Abstract
Abstract. Snow is an important climate regulator because it greatly increases the surface albedo of middle and high latitudes of the Earth. Earth system models (ESMs) often adopt two-stream approximations with different radiative transfer techniques, the same snow therefore has different solar radiative properties depending whether it is on land or on sea ice. Here we intercompare three two-stream algorithms widely used in snow models, improve their predictions at large zenith angles, and introduce a hybrid model suitable for all cryospheric surfaces in ESMs. The algorithms are those employed by the SNow ICe and Aerosol Radiative (SNICAR) module used in land models, dEdd–AD used in Icepack, the column physics used in the Los Alamos sea ice model CICE and MPAS-Seaice, and a two-stream discrete-ordinate (2SD) model. Compared with a 16-stream benchmark model, the errors in snow visible albedo for a direct-incident beam from all three two-stream models are small (<±0.005) and increase as snow shallows, especially for aged snow. The errors in direct near-infrared (near-IR) albedo are small (<±0.005) for solar zenith angles θ<75∘, and increase as θ increases. For diffuse incidence under cloudy skies, dEdd–AD produces the most accurate snow albedo for both visible and near-IR (<±0.0002) with the lowest underestimate (−0.01) for melting thin snow. SNICAR performs similarly to dEdd–AD for visible albedos, with a slightly larger underestimate (−0.02), while it overestimates the near-IR albedo by an order of magnitude more (up to 0.04). 2SD overestimates both visible and near-IR albedo by up to 0.03. We develop a new parameterization that adjusts the underestimated direct near-IR albedo and overestimated direct near-IR heating persistent across all two-stream models for θ>75∘. These results are incorporated in a hybrid model SNICAR-AD, which can now serve as a unified solar radiative transfer model for snow in ESM land, land ice, and sea ice components.
Highlights
Snow cover on land, land ice, and sea ice, modulates the surface energy balance of middle and high latitudes of the Earth, principally because even a thin layer of snow can greatly increase the surface albedo
We evaluate the accuracy and biases of three two-stream models listed in Table 2, including the algorithms used in SNow ICe and Aerosol Radiative (SNICAR) and dEdd–AD, for representing reflectance and heating
The adoption of the dEdd–AD radiative transfer algorithm in SNICAR, and the implementation of SNICAR snow SSPs in dEdd–AD enables a consistent simulation of the radiative effects of light-absorbing particles in the cryosphere across Earth system models (ESMs) components. This intercomparison and evaluation has shown multiple ways that the solar properties of cryospheric surfaces can be improved in the current generation of ESMs. We have merged these findings into a hybrid model SNICAR-AD, which is primarily composed of the radiative transfer scheme of dEdd–AD, five-band snow–aerosol SSPs of SNICAR, and the parameterization to correct for snow albedo biases when solar zenith angle exceeds 75◦
Summary
Land ice, and sea ice, modulates the surface energy balance of middle and high latitudes of the Earth, principally because even a thin layer of snow can greatly increase the surface albedo. Flanner and Zender (2005) developed the SNow Ice and Aerosol Radiation model (SNICAR) that utilizes two-stream approximations (Wiscombe and Warren, 1980; Toon et al, 1989) to predict heating and reflectance for a multilayer snowpack They implemented SNICAR in the Community Land Model (CLM) to predict snow albedo and vertically resolved solar absorption for snow-covered surfaces. 7, we summarize the major differences of algorithm implementations between SNICAR and dEdd–AD in ESMs We use these results to develop and justify a unified surface shortwave radiative transfer method for all Earth system model components in the cryosphere, presented in Sect.
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