1. Spatio-temporal Variability 2nd GEO-CAPE Community Workshopof
Ozone Laminae
Michael J. Newchurch1, Guanyu Huang1, John Burris2, Shi Kuang1, Wesley Cantrell1, Lihua Wang1, Patrick I. Buckley1, Brad Pierce3
1 Atmospheric Science Department, University of Alabama in Huntsville
2Goddard Space Flight Center, NASA
3NOAA/NESDIS/STAR
2nd GEO-CAPE Community Workshop
Boulder, CO
May 11-13, 2011

2. Outline Vertical information from space-borne observations.
Sondes and lidars and laminar structures
Vertical correlation of ozone
STE of ozone
Birmingham ozone/aerosol nocturnal-jet plume
Modeling of laminar structures
Ozone lidar network

3. High-resolution PBL lidar observation suggests both UV and Vis radiances required to capture significant PBL signal for satellite
Huntsville lidar observation on Aug. 4, 2010
Lidar obs. convolved with OMI UV averaging kernel---- unable to capture the highly variable ozone structure in PBL
sets the stage for GEO CAPE formulation
Lidar obs. Convolved with OMI UV-Vis averaging kernel----Captures the PBL ozone structure. X. Liu et al.

4. Theoretical retrievals from multi-spectral measurements
Courtesy of Natraj, Liu, et al.
True
A priori
UV retrieval
Vis retrieval
TIR retrieval
UV + Vis
UV + TIR
UV + Vis + TIR
Figure 8. Curtain plot of tropospheric ozone profiles for (a) true, (b) a priori, (c) UV
retrievals, (d) visible, (e) TIR retrievals, (f) UV+VIS retrievals, (g) UV+TIR retrievals, (h)
UV+VIS+TIR retrievals. The atmospheric profiles are arranged in the same order as
in Table 2.

5. J O U R N A L O F A P P L I E D M E T E O R O L O G Y VOLUME 38 The Role of Vertical Mixing in the Temporal Evolution of Ground-Level Ozone Concentrations JIAN ZHANG AND S. TRIVIKRAMA RAO Department of Earth and Atmospheric Sciences, University at Albany, State University of New York, Albany, New York (Manuscript received 15 July 1998, in final form 19 February 1999)
…The results reveal that a greater reduction in the ground-level ozone concentration can be achieved by decreasing the concentrations of ozone and precursors aloft than can be achieved from a reduction of local emissions…

6. Typical, large diurnal variability in the Boundary Layer Zhang and Rao, 1999

7. Continuous Wavelet Transform (CWT)
The CWT coefficient is defined as:
a is the spatial extent or dilation of the function.
b is the location at which the wavelet function is centered—the translation of the function.
f(z) is the signal of interest, in this case, an ozone profile.
and are the top and the bottom of the profile.
is the wavelet function.

8. Laminar structure analyzed by CWT and the gradient method

9. Seasonal Variations Occur in Altitudinal Distributions- Layer Height WRT to Tropopause Height
Gradient
Wavelet
Spring
Low frequency of layers near tropopause
Summer
High frequency of layers below tropopause
Seasonal variability
Trinidad Head 9

10. For example: O3 peak altitude, mixing ratio at peak. A
Fine structure in the temporal variations of layer attributes can be quantified by Wavelet and Gradient methods from Lidar observations.
Layer A Max-Min
Max: 50.1 ppbv Min: ppbv
Mean max-min : 2.5 ppbv / 10min
+7.9 ppbv / 10min
-2.4 ppbv / 10min
Temporal variability from other layer attributes can be similarly quantified.
For example: O3 peak altitude, mixing ratio at peak. A B
Layer B Thickness
Max: 4.8 km Min: 3.0 km
Mean Thickness: 0.3 km /10min
+0.9 km /10min
-0.3 km /10min 10 10 10

11. Ozone in the free troposphere is not correlated with surface ozone
Seasonal correlation of surface w/ ozone aloft
Huntsville Ozonesonde Data
P(R^2>0.5)= % 15% % %

12. Laminar structures cause anomalous behavior in correlations
Huntsville Lidar Data
EPA Surface Data

13. Horizontal Variability
Surface ozone of 24 sonde profiles compared with local EPA site: The variance in the surface ozone amounts at the ozonesonde/lidar site seen in the EPA HSV-Airport Rd. site (~10 km distant; Summer 2010) is about 75%. The other 25% is the HORIZONTAL variance.
UAHuntsville Campus Ozone
Measured with ozonesonde
1/28/2011
June 19
Inside
ppbv
Percent difference reaches ~30% for measurements away from buildings.

14. What We Missed with the Weekly Ozonesonde Measurements?
Apr. 17
Apr. 23
What We Missed with the Weekly Ozonesonde Measurements?
May 1
Apr. 27
Additional sonding on Tue. after the lidar detection of Stratosphere-troposphere
exchange (STE)
Dry air

15. Tropospheric ozone variability due to STE captured by the HSV lidar
O3 lidar retrieval
500ppbv
10min resolution
Cloud
Cloud
Cloud
sonde

16. Different variation structures for ozone and aerosol suggest local photochemistry dominates the production
Ozone mixing ratio, August 4, 2010
O3 diurnal variation
Kuang: This slide is to demonstrate the aerosol is not necessarily correlated with ozone depending on their sources. I suggest using the previous one, slide 3, to emphasize lidar’s significance for satellite and skip this one.
Use either the previous slide or this one but not both? Needs a “so what” message. With a DIAL you’ll get the aerosol anyway, right?
Aerosol ext. coeff. at 291nm from O3 DIAL
The rapid aerosol variation in the PBL suggests the importance of a collocated aerosol measurement.

17. Nocturnal ozone enhancement associated with low-level jet
Lidar
Oct. 4, 2008
Co-located wind profiler
Low-level jet
Aerosol ext.coeff. at 291nm from O3 lidar
(a)
Kuang: Ozone and aerosol plums rise the same time as the LLJ. But the time range of the lidar data acquisition did not fully cover the LLJ. So added a dashed circle to label the LLJ.
What is the take home message here? According to your circles, most of the ozone action seems well in advance of the jet, 1-2 UTC. Aerosol really kicks up later, 3-5 UTC
Positive correlation of ozone and aerosol due to transport
Co-located ceilometer backscatter
Kuang et al. submitted to Atmospheric Environment
Aerosol

18. over estimates depth of 6-8km layer shows collapse of PBL May 3, 2010
RAQMS misses ozone
layer at 2-4km
over estimates depth of
6-8km layer
shows collapse of PBL
May 3, 2010
Daytime PBL top collapsed
May 01
May 02
May 03
May 04
May 05
May 06
May 07
May 08

19. RAQMS is in good agreement with Huntsville Lidar above ~3km
May 6 (high PBL O3)
RAQMS is in good agreement
with Huntsville Lidar above ~3km
under estimates low level ozone
enhancement
May 01
May 02
May 03
May 04
May 05
May 06
May 07
May 08
Saharan dust event
O3 AQ event

20. RAQMS shows diffuse free Tropospheric ozone
May 7
RAQMS shows diffuse free
Tropospheric ozone
Does not resolve thin filaments observed
By lidar
May 01
May 02
May 03
May 04
May 05
May 06
May 07
May 08
Saharan dust event
O3 AQ event

21. Ozone Lidar Network
Technology developed to produce a/c instruments (Browell/NASA, Hardesty/NOAA) and ground-based (McDermid/NASA/TMF, Newchurch/UAH&NASA). A few other ozone lidars operate in Europe and Asia.
NASA has formed a working group to identify a pathway in science and technology to eventually create a network of ground-based ozone lidars.
Such an ozone lidar network would be very complementary to the NASA GEO-CAPE geostationary AQ/Ocean satellite planned for ~2020.

22. 4-hour temporal resolution vs. 10-minute resolution
$800/ ozonesonde launch
No more than 6 launch per 24 hours = 4-hour resolution
$800/launch*6launch/day*365days/year=$1,752,000/year
Vs.
Lidar 10-minute observations
sonde

23. Conclusions
Ozonesonde and lidar observations identify ubiquitous laminar structures.
Laminar transport from STE and NBL transport can be important for AQ.
Current regional models often do not resolve laminar structures of importance to surface AQ.
An ozone lidar network is a potential solution to acquire the vertical ozone information needed by AQ practitioners.

24. Correlation Lengths
Definition: the altitude over which R^2 decreases from 1 to 0.5.
Each line is a regression through the correlations of at least 0.5.
Correlations >0.5 above the first occurrence of a statistically insignificant value (<0.5) are not considered.
Conclusion:
Measurements of ozone above correlation length carries no info about surface ozone.
Corollary: To determine surface ozone concentration, a measurement must contain info from within the correlation length.
Two clusters