Using NOAA observations for TEMPO validation and applications

Transcription

1 Satellite Data Analysis Global Observation Network Aircraft Observatories Using NOAA observations for TEMPO validation and applications Sondes Ships Earth System Modeling Data Assimilation Mobile Laboratories Wind Profilers Instrumented Ground Sites Greg Frost Laboratory Analysis Tall Towers NOAA Earth System Research Laboratory Boulder, Colorado Acknowledgments: Brian McDonald, Si-Wan Kim, Carsten Warneke, Dan Murphy, Drew Rollins, Andy Langford, Stuart McKeen, Li Zhang, Tom Ryerson Western U.S. TEMPO Early Adopters Workshop, April 2018

2 NOAA Earth System Research Laboratory Field Campaigns (since 2000) FIREX ( ) ITCT (2002) UWFPS (2017) SONGNEX (2015) ICARTT (2004) CALNEX (2010) SENEX (2013) TEXAQS (2000, 2006)

3 ESRL approach to satellite validation Field observations calibrate chemical-transport models Sant a Clarit a Aircraft NO2 5 / 1 9 / ( Wed) NOAA P3 Obs. Burbank N Main St Upland Font ana San Bernadino 8 Pomona VA Hospit al Pico Rivera 12 6 Reseda Azusa N Main St Upland La Habra Riverside Pico Rivera La Habra 2 N Long Beach San Bernadino Mira Loma West chest er ParkWay Compt on Banning Airport Font ana Pomona VA Hospit al Glendora Pasadena 4 West chest er ParkWay Compt on 12 Burbank Mira Loma 14 NO2 ( ppbv) Azusa 5 / 1 9 / ( Wed) WRF-Chem 10 Glendora Pasadena Model NO2 Sant a Clarit a NO2 ( ppbv) Reseda Riverside Banning Airport 2 N Long Beach Long Beach Long Beach Cost a Mesa Cost a Mesa Lake Elsinore Lake Elsinore Kim et al., JGR, 2016 Model then simulates NO2 columns at TEMPO resolution Pasadena Fontana LAX Ontario Riverside 08 PST 17 PST Irvine (1015 molec. cm-2) Si-Wan Kim et al. While aircraft data provide reliable measures of tropospheric composition, their sampling is sparse relative to that of TEMPO Use aircraft data to evaluate and improve model simulations Then use model to simulate columns for comparison to TEMPO

4 Resolution = 10 km Approx. OMI resolution Los Angeles Basin mobile source CO 2 emissions from fuel-based inventory Mobile source NO x emissions have a similar spatial pattern to those of CO 2 McDonald et al. (J. Geophys. Res. 2014)

5 Resolution = 1 km TEMPO with oversampling Los Angeles Basin mobile source CO 2 emissions from fuel-based inventory Mobile source NO x emissions have a similar spatial pattern to those of CO 2 TEMPO s high spatial resolution will allow it to resolve emission sources, including urban areas and roadways TEMPO will provide constraints on inventory emission magnitudes, spatial allocation, and possibly even sector partitioning McDonald et al. (J. Geophys. Res. 2014)

6 Day of week variations NO 2 Column (cm -2 ) Selected Western US Cities SCIAMACHY NO2 (U. Bremen), May-Sept NOAA analysis of satellite retrievals demonstrates weekday-weekend modulation in urban NOx emissions TEMPO will be able to produce similar plots for North American urban areas in a few weeks, rather than after months or years of data averaging Thu Fri Sat Sun Mon Tue Wed Kim, S.-W., et al. (2009) J. Geophys. Res.

7 Long-Term Trends in Total U.S. NO x Emissions Consistent with literature Anderson et al., Atmos. Env Travis et al., Atmos. Chem. Phys FIVE = Fuel-based Inventory of motor Vehicle Emissions (McDonald et al. JGR 2012; ES&T 2013) TEMPO will provide independent validation of inventory improvements TEMPO will benefit from process-based understanding of emissions

8 High-resolution retrievals require high-resolution inputs Quantify high-resolution inputs to air mass factor: vertical profiles, terrain height Use field campaign data and regional model to understand sensitivities Ratio of HCHO AMFs = Default AMF/WRF-Chem AMF Ratio of AMFs Si-Wan Kim TEMPO will benefit from high-resolution modeling calibrated by aircraft data

9 Evaluating NOAA Global Model with ATom Pole-to-Pole Profiles L. Zhang, G. Grell, R. Ahmadov, S. McKeen, K. Froyd, J. Schwarz, D. Murphy, C. Sweeney, K. McKain, T. Ryerson 8/15/16 NASA s Atmospheric Tomography Mission is conducting continuous poleto-pole profiling from 0.2 to 12 km altitude in 4 seasons between 2016 and ATom data are used to assess performance of models within NOAA s NGGPS (Next Generation Global Prediction System) CO 8/17/16 Preliminary Aircraft Data FIM/Chem Model Pole-to-pole sampling provides excellent evaluation opportunities for GEO constellation products and validation of the global models used for GEO retrievals. THESE ARE PRELIMINARY DATA FROM THE ATMOSPHERIC TOMOGRAPHY MISSION THAT HAVE BEEN MADE AVAILABLE TO FACILITATE SCIENTIFIC ASSESSMENT. THESE DATA HAVE NOT COMPLETED POST-MISSION CHECKS FOR QUALITY ASSURANCE/QUALITY CONTROL (QA/QC) AND FINAL CALIBRATIONS. BY DOWNLOADING THESE DATA, THE USER AGREES THAT THESE PRELIMINARY DATA MAY NEVER BE USED OR PUBLISHED IN ARCHIVAL MEDIA SUCH AS JOURNALS OR MEETING PROCEEDINGS. ARCHIVAL PUBLICATIONS MUST USE ONLY PUBLIC RELEASE DATA THAT HAVE COMPLETED QA/QC. PUBLIC RELEASE OF ATOM DATA IS ANTICIPATED WITHIN 12 MONTHS AFTER EACH PHASE OF THE ATOM PROJECT.

10 Fire Influence on Regional and Global Environments Experiment and Air Quality (FIREX-AQ) NOAA/NASA Interagency Intensive Study of North American Fires August-September 2019 Emissions Smoke transport Chemical transformations Air quality forecasting Satellite advancements DC-8 range from Boise, ID DC-8 range from Salina, KS Twin Otter range from Boise, ID Carsten Warneke, Barry Lefer TEMPO will be a critical tool for mission planning/ forecasting and analysis of data from these or future experiments

11 Frequency Aircraft aerosol measurements leading to better satellite retrievals D. Murphy, G. Adler, C. Brock, F. Erdesz, K. Froyd, K. Manfred, A. Middlebrook, M. Richardson, N. Wagner, C. Williamson Development of new aerosol instrumentation and deployment in aircraft missions provides systematic measurements of intensive properties needed for aerosol retrievals: - single scattering albedo - ambient to dry extinction - scattering phase function - size distribution modes and widths Comparing different instruments US boundary layer Ratio of ambient to dry extinction Factor of 5 NOAA aerosol instrumentation could contribute to TEMPO calibration, validation and algorithm development

12 New ESRL SO 2 Measurements VIRGAS (Volcano-plume Investigation Readiness and Gas-phase and Aerosol Sulfur) 2015: NASA WB-57 aircraft experiment with NOAA SO 2 measurements in UTLS (upper troposphere/lower stratosphere) Changes understanding of sulfur sources, aides in satellite data evaluation, and presents implications for design of climate intervention scenarios TEMPO SO 2 would benefit from validation by NOAA aircraft instrument A. W. Rollins et al., Geophys. Res. Lett., 2017 Less UTLS SO 2 than some climate models or satellite retrievals suggest

13 Backup slides

14 TEMPO offers enhanced information about atmospheric composition and chemical processes compared with LEO platforms Kelly Chance and Jay Al-Saadi Fishman et al., BAMS, 2008 TEMPO s hourly sampling and high spatial resolution will enable it to Evaluate emission sources and chemical processes in unprecedented ways Resolve daytime cycles in emissions and chemistry Improve detection of lower frequency variations in emissions and processes

15 TEMPO in global GEO monitoring constellation TEMPO Sentinel-4 GEMS Spatial coverage of funded GEO spectrometers Courtesy Jhoon Kim, Andreas Richter Policy-relevant science and environmental services enabled by common observations Improved emissions at common confidence levels over Northern Hemisphere Improved air quality forecasts and assimilation systems Improved assessment of impacts

16 Mobile Source NO x Reductions Concentrated in Cities TEMPO s high resolution is ideal for evaluating inventories in cities Total U.S. NO x emissions decreases by ~15% TEMPO could help constrain sectorspecific emissions estimates in inventories Brian McDonald, in prep

17 Ozone Exceedance Days Sensitive to Mobile Source NO x Emissions Bias in summer 2013 O 3 exceedance days (>70 ppb) modeled with NEI 2011 vs. AQS data FIVE is better FIVE is worse Brian McDonald, in prep