业务高分辨率天气模式中的吹雪表示及相关能见度降低

Timothy D. Corrie, B. Geerts, Tatiana G. Smirnova, Stanley G. Benjamin, Michael Charnick, Matthew Brothers, Siwei He, Zachary J. Lebo, Eric P. James
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引用次数: 0

摘要

吹雪会迅速降低能见度,因此对驾车者来说是一种危险。美国的数值天气预报模型并不能捕捉到雪到达地面后的运动,但可以根据模型预测的与吹雪发生相关的地表和环境条件来诊断吹雪导致的能见度降低。最近开发的预测吹雪浓度和相关能见度降低的诊断框架被应用于高分辨率快速刷新(HRRR)和快速刷新预报系统(RRFS)模型输出,包括地表积雪情况,以预测吹雪导致的地表能见度降低。研究了 2018 年至 2023 年怀俄明州周围的 12 次吹雪事件。分析表明,吹雪导致的能见度降低往往被过高预测,这是由于最初假设雪层完全可漂移造成的。本研究采用两种方法对吹雪水库的老化进行了改进。第一种方法是根据 HRRR 和 RRFS 试验模型中使用的 RUC 陆面模型(RUC LSM)中的时变雪密度估算可漂移性,并与 RRFS 模型一起进行实时评估。第二种补充方法使用基于过程的方法诊断雪堆漂移性,该方法需要近期降雪、风速和表层温度数据。与完全漂移性假设相比,这种方法在预报技能方面的改进有限。为了改进基于模型的对吹雪导致能见度降低的诊断,需要开展实证工作,以确定雪堆可漂移性与近期降雪量和其他天气条件之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Representation of Blowing Snow and Associated Visibility Reduction in an Operational High-Resolution Weather Model
Blowing snow is a hazard for motorists because it may rapidly reduce visibility. Numerical weather prediction models in the United States do not capture the movement of snow once it reaches the ground, but visibility reductions due to blowing snow can be diagnosed based on model-predicted land surface and environmental conditions that correlate with blowing snow occurrence. A recently developed diagnostic framework for forecasting blowing snow concentration and the associated visibility reduction is applied to High-Resolution Rapid Refresh (HRRR) and Rapid Refresh Forecast System (RRFS) model output including surface snow conditions to predict surface visibility reduction due to blowing snow. Twelve blowing snow events around Wyoming from 2018 to 2023 are examined. The analysis shows that visibility reductions due to blowing snow tend to be overpredicted, caused by the initial assumption of full driftability of the snowpack. This study refines the aging of the blowing snow reservoir with two methods. The first method estimates driftability based on time-varying snow density from the RUC Land-Surface Model (RUC LSM) used in the HRRR and experimental RRFS models and is evaluated in a real-time context with the RRFS model. The second, complementary method diagnoses snowpack driftability using a process-based approach that requires data for recent snowfall, wind speed, and skin temperature. Compared to the full driftability assumption, this method shows limited improvements in forecasting skill. In order to improve model-based diagnosis of visibility reduction due to blowing snow, empirical work is needed to determine the relation between snowpack driftability and the recent history of snowfall and other weather conditions.
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