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Modification of SNTHERM Albedo Algorithm and Response from Black Carbon in Snow

机译:SNETHERM ALBEDO算法的修改与雪中黑碳的响应

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We carried out numerical experiments of snow accumulation and depletion as well as snow albedo for a Snow pack Telemetry (SNOTEL) site, using a one-dimensinal energy and mass balance snow model (SNTHERM) and a two-stream, multi-layer Snow, Ice, and Aerosol Radiation model (SNICAR). We developed SNTHERM SNICAR model by replacing the snow albedo algorithm in SNTHERM with SNICAR algorithm, to improve understanding of snow accumulation and snow-pack ablation processes and response from black carbon (BC) in snow. Model was tested against observed snow water equivalent (SWE) during the water year 2000 and 2002. Results show that both models do a very good job at predicting SWE, although underestimates and earlier melt-out happen. Snow albedo got from SNTHERM SNICAR model is lower than that got from SNTHERM. Decrease in albedo, duo to BC mixed in snow, leads to faster snowmelt process and shorter duration of snow cover.
机译:我们对雪堆遥测(Snotel)网站进行了雪积累和耗尽以及雪剂的数值实验,使用一维能源和质量平衡雪模型(SNITHER)和两条多层雪,冰和气溶胶辐射模型(SniCAR)。我们通过用SNICAR算法替换SNITHTH中的SNITHEROM算法开发了SNISHTHER SNICAR模型,以改善雪中积雪和雪堆消融过程的理解,并在雪中的黑碳(BC)的响应。在2000年和2002年期间,对观察到的雪水等同(SWE)进行了测试。结果表明,两种模型在预测SWE时,两种模型都做得非常好,但低估了和早期的融化发生。来自Snirm SniCar模型的Snow Albedo获得了低于Sntherm的雪。 Albedo的减少,Duo到BC混合在雪中,导致更快的雪花过程和雪覆盖持续时间更短。

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