Nested Global and Regional aerosol and ozone assimilation and forecasting experiments during the NOAA CalNex field mission R. Bradley Pierce 1, Todd Schaack.

Slides:



Advertisements
Similar presentations
MOPITT CO Louisa Emmons, David Edwards Atmospheric Chemistry Division Earth & Sun Systems Laboratory National Center for Atmospheric Research.
Advertisements

Satellite based estimates of surface visibility for state haze rule implementation planning Air Quality Applied Sciences Team 6th Semi-Annual Meeting (Jan.
CO budget and variability over the U.S. using the WRF-Chem regional model Anne Boynard, Gabriele Pfister, David Edwards National Center for Atmospheric.
GEOS-5 Simulations of Aerosol Index and Aerosol Absorption Optical Depth with Comparison to OMI retrievals. V. Buchard, A. da Silva, P. Colarco, R. Spurr.
Quantifying uncertainties of OMI NO 2 data Implications for air quality applications Bryan Duncan, Yasuko Yoshida, Lok Lamsal, NASA OMI Retrieval Team.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Figure 1: August 2006 RAQMS and Observed TOC Figure 2: September 2 nd,
Integrating satellite observations for assessing air quality over North America with GEOS-Chem Mark Parrington, Dylan Jones University of Toronto
Transpacific transport of pollution as seen from space Funding: NASA, EPA, EPRI Daniel J. Jacob, Rokjin J. Park, Becky Alexander, T. Duncan Fairlie, Arlene.
Predictability study using the Environment Canada Chemical Data Assimilation System Jean de Grandpré Yves J. Rochon Richard Ménard Air Quality Research.
Objective: Work with the WRAP, CenSARA, CDPHE, BLM and EPA Region 8 to use satellite data to evaluate the Oil and Gas (O&G) modeled NOx emission inventories.
Evaluation of Real-time Air Quality Forecasts from WRF-NMM/CMAQ and NMMB/CMAQ Using Discover-AQ P-3B Airborne Measurements Youhua Tang 1,2, Jeffery T.
Understanding the Influence of Biomass Burning on Tropospheric Ozone through Assimilation of TES data Jennifer Logan Harvard University Dylan Jones, Mark.
Assimilation of EOS-Aura Data in GEOS-5: Evaluation of ozone in the Upper Troposphere - Lower Stratosphere K. Wargan, S. Pawson, M. Olsen, J. Witte, A.
ANTHROPOGENIC AND VOLCANIC CONTRIBUTIONS TO THE DECADAL VARIATIONS OF STRATOSPHERIC AEROSOL Mian Chin, NASA Goddard Space Flight Center Plus: Thomas Diehl,
Aircraft spiral on July 20, 2011 at 14 UTC Validation of GOES-R ABI Surface PM2.5 Concentrations using AIRNOW and Aircraft Data Shobha Kondragunta (NOAA),
Visualization, Exploration, and Model Comparison of NASA Air Quality Remote Sensing data via Giovanni Ana I. Prados, Gregory Leptoukh, Arun Gopalan, and.
NASA Air Quality Remote Sensing Training LADCO, Madison, Wisconsin March 12 – 15, 2011 Model and Satellite comparison overview R. Bradley Pierce NOAA/NESDIS/STAR.
Developing a High Spatial Resolution Aerosol Optical Depth Product Using MODIS Data to Evaluate Aerosol During Large Wildfire Events STI-5701 Jennifer.
Chemical and Aerosol Data Assimilation Activities during CalNex R. Bradley Pierce NOAA/NESDIS/STAR Allen Lenzen 1, Todd Schaack 1, Tom Ryerson 2, John.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Tropospheric Emission Spectrometer Case Study.
1 Satellite data assimilation for air quality forecast 10/10/2006.
The Use of Current and Future Hyperspectral Trace Gas Retrievals in Atmospheric Chemistry Research at NOAA R. Bradley Pierce NOAA/NESDIS/STAR Collaborators:
AGU 2002 Fall Meeting NASA Langley Research Center / Atmospheric Sciences Validation of GOES-8 Derived Cloud Properties Over the Southeastern Pacific J.
AN ENHANCED SST COMPOSITE FOR WEATHER FORECASTING AND REGIONAL CLIMATE STUDIES Gary Jedlovec 1, Jorge Vazquez 2, and Ed Armstrong 2 1NASA/MSFC Earth Science.
Studies of Emissions & Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) Brian Toon Department of Atmospheric and Oceanic.
Significant contributions from: Todd Schaack and Allen Lenzen (UW-Madison, Space Science and Engineering Center) Mark C. Green (Desert Research Institute)
MELANIE FOLLETTE-COOK KEN PICKERING, PIUS LEE, RON COHEN, ALAN FRIED, ANDREW WEINHEIMER, JIM CRAWFORD, YUNHEE KIM, RICK SAYLOR IWAQFR NOVEMBER 30, 2011.
Evaluating ammonia (NH 3 ) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in situ aircraft measurements William Battye,
Variational Assimilation of MODIS AOD using GSI and WRF/Chem Zhiquan Liu NCAR/NESL/MMM Quanhua (Mark) Liu (JCSDA), Hui-Chuan Lin (NCAR),
Source-Specific Forecasting of Air Quality Impacts with Dynamic Emissions Updating & Source Impact Reanalysis Georgia Institute of Technology Yongtao Hu.
Global Observing System Simulation Experiments (Global OSSEs) How It Works Nature Run 13-month uninterrupted forecast produces alternative atmosphere.
Melanie Follette-Cook Christopher Loughner (ESSIC, UMD) Kenneth Pickering (NASA GSFC) CMAS Conference October 27-29, 2014.
1 JRA-55 the Japanese 55-year reanalysis project - status and plan - Climate Prediction Division Japan Meteorological Agency.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Infrared Temperature and.
Near-Real-Time Simulated ABI Imagery for User Readiness, Retrieval Algorithm Evaluation and Model Verification Tom Greenwald, Brad Pierce*, Jason Otkin,
Characterization of Aerosols using Airborne Lidar, MODIS, and GOCART Data during the TRACE-P (2001) Mission Rich Ferrare 1, Ed Browell 1, Syed Ismail 1,
Goal: “What are the sources and physical mechanisms that contribute to high ozone concentrations aloft that have been observed in Central and Southern.
CARB Board Meeting San Diego, 23 July 2009 DAVID PARRISH Chemical Sciences Division Earth System Research.
OMPS Products Applications Craig Long NOAA/NWS/NCEP Climate Prediction Center SUOMI NPP SDR Product Review -- 23/24 October NCWCP Auditorium.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Tropospheric Emission Spectrometer Studying.
Comparison of NOAA/NCEP 12km CMAQ Forecasts with CalNEX WP-3 Measurements Youhua Tang 1,2, Jeffery T. McQueen 2, Jianping Huang 1,2, Marina Tsidulko 1,2,
MACC-II analyses and forecasts of atmospheric composition and European air quality: a synthesis of observations and models Richard Engelen & the MACC-II.
Tianfeng Chai 1,2, Hyun-Cheol Kim 1,2, Daniel Tong 1,2, Pius Lee 2, Daewon W. Byun 2 1, Earth Resources Technology, Laurel, MD 2, NOAA OAR/ARL, Silver.
Jetstream 31 (J31) in INTEX-B/MILAGRO. Campaign Context: In March 2006, INTEX-B/MILAGRO studied pollution from Mexico City and regional biomass burning,
1 RAQMS-CMAQ Atmospheric Chemistry Model Data for the TexAQS-II Period : Focus on BCs impacts on air quality simulations Daewon Byun 1, Daegyun Lee 1,
This report presents analysis of CO measurements from satellites since 2000 until now. The main focus of the study is a comparison of different sensors.
Chemical Data Assimilation: Aerosols - Data Sources, availability and needs Raymond Hoff Physics Department/JCET UMBC.
Airborne Sunphotometry and Closure Studies during the SAFARI-2000 Dry Season Campaign B. Schmid BAER/NASA Ames Research Center, Moffett Field, CA, USA.
Analysis of TES Observations from the 2006 TexAQS/GoMACCS Campaign Greg Osterman, Kevin Bowman Jet Propulsion Laboratory California Institute of Technology.
MOPITT and MOZART for Flight Planning and Analysis of INTEX-B Louisa Emmons Peter Hess, Avelino Arellano, Gabriele Pfister, Jean-François Lamarque, David.
Breakout Session 1 Air Quality Jack Fishman, Randy Kawa August 18.
Global Aerosol Forecasting System Applications to Houston/Costa Rica Aura Validation Experiments Arlindo da Silva Global Modeling and Assimilation Office,
TES and Surface Measurements for Air Quality Brad Pierce 1, Jay Al-Saadi 2, Jim Szykman 3, Todd Schaack 4, Kevin Bowman 5, P.K. Bhartia 6, Anne Thompson.
A Brief Overview of CO Satellite Products Originally Presented at NASA Remote Sensing Training California Air Resources Board December , 2011 ARSET.
A study of process contributions to PM 2.5 formation during the 2004 ICARTT period using the Eta-CMAQ forecast model over the eastern U.S. Shaocai Yu $,
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS SURFACE PRESSURE MEASUREMENTS FROM THE ORBITING CARBON OBSERVATORY-2.
NASA, CGMS-43, May 2015 Coordination Group for Meteorological Satellites - CGMS Use of Satellite Observations in NASA Reanalyses: MERRA-2 and Future Plans.
A Study of Variability in Tropical Tropospheric Water Vapor Robert L. Herman 1, Robert F. Troy 2, Holger Voemel 3, Henry B. Selkirk 4, Susan S. Kulawik.
Climate, Meteorology and Atmospheric Chemistry.
Assessment of Upper atmospheric plume models using Calipso Satellites and Environmental Assessment and Forecasting Chowdhury Nazmi, Yonghua Wu, Barry Gross,
Impact of OMI data on assimilated ozone Kris Wargan, I. Stajner, M. Sienkiewicz, S. Pawson, L. Froidevaux, N. Livesey, and P. K. Bhartia   Data and approach.
The study of cloud and aerosol properties during CalNex using newly developed spectral methods Patrick J. McBride, Samuel LeBlanc, K. Sebastian Schmidt,
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Development of a visibility retrieval for the GOES-R Advanced Baseline.
Literature Review: Impacts of background ozone production on Houston and Dallas, TX Air Quality during the TexAQS field mission R. Bradley Pierce (NOAA/NESDIS),
Vertically resolved CALIPSO-CloudSat aerosol extinction coefficient in the marine boundary layer and its co-variability with MODIS cloud retrievals David.
Regional O3 OSSEs Brad Pierce (NOAA)
During April 2008, as part of the International Polar Year (IPY), NOAA’s Climate Forcing and Air Quality Programs engaged in an airborne field measurement.
Evaluation of the MERRA-2 Assimilated Ozone Product
Satellite data assimilation for air quality forecast
Off-line 3DVAR NOx emission constraints
Presentation transcript:

Nested Global and Regional aerosol and ozone assimilation and forecasting experiments during the NOAA CalNex field mission R. Bradley Pierce 1, Todd Schaack 2, Allen Lenzen 2, Pius Lee 3, Tom Ryerson 4, Ilana Pollack 4,Owen Cooper 4, Chris Hostetler 5, Rich Ferrare 5, David Winker 5 Ilana Pollack 4,Owen Cooper 4, Chris Hostetler 5, Rich Ferrare 5, David Winker 5 1 NOAA/NESDIS/STAR Advanced Satellite Products Branch, Madison WI 2 UW-Madison Space Science and Engineering Center, Madison, WI 3 NOAA ARL, Silver Spring, MD 4 NOAA ESRL Chemical Sciences Division, Boulder, CO 5 NASA Langley Research Center, Hampton, VA

During May-June 2010 the National Oceanic and Atmospheric Administration (NOAA) and the California Air Resources Board (CARB), conducted a joint field study of atmospheric processes over California and the eastern Pacific coastal region called CalNex emphasizing the interactions between air quality and climate change issues. NOAA WP-3D Flight Track Map NOAA CalNex Field Mission

Online global chemical and aerosol assimilation/forecasting system This talk presents results from post mission studies focused on: 1)Evaluation of the RAQMS large-scale ozone and aerosol analyses using airborne, ground based, and satellite measurements during CalNex 2)Evaluation of the RAQMS large-scale ozone and aerosol forecast skill. 3)Nested RAQMS/WRF-CHEM aerosol assimilation studies 4)Nested RAQMS/NAM-CMAQ ozone assimilation studies Real-time assimilation: Microwave Limb Sounder (MLS) stratospheric ozone profiles (above 50mb) Ozone Monitoring Instrument (OMI) total ozone column (cloud cleared) Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) Real-time fire detection: Moderate Resolution Imaging Spectroradiometer (MODIS)

CalNex-2010 O 3 sondes – Owen Cooper (NOAA ESRL) RAQMS NO ASSIM is low biased up to 30% of Ozonesonde CalNex Ozonesonde NO ASSIM Tropospheric low bias

CalNex-2010 O 3 sondes – Owen Cooper (NOAA ESRL) RAQMS MLS+OMI analysis is within 20% of Ozonesonde CalNex Ozonesonde MLS+OMI ASSIM Reduced tropospheric bias

Comparison with NOAA P3 Insitu O3 Measurements (Primarily LA Basin/Central Valley) Assimilation of MLS+OMI O3 retrievals results in increased lower-tropospheric O3 (and improved agreement with airborne insitu O3) over Southern California No AssimMLS+OMI Assim Insitu O3 from Tom Ryerson, NOAA ESRL

V3-01 aerosol profile retrievals 5 o Lat, 10 o Lon, 1km bins CAD< -20, COT=0.0 QC=0,1 (unadjusted retrievals) New 1x1 degree Re-analysis with Corrected dust and Sea-salt aod calculation CALIPSO and Co-located RAQMS AOD May-June 2010 Clear sky CALIPSO scenes are dominated by Saharan Dust and South Asian emissions during May-June 2010 RAQMS overestimates Saharan Dust and SE Asian and S African biomass burning AOD relative to CALIPSO during May-June 2010 Dave Winker, NASA LaRC

1x1 Degree Re-analysis

RAQMS 1x1 Degree Re-analysis Captures Structure of Dust Plume very well CALIPSO vs. RAQMS Extinction 13:52Z 06/01/2010

CALIPSO vs. RAQMS Extinction 03:12Z 06/01/2010 RAQMS 1x1 Degree Re-analysis Captures Structure of Dust Plume Very well

RAQMS 1x1 Degree Re-analysis underestimates Dust Extinction away from source CALIPSO vs. RAQMS Extinction 04:51Z 06/01/2010

V3-01 aerosol profile retrievals 5 o Lat, 10 o Lon, 1km bins CAD< -20, COT=0.0 QC=0,1 (unadjusted retrievals) New 1x1 degree Re-analysis with Corrected dust and Sea-salt aod calculation CALIPSO and Co-located RAQMS AOD May-June 2010 Clear sky CALIPSO scenes are dominated by Saharan Dust and South Asian emissions during May-June 2010 RAQMS overestimates Saharan Dust and SE Asian and S African biomass burning AOD relative to CALIPSO during May-June 2010 Dave Winker, NASA LaRC

Comparison with HSRL Lidar Measurements (Primarily LA Basin, Chris Hostetler, NASA LaRC) RAQMS free tropospheric median aerosol extinction is in very good agreement with HSRL Variability is underestimated, particularly for lower values of aerosol extinction Largest biases are found within the LA Basin Boundary Layer (below 1000m) were RAQMS median extinction is low

Assessment of Global 850mb O3 and Aerosol Extinction Forecast Skill Anomaly Correlations (AC) Correlation between forecast and analysis May-June mean removed Spectrally truncated to wavenumber 20 Averaged from 20N-80N useful Skill

Northern Hemisphere 850mb May-June 2010 Anomaly Correlations (AC) (No Assimilation) useful Skill 850mb ozone forecasts have useful skill past 3 days (significantly better than water vapor) 850mb extinction forecasts do not have useful skill at 1 day

Northern Hemisphere 850mb May-June 2010 Anomaly Correlations (AC) (With MLS/OMI/MODIS Assimilation) useful Skill Assimilation of O3 retrievals results in slight improvements in 850mb ozone forecasts Assimilation of AOD retrievals results in significant improvement in 850mb extinction forecasts with useful skill at ~1.5 days

useful Skill Northern Hemisphere 850mb May-June 2010 Anomaly Correlations (AC) (No Assimilation) Only 850mb SO4 extinction forecasts useful skill past 1 day Black and organic carbon (BC+OC) and dust extinctions are both poorly initialized and forecasted

Northern Hemisphere 850mb May-June 2010 Anomaly Correlations (AC) (With MODIS Assimilation) useful Skill MODIS AOD assimilation results in small changes in 850mb SO4 extinction forecasts MODIS AOD assimilation results in significant improvements in black and organic carbon (BC+OC) and dust forecast skill (dust prediction useful at 2 days)

12km WRF-CHEM 00Z-24Z May 31 st, 2010 RAQMS/WRF-CHEM May-June 2010 aerosol analysis GOCART aerosol module, MODIS AOD assimilation, Two nests: 36km and 12km

WRF-CHEM 12km (NO ASSIM) vs Aeronet Note: need to cloud clear WRF-CHEM analysis to account for miss match between observed and predicted clouds

MODIS AOD assimilation does not have a significant impact on regional scale AOD over CONUS during May-June 2010 Assimilation results in slight reduction in correlation and slight increase in RMS error WRF-CHEM 12km (MODIS ASSIM) vs Aeronet

Development of GOES Total Column Ozone Assimilation Within Operational NAM-CMAQ We currently developing capabilities to assimilate GOES Sounder TCO retrievals into the Community Multi-scale Air Quality (CMAQ; model.org/) model using the NCEP Grid-point Statistical Interpolation (GSI) analysis scheme. model.org/ GOES provides hourly TCO during day and night. OMI daytime TCO is used for bias correction

Three NAM-CMAQ/GOES TCO Experiments have been conducted: RAQMS Lateral Boundary Conditions/default background errors Fixed Lateral Boundary Conditions/default background errors Fixed Lateral Boundary Conditions+GFS UT/LS/GFS background errors Fixed LBC underestimates TCO, Fixed LBC+GFS UT/LS overestimates TCO

RAQMS LBC Default Background Errors FIXED LBC Default Background Errors FIXED LBC +GFS UT/LS GFS Background Errors CalNex-2010 O 3 sondes – Owen Cooper (NOAA ESRL) CalNex Ozonesonde RAQMS LBC and default background errors results in free tropospheric overestimates but good PBL and UT/LS FIXED LBC and default background errors results in free tropospheric and PBL overestimates with UT/LS underestimates FIXED LBC+GFS UT/LS and GFS background errors results in best agreement with IONS ozonesonde

Current Directions Work with NOAA Air Resources Lab and the National Air Quality Forecasting Capability team to test impact of improved vertical resolution on GOES TCO assimilation within NMMB-CMAQ Work with NASA Air Quality Applied Science Team to implement 3D tropospheric POX/LOX within GFS to provide improved time-dependent lateral boundary conditions to NMMB-CMAQ Evaluate the relative impacts of IASI ozone profile and ozone band radiance assimilation on GFS tropospheric ozone distributions Focus on NASA DISCOVER-AQ mission timeframe (July 2011)

I would like to acknowledge Dr. Daewon Byun’s personal contribution to this effort. He conducted the first experiments on assimilation of GOES TCO within CMAQ nearly a decade ago, and always provided enthusiastic support for using satellite measurements to improve regional air quality predictions Benchmark Study conducted in collaboration with EPA/ORD (Alice Gilliland, Ken Schere) and the University of Houston Institute for Multidimensional Air Quality Studies (Daewon Byun)