GEO-CAPE Atmosphere SWG activities Daniel J. Jacob Co-Lead, GEO-CAPE Atmosphere Science Working Group

The SWG defines mission requirements, evaluates implementation options Science Traceability Matrix (STM) Science Value Matrix (SVM) Weiss et al., IEEAC 2004 GEO-CAPE also has an Applications Traceability Matrix (ATM) and corresponding Applications Value Matrix (AVM) STM leads: Doreen Neil. Daniel Jacob SVM leads: Doreen Neil, David Edwards ATM/AVM leads: Jessica Neu, Rob Pinder

Science Questions for GEO-CAPE - Atmosphere What are the temporal and spatial variations of emissions of gases and aerosols important for air quality and climate? How do physical, chemical, and dynamical processes determine tropospheric composition and air quality over scales ranging from urban to continental, diurnal to seasonal? 3. How does air pollution drive climate forcing and how does climate change affect air quality on a continental scale? 4. How do we improve air quality forecasts and assessments for societal benefit? 5. How does intercontinental transport affect air quality? 6. How do episodic events such as wild fires, dust outbreaks, and volcanic eruptions affect atmospheric composition and air quality? Fishman et al. [2012]

Measurement requirements for GEO-CAPE: spectral regions and precision Species Precision Rationale O3 Stratosphere: 5% 2 km-tropopause: 15 ppb 0-2 km: 10 ppb Surface AQ, transport, climate forcing CO 2 km – tropopause: 20 ppb 0-2 km: 20 ppb CO emission, transport Aerosol 0.05 (AOD) Surface AQ, aerosol sources and transport, climate forcing NO2 1x1015 cm-2 NOx emissions, chem. HCHO 1x1016 cm-2 VOC emissions, chem. SO2 SOx emissions, chem. CH4 Troposphere: 20 ppb CH4 emissions NH3 0-2 km: 2 ppb NH3 emissions CHOCHO 4x1014 cm-2 VOC emissions, chem., aerosol formation Absorbing aerosol 0.02 (AAOD) Climate forcing Aerosol index 0.1 Aerosol events Aerosol centroid height 1 km Aerosol plume height, large-scale transport, AOD to PM conversion

Measurement requirements for GEO-CAPE: viewing geometry, resolution, frequency Orbit centered over ~100o W, observing domain north of 10o N Hourly data over land/coastlines with pixel resolution of 1x1 km2 (aerosols), 4x4 km2 (gases), for SZA<70o (some species), <50o (others) Daily data over open oceans (O3, CO, aerosol) with pixel resolution of 16x16 km2 Observing domain

What do TEMPO selection and geostationary constellation mean for achieving GEO-CAPE goals? TEMPO (UV/Vis) will monitor tropospheric ozone (2 levels), aerosols, NO2, SO2, formaldehyde, glyoxal with 1-hour temporal resolution, 4x2 km2 spatial resolution TEMPO will be part of a geostationary constellation with other sensors observing Europe and East Asia Kelly Chance, PI Next frontier in satellite observations of atmospheric composition! TEMPO Sentinel-4 GEMS

Mapping of TEMPO on the GEO-CAPE Science Value Matrix GCIRI addition Doreen Neil, NASA LaRC TEMPO delivers 70% of GEO-CAPE science; A concurrent GEO-CAPE IR Instrument (GCIRI) can deliver the other 30% Preliminary mapping on the Applications Value Matrix has similar results

Current role of the GEO-CAPE Atmosphere SWG Evaluate TEMPO capabilities, develop science +application products for TEMPO Assess value of different GCIRI additions to TEMPO Develop value of constellation for mission science Four reconstituted WGs for FY13: Working Grouo Chairs Motivating question Aerosols Mian Chin, Jun Wang What can TEMPO really do for aerosols, and is there a measurement need beyond TEMPO+GOES-R? Emissions Daven Henze, Greg Frost How well can TEMPO and GCIRI constrain emissions? Urban/Regional OSSE Brad Pierce, Kevin Bowman How well can TEMPO and GCIRI inform urban-scale and regional AQ? Global OSSE David Edwards, Arlindo daSilva How well can TEMPO and GCIRI inform continental-scale atmospheric composition, and how can we best exploit the constellation?

Observing System Simulation Experiment (OSSE) How can knowledge of a state x be improved by the proposed measurement of y? We need three models: CTM 1 y = F1(x) defines the “true” atmosphere (Nature Run) CTM 2 y = F2(x) +  is the forward model (Control Run) Instrument model describes measurement of y including smoothing, noise Model 1 Instrument model “True” x “True” y “Measured” y’ Prior estimate xA ± SA Model 2 Data assimilation Compare x’ ± S’ to x and to xA ± SA : Is the measurement worth it? improved estimate x’ ± S’ Good error characterization for instrument model Independence of Model 1 and Model 2 Realistic atmospheric variability in Model 1 State of science for Model 2 A reliable OSSE requires:

Global OSSE WG Foci: Improve realism of GEO-CAPE OSSEs Demonstrate value of constellation GEOS-5 10-km resolution “true” atmosphere with aerosols, chemistry (Arlindo daSilva, NASA) ECMWF workshop, Oct 2012 Spread in MOPITT AKs for surface & 500 hPa CO retrievals (CONUS) Improving instrument models: variability of averaging kernel matrix for MOPITT CO (Worden et al., 2013)

Urban/Regional OSSE WG Foci: Continuation of regional OSSE development initiated in FY12 Initiation of urban OSSE for GEOCAPE multi-spectral ozone retrievals. Atlanta ozone (CMAQ) “True” regional and urban atmospheres generated Aerosol extinction, surface reflectance, variable AK matrices included for more realistic instrument modeling Atlanta surface reflectance, different times of day Atlanta aerosol extinction (CMAQ)

Emissions WG Focus: Assess GEO-CAPE constraints on emissions of NOx, VOCs, NH3, aerosols Can we detect doubling of CH4 emissions from natural gas in western US? Step 1: Perturb model natural gas emissions by 2x in west. Step 3: Assimilate pseudo-obs into GEOS-Chem adjoint inversion Perturbed/prior emissions GEOS-Chem CTM “Observed” enhancement GEOS-Chem Adjoint 1.0 1.0 2.0 2.0 -1.0 [ppb] 1.0 1.0 Step 2: Sample model as GEOCAPE OSSE Observation Platform Error reduction in perturbed region Error reduction in North America GEOCAPE 88 % 96 % TES-like LEO 8 % 93 % 0.75 0.0 200 1000 Pressure [hpa] Rows of GEOCAPE averaging kernel matrix GEOS-Chem CTM 0.1 hPa 954 hPa . Only GEOCAPE locates emissions correctly

Aerosols WG ln(Io/I) Foci: Improve understanding of TEMPO capabilities Assess added value from concurrent GOES-R observations Aerosol retrieval availability (April 10, 2012) Fraction clear sky 1x1 km (GEO-CAPE) 4x2 km (TEMPO) σ < 0.0025 σ < 0.005 σ < 0.01 a b c 1x1 km2 MODIS cloud criteria TEMPO 4x2 km2 relaxed cloud criteria Satellite simulator for geo aerosol OSSEs ln(Io/I) Successful mapping w/TEMPO will require relaxed cloud criteria