Larkin et al., 2009: Rapid response field observations to calibrate the BlueSky smoke prediction model.

Reference

Abstract

The BlueSky smoke modeling framework, developed with support from the National Fire Plan and recently reworked through a grant from NASA, is used to enable a variety of real-time predictions of surface smoke concentrations from prescribed fires, wildfires, and agricultural burns. These predictions form the basis of several decision support systems and are used by air quality regulators and land managers to assess the impacts from planned and ongoing fires. Field observations are needed to assess these predictions, change parameters and model path choices, and improve the accuracy of the resulting smoke predictions.

This project collected fine particulate matter observations in smoke plumes during 3 field deployments. Observations were made during: the Tripod Fire of 2006; the Montana/Idaho fires of 2007; and the California fires of 2008. The observed data were collected on a rapid-response basis and the monitors were deployed in a coordinated effort with other groups and organizations in order to maximize their effectiveness. The observations were then used to analyze the potential for systematic bias in BlueSky-enabled model predictions of smoke surface concentrations. Several improvements to BlueSky over the years of the study were implemented, and with the use of the California data a new way to interpret the BlueSky model output was developed.

The field work done through this project and the real-time fine particulate matter observations helped form the basis of a new U.S. Forest Service Emergency Smoke Forecast System prototype developed at the behest of the USFS Fire and Aviation Management. The observed data collected by this project have been included in after action reports for the California fires and they have been submitted to the Smoke and Emissions Model Intercomparison Project (SEMIP) for use in its database.

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