Www.mtri.org A 2012 NASA-CMS Phase 2 study Lead Investigators: Nancy HF French, MTRI Don McKenzie, US Forest Service, PNW, FERA Eric Kasischke, University.

Slides:



Advertisements
Similar presentations
Has EO found its customers? Global Vegetation Monitoring Unit GLC2000 GLOBAL LEGEND GLC 2000 – “FIRST RESULTS” WORKSHOP JRC – Ispra, March 2002.
Advertisements

1 1. FY09 GOES-R3 Project Proposal Title Page Title: Trace Gas and Aerosol Emissions from GOES-R ABI Project Type: GOES-R algorithm development project.
The Alaska Forest Disturbance Carbon Tracking System T. Loboda, E. Kasischke, C. Huang (Univ. MD), N. French (MTRI) J. Masek, J. Collatz (GSFC), D. McGuire,
The Downscaled Climate Projection Has Arrived – NOW WHAT?
National Assessment of Ecological C Sequestration and Greenhouse Gas Fluxes – the USGS LandCarbon Project Zhiliang Zhu, Project Chief, What.
A Synthesis of Terrestrial Carbon Balance of Alaska and Projected Changes in the 21 st Century: Implications for Climate Policy and Carbon Management To.
Global Fire Emissions and Fire Effects on Biophysical Properties and the Associated Radiative Forcing Yufang Jin 1, James Randerson 1, G. R. van der Werf.
CMS – 2012 Reduction in Bottom-Up Land Surface CO 2 Flux Uncertainty in NASA’s Carbon Monitoring System Flux Project through Systematic Multi-Model Evaluation.
Magnitude and Spatial Distribution of Uncertainty in Ecosystem Production and Biomass of Amazonia Caused by Vegetation Characteristics Christopher Potter.
Map of the Arctic (1595) by Mercator W.P 1.4: Land cover and Fire and their representation in models. Objective 1: To amalgamate high latitude land cover.
Carbon Cycle and Ecosystems Important Concerns: Potential greenhouse warming (CO 2, CH 4 ) and ecosystem interactions with climate Carbon management (e.g.,
Fire Modeling issues: fire effects on regional air quality under a changing climate Douglas G. Fox
Fire regimes and the World’s biomes 23 September 2010.
03/06/2015 Modelling of regional CO2 balance Tiina Markkanen with Tuula Aalto, Tea Thum, Jouni Susiluoto and Niina Puttonen.
Carbon Benefits Project: Measurement of Carbon in Woody Biomass Mike Smalligan, Research Forester Global Observatory for Ecosystem Services Department.
Forest Growth Model and Data Linkage Issues Limei Ran Carolina Environmental Program UNC Steve McNulty Jennifer Moore Myers Southern Global Change Program,
Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.
3/21/11 Land cover / change Cover themes – Forests – Agriculture – Fire – Water – Land cover Cover dynamics – Phenological change – Disturbance – Specific.
The Carbon Benefits Project: Modelling, Measurement and Monitoring Approximately 30% of greenhouse gas (GHG) emissions come from land use and land use.
Improving Estimates of Hydrologic Extremes: Applications to the Olympic National Forest Ingrid Tohver PNW Climate Science Conference September 14, 2011.
Sampling Methods for Estimating Accuracy and Area of Land Cover Change.
Nancy HF French, Don McKenzie, Tyler Erickson Poster # 301 with on-line demo – Wednesday Development and use of the Wildland Fire Emissions.
CSIRO LAND and WATER Estimation of Spatial Actual Evapotranspiration to Close Water Balance in Irrigation Systems 1- Key Research Issues 2- Evapotranspiration.
Compton Tucker, GSFC Sassan Satchi, JPL Jeff Masek, GSFC Rama Nemani, ARC Diane Wickland, HQ Terrestrial Biomass Pilot Product: Estimating Biomass and.
Georgia Institute of Technology Air Quality Impacts from Prescribed Burning: Fort Benning Case Study M. Talat Odman Georgia Institute of Technology School.
Flux-Biomass Integration Scott Denning, Colorado State University Nancy French, Michigan Technological University Eric Kasischke, Univ of Maryland Don.
National Fire & Air Workshop January 28-30, 2003 Westward Look Resort Tucson, AZ Emission Inventory for Prescribed and Wildland Fire: –What we mean by.
Oct-03FOFEM 5 Overview An Overview of FOFEM 5 Missoula Fire Sciences Laboratory Systems for Environmental Management.
USDA Forest Service Remote Sensing Applications Center Forest Inventory and Analysis New Technology How is FIA integrating new technological developments.
Jorge Peña Arancibia, Francis Chiew, Tim McVicar, Yongqiang Zhang, Albert Van Dijk, Mohammed Mainuddin and others 29 April 2014 CSIRO LAND AND WATER Dynamic.
Improving the Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Satellite Data E.Kantzas, S.Quegan & M.Lomas School of Maths.
Forest Inventory and Analysis USDA Forest Service PNW Research Station Remote sensing; The world beyond aerial photos.
Operational Agriculture Monitoring System Using Remote Sensing Pei Zhiyuan Center for Remote Sensing Applacation, Ministry of Agriculture, China.
F I A Forest Inventory and Analysis Program The Nation’s Forest Census 2010 FIA Biomass Update W. Brad Smith.
Estimates of Biomass Burning Particulate Matter (PM2.5) Emissions from the GOES Imager Xiaoyang Zhang 1,2, Shobha Kondragunta 1, Chris Schmidt 3 1 NOAA/NESDIS/Center.
Getting Ready for the Future Woody Turner Earth Science Division NASA Headquarters May 7, 2014 Biodiversity and Ecological Forecasting Team Meeting Sheraton.
MODIS-Based Techniques for Assessing of Fire Location and Timing in the Alaskan Boreal Forest Nancy H.F. French 1, Lucas Spaete 1, Elizabeth Hoy 2, Amber.
BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms.
15-18 October 2002 Greenville, North Carolina Global Terrestrial Observing System GTOS Jeff Tschirley Programme director.
Participant NameOrganization Collatz, George (Jim) (WG Lead)NASA GSFC Brown, MollyNASA GSFC Denning, ScottColorado State University Escobar, VanessaSigma.
Habitat Diversity What is the link between Evolution & Adaptation, & the diversity of Habitats found on Earth?
Research - Alaska Analysis Team – Anchorage Bill van Hees – Team leader Bert Mead – Research forester Beth Schulz – Research forester Ken Winterberger.
Causes of Haze Assessment Update for Fire Emissions Joint Forum -12/9/04 Meeting Marc Pitchford.
An Adaptive Management Model for the Red River Basin of the North.
AAG 2010 Washington DC Savanna Vegetation Changes as Influenced by Climate in East Africa Gopal Alagarswamy, Chuan Qin, Jiaguo Qi, Jeff Andresen, Jennifer.
Variations in Continental Terrestrial Primary Production, Evapotranspiration and Disturbance Faith Ann Heinsch, Maosheng Zhao, Qiaozhen Mu, David Mildrexler,
Development of Wildland Fire Emission Inventories with the BlueSky Smoke Modeling Framework Sean Raffuse, Erin Gilliland, Dana Sullivan, Neil Wheeler,
Scaling Up Above Ground Live Biomass From Plot Data to Amazon Landscape Sassan S. Saatchi NASA/Jet Propulsion Laboratory California Institute of Technology.
Pollutant Emissions from Large Wildfires in the Western United States Shawn P. Urbanski, Matt C. Reeves, W. M. Hao US Forest Service Rocky Mountain Research.
Roger Ottmar Research Forester Fire and Environmental Research Applications Team Pacific Wildland Fire Sciences Laboratory USDA Forest Service Research—PNW.
Impact of the changes of prescribed fire emissions on regional air quality from 2002 to 2050 in the southeastern United States Tao Zeng 1,3, Yuhang Wang.
Denver 2004 TGP1 PM2.5 Emissions Inventory Workshop Denver, CO March 2004 Thompson G. Pace USEPA Emissions Estimation for Wildland Fires.
Hydrologic Data Assimilation with a Representer-Based Variational Algorithm Dennis McLaughlin, Parsons Lab., Civil & Environmental Engineering, MIT Dara.
Uncertainties in Wildfire Emission Estimates Workshop on Regional Emissions & Air Quality Modeling July 30, 2008 Shawn Urbanski, Wei Min Hao, Bryce Nordgren.
Citation: Moskal., L. M. and D. M. Styers, Land use/land cover (LULC) from high-resolution near infrared aerial imagery: costs and applications.
INTEGRATING SATELLITE AND MONITORING DATA TO RETROSPECTIVELY ESTIMATE MONTHLY PM 2.5 CONCENTRATIONS IN THE EASTERN U.S. Christopher J. Paciorek 1 and Yang.
Terrestrial ECVs Fire/burnt area, Land cover, Soil Moisture.
Application of Fuel Characteristic Classification System to Ph II EI (add-on task to Inter RPO project) Fire Emissions Joint Forum Meeting Spokane, WA.
USDA Forest Service, Remote Sensing Applications Center, FSWeb: WWW: National Geospatial Fire.
Wildland Fire Emissions Study – Phase 2 For WRAP FEJF Meeting Research in progress by the CAMFER fire group: Peng Gong, Ruiliang Pu, Presented by Nick.
NASA CMS Algorithm Assessment/Intercomparison Working Group Summary Presentation November 6 th, 2013 Coordinator: Scott Powell Members: David Baker, Molly.
Arctic RIMS & WALE (Regional, Integrated Hydrological Monitoring System & Western Arctic Linkage Experiment) John Kimball FaithAnn Heinsch Steve Running.
The application of Models-3 in national policy Samantha Baker Air and Environment Quality Division, Defra.
Western Mensurationists Meeting 2016
Terrestrial-atmosphere (1)
Continental Modeling and Analysis of the North American Carbon Cycle
Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.
Bob McGaughey Pacific Northwest Research Station
Igor Appel Alexander Kokhanovsky
Ecosystems.
Presentation transcript:

A 2012 NASA-CMS Phase 2 study Lead Investigators: Nancy HF French, MTRI Don McKenzie, US Forest Service, PNW, FERA Eric Kasischke, University of Maryland Presented by: Michael Billmire, MTRI (WFEIS technical lead) Regional Fire Emissions Products using the Wildland Fire Emissions Information System

wfeis.mtri.org

Modeling Wildland Fire Emissions Fuel moisture

Modeling Wildland Fire Emissions: WFEIS Fuel moisture Burned area products provide: burn area location -> tells us fuel loadings, fuel moisture day -> tells us fuel moisture Options: MODIS MCD64A1 MTBS burn perimeters Daily progression (MODIS Active Fire interpolated to MTBS) SmartFire 2011 NEI Agricultural NEI (McCarty)

Modeling Wildland Fire Emissions: WFEIS Fuel moisture Fuel type (from 1-km FCCS map) linked to stratified fuel loadings (biomass)

Modeling Wildland Fire Emissions: WFEIS Fuel moisture Daily gridded weather Daily fuel moisture interpolated from RAWS data from 1986 through 2013 at 40-km scale for all of CONUS

Modeling Wildland Fire Emissions: WFEIS Fuel moisture Consumption & Emissions model (CONSUME)

Modeling Wildland Fire Emissions: WFEIS Fuel moisture

Main Project Objectives Improve WFEIS Improve inputs: fuel loading (biomass), fuel moisture Develop methodology for uncertainty measurement for emissions estimations Produce regional emissions estimates Compare these estimates to CASA GFED estimates

Objective Improve WFEIS inputs

aggregated classes Biomass varies across instances of each class Refining the fuels map for CONUS (Co-I McKenzie) Each instance of a class (cell) is assigned a unique set of fuel loadings.

Refining the fuels map for CONUS (Co-I McKenzie) We can use remote sensing products to help to more appropriately characterize canopy fuels and thus provide fuel load variation within a single fuel type Tree cover Non-tree cover Bare ground continuous values

14 Canopy fuel loadings in forested fuelbeds are generally lower. Exceptions in northern Rocky Mts, Northeast, Gulf coast, upper Michigan. As expected, spatial variation is more “realistic” in MODIS- enhanced fuel layer. Refining the fuels map for CONUS (Co-I McKenzie) Result: The new 1-km MODIS-enhanced FCCS

15 Task: Improved Fuel Moisture Inputs Before: -by Level II CEC Ecoregion Now: -by 40 km grid cell (interpolated from RAWS) “Improved” = better spatial resolution updated through 2013

Develop methodology for assessing uncertainty Achievements: –Developed a framework for estimating the various components of WFEIS model uncertainty –Mathematically rigorous documentation of the (~60) Consume regression equations –Identified all possible sources of error: Coefficient error for each regression-based prediction equation Input measurement error (e.g. measurements from field work) Classification error (e.g. accuracy of spatial data)

Provide Assessment of Uncertainty in Emissions Estimates Achievements : –Conducted case studies on two of Consume’s regression-based consumption equations –The two studies were done for the shrub and for the western woody fuel strata –These examples demonstrated both sample-based and Monte Carlo approaches to uncertainty and sensitivity analysis.

Objective Produce regional emissions estimates

WFEIS Emissions Estimates

All available at:

Region 11 – Mediterranean California This is the only ecoregion in the continental US with a Mediterranean climate – summers are hot and dry, and winters are mild. Droughts are common, with precipitation averaging from 200-1,000 mm per year. With irrigation, these features create a prime environment for high value agriculture. Native vegetation is dominated by shrubs, with patchy areas of grasslands and forests of evergreen and deciduous trees Mediterranean California

Objective Compare to CASA GFED estimates

GFED comparison to WFEIS (with collaborator Collatz) Comparison between GFEDv3 (published emissions) and WFEISv0.3 for TENA/CONUS GFEDv3 is the fire emissions module in CASA-GFED, one of the models used in the CMS-Flux pilot for terrestrial C flux estimates

GFED comparison to WFEIS (with collaborator Collatz)  Summary of differences between major model components

GFED comparison to WFEIS (with collaborator Collatz) Modeled emission results comparison –Carbon: GFED ~50% of WFEIS

GFED comparison to WFEIS (with collaborator Collatz) Modeled emission results comparison –CO 2 : GFED ~95% of WFEIS

Project is complete, BUT we are currently seeking funding for the continued development/maintenance of WFEIS and are eager to get to work on the following important tasks: –Full uncertainty characterization of the CONSUME model Started under this project; statistical framework established and demonstrated test cases for several of the ~60 consumption equations Once complete, the end goal is for WFEIS outputs (and any other modeling effort making use of the CONSUME model) to deliver uncertainty estimates The Road Ahead

Project is complete, BUT we are currently seeking funding for the continued development/maintenance of WFEIS and would love to get to work on the following important tasks: Integrate information on land disturbance from remote sensing and other geospatial products to update dynamically the representation of fuel loadings in WFEIS The Road Ahead

Project is complete, BUT we are currently seeking funding for the continued development/maintenance of WFEIS and would love to get to work on the following important tasks: Develop international versions of WFEIS The Road Ahead

Project Team Michigan Tech Research Institute Nancy HF French, PI Michael Billmire, Arthur Endsley, Nicholas Molen, Jessica McCarty, Reid Sawtell, Amanda Grimm, Amy Howes, Kim Mobley USFS Fire and Environmental Research and Applications and University of Washington Don McKenzie, Co-I Roger Ottmar, Susan Prichard, Rob Norheim Eric S Kasischke, Co-I, UMd Jim Collatz, Collaborator, GSFC

GFED comparison to WFEIS (with collaborator Collatz) Burned area comparison –GFED 2% higher than WFEIS

GFED comparison to WFEIS (with collaborator Collatz) Fuel available comparison –GFED 55% lower than WFEIS

GFED comparison to WFEIS (with collaborator Collatz) Combustion completeness comparison –GFED 15% higher than WFEIS

GFED comparison to WFEIS (with collaborator Collatz) Emission factors comparison –Carbon: GFED 5% lower than WFEIS –CO 2 : GFED 80% higher than WFEIS