Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media

Stamnes, Knut; Tsay, S. C.; Wiscombe, W. J.; Jayaweera, K. O. L. F.

doi:10.1364/ao.27.002502

Cited by 3,154 publications

(1,947 citation statements)

References 14 publications

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“…MODTRAN solves the radiative transfer equation by including the effects of molecular and particulate absorption/emission and scattering, surface reflections and emission, solar/lunar illumination, and spherical refraction. The absorption and scattering processes, considering the atmospheric extinction both for aerosols and molecules, are rigorously calculated using DISORT [60] and Correlated-k [61] algorithms. In addition, MODTRAN uses a spherically symmetric atmosphere, consisting of homogeneous layers, each one characterized by its temperature, pressure and concentration of atmospheric compounds.…”

Section: Modtran5mentioning

confidence: 99%

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

et al. 2016

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Abstract:Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especially when many state conditions and model couplings need to be studied. To overcome this problem, it is proposed to substitute RTMs through surrogate meta-models also named emulators. Emulators approximate the functioning of RTMs through statistical learning regression methods, and can open many new applications because of their computational efficiency and outstanding accuracy. Emulators allow fast global sensitivity analysis (GSA) studies on advanced, computationally expensive RTMs. As a proof-of-concept, three machine learning regression algorithms (MLRAs) were tested to function as emulators for the leaf RTM PROSPECT-4, the canopy RTM PROSAIL, and the computationally expensive atmospheric RTM MODTRAN5. Selected MLRAs were: kernel ridge regression (KRR), neural networks (NN) and Gaussian processes regression (GPR). For each RTM, 500 simulations were generated for training and validation. The majority of MLRAs were excellently validated to function as emulators with relative errors well below 0.2%. The emulators were then put into a GSA scheme and compared against GSA results as generated by original PROSPECT-4 and PROSAIL runs. NN and GPR emulators delivered identical GSA results, while processing speed compared to the original RTMs doubled for PROSPECT-4 and tripled for PROSAIL. Having the emulator-GSA concept successfully tested, for six MODTRAN5 atmospheric transfer functions (outputs), i.e., direct and diffuse at-surface solar irradiance (E di f , E dir ), direct and diffuse upward transmittance (T dir , T di f ), spherical albedo (S) and path radiance (L 0 ), the most accurate MLRA's were subsequently applied as emulator into the GSA scheme. The sensitivity analysis along the 400-2500 nm spectral range took no more than a few minutes on a contemporary computer-in comparison, the same analysis in the original MODTRAN5 would have taken over a month. Key atmospheric drivers were identified, which are on the one hand aerosol optical properties, i.e., aerosol optical thickness (AOT), Angstrom coefficient (AMS) and scattering asymmetry variable (G), mostly driving diffuse atmospheric components, E di f and T di f ; and those affected by atmospheric scattering, L 0 and S. On the other hand, as expected, AOT, AMS and columnar water vapor (CWV) in the absorption regions mostly drive E dir and T dir atmospheric functions. The presented emulation schemes showed very promising results in replacing costly RTMs, and we think they can contribute to the adoption of machine learning techniques in remote sensing and environmental applications.

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Section: Modtran5mentioning

confidence: 99%

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

et al. 2016

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“…Our first modeling approach used the DISORT code of Stamnes et al (1988) in conjunction with snow grain optical properties from Mie theory. This method approximates snow crystals as disconnected spheres and models the reflection of diffuse and directional light by a discrete number of snow layers of finite thickness but infinite in the horizontal direction.…”

Section: Reflectance Modeling At 1310 Nmmentioning

confidence: 99%

“…For example, using the DISORT radiative transfer model of Stamnes et al (1988), we calculated light transmission through the troposphere and in the snowpack, and found that a reduction in SSA of snow from 32 to 16 m 2 kg −1 at the summer solstice at noon, 65 • N, causes an instantaneous forcing of 22 W m −2 at the tropopause, increasing column solar absorption by about 6.5%.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

et al. 2009

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Abstract. Even though the specific surface area (SSA) and the snow area index (SAI) of snow are crucial variables to determine the chemical and climatic impact of the snow cover, few data are available on the subject. We propose here a novel method to measure snow SSA and SAI. It is based on the measurement of the hemispherical infrared reflectance of snow samples using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement). DUFISSS uses the 1310 or 1550 nm radiation of laser diodes, an integrating sphere 15 cm in diameter, and InGaAs photodiodes. For SSA<60 m 2 kg −1 , we use the 1310 nm radiation, reflectance is between 15 and 50% and the accuracy of SSA determination is 10%. For SSA>60 m 2 kg −1 , snow is usually of low density (typically 30 to 100 kg m −3 ), resulting in insufficient optical depth and 1310 nm radiation reaches the bottom of the sample, causing artifacts. The 1550 nm radiation is therefore used for SSA>60 m 2 kg −1 . Reflectance is then in the range 5 to 12% and the accuracy on SSA is 12%. We propose empirical equations to determine SSA from reflectance at both wavelengths, with that for 1310 nm taking into account the snow density. DUFISSS has been used to measure the SSA of snow and the SAI of snowpacks in polar and Alpine regions.

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“…3.4. The 1-D radiative transfer equation is solved by the DIScrete-Ordinate-method Radiative Transfer (DISORT) solver with 32 streams in pseudospherical geometry (Stamnes et al, 1988;Buras et al, 2011;Dahlback and Stamnes, 1991). The radiative transfer model computes both the direct and the multiple scattered diffuse radiation, L(θ, φ).…”

Section: Radiative Transfer Modelmentioning

confidence: 99%

Tilt error in cryospheric surface radiation measurements at high latitudes: a model study

2016

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Abstract. We have evaluated the magnitude and makeup of error in cryospheric radiation observations due to small sensor misalignment in in situ measurements of solar irradiance. This error is examined through simulation of diffuse and direct irradiance arriving at a detector with a cosine-response fore optic. Emphasis is placed on assessing total error over the solar shortwave spectrum from 250 to 4500 nm, as well as supporting investigation over other relevant shortwave spectral ranges. The total measurement error introduced by sensor tilt is dominated by the direct component. For a typical highlatitude albedo measurement with a solar zenith angle of 60 • , a sensor tilted by 1, 3, and 5 • can, respectively introduce up to 2.7, 8.1, and 13.5 % error into the measured irradiance and similar errors in the derived albedo. Depending on the daily range of solar azimuth and zenith angles, significant measurement error can persist also in integrated daily irradiance and albedo. Simulations including a cloud layer demonstrate decreasing tilt error with increasing cloud optical depth.

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Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media

Cited by 3,154 publications

References 14 publications

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

Tilt error in cryospheric surface radiation measurements at high latitudes: a model study

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