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

2. 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

3. Science Questions for GEO-CAPE - Atmosphere 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? 1.What are the temporal and spatial variations of emissions of gases and aerosols important for air quality and climate? 2.How do physical, chemical, and dynamical processes determine tropospheric composition and air quality over scales ranging from urban to continental, diurnal to seasonal? Fishman et al. [2012]

4. Measurement requirements for GEO-CAPE: spectral regions and precision SpeciesPrecisionRationale O3O3 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 Aerosol0.05 (AOD)Surface AQ, aerosol sources and transport, climate forcing NO 2 1x10 15 cm -2 NO x emissions, chem. HCHO1x10 16 cm -2 VOC emissions, chem. SO 2 1x10 16 cm -2 SO x emissions, chem. CH 4 Troposphere: 20 ppbCH 4 emissions NH 3 0-2 km: 2 ppbNH 3 emissions CHOCHO4x10 14 cm -2 VOC emissions, chem., aerosol formation Absorbing aerosol0.02 (AAOD)Climate forcing Aerosol index0.1Aerosol events Aerosol centroid height 1 kmAerosol plume height, large-scale transport, AOD to PM conversion

5. Orbit centered over ~100 o W, observing domain north of 10 o N Hourly data over land/coastlines with pixel resolution of 1x1 km 2 (aerosols), 4x4 km 2 (gases), for SZA<70 o (some species), <50 o (others) Daily data over open oceans (O 3, CO, aerosol) with pixel resolution of 16x16 km 2 Observing domain Measurement requirements for GEO-CAPE: viewing geometry, resolution, frequency

6. What do TEMPO selection and geostationary constellation mean for achieving GEO-CAPE goals? TEMPO (UV/Vis) will monitor tropospheric ozone (2 levels), aerosols, NO 2, SO 2, formaldehyde, glyoxal with 1-hour temporal resolution, 4x2 km 2 spatial resolution TEMPO will be part of a geostationary constellation with other sensors observing Europe and East Asia TEMPO Sentinel-4 GEMS Next frontier in satellite observations of atmospheric composition! Kelly Chance, PI

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

8. Current role of the GEO-CAPE Atmosphere SWG 1.Evaluate TEMPO capabilities, develop science +application products for TEMPO 2.Assess value of different GCIRI additions to TEMPO 3.Develop value of constellation for mission science Four reconstituted WGs for FY13: Working Grouo ChairsMotivating question AerosolsMian Chin, Jun Wang What can TEMPO really do for aerosols, and is there a measurement need beyond TEMPO+GOES-R? EmissionsDaven 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 OSSEDavid Edwards, Arlindo daSilva How well can TEMPO and GCIRI inform continental-scale atmospheric composition, and how can we best exploit the constellation?

9. 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 = F 1 (x ) defines the “true” atmosphere (Nature Run) CTM 2 y = F 2 (x) +  is the forward model (Control Run) Instrument model describes measurement of y including smoothing, noise “True” x “True” y “Measured” y’ Prior estimate x A ± S A improved estimate x’ ± S’ Data assimilation Model 1Instrument model Compare x’ ± S’ to x and to x A ± S A : Is the measurement worth it? A reliable OSSE requires: 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 Model 2

10. Global OSSE WG ECMWF workshop, Oct 2012 Foci: 1.Improve realism of GEO-CAPE OSSEs 2.Demonstrate value of constellation GEOS-5 10-km resolution “true” atmosphere with aerosols, chemistry (Arlindo daSilva, NASA) Improving instrument models: variability of averaging kernel matrix for MOPITT CO (Worden et al., 2013) Spread in MOPITT AKs for CO retrievals Spread in MOPITT AKs for surface & 500 hPa CO retrievals(CONUS) (CONUS)

11. 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) Atlanta aerosol extinction (CMAQ) Atlanta surface reflectance, different times of day “True” regional and urban atmospheres generated Aerosol extinction, surface reflectance, variable AK matrices included for more realistic instrument modeling

12. Emissions WG Focus: Assess GEO-CAPE constraints on emissions of NO x, VOCs, NH 3, aerosols 1.0 2.0 Step 1: Perturb model natural gas emissions by 2x in west. Step 2: Sample model as GEOCAPE OSSE Step 3: Assimilate pseudo-obs into GEOS-Chem adjoint inversion GEOS-Chem CTM GEOS-Chem Adjoint GEOS-Chem CTM 0.750.0 200 1000 Pressure [hpa] Rows of GEOCAPE averaging kernel matrix 0.1 hPa 954 hPa Perturbed/prior emissions “Observed” enhancement Observation Platform Error reduction in perturbed region Error reduction in North America GEOCAPE88 %96 % TES-like LEO 8 %93 %. Only GEOCAPE locates emissions correctly 1.0 2.0 [ppb] Can we detect doubling of CH 4 emissions from natural gas in western US?

13. Aerosols WG Foci: Improve understanding of TEMPO capabilities Assess added value from concurrent GOES-R observations Fraction clear sky 1x1 km (GEO-CAPE) Fraction clear sky 4x2 km (TEMPO) σ < 0.0025 Fraction clear sky 4x2 km (TEMPO) σ < 0.005 Fraction clear sky 4x2 km (TEMPO) σ < 0.01 σ < 0.0025 abc Fraction clear sky 1x1 km (GEO-CAPE) Fraction clear sky 4x2 km (TEMPO) σ < 0.0025 Fraction clear sky 4x2 km (TEMPO) σ < 0.005 Fraction clear sky 4x2 km (TEMPO) σ < 0.01 σ < 0.0025 abc 1x1 km 2 MODIS cloud criteria TEMPO 4x2 km 2 relaxed cloud criteria Successful mapping w/TEMPO will require relaxed cloud criteria Satellite simulator for geo aerosol OSSEs ln(I o /I  ) Aerosol retrieval availability (April 10, 2012)

15. 1. Nature Run Model Required state: 4. Retrieved Products: Radiative Transfer Instrument Description Noise: 2. The Forward Model Simulated signal: Measurement Sensitivity: 2. The Forward Model Simulated signal: Measurement Sensitivity: Observing System Simulation Experiment (OSSE) Framework for GEO-CAPE David Edwards (NCAR) “True “atmosphere or “Nature” run OSSE Test!

16. OSSEs to evaluate the utility of GEO-CAPE methane observations for constraining North American emissions 1.0 2.0 Can we detect doubling of emissions from natural gas in the western US? How do results compare to traditional LEO capabilities? Step 1: Perturb model natural gas emissions by 2x in west. Step 2: Sample model atmosphere with GEOCAPE obs. operator Step 3: Assimilate pseudo-obs into GEOS-Chem adjoint inversion GEOS-Chem CTM GEOS-Chem Adjoint GEOS-Chem CTM 0.750.0 200 1000 Pressure [hpa] Rows of GEOCAPE averaging kernel matrix 0.1 hPa 954 hPa Perturbed/prior emissions “Observed” enhancement Observatio n Platform Error reduction in region Error reduction in N America GEOCAPE88 %96 % LEO (TES)8 %93 % Only GEOCAPE locates emissions within the perturbed region. [ppb] Emission error reduction achieved in OSSE