Near-real-time verification of aerosol forecasts using PM2.5 and PM10 from surface monitors
Abstract
Forecast models of atmospheric aerosols predict the three-dimensional distribution of particles from smoke, dust, pollution, sea salt, and other sources to enable decision support for public health, aviation operations, and a host of other applications. Public health researchers are primarily interested in the exposure to fine particles very close to the surface, generally in the lowest 100 meters. A variety of air quality monitoring networks sample in this layer. Direct comparison of atmospheric models to surface measurements can be complicated by a number of factors, including imprecise representation of topography and surface boundary layers in the models. In order to 1) monitor forecast model performance in a qualitative sense, and 2) develop improved methodology for quantitative modelled particulate matter (PM) verification, we developed a near real-time monitoring tool to compare aerosol forecast model data from the Navy Aerosol Analysis and Prediction System (NAAPS) to surface-based PM2.5 and PM10 data from the US Environmental Protection Agency (EPA) and other sources. This tool automates the collection of EPA data, as well as plotting and publishing of corresponding results. Several applications of this system are discussed, including the support of intensive field measurement campaigns and diagnosis of regional air quality events in near real time.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFMIN43D0926C
- Keywords:
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- 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 1863 Snow and ice;
- HYDROLOGYDE: 4315 Monitoring;
- forecasting;
- prediction;
- NATURAL HAZARDSDE: 7924 Forecasting;
- SPACE WEATHER