1. Steve Edburg Assistant Research Professor Laboratory for Atmospheric Research Washington State University sedburg@wsu.edu

2. My Background Large-eddy simulation (LES) – PhD work at WSU Earth system modeling (EaSM) – Postdoctoral work at UI

3. SOIL SUN Gas emission from biological processes in forest and soil FOREST air + trace gases INFLOW Mixing & Chemical Reactions Products and reactants from biosphere atmosphere interaction OUTFLOW

4. LES Overview Gap in knowledge: The role of turbulence on chemical production or loss within a forest canopy is unknown Objective: Our objective was to determine if reaction rates are modified by intermittent turbulent structures Hypothesis: Our central hypothesis was that turbulent structures alter reactions rates by un-evenly mixing trace gases above the canopy with gases emitted from trees Goal: Use large-eddy simulation to determine the influence of coherent structures on trace gas reaction rates

5. Side View Animation

6. Top View Animation

7. Scalar Segregation

8. Earth System Modeling

9. EaSM Overview Knowledge gap: Impact of bark beetle outbreak on carbon cycling is unknown Objective: Quantify the impact of bark beetles on carbon cycling across the western US Aims: – Create a regional insect disturbance product; – modify a Earth system model; – conduct simulations with and without outbreaks

10. USDA Forest Service, 2004 In 2009, 4.3 Mha/10.6 Macres affected by bark beetles 3.6 Mha/8.8 Macres affected by mountain pine beetle Why is this issue important? 1.Infestations are widespread throughout western US 10

11. Photo by C. Schnepf, forestryimages.org Dead tree, needles onNeedles off Snag fall/understory growth Physical and biogeochemical characteristics compared with undamaged forest 1.Reduced GPP 2.Reduced ET 1.Reduced LAI 2.Reduced Interception 1.Increased R h 2.Initial recovery Year following attackAfter 3-5 years After several decades Photo by Arjan Meddens 11

12. Simulated Soil N Dynamics Play a Key Role in C Fluxes and Recovery 5 yr 10 yr 25 yr Point simulation in Idaho: 95% mortality over 3 years

14. Future Research

15. “Daily Forecasts of Wildland Fire Impacts on Air Quality in the Pacific Northwest: Enhancing the AIRPACT Decision Support System ” Team: S. Edburg, B. Lamb, J. Vaughan, A. Kochanski, M.A. Jenkins, J. Mandel, N. Larkin, T. Strand, and R. Mell Pending, submitted in December 2011 to NASA ROSES: Wildland Fires

16. Project Overview Our long-term goal is to continue the development of AIRPACT and evaluation tools to support decision making activities The objective of this proposal is to improve the representation of wildland fires within AIRPACT Our specific aim is to implement the WRF-Fire model within AIRPACT and evaluate simulations with satellite products We expect this will improve the plume rise and emission estimates and our evaluation techniques In our opinion, this will improve daily predictions of wildland fire impacts on air quality across the pacific northwest

17. EOS inputs: MOPITT (CO) MODIS / GOES CMAQ -Influence of fire on the Air Quality forecast (e.g. PM 2.5, O 3, NO 2, CO, NMHC) SMARTFIRE -Fire location -Fire area BlueSky Modeling Framework -Speciated emissions -Time rate of emissions -Plume injection height of emissions S.M.O.K.E -Emissions preprocessor WRF-Fire -Time rate of emissions -Plume Injection Heights -Influence of meteorology on fire spread and intensity Proposed Additions EOS Evaluation -OMI NO 2 & O 3 -MISR/CALPISO aerosol AIRPACT WRF -Meteorological Input -72 hour forecast

18. Example of WRF-Fire