Wildfire Plume Injection Heights Over North America: An Analysis of MISR Observations Maria Val Martin and Jennifer A. Logan (Harvard Univ., USA) Fok-Yan.

Slides:



Advertisements
Similar presentations
Global transport and radiative forcing of biomass burning aerosols Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,
Advertisements

ISTP Oktober Aerosol boomerang: Rapid around-the-world transport of smoke from the December 2006 Australian forest fires observed from.
Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,
1 Satellite Imagery Interpretation. 2 The SKY Biggest lab in the world. Available to everyone. We view from below. Satellite views from above.
Allison Parker Remote Sensing of the Oceans and Atmosphere.
The Problem of Parameterization in Numerical Models METEO 6030 Xuanli Li University of Utah Department of Meteorology Spring 2005.
1 An initial CALIPSO cloud climatology ISCCP Anniversary, July 2008, New York Dave Winker NASA LaRC.
Global Winds Michael J. Garay
Jared H. Bowden Saravanan Arunachalam
Semi-direct effect of biomass burning on cloud and rainfall over Amazon Yan Zhang, Hongbin Yu, Rong Fu & Robert E. Dickinson School of Earth & Atmospheric.
Injection height for biomass burning emissions from boreal forest fires Fok-Yan Leung April 12, Harvard University Special thanks to: Jennifer Logan,
How Important Are Temporal Constraints and Vertical Injection of Boreal Fire Emissions? Yang Chen 1,3, Qinbin Li 1,2, James Randerson 3, Evan Lyons 2 Ralph.
Pyro-convective smoke plume observed at ~10 km over British Columbia, June 2004 Vertical transport of surface fire emissions observed from space Siegfried.
Climate change, fires, and carbon aerosol over N. America with preliminary detour to discuss GCAP model development (GCAP= Global change and air pollution)
Quantifying aerosol direct radiative effect with MISR observations Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,
ATS 351 Lecture 8 Satellites
1 AirWare : R elease R5.3 beta AERMOD/AERMET DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA
CNRM activities during CarboEurope Regional Experiment Strategy - forecasting support - wind profiler - Ceilometer - Radiosonde soundings - Surface flux.
Comparisons of TES v002 Nadir Ozone with GEOS-Chem by Ray Nassar & Jennifer Logan Thanks to: Lin Zhang, Inna Megretskaia, Bob Yantosca, Phillipe LeSager,
Detect and Simulate Vegetation, Surface Temperature, Rainfall and Aerosol Changes: From Global to Local Examples from EOS MODIS remote sensing Examples.
Rynda Hudman 1,2, Dominick Spracklen 1,3, Jennifer Logan3 Loretta J
METR112-Climate Modeling Basic concepts of climate Modeling Components and parameterization in the model sensitivity of the model.
GEOS-CHEM meeting: Effects of enhanced boreal forest fires on global CO Fok-Yan Leung with help and thanks to Jennifer Logan, Ed Hyer, Eric Kasischke,
METR112-Climate Modeling Basic concepts of climate Modeling Components and parameterization in the model sensitivity of the model.
Satellite Imagery Meteorology 101 Lab 9 December 1, 2009.
64 or 128 Columns 2°2° 2.5° Depiction of Multi-scale Modeling Framework (MMF) A Cloud Resolving Model with an Adaptive Vertical Grid Roger Marchand and.
Outline Further Reading: Chapter 04 of the text book - satellite orbits - satellite sensor measurements - remote sensing of land, atmosphere and oceans.
PREFER 1 st Annual Review Meeting, 5-6 Dec 2013, Milano-Italy PREFER WP3.1 - Information Support to Preparedness/Prevention Phase Product: “Daily Fire.
Assessment of the vertical exchange of heat, moisture, and momentum above a wildland fire using observations and mesoscale simulations Joseph J. Charney.
An Earth system satellite mission? Paul Palmer, Claire Bulgin, and Siegfried Gonzi
Chapter 4: How Satellite Data Complement Ground-Based Monitor Data 3:15 – 3:45.
EARTH’S CLIMATE. Latitude – distance north or south of equator Elevation – height above sea level Topography – features on land Water Bodies – lakes and.
Improved representation of boreal fire emissions for the ICARTT period S. Turquety, D. J. Jacob, J. A. Logan, R. M. Yevich, R. C. Hudman, F. Y. Leung,
1 Applications of Remote Sensing: SeaWiFS and MODIS Ocean Color Outline  Physical principles behind the remote sensing of ocean color parameters  Satellite.
Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other.
Maria Val Martin and J. Logan (Harvard Univ., USA) D. Nelson, C. Ichoku, R. Kahn and D. Diner (NASA, USA) S. Freitas (INPE, Brazil) F.-Y. Leung (Washington.
GSFC. Glaciation Level and Vertical Profile of Droplet Size Associated with Cloud-Aerosol Interactions (D. Rosenfeld) Clean Polluted.
Thanks to David Diner, David Nelson and Yang Chen (JPL) and Ralph Kahn (NASA/Goddard) Research funded by NSF and EPA Overview of the 2002 North American.
US Aerosols : Observation from Space, Climate Interactions Daniel J. Jacob and funding from NASA, EPRI, EPA with Easan E. Drury (now at NREL), Loretta.
Future climate change drives increases in forest fires and summertime Organic Carbon Aerosol concentrations in the Western U.S. Dominick Spracklen, Jennifer.
Toward a mesoscale flux inversion in the 2005 CarboEurope Regional Experiment T.Lauvaux, C. Sarrat, F. Chevallier, P. Ciais, M. Uliasz, A. S. Denning,
Pathways for North American Outflow - Hindcast for ICART 2 Qinbin Li, Daniel J. Jacob, Rokjin Park, Colette L. Heald, Yuxuan Wang, Rynda Hudman, Robert.
Pyro-convective smoke plume observed at ~10 km over British Columbia, June 2004 Vertical transport of surface fire emissions observed from space Siegfried.
On contribution of wild-land fires to atmospheric composition M.Prank 1, J. Hakkarainen 1, T. Ermakova 2, J.Soares 1, R.Vankevich 2, M.Sofiev 1 1 Finnish.
Synergy of MODIS Deep Blue and Operational Aerosol Products with MISR and SeaWiFS N. Christina Hsu and S.-C. Tsay, M. D. King, M.-J. Jeong NASA Goddard.
MINX Document 3 MINX – Overview and Plume Case Studies David Nelson Raytheon Company, Jet Propulsion Laboratory, California Institute of Technology May,
Investigation of the Effects of Changing Climate on Fires and the Consequences for U.S. Air Quality, Using a Hierarchy of Chemistry and Climate Models.
Earth’s climate and how it changes
Modeling and Evaluation of Antarctic Boundary Layer
Ray Nassar, Jennifer Logan, Lee Murray, Lin Zhang, Inna Megretskaia Harvard University COSPAR, Montreal, 2008 July Investigating Tropical Tropospheric.
Using CO observations from space to track long-range transport of pollution Daniel J. Jacob with Patrick Kim, Peter Zoogman, Helen Wang and funding from.
Validation of Satellite-derived Clear-sky Atmospheric Temperature Inversions in the Arctic Yinghui Liu 1, Jeffrey R. Key 2, Axel Schweiger 3, Jennifer.
Assimilation of Satellite Derived Aerosol Optical Depth Udaysankar Nair 1, Sundar A. Christopher 1,2 1 Earth System Science Center, University of Alabama.
Climate. Weather: a local area’s short-term temperature, precipitation, humidity, wind speed, cloud cover, and other physical conditions of the lower.
Solène Turquety – AGU fall meeting, San Francisco, December 2006 High Temporal Resolution Inverse Modeling Analysis of CO Emissions from North American.
Characterization of the Station Fire, Los Angeles Aug. – Sept NASA Team MODIS Data products: Robert Levy Lorraine Remer N. Christina Hsu Charles.
Description of the climate system and of its components
NASA Aqua.
Simulation of the Arctic Mixed-Phase Clouds
Horizontally Oriented Ice and Precipitation in Maritime Clouds Using CloudSat, CALIOP, and MODIS Observations Alexa Ross Steve Ackerman Robert Holz University.
evaluation with MOPITT satellite observations for the summer 2004
WindNinja Model Domain/Objective
Hyperspectral Wind Retrievals Dave Santek Chris Velden CIMSS Madison, Wisconsin 5th Workshop on Hyperspectral Science 8 June 2005.
Aura Science Team meeting
Models of atmospheric chemistry
Vertical transport of surface fire emissions observed from space
Wildfire Plume Height Simulations
2019 TEMPO Science Team Meeting
Current Research on 3-D Air Quality Modeling: wildfire!
Fig. 1 Modern dust transport over the North Atlantic basin.
Presentation transcript:

Wildfire Plume Injection Heights Over North America: An Analysis of MISR Observations Maria Val Martin and Jennifer A. Logan (Harvard Univ., USA) Fok-Yan Leung (Washington State Univ., USA) David L. Nelson, Ralph A. Kahn and David J. Diner (NASA) Saulo Freitas (INPE, Brazil) Research funded by NSF and EPA

Wildfire Plume Injection Heights Over North America: An Analysis of MISR Observations Outline: An statistical analysis of aerosol injection heights over North America The use of a 1-D plume-rise model to develop a parameterization of the injection heights of North American wildfire emissions

Multi-angle Imaging SpectroRadiometer- MISR 9 view angles at Earth surface: nadir to 70.5º forward and backward 4 bands at each angle: 446, 558, 672, 866 nm Continuous pole-to-pole coverage on orbit dayside 400-km swath 9 day coverage at equator 2 day coverage at poles Overpass around local noon time in high and mid- latitudes 275 m km sampling In polar orbit aboard Terra since December 1999

Analysis of Fire Plumes: MISR INteractive eXplorer (MINX) ( Cross-section of heights as a function of distance from the source Histogram of heights retrieved by MINX Plume over central Alaska on June 2002

About 3000 plumes digitalized over North America N = N = N = N = N = 690

Plume Distribution and Atmospheric Conditions Meteorological fields from GEOS-4 and GEOS-5 2x2.5 Histogram of Plume Height Retrievals Atmospheric Stability Profile Stable Layer Boundary Layer (BL) Max Avg Median Mode Plume Height? Each individual height

5-30% smoke emissions are injected above the boundary layer Kahn et al, [2008] Distribution of MISR heights-PBL for smoke plumes –25% –15% –28% –18% 2004

Percentage of smoke above BL varies with vegetation type and fire season Vegetation classification based on MODIS IGBP land cover (1x1 km) % Height retrievals with [Height-PBL] > 0.5 km ( Trop Forest Cropland Extra-Trop Forest Boreal Forest Boreal Shrub Non-Bor Shrub Boreal Grass Non-Bor Grass

Kahn et al, [2007] Leung et al, [in prep] 11% 13% 7% 24% 13% Smoke emissions tend to get confined within stable layers in the atmosphere, when they exist Distribution of all individual heights in the FT – Stable Layer MISR Heights – Stable Layer ≈ 0 km

1-D Plume-resolving Model Detailed information in Freitas et al, [2007] Key input parameters: Instant fire size: MODIS fire counts (scaled by max FRP observed over vegetation type [Charles Ichoku, personal communication]) (> 80% fires <25 Ha) Total heat flux: Max MODIS FRP observed over vegetation type x 10 [Wooster et al, 2005] (~ W/m 2 ) RH, T, P, wind speed and direction: from GEOS- 4 meteo fields 2x2.5 Fuel moisture content: from Canadian Fire Weather Model

Simulation of a boreal fire plume in Alaska and a grassland fire plume in Mexico Fire Size= 300 Ha Heat Flux= 18 kW/m 2 Fire Size= 3.8 Ha Heat Flux= 9 kW/m 2 MISR Retrieved Heights MISR Smoke Plume 1D Plume-rise Model Boreal Forest Fire Trop. Grassland Fire

Simulation of a boreal fire plume in Alaska and a grassland fire plume over Mexico Fire Size= 300 Ha Heat Flux= 18 kW/m 2 Fire Size= 3.8 Ha Heat Flux= 9 kW/m 2 MISR Retrieved Heights MISR Smoke Plume 1D Plume-rise Model Boreal Forest Fire Trop. Grassland Fire 6200 m6500 m 600 m 555 m

The 1-D Plume-resolving Model simulates fairly well the observed MISR heights Correlation between simulated plume heights and MISR observed heights over North America

 5-30% of smoke emissions are injected above the BL.  The percentage of smoke that reaches the FT varies with vegetation type and fire season.  When smoke emissions reach the free troposphere, they tend to get trapped in stable layers, if they are present.  1-D plume-resolving model simulates fairly well the observed MISR plume heights.  In the future, we plan to embed the 1-D plume-resolving model with GEOS-Chem to simulate vertical transport of North American wildfire emissions. Concluding Remarks

Extra Slides

The 1D plume-resolving model: Governing equations dynamics thermodynamics water vapor conservation bulk microphysics cloud water conservation rain/ice conservation

The 1D plume-resolving model: The lower boundary conditions