Abstract. Accurate modeling of cryospheric surface albedo is essential for ourunderstanding of climate change as snow and ice surfaces regulate the globalradiative budget and sea-level through their albedo and massbalance. Although significant progress has been made using physicalprinciples to represent the dynamic albedo of snow, models of glacier icealbedo tend to be heavily parameterized and not explicitly connected withphysical properties that govern albedo, such as the number and size of airbubbles, specific surface area (SSA), presence of abiotic and biotic lightabsorbing constituents (LACs), and characteristics of any overlyingsnow. Here, we introduce SNICAR-ADv4, an extension of the multi-layertwo-stream delta-Eddington radiative transfer model with theadding–doubling solver that has been previously applied to represent snowand sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnelreflectance and transmittance between overlying snow and higher-densityglacier ice, scattering by air bubbles of varying sizes, and numerous typesof LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadbandalbedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03for bare and bubble-free ice under direct light. Our results indicate thatrepresenting ice with a density of 650 kg m−3 as snow with norefractive Fresnel layer, as done previously, generally overestimates theBBA by an average of 0.058. However, because mostnaturally occurring ice surfaces are roughened “white ice”, we recommendmodeling a thin snow layer over bare ice simulations. We find optimalagreement with measurements by representing cryospheric media with densitiesless than 650 kg m−3 as snow and larger-density media as bubbly icewith a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedoimpacts from LACs with changing ice SSA, with peak impact per unit mass ofLACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACsactually increase the albedo. SNICAR-ADv4 represents smooth transitionsbetween snow, firn, and ice surfaces and accurately reproduces measuredspectral albedos of a variety of glacier surfaces. This work paves the wayfor adapting SNICAR-ADv4 to be used in land ice model components of Earthsystem models.
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SNICAR-ADv3: a community tool for modeling spectral snow albedo
Abstract. The Snow, Ice, and Aerosol Radiative (SNICAR) model has been used in various capacities over the last 15 years to model the spectral albedo of snow with light-absorbing constituents (LACs). Recent studies have extended the model to include an adding-doubling two-stream solver and representations of non-spherical ice particles; carbon dioxide snow; snow algae; and new types of mineral dust, volcanic ash, and brown carbon. New options also exist for ice refractive indices and solar-zenith-angle-dependent surface spectral irradiances used to derive broadband albedo. The model spectral range was also extended deeper into the ultraviolet for studies of extraterrestrial and high-altitude cryospheric surfaces. Until now, however, these improvements and capabilities have not been merged into a unified code base. Here, we document the formulation and evaluation of the publicly available SNICAR-ADv3 source code, web-based model, and accompanying library of constituent optical properties. The use of non-spherical ice grains, which scatter less strongly into the forward direction, reduces the simulated albedo perturbations from LACs by ∼9 %–31 %, depending on which of the three available non-spherical shapes are applied. The model compares very well against measurements of snow albedo from seven studies, though key properties affecting snow albedo are not fully constrained with measurements, including ice effective grain size of the top sub-millimeter of the snowpack, mixing state of LACs with respect to ice grains, and site-specific LAC optical properties. The new default ice refractive indices produce extremely high pure snow albedo (>0.99) in the blue and ultraviolet part of the spectrum, with such values only measured in Antarctica so far. More work is needed particularly in the representation of snow algae, including experimental verification of how different pigment expressions and algal cell concentrations affect snow albedo. Representations and measurements of the influence of liquid water on spectral snow albedo are also needed.
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- NSF-PAR ID:
- 10382459
- Date Published:
- Journal Name:
- Geoscientific Model Development
- Volume:
- 14
- Issue:
- 12
- ISSN:
- 1991-9603
- Page Range / eLocation ID:
- 7673 to 7704
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract. It is well understood that the distribution and quantity of liquid water in snow is relevant for snow hydrology and avalanche forecasting, yet detecting and quantifying liquid water in snow remains a challenge from themicro- to the macro-scale. Using near-infrared (NIR) spectral reflectancemeasurements, previous case studies have demonstrated the capability toretrieve surface liquid water content (LWC) of wet snow by leveraging shifts in the complex refractive index between ice and water. However, different models to represent mixed-phase optical properties have been proposed, including (1) internally mixed ice and water spheres, (2) internally mixed water-coated ice spheres, and (3) externally mixed interstitial ice and water spheres. Here, from within a controlled laboratory environment, we determined the optimal mixed-phase optical property model for simulating wet snow reflectance using a combination of NIR hyperspectral imaging, radiative transfer simulations (Discrete Ordinate Radiative Transfer model, DISORT), and an independent dielectric LWC measurement (SLF Snow Sensor). Maps of LWC were produced by finding the lowest residual between measured reflectance and simulated reflectance in spectral libraries, generated for each model with varying LWC and grain size, and assessed against the in situ LWC sensor. Our results show that the externally mixed model performed the best, retrieving LWC with an uncertainty of ∼1 %, while the simultaneously retrieved grain size better represented wet snow relative to the established scaled band area method. Furthermore, the LWC retrieval method was demonstrated in the field by imaging a snowpit sidewall during melt conditions and mapping LWC distribution in unprecedented detail, allowing for visualization of pooling water and flow features.more » « less
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Abstract. Scattering codes are used to study the optical properties of polar stratospheric clouds (PSCs). Particle backscattering and depolarization coefficients can be computed with available scattering codes once the particle size distribution (PSD) is known and a suitable refractive index is assumed. However, PSCs often appear as external mixtures of supercooled ternary solution (STS) droplets, solid nitric acid trihydrate (NAT) and possibly ice particles, making the assumption of a single refractive index and a single morphology to model the scatterers questionable.Here we consider a set of 15 coincident measurements of PSCs above McMurdo Station, Antarctica, using ground-based lidar, a balloon-borne optical particle counter (OPC) and in situ observations taken by a laser backscattersonde and OPC during four balloon stratospheric flights from Kiruna, Sweden. This unique dataset of microphysical and optical observations allows us to test the performances of optical scattering models when both spherical and aspherical scatterers of different composition and, possibly, shapes are present. We consider particles as STS if their radius is below a certain threshold value Rth and NAT or possibly ice if it is above it. The refractive indices are assumed known from the literature. Mie scattering is used for the STS, assumed spherical. Scattering from NAT particles, considered spheroids of different aspect ratio (AR), is treated with T-matrix results where applicable. The geometric-optics–integral-equation approach is used whenever the particle size parameter is too large to allow for a convergence of the T-matrix method.The parameters Rth and AR of our model have been varied between 0.1 and 2 µm and between 0.3 and 3, respectively, and the calculated backscattering coefficient and depolarization were compared with the observed ones. The best agreement was found for Rth between 0.5 and 0.8 µm and for AR less than 0.55 and greater than 1.5.To further constrain the variability of AR within the identified intervals, we have sought an agreement with the experimental data by varying AR on a case-by-case basis and further optimizing the agreement by a proper choice of AR smaller than 0.55 and greater than 1.5 and Rth within the interval 0.5 and 0.8 µm. The ARs identified in this way cluster around the values 0.5 and 2.5.The comparison of the calculations with the measurements is presented and discussed. The results of this work help to set limits to the variability of the dimensions and asphericity of PSC solid particles, within the limits of applicability of our model based on the T-matrix theory of scattering and on assumptions on a common particle shape in a PSD and a common threshold radius for all the PSDs.more » « less
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/gmd-14-7673-2021
