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Collaborative Research: RAPID--Smoke Forecasting Support for the Western Wildfire Experiment for Cloud Chemistry, Aerosol absorption and Nitrogen (WE-CAN) Field Intensive

Collaborative Research: RAPID--Smoke Forecasting Support for the Western Wildfire Experiment for Cloud Chemistry, Aerosol absorption and Nitrogen (WE-CAN) Field Intensive
合作研究:RAPID——为西部野火云化学、气溶胶吸收和氮气(WE-CAN)场密集实验提供烟雾预报支持
批准号:
1747559
负责人:
Emily Fischer
金额:
$3.4万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2018-08-31

项目摘要

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中文摘要
翻译
该项目为美国国家科学基金会赞助的西部野火云化学、气溶胶吸收和氮实验(WE-CAN)野外活动提供预测能力。WE-CAN是计划于2018年夏季进行的主要现场密集项目,包括在NSF/NCAR C-130上部署复杂的大气化学仪器,对美国西部野火羽流的排放和演变的第一天进行采样和系统表征。目前正在为这一实地运动进行规划,迫切需要预测能力,以确保运动的成功。WE-CAN野外活动将提供有关野火排放的新信息,包括烟羽中主要有毒物质的排放信息、烟羽中细颗粒物随时间的演变以及烟雾颗粒与附近云层的相互作用。这项工作提供的对WE-CAN的支持包括使用(1)实时高分辨率快速刷新烟雾(hrrp - smoke)建模系统,以及(2)FxCAVE(预报扩展通用AWIPS可视化环境)虚拟客户端,该客户端提供可操作的国家气象局(NWS)预报观测和预报模型。WE-CAN将至少有4名研究生预报员参与。
英文摘要
This project is providing forecasting capabilities for the NSF-sponsored Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen (WE-CAN) field campaign. WE-CAN is a major field intensive planned for summer 2018 and includes deployment of sophisticated atmospheric chemistry instrumentation on the NSF/NCAR C-130 to sample and systematically characterize the emissions and first day of evolution of western U.S. wildfire plumes. Planning for this field campaign is currently underway and forecasting capabilities are urgently needed to ensure the success of the campaign. The WE-CAN field campaign will provide new information about emissions from wildfires, including information on the emissions of major toxic species in smoke plumes, the evolution of fine particulate matter in the plume over time, and the interactions of smoke particles with nearby clouds. The support for WE-CAN provided by this effort includes the use of (1) the real-time High Resolution Rapid Refresh smoke (HRRR-Smoke) modeling system, and (2) the FxCAVE (Forecast-extended Common AWIPS Visualization Environment) virtual client that delivers operational National Weather Service (NWS) forecast observations and forecast models. There will be at least 4 graduate student forecasters involved in WE-CAN.
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