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56+4Meteorological and air quality forecasting using the WRF-STEM model during the 2008 ARCTAS field campaign

机译:56 + 4在2008年ARCTAS野战期间使用WRF-STEM模型进行的气象和空气质量预测

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In this study, the University of Iowa's Chemical Weather Forecasting System comprising meteorological predictions using the WRF model, and off-line chemical weather predictions using tracer and full chemistry versions of the STEM model, designed to support the flight planning during the ARCTAS 2008 mission is described and evaluated. The system includes tracers representing biomass burning and anthropogenic emissions from different geographical emissions source regions, as well as air mass age indicators. We demonstrate how this forecasting system was used in flight planning and in the interpretation of the experimental data obtained through the case study of the summer mission ARCTAS DC-8 flight executed on July 9 2008 that sampled near the North Pole. The comparison of predicted meteorological variables including temperature, pressure, wind speed and wind direction against the flight observations shows that the WRF model is able to correctly describe the synoptic circulation and cloud coverage in the Arctic region The absolute values of predicted CO match the measured CO closely suggesting that the STEM model is able to capture the variability in observations within the Arctic region. The time-altitude cross sections of source region tagged CO tracers along the flight track helped in identifying biomass burning (from North Asia) and anthropogenic (largely China) as major sources contributing to the observed CO along this flight. The difference between forecast and post analysis biomass burning emissions can lead to significant changes (~ 10-50%) in primary CO predictions reflecting the large uncertainty associated with biomass burning estimates and the need to reduce this uncertainty for effective flight planning.
机译:在这项研究中,爱荷华大学的化学天气预报系统包括使用WRF模型的气象预报以及使用STEM模型的示踪剂和完整化学版本的离线化学天气预报,旨在支持ARCTAS 2008任务期间的飞行计划。描述和评估。该系统包括代表不同地理排放源区域的生物质燃烧和人为排放的示踪剂,以及空气质量年龄指标。我们演示了如何将这种预测系统用于飞行计划,以及如何解释该数据,这些数据是通过对2008年7月9日在北极附近采样的夏季任务ARCTAS DC-8飞行的案例研究获得的。将预测的气象变量(包括温度,压力,风速和风向)与飞行观测值进行比较,表明WRF模型能够正确描述北极地区的天气环流和云量。预测的CO的绝对值与测得的CO匹配紧密表明,STEM模型能够捕获北极地区观测数据的变化性。沿航迹标出的源区域带有时间标记的一氧化碳示踪剂的时空断面有助于识别生物燃料燃烧(来自北亚)和人为因素(主要是中国),这是沿此飞行观测到的一氧化碳的主要来源。预测和分析后生物质燃烧排放之间的差异可能导致主要CO预测发生重大变化(约10-50%),这反映了与生物质燃烧估计相关的巨大不确定性,以及需要减少这种不确定性以进行有效的飞行计划。

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