Improved snow darkening coefficient for large-scale albedo modelling with Crocus

Description Light-absorbing particles (LAPs) deposited at the snow surface significantly reduce its albedo and strongly affect the snow melt dynamics. The explicit simulation of these effects with advanced snow radiative transfer models can be associated with a large computational cost. Consequently, many albedo schemes used in snowpack models still rely on empirical parameterizations that do not account for the spatial variability of LAP deposition. In Gaillard et al. (2024), a new strategy of intermediate complexity that includes the effects of spatially variable LAP deposition on snow albedo was tested with the snowpack model Crocus. It relies on an optimization of the snow darkening coefficient that controls the evolution of snow albedo in the visible range. A global dataset of LAP-informed and spatially variable values of the snow darkening coefficient was constructed. The revised snow darkening coefficient improved snow albedo simulations at the ten sites considered in the study by 10%, with the largest improvements found in the Arctic (more than 25%). The uncertainties in the values of the snow darkening coefficient resulting from the inter-annual variability of LAP deposition on snow were also computed. The data are distributed in a NetCDF file (gamma_tot_publish_v2.nc). More details about the dataset and the file format are given in the file readme_gamma_v2.pdf.沉降于雪面的吸光粒子（Light-absorbing particles, LAPs）会显著降低雪面反照率，并强烈影响积雪消融动力学过程。采用先进的积雪辐射传输模型对这些效应进行显式模拟，往往伴随极高的计算成本。因此，众多积雪模型中所使用的反照率参数化方案，仍依赖于无法反映吸光粒子沉降空间异质性的经验公式。在Gaillard等人2024年的研究中，一种兼顾空间异质性吸光粒子沉降效应的中等复杂度新策略，借助积雪模型Crocus完成了测试。该策略通过优化积雪暗化系数，实现对可见光波段雪面反照率演化过程的调控。研究构建了一套包含吸光粒子信息、且具备空间变异性的积雪暗化系数全球数据集。经修正后的积雪暗化系数，将本研究涉及的10个观测站点的雪面反照率模拟精度提升了10%，其中北极地区的改善幅度最为显著，超过25%。研究同时量化了由积雪吸光粒子沉降年际变异性所带来的积雪暗化系数数值不确定性。 本数据集以NetCDF格式文件（gamma_tot_publish_v2.nc）进行分发，关于数据集与文件格式的更多细节，请参阅readme_gamma_v2.pdf。