• WILDLAND FIRES

    Effects of fire-atmosphere coupling on fire propagation, and plume dynamics

    Read More
    Wildland fires

  • WILDLAND FIRES

    Evolution of large fire events and their impacts on local weather conditions

    Details
    Large fire events

  • FIRE FORECASTING

    Numerical forecasting of fire progression plume, rise and smoke dispersion

    Fire forecasting
    Slide 3

  • AIR QUALITY IMPACTS OF WILDLAND FIRES

    Plume rise and dispersion, interactions between wildfire smoke and urban emissions

    AIR QUALITY AND SMOKE
    Slide 3

Welcome to Adam Kochanski's website

About ME

Adam Kochanski, Ph.D.

Assistant Professor
Phone: (408) 924-5200
Fax: (408) 924-5191
San Jose State University
Department of Meteorology and Climate Science
Wildfire Interdisciplinary Research Center
One Washington Square
Duncan Hall 620
San Jose, California 95192-0104

For experimental forecasts and real time fuel moisture products click HERE

Adam Kochanski

I'm an atmospheric modeler and co-developer of WRF-SFIRE (a coupled fire-atmosphere model), interested in improving our understanding of wildland fires and their impacts on local weather and air quality. I'm fascinated by the wide range of scales associated with wildand fires and the mechanisms allowing fires to create their own weather. I'm also interested in assimilation of satellite observations into coupled fire-atmosphere models as well as the impact of regional climate change on local hydrological cycles, fuel moisture and fire behavior. I perform numerical experiments using a wide range of numerical models executed on large supercomputers. I mostly work with the Weather Research and Forecasting model WRF the coupled fire-atmosphere model WRF-SFIRE, chemical transport model WRF-CHEM, QUIC urban model, and Stochastic Lagrangian Particle model STILT.

Research interests:

My research focuses on wildland fires - especially processes involving feedbacks between wildland fires and the atmosphere. I analyze observational data and simulate fire-atmosphere interactions using coupled fire-atmosphere model WRF-SFIRE run on powerful supercomputers. My overarching goal is to build better modeling systems accurately forecasting fire progression, smoke dispersion, and air quality impacts of wildland fires. My research is supported by many agencies such as the National Science Foundation, Joint Fire Science Program, US Forest Service and NASA.
In a nutshell, my research areas include:

  • Coupled fire-atmosphere modeling
  • Numerical forecasting of large wildland fire events
  • Air quality impacts of wildland fires
  • Plume dynamics and the impact of fire-atmosphere coupling on fire behavior
  • Smoke modeling
  • Fuel moisture modeling
  • Satellite data assimilation

WRF-SFIRE

What is WRF-SFIRE?

WRF-SFIRE is a coupled fire-atmosphere model based on WRF (Weather Research Forecasting System and SFIRE. With this system, fire behavior can be driven by a realistic large-scale meteorological forcing, while heat and moisture fluxes at the fireline are fed back into WRF from SFIRE, altering air temperature, humidity, and local winds. These fire-affected winds are then used to compute the fire's rate of spread, resulting in a two-way atmosphere-fire coupling. WRF-SFIRE can be run both in an idealized and in a real mode, at a wide range of horizontal resolutions. WRF-SFIRE is capable of simulating large-scale, high-intensity wildfires under various topographical, meteorological, and vegetation conditions. WRF-SFIRE includes a predictive fuel moisture model providing a detailed temporal evolution of the dead fuel moisture, whihc enables rndering of diurnal changes in fire activity associated with nighttime fuel moisture recovery, as well as changes in fire behavior driven by long-term variations in the fuel moisture. WRF-SFIRE has also recently been coupled with WRF-CHEM. In this configuration, emission fluxes of WRF-CHEM-compatible chemical species and aerosols are computed based on the fuel consumption rate, and ingested into the atmosphere where they undergo chemical and physical transformations rendered by WRF-CHEM's chemical mechanisms (MOZART, RADM2 or GOCART).


WRF-SFIRE-CHEM diagram

WRF-SFIRE-CHEM diagram

WRF-SFIRE resources

The best source of information about WRF-SFIRE is the Open Wildland Fire Modeling Community (OWFM) website. In particular the WRF-SFIRE users guide is a good starting point describing how to get the software from git and run simple cases. Plese also check our wiki page for links to numerous How-To articles. Additionally, on the right side you will find presentations from my WRF-SFIRE Hands-On toutorial organized during the Workshop on Modelling of Wildfires and their Environmental Impacts by the International Centre for Theoretical Physics (ICTP) in Trieste. You can also check our conference presentations posted on OpenWFM.org.
If you are new to WRF, there is a great on-line tutorial prepared by NCAR, avaialbe at their WRF ARW website. It is strongly suggested to take this tutorial prior to getting into WRF-SFIRE, as WRF-SFIRE tutorials focus more on SFRIE specifics, than general WRF subjects.

Sample Simulations

idealized plume simulation

fire progresion, smoke and fuel moisture simulated as a real case

winds, fire progression, plume rise and dispersion simulated as a real case

Regional climate simulation

Large eddy cloud simulation

QUIC urban model simulation

QUIC urban model smiulation

See more visualizations

Publications

Kochanski A. K., Herron-Thorpe F., Mallia D. V., Mandel J., Vaughan J. K. (2021). Integration of a Coupled Fire-Atmosphere Model Into a Regional Air Quality Forecasting System for Wildfire Events, Frontiers in Forests and Global Change, 2021, 4, 167, DOI=10.3389/ffgc.2021.728726.

Mandal A, Nykiel G, Strzyzewski T., Kochanski A., Wrońska W, Gruszczyńska M, Figurski M. (2021). High resolution fire danger forecast for Poland based on Weather Research and Forecasting Model, International Journal of Wildland Fire, Accepted.

M. Halubok, A. K. Kochanski, R. Stoll and B. N. Bailey (2021). Errors in the estimation of leaf area density from aerial LiDAR data: Influence of statistical sampling and heterogeneity, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3123585.

Farguell, A.; Mandel, J.; Haley, J.; Mallia, D.V.; Kochanski, A.; Hilburn, K. Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data. Remote Sens. 2021, 13, 2203. https://doi.org/10.3390/rs13112203

Su, J.-Y.; Goel, R.; Burian, S.; Hinners, S.J.; Kochanski, A.; Strong, C.; Barber, M.E. Water Quality Trading Framework with Uncertainty for River Systems Due to Climate and Population Characteristics. Water 2021, 13, 1738. https://doi.org/10.3390/w13131738

Riley, C.; Rupper, S.; Steenburgh, J.W.; Strong, C.; Kochanski, A.K.; Wolvin, S. Characteristics of Historical Precipitation in High Mountain Asia Based on a 15-Year High Resolution Dynamical Downscaling. Atmosphere 2021, 12, 355. https://doi.org/10.3390/atmos12030355

Mallia D.V; Kochanski A.K., Kelly K.E., Whitaker R., Xing W., Mitchell L., Jacques A., Farguell A., Mandel J., Gaillardon P-E, Becnel T., Krueger S. (2020) Evaluating wildfire smoke transport within a coupled fire-atmosphere model using a high-density observation network for an episodic smoke event along Utah's Wasatch Front. Journal of Geophysical Research Atmosphere, 125, e2020JD032712 https://doi.org/10.1029/2020JD032712

Mallia, D.V.; Kochanski, A.K.; Urbanski, S.P.; Mandel, J.; Farguell, A.; Krueger, S.K. Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn. Atmosphere 2020, 11, 832.https://www.mdpi.com/2073-4433/11/8/832/htm

Herr V., Kochanski A. K. , Miller V. V., McCrea R., O'Brien D., Mandel J.(2020) A method for estimating the socioeconomic impact of Earth observations in wildland fire suppression decisions. International Journal of Wildland Fire 29, 282-293. https://doi.org/10.1071/WF18237

Hasan M, Strong C, Kochanski A, Burian S, Barber M, 2020. Validating dynamically downscaled climate projections for mountainous watersheds using historical runoff data coupled with the Distributed Hydrologic Soil Vegetation Model (DHSVM), Water, doi:10.3390/w12051389.

Kochanski, A. K., Mallia, D. V., Fearon, M. G., Mandel, J., Souri, A. H., & Brown, T. ( 2019). Modeling wildfire smoke feedback mechanisms using a coupled fire-atmosphere model with a radiatively active aerosol scheme. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2019JD030558

K.B. Khatri C. Strong N. von Stackelberg M. Buchert A.K. Kochanski (2019). Impact of Climate and Land Use Change on Streamflow and Sediment Yield in a Snow-Dominated Semiarid Mountainous Watershed. JAWRA Journal of the American Water Resources AssociationVolume 55, Issue 6 DOI:10.1111/1752-1688.12803

Liu Y., Kochanski A., Kirk B. R., Mell W., Linn R., Paugam R., Mandel J., Fournier A., Jenkins M., Goodrick S., Achtemeier G., Zhao F., Ottmar R., French N. , Larkin N., Brown T., Hudak A., Dickinson M., Potter B., Clements C., Urbanski S., Prichard S., Watts A., McNamara Derek (2019) Fire behaviour and smoke modelling: model improvement and measurement needs for next-generation smoke research and forecasting systems. International Journal of Wildland Fire 28, 570-588. https://doi.org/10.1071/WF18204

Clements, C. B., A. K. Kochanski, D. Seto, B. Davis, C. Camacho, N. P. Lareau, J. Contezac, W. E. Heilman, S. K. Krueger, B. Butler, J. Restaino, R. D. Ottmar, R. Vihnanek, J. Flynn, Jean-Baptiste Filippi, T. Barboni, D. E. Hall, J. Mandel, M. A. Jenkins, and J. O'Brien, B. Hornsby, and C. Teske, (2019) The FireFlux II Experiment: A model-guided field experiment to understand fire-atmosphere interactions and fire spread International Journal of Wildland Fire. https://www.publish.csiro.au/WF/WF18089

Prichard S., N. Larkin, Roger Ottmar, Nancy French, Kirk Baker, Tim Brown, Craig Clements, Matt Dickinson, Andrew Hudak, Adam Kochanski, Rod Linn, Yongqiang Liu, Brian Potter, William Mell, Danielle Tanzer, Shawn Urbanski, Adam Watts, (2019) The Fire and Smoke Model Evaluation Experiment - A Plan for Integrated, Large Fire-Atmosphere Field Campaigns. Atmosphere 2019, 10(2), 66; https://doi.org/10.3390/atmos10020066

Arunchandra S. Chandra, Paquita Zuidema, Steven Krueger, Adam Kochanski, Simon P. de Szoeke and Jianhao Zhang (2018) Moisture distributions in tropical cold pools from equatorial Indian Ocean observations and cloud-resolving simulations. Journal of Geophysical Research doi: 10.1029/2018jd028634

Kochanski A.K, A. Fournier and J. Mandel (2018). Experimental Design of a Prescribed Burn Instrumentation. Atmosphere 2018, 9(8), 296; https://doi.org/10.3390/atmos9080296

Mallia, D.V.; Kochanski, A.K.; Urbanski, S.P.; Lin, J.C. Optimizing Smoke and Plume Rise Modeling Approaches at Local Scales. Atmosphere 2018, 9, 166.

Krishna B. Khatri, Courtenay Strong, Adam K. Kochanski., Steven Burian, Craig Miller, Candice Hasenyager (2018), Water Resources Criticality Due to Future Climate Change and Population Growth: Case of River Basins in Utah, USA Journal of Water Resources Planning and Management DOI 10.1061/(ASCE)WR.1943-5452.00009

Souri, A. H., Choi, Y., Jeon, W., Kochanski, A. K., Diao, L., Mandel, J., Bhave, P. V., & Pan, S. (2017). Quantifying the impact of biomass burning emissions on major inorganic aerosols and their precursors in the U.S. Journal of Geophysical Research: Atmospheres, 122. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000959

Mallia, D. V., A. Kochanski, C. Pennell, W. Oswald, and J. C. Lin, (2017) Wind-blown dust modeling using a backward Lagrangian particle dispersion model. J. Appl. Meteor. Climate., 56, 2845-2867.

Strong C, Khatri K, Kochanski A., Lewis C, Allen N. (2017). Reference evapotranspiration from coarse-scale and dynamically downscaled data in complex terrain: sensitivity to interpolation and resolution, Journal of Hydrology, odi: 10.1016/j.hydrol.2017.02.045.

Scalzitti J, Strong C, Kochanski A, (2016). Climate change impact on the roles of temperature and precipitation in western U.S. snowpack variability, Geophysical Research Letters doi:10.1002/2016GL068798

Scalzitti J, Strong C, Kochanski A, (2016). A 26 year high-resolution dynamical downscaling over the Wasatch Mountains: Synoptic effects on winter precipitation performance, Journal of Geophysical Research, doi: 10.1002/2015JD024497

Kochanski A. K., E. R. Pardyjak, R. Stoll, A. Gowardhan, M.J Brown, W.J. Steenburgh (2015) One-Way Coupling of the WRF - QUIC Urban Dispersion Modeling System Journal of Applied Meteorology And Climatology DOI: 10.1175/JAMC-D-15-0020.1

Kochanski A. K., Jenkins M.A., Yedinak K., Mandel J., Beezley J, and Lamb B. (2015) Toward an integrated system for fire, smoke and air quality simulations, International Journal of Wildland Fire - http://dx.doi.org/10.1071/WF14074

Vejmelka M, Kochanski A, Mandel J, (2015) Data assimilation of dead fuel moisture observations from remote automated weather stations, International Journal of Wildland Fire 25, 558-568. http://dx.doi.org/10.1071/WF14085

Strong C., A. K. Kochanski, E.T. Crosman (2014) A slab model of the Great Salt Lake for regional climate simulation J. Adv. Model. Earth Syst., 6, 602-615, doi:10.1002/2014MS000305.

Mandel, J., Amram, S., Beezley J. D., Kelman G., Kochanski A. K., Kondratenko V. Y., Lynn, B. H., Regev, B., and Vejmelka, M. (2014): Recent advances and applications of WRF-SFIRE, Nat. Hazards Earth Syst. Sci., 14, 2829-2845, doi:10.5194/nhess-14-2829-2014, 2014.

Kochanski, A. K., Jenkins M. A., Mandel J, Beezley J. D. and Krueger S. K., (2013): Evaluation of WRF-Sfire Performance with Field Observations from the FireFlux experiment. Geoscientific Model Development 6, 1109-1126, 2013 doi:10.5194/gmd-6-1109-2013

Kochanski A. K., Jenkins M.A., Krueger S. K., Mandel J., and Beezley J. D., (2013): Real time simulation of 2007 Santa Ana fires, Forest Ecology and Management 15, 136-149, 2013 doi:10.1016/j.foreco.2012.12.014

Kochanski, A. K., Jenkins M. A., Sun R., Krueger S. K., and Charney J. J., (2013): The importance of low-level environmental vertical wind shear to wildfire propagation: Proof of concept, Journal of Geophysical Research 118(15) 8238-8252 DOI: 10.1002/jgrd.50436.

Mandel J.,J. D. Beezley, Kochanski A. K., Kondratenko V. Y., Kim M. (2012): Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire–Atmosphere DDDAS. Procedia Computer Science, Volume 9, 2012, Pages 1100-1109, https://doi.org/10.1016/j.procs.2012.04.119

Mandel J., J. D. Beezley, and A. K. Kochanski (2011): Coupled atmosphere-wildland fire modeling with WRF-Fire version 3.3, Geoscientific Model Development, 4, 591-610, doi:10.5194/gmd-4-591-2011

Jordanov, G., J. D. Beezley, N. Dobrinkova, A. K. Kochanski, and J. Mandel, (2011) Simulation by WRF-Fire of the 2009 Harmanli fire (Bulgaria) Large-Scale Scientific Computing, Lecture Notes in Computer Science Volume 7116, 2012, pp 291-298.

Kahn B. H., J. Teixeira1, E. J. Fetzer, A. Gettelman, S. M. Hristova-Veleva, X. Huang, A. K. Kochanski, M. Kohler, S. K. Krueger, R. Wood, and M. Zhao: (2011) Temperature and water vapor variance scaling in global models: Comparisons to satellite and aircraft data. J. Atmos. Sci., 68(9), 2156-2168.

Kochanski, A. K., Koracin D., Dorman C. (2006) Comparison of the wind stress algorithms and their influence on the wind stress using buoy measurement over the shelf of Bodega Bay, California. Deep Deep-Sea Research II 53, 2865-2886

Wind Stress Curl and Upwelling along the California Coast, Koracin, D., Kochanski A., Dorman, C.E., Dever, E.P Bulletin of the American Meteorological Society, Volume 86, number 5, May 2005, pages 629-630.

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Copyright © 2018 Adam Kochanski