Atmospheric radiation: 1975–1983

Wiscombe, W. J.

doi:10.1029/rg021i005p00997

Cited by 13 publications

(11 citation statements)

References 1,406 publications

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“…The next step is to integrate the absorption coefficients along the (vertical) path through the atmosphere using the function ac2dod (see In [4] in Figure 3). Similar to cross sections and absorption coefficients this returns a list of (nLevels-1) subclassed NumPy arrays odArray, where each list member is essentially the delta / differential / layer optical depth spectrum along with its attributes lower and upper altitudes, pressures, and temperatures (and the wavenumber interval, too).…”

Section: Optical Depthsmentioning

confidence: 99%

“…in the atmospheric sciences, both for Earth and (exo-)planets [1][2][3]. Many radiative transfer models have been developed in recent decades (see [4], for an early review and https://en.wikipedia.org/wiki/Atmospheric_ radiative_transfer_codes for an up-to-date listing (All links in this paper were checked and active 4 April 2019. )), ranging from simple approximations to complex, often highly optimized codes and usually tailored to a specific spectral domain.…”

Section: Introductionmentioning

confidence: 99%

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Py4CAtS—PYthon for Computational ATmospheric Spectroscopy

et al. 2019

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Radiation is a key process in the atmosphere. Numerous radiative transfer codes have been developed spanning a large range of wavelengths, complexities, speeds, and accuracies. In the infrared and microwave, line-by-line codes are crucial esp. for modeling and analyzing high-resolution spectroscopic observations. Here we present Py4CAtS—PYthon scripts for Computational ATmospheric Spectroscopy, a Python re-implemen-tation of the Fortran Generic Atmospheric Radiation Line-by-line Code GARLIC, where computationally-intensive code sections use the Numeric/Scientific Python modules for highly optimized array processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts (and corresponding functions) to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross sections for given pressure(s) and temperature(s), to combine cross sections to absorption coefficients and optical depths, and to integrate along the line-of-sight to transmission and radiance/intensity. Py4CAtS can be used in three ways: in the (Unix/Windows/Mac) console/terminal, inside the (I)Python interpreter, or Jupyter notebook. The basic design of the package, numerical and computational aspects relevant for optimization, and a sketch of the typical workflow are presented. In conclusion, Py4CAtS provides a versatile environment for “interactive” (and batch) line-by-line radiative transfer modeling.

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Section: Optical Depthsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Py4CAtS—PYthon for Computational ATmospheric Spectroscopy

et al. 2019

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“…Net radiation, sensible and latent heat fluxes are the primary components of the snow cover energy balance (Price and Dunne, ; Marks and Dozier, ; Marks et al , ; Pomeroy et al , ; Nayak et al , ). Even in complex mountainous terrain or under vegetation, radiation has been reliably measured and modelled with robust sensors, supported by an extensive body of research presenting both methods and well‐validated modelling approaches (Marks and Dozier, ; Wiscombe, ; Anderson, ; Dozier and Frew, ; Marks and Dozier, ; Dubayah, ; Pomeroy and Dion, ; Hardy et al , ; Link et al , ; Pohl et al , ; Sicart et al , ; Bewley et al , ; Essery and Marks, ). There are, however, few direct measurements of sublimation in complex terrain using eddy covariance (EC).…”

Section: Introductionmentioning

confidence: 99%

Estimating surface sublimation losses from snowpacks in a mountain catchment using eddy covariance and turbulent transfer calculations

Reba

Pomeroy

Marks

et al. 2012

Hydrological Processes

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Abstract:Sublimation is a critical component of the snow cover mass balance. Although sublimation can be directly measured using eddy covariance (EC), such measurements are relatively uncommon in complex mountainous environments. The EC measurements of surface snowpack sublimation from three consecutive winter seasons (2004, 2005 and 2006) at a wind-exposed and wind-sheltered site were analysed to characterise sublimation in mountainous terrain. During the 2006 snow season, snow surface and near-surface air temperature, humidity and wind were also measured, permitting the calculation of sublimation rates and a comparison with EC measurements. This comparison showed that measured and simulated sublimation was very similar at the exposed site but less so at the sheltered site. Wind speeds at the exposed site were nearly four times than that at the sheltered site, and the exposed site yielded measured sublimation that was two times the magnitude of that at the sheltered site. The time variation of measured sublimation showed diurnal increases in the early afternoon and increased rates overall as the snow season progressed. Measured mean daily sublimation rates were 0.39 and 0.15 mm day À1 at the exposed and sheltered sites, respectively. At the exposed site, measured sublimation accounted for 16% and 41% of the maximum snow accumulation in 2006 and 2005, respectively. At the sheltered site, measured seasonal sublimation was approximately 4% in 2004 and 2006 and 8% in 2005 of the maximum snow water equivalent. Simulated sublimation was only available for 2006 and suggested smaller but comparable percentages to the sublimation estimated from observations. At the exposed site, a total of 42 mm sublimated for the snow season, which constituted 12% of the maximum accumulation. At the sheltered site, 17 mm (2.2% of maximum accumulation) was sublimated over the snow season.

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“…Discrete ordinate-matrix exponential approach. To simplify the exposition, wc deal only with the zero-order Fourier component or the azimuthally averaged version of equation (6) Wiscombe [1976Wiscombe [ , 1983 for references). These methods or slight variants thereof are also referred to as discrete space theory [Preisendorfer, 1965;Stephens, 1980] ,,,,-: ,,,,,,-:,-,,, r,-, -,,,,',',-'…”

Section: Connection Between the Discrete Ordinate And The Doubling Mementioning

confidence: 99%

“…Finally, the problem concerning how to integrate properly across a band of absorbing lines needs further elaboration as discussed by Wiscombe [1983]. In particular, the pressure and temperature dependence of the absorption must be properly accounted for [Chou and Arking, 1981].…”

Section: To What Extent Will the Zenith Measurements Of The Airglow Imentioning

confidence: 99%

The theory of multiple scattering of radiation in plane parallel atmospheres

Stamnes¹

1986

Reviews of Geophysics

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A review is provided of multiple scattering theory associated with radiative transfer problems in planetary atmospheres. The radiative transfer equation pertaining to a scattering, absorbing, and emitting medium is considered. Analytic solutions are presented and computational aspects are discussed for plane parallel atmospheres. These computationally efficient and reliable solutions can be used to attack a multitude of radiative transfer problems in realistic atmospheres. Computational illustration is provided, a discussion of certain applications of the theory is presented, and some remaining theoretical problems are pointed out.

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Atmospheric radiation: 1975–1983

Cited by 13 publications

References 1,406 publications

Py4CAtS—PYthon for Computational ATmospheric Spectroscopy

Py4CAtS—PYthon for Computational ATmospheric Spectroscopy

Estimating surface sublimation losses from snowpacks in a mountain catchment using eddy covariance and turbulent transfer calculations

The theory of multiple scattering of radiation in plane parallel atmospheres

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