Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
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Published:2023-01-04
Issue:1
Volume:16
Page:75-94
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Hao DaleiORCID, Bisht GautamORCID, Rittger KarlORCID, Bair EdwardORCID, He CenlinORCID, Huang HuilinORCID, Dang Cheng, Stillinger TimboORCID, Gu YuORCID, Wang HailongORCID, Qian Yun, Leung L. RubyORCID
Abstract
Abstract. With the highest albedo of the land surface, snow plays a vital
role in Earth's surface energy budget and water cycle. Snow albedo is
primarily controlled by snow grain properties (e.g., size and shape) and
light-absorbing particles (LAPs) such as black carbon (BC) and dust. The
mixing state of LAPs in snow also has impacts on LAP-induced snow albedo
reduction and surface radiative forcing (RF). However, most land surface
models assume that snow grain shape is spherical and LAPs are externally
mixed with the snow grains. This study improves the snow radiative transfer
model in the Energy Exascale Earth System Model version 2.0 (E3SM v2.0) Land
Model (ELM v2.0) by considering non-spherical snow grain shapes (i.e.,
spheroid, hexagonal plate, and Koch snowflake) and internal mixing of
dust–snow, and it systematically evaluates the impacts on the surface energy budget
and water cycle over the Tibetan Plateau (TP). A series of ELM simulations
with different treatments of snow grain shape, mixing state of BC–snow and
dust–snow, and sub-grid topographic effects (TOP) on solar radiation are
performed. Compared with two remote sensing snow products derived from the
Moderate Resolution Imaging Spectroradiometer, the control ELM
simulation (ELM_Control) with the default configurations of
spherical snow grain shape, internal mixing of BC–snow, external mixing of
dust–snow, and without TOP as well as the ELM simulation with new model features
(ELM_New) can both capture the overall snow distribution
reasonably. Additionally, ELM_New overall shows smaller
biases in snow cover fraction than ELM_Control in spring when
snowmelt is important for water management. The estimated LAP-induced RF in
ELM_New ranges from 0 to 19.3 W m−2 with the
area-weighted average value of 1.5 W m−2 that is comparable to the
reported values in existing studies. The Koch snowflake shape, among
other non-spherical shapes, shows the largest difference from the spherical
shape in spring when snow processes related to the surface energy budget and
water cycle have high importance. The impacts of the mixing state of LAP in
snow are smaller than the shape effects and depend on snow grain shape.
Compared to external mixing, internal mixing of LAP–snow can lead to larger
snow albedo reduction and snowmelt, which further affect the surface energy
budget and water cycle. The individual contributions of non-spherical snow
shape, mixing state of LAP–snow, and local topography impacts on the snow
and surface fluxes have different signs and magnitudes, and their combined
effects may be negative or positive due to complex and nonlinear
interactions among the factors. Overall, the changes in net solar radiation
in spring due to individual and combined effects range from −28.6 to 16.9 W m−2 and −29.7 to 12.2 W m−2, respectively. This study advances
understanding of the role of snow grain shape and mixing state of LAP–snow
in land surface processes and offers guidance for improving snow simulations
and RF estimates in Earth system models under climate change.
Funder
National Oceanic and Atmospheric Administration
Publisher
Copernicus GmbH
Reference94 articles.
1. Andreae, M. O. and Gelencsér, A.: Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols, Atmos. Chem. Phys., 6, 3131–3148, https://doi.org/10.5194/acp-6-3131-2006, 2006. 2. Bair, E. H., Rittger, K., Skiles, S. M., and Dozier, J.: An Examination of
Snow Albedo Estimates From MODIS and Their Impact on Snow Water Equivalent
Reconstruction, Water Resour. Res., 55, 7826–7842, 2019. 3. Bair, E., Stillinger, T., Rittger, K., and Skiles, M.: COVID-19 lockdowns
show reduced pollution on snow and ice in the Indus River Basin, P.
Natl. Acad. Sci. USA, 118, e2101174118, https://doi.org/10.1073/pnas.2101174118, 2021a. 4. Bair, E. H., Stillinger, T., and Dozier, J.: Snow Property Inversion From
Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach With
Examples From MODIS and Landsat 8 OLI, IEEE Trans. Geosci.
Remote Sens., 59, 7270–7284, 2021b. 5. Bair, E. H., Dozier, J., Stern, C., LeWinter, A., Rittger, K., Savagian, A., Stillinger, T., and Davis, R. E.: Divergence of apparent and intrinsic snow albedo over a season at a sub-alpine site with implications for remote sensing, The Cryosphere, 16, 1765–1778, https://doi.org/10.5194/tc-16-1765-2022, 2022.
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