Evaluating the information from SNPP CrIS NH3 retrievals

1. Evaluating the information from SNPP CrIS NH3 retrievals Karen Cady-Pereira1, Matthew Alvarado1, Jeana Mascio1 ,Chantelle Lonsdale1, Rui Wang2, Xuehui Guo2, Mark Zondlo2, Daven Henze3, Hansen Cao3, Mark Shephard4 1. Atmospheric and Environmental Research (AER) 2. Princeton University 3. Colorado State University 4. Environment and Climate Change Canada Acknowledgement: NASA 80NSSC18K1562

2. NH3 from SNPP CrIS CrIS Surface NH3: 2013-2017 Mean CrIS NH3 global daily coverage captures spatial and temporal variability • But end users will ask: • How well does it compare to in situ data? • Which is the best metric for my objective? • Can it improve model emission estimates? MAM SON

3. DISCOVER-AQ NH3: aircraft instruments Jan 30 NASA P3B flight over California m • Picarro slow response leads to hysteresis: • Overestimates on ascent and underestimates on descent • PTR-ToF-MS signal is very noisy • in situ NH3 instruments often disagree since it is difficult to measure Co-location criteria with CrIS: 15 km and 1 hour PTR-MS data from Wisthaler group (U. Innsbruck / U. Oslo) Picarro data from J.B. Nowak* and J.A. Neuman, CIRES University of Colorado/ESRL NOAA,

4. DAQ California: CrIS vs PTR/Picarro Jan/Feb 2013 Jan 21, 2013 thin BL inversion layer high NH3 • Why is CrIS biased lowed at the surface? • Spatial inhomogeneity is likely cause • Elevated concentrations are highly localized Kang et al., 2015

5. CMAQ profiles vs CrISapriori • Selected ~850 CMAQ NH3 profiles from SENEX period/region • The average CMAQ resembles the CrISmoderate a priori profile • But manyCMAQprofiles have very different shapes from the CrISpollutedandmoderateapriori profiles • Well mixed BL • Elevated amounts above BL • Do these differences impact the retrieval metrics?

6. Simulated CrIS retrievals NH3 on - off • Used the CMAQ profiles as input to our forward model (OSS) and added typical CrIS noise to the output radiances • Ran the simulations with and without NH3 to determine NH3 signal • Since the NH3 signal is very dependent on the thermal contrast (TCON) ran sets of simulations with different TCON values: 15K and 5K • Selected TCON values are high but not unusual over many source regions BT Diff [K]

7. NH3 Signal Drivers CMAQ Surface NH3 • Since NH3 is concentrated in the boundary layer, surface NH3 is a strong driver of the NH3 signal • Kharol et al. (2019) have shown similar correlation between AMoN and CrIS surface data Peak BT Diff [K] ppbv CMAQ Total Column NH3 • In this simulation total column and the NH3 signal are almost perfectly correlated • Could total column be the most robust retrieval metric? molec/cm2

8. Surface NH3: Retrieved vs CMAQ CMAQ +AK linear CMAQ no AK CMAQ+AK log • Straight comparisons (no AK) • CrIS biased high for polluted profiles and low for moderate • Applying the operator improves correlation and reduce bias • Retrieval is performing as well as possible TCON: 15K • Similar results for weaker signal, but: • Selection of a priori has larger impact on the spread of the retrieved surface amounts TCON: 5K

9. Retrieved Total Column: CrIS vs CMAQ CMAQ no AK CMAQ+AK log CMAQ +AK linear • Correlations • Very high and better than surface correlations • A priori selection has little effect on the spread of the retrieved column • Applying the AK also has little impact TCON: 15K • Correlations • Higher and better than surface correlations • But a priori selection does have an impact on the spread TCON: 5K

10. Inverse modeling constraints on sources of NH3 using CrIS remote sensing measurements Hansen Cao (Hansen.cao@Colorado.edu), Daven K. Henze, Mark W. Shephard, Enrico Dammers, Karen Cady-Pereirda, Matthew Alvarado, Chantelle Lonsdale, Gan Luo, Fangqun Yu, Liye Zhu, Jesse Bash, Venkatesh Rao Acknowledgement NASA 80NSSC18K0689 Updated GEOS-Chem better captures diurnal cycle in SEARCH NH3 and seasonal pattern in AMoN NH3 measurements in 2014 • Motivation: significant, persistent uncertainties in the timing and distribution of NH3 emissions in North America • Methods: Top-down NH3 emission estimation • NH3 column concentrations sensitive to emissions upwind • For high resolution inversions with noisy pseudo CrIS data (Li et al. (2019): • 4D-Var more accurate • mass-balance prone to errors • Here we apply 4D-Var using GEOS-Chem adjoint at 0.25° x 0.3125° • Conclusions: inversions with simulated CrIS • - increased GC correlation with 2014 AMoN surface NH3 • - increased correlation with January SEARCH diurnal cycle • - increased correlation with July SEARCH diurnal cycle and reduced nighttime bias Annual R(updated GC, AMoN) R(default GC, AMoN) JAN JUL Local solar time

11. Emission optimization reduced difference between GEOS-Chem NH3 and CrIS NH3 CrIS H(GC a priori) H(GC a posteriori) • CrISsurface NH3(2014) higher in warm months over agricultural areas • H(GC a priori) generally captured CrIS-observed spatial pattern and seasonal variation, but underestimated the magnitude during warm months • H(GC a posteriori) better reproduced CrIS-observed magnitude and seasonal variation of surface NH3

12. Top-down constraints on NH3 emissions from CrIS Posterior Prior • Posterior annual anthropogenicemission estimate for CONUS is higher than prior estimate by 51%. • Posterior annual anthropogenicemissionincreasedacross most of contiguous US, with 10-30% decreasesfound in central California • Posterior monthly emissionfor CONUS increased throughout the whole year • Sensitivity tests: 20-30% reductions in SO2 and NOx emissions led to difference < 4% in posterior monthly emission estimate for both months: • difference in spatial distribution: • * SO2/NOxemissions from east US * NH3 emissions from central US 2.95 Tg N a-1 4.43 Tg N a-1 CONUS monthly emission Posterior - prior

13. CrIS-derived NH3 emissions improved agreement between GEOS-Chem simulation and in-situ measurements in 2014 N( R>0.8 ) = 22 N( R>0.8 ) = 5 JUL NH3 [ppb] R(Prior, AMoN) R(Posterior, AMoN) Local solar time N( |NMB| > 0.5 ) = 24 N( |NMB| > 0.5 ) = 47 NMB(Posterior) NMB(Prior) • CrIS-derived NH3emission enabled GC to better reproduce seasonal variability and magnitude of AMoN NH3 at most sites • CrIS-derived NH3emission enable GC to better reproduce domain averages of hourly SEARCH NH3 concentrations and monthly measurements of NH4+wet deposition from NADP network

14. Conclusions • NH3 from CrIS now available for 2013 through 2017 • 2018 currently being processed • Available upon request from Environment Canada • mark.shephard@Canada.ca • Validation against aircraft measurements from DISCOVER-AQ show that the algorithm is performing well, but that straight surface measurements are biased low • Surface NH3 provides useful information when averaged; total column appears to be the best metric for well mixed boundary layers • Emissions obtained from using CrIS profiles in a 4D-var approach for GEOS-Chem over North America showed reduced bias and increased correlation with respect to AMoN and SEARCH surface data, including daily variability

16. Example Retrieved Profiles Polluted Moderate Smooth: Log AK Dashed-Dotted: Linearized AK

17. Simulated CrIS – CMAQ NH3 Bias TCON: 15K TCON: 5K TCON: 5K TCON: 15K

18. Total Column Correlations +15K Simulations +5K Simulations

19. Surface NH3 Correlations +15K Simulations +5K Simulations

20. Surface and column correlations with NH3 signal TCON = 5K TCON = 15K Surface Column

21. A Tale of Two Cities CrIS TES Beijing transect region transect Delhi region