Assessing 1D Atmospheric Solar Radiative Transfer Models: Interpretation and Handling of Unresolved Clouds

Abstract

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended? One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within Ϯ2%. Most 1D codes underestimate atmospheric absorptance by typically 15-25 W m Ϫ2 at overhead sun for the standard tropical atmosphere regardless of clouds. Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for the clear and overcast cases. The majority of 1D codes fall into the extreme category of maximum/random overlap of PPH clouds and thus generally disagree with full 3D benchmark values. Given the fairly limited scope of these tests and the inability of any one code to perform extremely well for all cases begs the question that a paradigm shift is due for modeling 1D solar fluxes for cloudy atmospheres.

Quantifying the magnitude of anomalous solar absorption

“…In simulations done without any aerosol, we have traced this difference to the computed water vapor absorption. Comparisons between RAPRAD and line-by-line codes for some specific cases show agreement at the level of 1% in absorption [Barker et al, 2003]. We suspect that the difference between SBDART and RAPRAD can be traced to the use of exponential sums rather than correlated-k theory distributions, but further research is needed to confirm this hypothesis.…”

“…In spectral regions that have overlapping absorption by two gases, we assume that the overlap is random and the two k-distributions are multiplied together. The identical correlated-k integration was used with a Monte Carlo code in a radiation code comparison study [Barker et al, 2003] and produced agreements of better than 1% in clear-sky absorption compared to a standard line-by-line code. For monochrome, near-conservative scattering cases, the d2-stream approximation is typically accurate to a few percent.…”

“…Radiation code comparison studies have demonstrated the weaknesses of some of these codes, but they continue to be used. The radiative transfer community has carried out a significant number of comparison tests and these results are readily available [e.g., Barker et al, 2003]. The broader atmospheric science community should take these comparisons seriously and use the models that are demonstrated to be of high accuracy, especially when trying to compare theory with measurements.…”

A 3D cloud‐construction algorithm for the EarthCARE satellite mission

“…Aerosols were neglected. The SW component of this code participated in Barker et al's (2003) model intercomparison and performed well relative to benchmarks. Both SW and LW codes were featured in Oreopoulos and Mlawer (2010).…”

Longwave 3D Benchmarks for Inhomogeneous Clouds and Comparisons with Approximate Methods

“…Misrepresenting the spatial and temporal distribution of water in large-scale atmospheric models (LSAMs) will produce errors in calculated fluxes that suggest unrealistic radiative forcings. The sensitivity and uncertainty in cloud effects on the earth's energy system are the motivation for many studies that seek to quantify the consequences of misrepresenting cloud radiative effects (Ellingson et al 1991;Barker et al 2003;Collins 2001).…”