Planning for an Unknown Future: Incorporating Meteorological Uncertainty into Predictions of the Impact of Fires and Dust on US Particulate Matter

EPA Grant Number: R835884
Title: Planning for an Unknown Future: Incorporating Meteorological Uncertainty into Predictions of the Impact of Fires and Dust on US Particulate Matter
Investigators: Fischer, Emily , Barnes, Elizabeth , Pierce, Jeffrey
Institution: Colorado State University
EPA Project Officer: Chung, Serena
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2019)
Project Amount: $349,969
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text |  Recipients Lists
Research Category: Air , Climate Change


Emissions of wildfire smoke and dust will likely increase over the western US with climate change. The focus of this work is to determine how model uncertainty in future meteorology translates into uncertainty in the contributions of smoke and dust to future particulate matter (PM) episodes.  This is an understudied issue that cuts across three of the five high priority foci for future climate and PM research. We will answer the following questions: 1) Do major synoptic events capture the variability in emissions and concentrations of PM from fires and dust over the western US? 2) What is the spread in future projections of air-quality relevant synoptic conditions over the western US in state-of-the-art coupled atmosphere-ocean climate models? 3) How does this spread in future meteorology propagate to uncertainty in A) emissions of PM from fires and dust sources, and B) the resulting PM concentrations?


The first stage of the proposed work will use a single coupled land-atmosphere-climate model (Community Earth System Model; CESM) to estimate climate-driven changes to fires and dust and the consequences for US PM concentrations. The work for this project will begin by analyzing the full suite of CESM output to identify relationships between meteorological parameters and the emissions and PM impacts associated with both wild fires and wind-generated dust in the CESM model.  We propose to investigate relationships with 1) high wind days, 2) precipitation days, 3) high temperature days, 4) blocking anticyclone events, 5) stagnation events, and 6) cyclone days.  This mix of parameters represents meteorological conditions that are hypothesized to be of importance for either fires or dust generation, can be classified using existing schemes, and can be quantified in the CESM output and a suite of climate models.

The second stage of the project will use output from a suite of state-of-the-art climate models to investigate uncertainties in the future response of the meteorological parameters of interest (stagnation events, precipitation days, etc.).  Here we will leverage 21st century climate simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. While all models document changes in climate extremes over the next century with increasing greenhouse gas emissions, there is substantial disagreement in the spatial patterns and magnitudes of the individual model responses. We will aggregate the responses of the meteorological statistics from 22 global climate models (GCMs) to produce uncertainty estimates of the future change in the meteorological parameters over the western US. Finally, we will combine the information from the analysis of the CESM output and the spread in the CMIP5 models.

Expected Results:

This project will improve the ability to protect environmental and public health by producing probability distributions of how wildfire and dust emissions and associated PM concentrations will change between present day and 2050.

Publications and Presentations:

Publications have been submitted on this project: View all 4 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 1 journal articles for this project

Supplemental Keywords:

ambient air, climate models, EPA Regions (1 through 10);

Progress and Final Reports:

  • 2016 Progress Report
  • 2017 Progress Report
  • 2018