the subjects treated in this lecture are covered in the following books:

Goody, R.M. and Yung,Y.L., 1995: Atmospheric Radiation:Theoretical Basis . Oxford University.

Chandrasekhar, S., 1950:Radiative transfer. Dover.

Liou, K.N., 2002:An introduction to atmospheric radiation.Academic Press.

Page 60: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Mechanism for absorption and scattering

Armstrong, B.H., 1967:Spectrum line profiles:the Voigt function. J. Quant. Spectrosc. Rad. Transfer, 52, pp. 281-294.

Clough, S.A., Kneizys, F.X. and Davis, R.W., 1989:Line shape and the water vapour continuum, Atmos. Research, 23, pp. 228-241.

Van de Hulst, H.C. 1957:Light scattering by Small Particles. Wiley.

Mishchenko, M.I., Hovenier, J.W. and Travis, L.D., 2000:Light scattering by Nonspherical particles. Academic Press.

Page 61: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Line-by-line models:

Edwards, D.P., 1992: GENLN2. A general line-by-line atmospheric transmittance and radiance model. NCAR Technical note NCAR/TN-367+STR (National Center for Atmospheric Research, Boulder, Co., 1992)

Clough, S.A., Jacono, M.J. and Moncet, J.L., 1992: Line-by-line calculations of atmospheric fluxes and cooling rates: application to water vapour. J. Geophys. Res., 97, pp. 15761-15785.

Miskolczi, F., Rizzi,R., Guzzi, R. and Bonzagni, M.M., 1998: A new high resolution atmospheric transmittance code and its application in the field of remote sensing. In Proceedings of IRS88: Current problems in atmospheric radiation, Lille, France, 18-24 August 1988, pp. 388-391.

Page 62: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Line-by-line models based on look-up tables:

Strow,L.L., Motteler,H.E., Benson,R.G.,Hannon, S.E. and De Souza-Machado,S., 1998: Fast computation of monochromatic infrared atmospheric transmittances using compressed look-up-tables. J. Quant. Spectrosc. Rad. Transfer, 59, pp. 481-493.

Scott, N.A. and Chedin,A., 1981: A fast line-by-line method for atmospheric absorption computation: the Automatized Atmospheric Absorption Atlas, J. Appl. Meteor., 20, pp. 802-812.

Page 63: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Fast models on fixed pressure levels:

Mc Millin L.M., Fleming, H.E. and Hill, M.L., 1979:Atmospheric transmittance of an absorbing gas. 3: A computationally fast and accurate transmittance model for absorbing gases with variable mixing ratios. Applied Optics, 18, pp. 1600-1606.

Eyre, J.R. 1991: A fast radiative transfer model for satellite sounding systems. ECMWF Research Department Technical Memorandum 176 (available from the librarian at ECMWF).

Matricardi, M. and Saunders, R., 1999: A fast radiative transfer model for simulation of IASI radiances. Applied Optics, 38, pp. 5679-5691.

Page 64: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

Bibliography

Regression based fast models on levels of fixed absorber amount:

Mc. Millin, L.M., Crone, L.J. and Kleespies, T.J., 1995:Atmospheric transmittances of an absorbing gas. 5. Improvements to the OPTRAN approach. Applied Optics, 24, pp. 8396-8399.

Physical models:

Garand, L., Turner, C., Chouinard, C. and Halle J., 1999: A physical formulation of atmospheric transmittances for the massive assimilation of satellite infrared radiances. J. Appl. Meteorol., 38, pp. 541-554.

Page 65: Training Course Module DA. Data assimilation and use of satellite data. Introduction to infrared radiative transfer. Marco Matricardi, ECMWF 26 April -

BibliographyPrincipal components model:

X. Liu, W.L. Smith, D.K. Zhou, A. Larar: “Principal component-based

radiative transfer model for hyperspectral sensors: theoretical

concept”, Appl. Opt, 45, 201-209 (2006).

M. Matricardi: “A principal component based version of the RTTOV

fast tradiative transfer model”, Q. J. R. Meteorol. Soc.,136,1823–1835

(2010).

OSS Method:

J.L. Moncet, G. Uymin, H.E. Snell, “Atmospheric radiance modelling

using the optimal spectral sampling (OSS) method”, Proc. Of SPIE,

5425, 368-374 (2004).