Simulation of Polar Ozone Depletion in SD-WACCM4 / MERRA

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1 Simulation of Polar Ozone Depletion in SD-WACCM4 / MERRA D. Kinnison (NCAR), S. Solomon (MIT), J. Bandoro (MIT), and R. Garcia (NCAR) June 16, 2015 WACCM Working Group Meeting, Baltimore MD. Image courtesy of NASA (Paul Newman, GSFC).

2 PSC Parameterization in WACCM Original Approach (Equilibrium Approach) NASA GMI: Considine et al., JGR, WACCM: Kinnison et al., JGR, We found that the model over De-NOy in early winter. This also limited the amount of HNO 3 available for STS formation. New observations: CALIOP (Pitts et al., JGR, 2009) showed liquid and solid PSC coexisted throughout the winter. STS, NAT, ICE Coexist: Wegner et al., JGR, Empirically, the partitioning of 80% total HNO 3 into STS and 20% into NAT best represents the evolution of HNO 3 (g) in WACCM. Consistent with Pitts et. al. mix2 PSC categories. Simulation of Polar Ozone Depletion: Solomon et al., in review, JGR, Examined the role of T, SAD sulfate, and PSC type on ozone depletion.

3 Image taken from Solomon et al., JGR, PSC Chemistry: Key Chemical Processes

4 De-H 2 O and De-NOy Processes: HNO 3 (g), H 2 O(g). Zonal Mean Image taken from Solomon et al., JGR, 2015.

5 Net Activation Processes: O 3, ClONO 2, and HCl SH: Zonal Mean, 31 hpa Comment: Exceptional model/mls agreement of HCl, ClONO 2, and O 3. Image taken from Solomon et al., JGR, 2015.

only affects het rates and denoy), the model accurately

6 Net Activation Processes: O 3, ClONO 2, and HCl NH: Zonal Mean, 82 N, 53 hpa Comment: With a -2Kbias to the het module (which only affects het rates and denoy), the model accurately represents ozone depletion. Image taken from Solomon et al., JGR, 2015.

7 Why re-evaluate PSC and O 3 Depletion? 1) Field and laboratory studies have provided new data on the spatial and temporal distribution of both liquid and solid stratospheric particles, as well as their composition, size distribution, and chemical reactivity? 2) Stratospheric modeling has progressed with the state-of-the-art global CTMs and CCMs. Many CCMs are now driven or nudged with reanalysis data. Therefore, better representing temperature and dynamical processes. 3) Observation show enhancement in stratospheric sulfate particles linked to a series of relatively small volcanic eruptions since Understanding the impact that these eruptions have on decadal trends may be important. 4) Examine the result of Drdla and Mueller (Ann. Geophys., 2012) that heterogeneous reactions on liquid particles (for T 195K) can represent polar ozone depletion.

8 Examine PSC Assumptions on Ozone Depletion Scenario Temperature PSCS Comments No Het - NONE Zeroed halogen het. rates. Reference - ALL TYPES CCMI Version 2Kbias -2K applied ALL TYPES Only to the Het Module. 3xSAD - ALL TYPES Show the sensitivity to sulfate SAD in polar region only. SOLID - NAT, ICE Liquid PSCs reactivity zeroed. LIQUID#1 T 195K LBS Test Drdla+Muller 2012 result. LIQUID#2 T 192K LBS, ~STS STS starts to form. LIQUID#3 No Threshold LBS, STS For all LIQs De-NOY occurs over entire T-range. Solomon et al., 2015, Simulation of Polar Ozone Depletion: An Update, in review, JGR,

9 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 Obs = ~160DU 9

10 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 REF = ~135DU 10

11 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 SOLID = ~100DU 11

12 TOZ (DU) *** 82 S *** Zonal Mean *** K Bias = ~170DU 12

13 TOZ (DU) *** 82 S *** Zonal Mean *** xSAD = ~160DU 13

14 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 LIQ#1 = ~40 DU 14

15 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 LIQ#2 = ~80 DU 15

16 TOZ (DU) *** 82 S *** Zonal Mean *** 2011 LIQ#3 = ~135 DU Image taken from Solomon et al., JGR,

17 TOZ (DU) *** 82 N *** Zonal Mean *** 2011 Image taken from Solomon et al., JGR,

19 -57 DU -96 DU -75 DU -118 DU

20 Summary of TOZ Simulations In the SH, the REF case underestimates the observed TOZ (OMI) by approximately ~25DU. In the SH, adding a -2K bias to the heterogeneous module overestimates the depletion by ~10DU. In the SH, adding a 3xSAD to the input CCM sulfate SAD (which is consistent with small volcanic eruptions) shows very good agreement with OMI TOZ. The model has more difficulty representing the observed TOZ in the NH. Only when the -2K bias and 3xSAD is applied does the model come close to the observed decrease. More work is needed to understand this model/observed difference. The depletion due to LIQUIDS and SOLIDS is not additive. REF SOLID only + LIQUID#3 (T no limit) 20

80S, 30hPa The Role of ClONO 2 and HCl When O 3 is depleted (Vortex Core). Cl + O 3 => ClO + O 2 (slow) Cl + CH 4 => HCl + CH 3. Douglass et al., 1995.

21 80S, 30hPa The Role of ClONO 2 and HCl When O 3 is depleted (Vortex Core). Cl + O 3 => ClO + O 2 (slow) Cl + CH 4 => HCl + CH 3. Douglass et al., Moderately depleted (e.g., vortex edge, or at lower pressures). ClO + NO 2 + M => ClONO 2 + M HCl recovery Delayed Image taken from Solomon et al., JGR, 2015.

22 HCl Rate Change as an Indicator Heterogeneous Chemical Processing. 30 hpa d[hcl] / dt Image taken from Solomon et al., JGR, 2015.

23 Summary of PSC Simulations We find that the occurrence of cold temperatures and PSC chemistry at T<192K is essential to produce substantial ozone loss (O3L). The magnitude of the calculated TOZ in both polar regions is sensitive to small differences in temperature and sulfate surface area density (~10-40DU). These sensitivities are important in quantifying ozone recover due to halogens. These results confirm earlier studies suggesting that liquid PSCs particles are sufficient to simulation nearly all of the O3L using current model chemistry. However, solid PSCs do play an important role in de-noy and de-h 2 O. They also add to the O3L for altitudes >18km. We ve shown that the rate of change of HCl can be used as a key indicator of ozone depletion chemistry, primarily outside of the vortex core ** Looking forward to including this PSC Chemistry in the CMIP6 Configuration! ** 23

Simulation of Polar Ozone Depletion: An Update

Simulation of Polar Ozone Depletion: An Update Image taken from www.zmescience.com D. Kinnison (NCAR), S. Solomon (MIT), and J. Bandoro (MIT) February 17, 2015 WACCM Working Group Meeting, Boulder Co.