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Forest Disturbance Processes

Employing Ensemble Data Assimilation, Parameter Estimation, and Field Data to Improve Fire-Weather Predictions in Mesoscale Models

[image:] Arttwork for the Eastern Area Modeling ConsortiumResearch Issue

Fire danger and fire behavior are strongly dependent on atmospheric conditions, both at the surface and aloft. Forecasting fire weather requires high temporal and spatial information about the condition and variability of atmospheric winds, temperatures, and moisture, especially within the planetary boundary layer. Since existing observations cannot diagnose the relevant small-scale weather variations across highly variable land-surface and terrain characteristics, numerical weather prediction models are being employed more and more to develop fire-weather forecasts and to predict fire behavior and fire danger. Given the inherent limitations of deterministic (single-run) modeling, recent studies have explored the benefits and shortcomings of short-range ensemble forecast modeling systems for application to different areas of weather forecasting.  However, the application of ensemble modeling systems to fire-weather forecasting has received comparatively little attention.

Our Research

[image:] 10-m wind speed ensemble mean error for the threshold exceeding 2.6 m/s for the (a) raw warm season, (b) raw fire threat days, (c) fire threat days with sequential bias correction, and (d) fire threat days with conditional bias correction.  In panel (d), the green asterisks indicate the locations of the KNYC, KPVD, and KORH weather stations. The Poconos and Berkshire Mountains are also labeled.Forecasts of fire weather are dependent on accurate predictions of low-level winds, temperature, relative humidity, and surface characteristics.  Additionally, fire-weather conditions are sensitive to sources of dry, high-momentum air aloft that can descend to the surface. Uncertainties in each of these parameters in atmospheric models can be addressed probabilistically using ensemble numerical weather forecasting techniques. Furthermore, the origin of errors within ensemble systems needs to be explored in order to improve ensemble results. The goal of this study is to use state-of-the-science data assimilation systems and new field data to evaluate the representation of the planetary boundary layer (PBL) within a weather prediction model used for forecasting fire weather conditions and to improve the manner in which the model represents the boundary layer.

Overall, we will explore the following objectives:

  • Run an Ensemble Kalman Filter (EnKF) data-assimilation system during fire weather seasons (March-April) starting in spring of 2014.
  • Employ the EnKF system to evaluate PBL parameterizations within a weather forecast model.
  • Enhance the EnKF and model system by including bias correction and calibration.
  • Use field study data (aircraft and surface tower measurements) over the New Jersey Pine Barrens to verify and potentially improve weather-forecast-model PBL schemes for fire-weather applications.

Expected Outcomes

The application and verification of the ensemble system for selected recent cases of significant fires in the northeastern United States is expected to result in conference presentations and publications in peer-reviewed journals. Improvements to to weather-forecast modeling systems through better representations of PBL processes and evolution will have a positive benefit for the numerical weather prediction modeling community. Although the present plan is focused on the Northeast, the proposed methodology is sufficiently general to transfer the modeling approaches to other regions of interest to the fire-weather modeling, forecast, and operational community both domestically and internationally.

Research Results

Erickson, M.E.; Colle, B. A.; Charney, J. 2013: Ensemble Verification and Post-processing of Fire Weather Indices Using the NCEP SREF over the Northeast United States. Tenth Symposium on Fire and Forest Meteorology. Bowling Green, KY, October 14-18, 2013.

Pollina, J.; Colle, B. A.; Charney, J. 2013: Climatology and meteorological evolution of major wildfire events over the Northeast U.S. Wea. Forecasting, 28:175–193.

Erickson, M. 2013.Towards the Usage of Post-processed Operational Ensemble Fire Weather Indices over the Northeast United States. Northeast U.S. Operational Workshop (NROW XIV), Albany, NY. December 2013.

Erickson, M. 2013. Ensemble Verification and Post-processing of Fire Weather Indices Using the NCEP SREF over the Northeast United States. 10th Symposium on Fire and Forest Meteorology, Bowling Green, KY, 15-17 October 2013.

Erickson, M.E.; Colle, B.A.; Charney, J. 2012. Impact of bias correction type and conditional training on Bayesian model averaging over the northeast United States. Weather Forecasting, 27:1449-1469.

Erickson, M. 2012. A Look at High Fire Threat Risk and Ensemble Modeling over the Northeast U.S. Tri-State Weather Conference, Danbury, CT, 12 October 2012.

Erickson, M. 2010. Ensemble Post-Processing and it's Potential Benefits for the Operational Forecaster. Northeast U.S. Operational Workshop (NROW XII), Albany, NY. November 2010.

Colle, B.A.; Erickson, M.; Charney, J. 2010. Calibrating ensembles for more anomalous weather conditions: Wildfire threat days over the Northeast U.S. DTC Ensemble Testbed (DET) Workshop. Boulder, CO. 18-19 August 2010.

Pollina, J. 2009. Meteorological Evolution and Model Performance for Fire Threat Days Over the Northeast U.S. Northeast U.S. Operational Workshop (NROW XI), Albany, NY. November 2009.

Pollina, J.; Colle, B.A.; Charney, J.J. 2009. Meteorological evolution of fire threat days over the Northeast U.S. Eighth symposium on Fire and Forest Meteorology. 2009 October 12-15; Kalispell, MT.

Colle, B.A.; Pollina, J.; Charney, J.J. 2009. Verification of short-range ensembles for fire threat days over the Northeast U.S.  Eighth Symposium on Fire and Forest Meteorology, American Meteorological Society, 13 - 15 October 2009, Kalispell, MT.

Charney, J.J., Colle, B.A.; Pollina, J. 2009.  The impact of WRF PBL parameterizations on the simulation of fire weather parameters over the northeast U.S.  10th Annual WRF Users’ Workshop, National Center for Atmospheric Research, 23-26 June 2009, Boulder, CO.

Research Participants

  • School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, NY
  • Joseph J. Charney, US Forest Service, Northern Research Station, Lansing, MI
Last Modified: September 8, 2014