# Presentation: 049351

## The vertical structure of ozone variability, as measured by MLS/AURA and ACE and modeled by the CMAM

- _Matthew Toohey_ (1), K. Strong (1), B. M. Quine (2),
- T. G. Shepherd (1), K. Semeniuk (2),
- P. F. Bernath (3), C.D. Boone (3), K. A. Walker (3).
- (1) University of Toronto
- (2) York University
- (3) University of Waterloo

- AURA Science meeting, 8-10 November 2005, Den Haag

## Acknowledgements

- MLS/AURA, ACE, CMAM, MANTRA science teams
- Canadian Space Agency
- Meteorological Service of Canada
- CREStech/ETech
- CFCAS
- NSERC

## Atmospheric variability

- Quantifying natural variability is important:
- In order to detect trends (e.g. midlatitude O3, HNO3 via MANTRA)
- In the definition of coincident measurements for validation
- Variability comes from sampling in space and time (due to mean spatial gradients and transient perturbations, seasonal cycle...).

## Some questions

- How well does our modeled prediction of trace gas variability agree with observations?
- What can the measurement of a variable atmosphere by different instruments tell us about those instruments?

## The CMAM (version 7)

- Canadian Middle Atmosphere Model: an upward extension of the CCCma spectral GCM up to roughly 100 km altitude1.
- Incorporates: radiation, interactive chemistry, gravity wave drag, as well as all the processes in the GCM.
- Full representation of stratospheric chemistry with relevant catalytic ozone loss cycles2.
- Heterogeneous reactions are included for sulphate aerosols. No PSCs.
- No QBO, warm winter poles, prescribed SSTs.
- 14 years of output used here.
**1**** Beagley et al., Atmos.-Ocean, 35:293, 1997.**
**2**** de Grandpre et al., Atmos.-Ocean, 35:385, 1997.**

## Observations

- MLS/AURA v1.51 L2 O3
- 2004-08 – 2005-10
- Ignored data with: negative l2gpPrecision, non zero Status, Quality < threshold.
- ACE-FTS v2.2 O3 (update), pressure
- 2004-01 – 2005-07
- Ignored data with: 0 mixing ratio, -888 or –999 flags in profile or errors.
- ACE profiles are shown in pressure coordinates
- ACE retrieved pressure is averaged for each z-layer for each subset of ACE data – ACE pressures should be considered approximate.
- I have not performed a least-squares fit of ACE to the MLS retrieval grid (as described in sec 1.6 of the MLS v1.5 L2 data quality and description document).

## Sampling - spatial

- Focus on northern midlatitudes, 39-61 N
- Take all observations, not just matches

- J      F      M      A      M       J       J       A       S       O       N      D

## Area weighting*

- Spatial sampling biases addressed through equal-area weighting
- Randomly remove profiles (or weight them), such that the number of observations (N) in latitude band  to  + , N goes as cos()
- Has advantage that P, the area-weighted PDF of discrete sampling of a tracer ,,
- is the likelihood of observing a value in the range from  to  + in some given area, and...
- is proportional to the area enclosed by the  and  +  contours in a contour plot of the field.
- * **As described in Sparling, Rev. of Geophys., 38:417-436, 2000.**** **

## Sampling - temporal

- Monthly statistics calculated for 2004-08 – 2005-10
- Special “fly-by” periods defined for ACE

- J      F      M      A      M       J       J       A       S       O       N      D

## Area weighted O3 statistics

- May 2005 monthly mean and standard deviation:
- CMAM climatology in red, yearly stats in grey
- Variability sources include: seasonal cycle, spatial gradients and small-scale structures.
-   agreement tells you (1) instrument noise < atm variability and (2) instrument Gains comparable

## O3 means - time series

## O3 mean differences - time series

## O3  - time series

## Summer variability

## Vertical O3 anomaly PDFs – May ’05

- CMAM
- MLS
- ACE

## Vertical O3 anomaly PDFs – May ’05

- CMAM
- MLS

## Vertical O3 anomaly PDFs – Mar ’05

- CMAM
- MLS

## Conclusions

- Agreement between MLS and ACE O3  profiles:
- Tells you nothing about retrieval accuracy
- Tells you little about retrieval precision
- But, is good circumstantial evidence that the retrievals respond with comparable amplitudes to changes in the atmosphere
- Agreement between the observations and the CMAM O3  profiles and PDFs:
- Is evidence that the model is doing a good job of modeling realistic stratospheric variability (esp. in summer midlatitudes).
- Gives us confidence in using the model to explore the mechanisms of variability

## Atmospheric variability

- True profiles of trace gas species in the middle atmosphere vary with time and space:
- For reasons radiative, dynamical, and chemical.
- Measured profiles of trace gas species vary:
- Because the atmosphere does, and because the instrument is not perfect.
- Temporal and/or spatial means of measured profiles will vary:
- Based on an instrument’s incomplete sampling
- Between instruments, based on differences in measurement technique and assumptions