A .-year signal in High Latitude Column Ozone

1、A 3.5-year signal in High Latitude Column OzoneJingqian Wang,1* Xun Jiang,1 Run-Lie Shia,2 and Yuk Yung21 Department of Earth and Atmospheric Sciences, University of Houston, TX 77204, USA.2 Division of Geological and Planetary Sciences, California Institute of Technology, 1200 East California Boule

2、vard, Pasadena, CA 91125, USA.* To whom all correspondence should be addressed. E-mail: jingqian.wangAbstractWe applied spectral analysis to monthly mean column ozonesonde data, which have relatively long record. There is a significant signal at 3.5 years for some stations. To reveal the source for

3、3.5-yr signal, we applied similar analysis to column ozone simulated by the Goddard Earth Observation System Chemistry-Climate Model (GEOS-CCM). GEOS-CCM is driven by real sea surface temperature, which has correct El Nio-Southern Oscillation (ENSO) signal at the surface. We found that 3.5-yr signal

4、 also exists in the model ozone. Since the model with realistic ENSO can reproduce the 3.5-yr signal, it is likely that the 3.5-yr signal is from the ENSO signal. We further applied Empirical Mode Decompostion (EMD) method to analyze the ozonesondes and model simulations. 3.5-yr signal is very signi

5、ficant in the EMD outputs from both observations and model simulations. 1. Introduction2. Datasets and Methods:2.1 DatasetsIn this paper, we will investigate column ozonesonde data, which have relatively long data record. (Data can be downloaded from /data_e.html). Twenty-one stat

6、ions with long record are found. These ozonesonde data will be compared with model simulation from GEOS-CCM (Stolarski et al., 2006b; Pawson et al., 2007). GEOSChemistry is a global 3-D chemical transport model (CTM) for atmospheric composition. It uses meteorological input from the Goddard Earth Ob

7、serving System (GEOS) of the NASA Global Modeling and Assimilation Office. Coupling between the circulation and chemistry arises through transport and the interactive nature of the radiation code, which allows for the feedback of O3, H2O, CO2, CH4, N2O, CFC-11, and CFC-12 with the circulation. Archi

8、ves of monthly mean ozone and meteorological fields were used from a simulation of the period 1951-2005 at 2 2.5 (latitude by longitude) with 55 layers between the surface and about 80km. At the lower boundary, sea surface temperature and sea ice are prescribed from observations compiled by Rayner e

9、t al. (2003), along with time-dependent World Meteorological Organization/United Nations Environment Programme (WMO/UNEP) and Intergovernmental Panel on Climate Change/Special Report on Emissions Scenarios (IPCC/SRES) surface mixing ratios for chemically active and greenhouse gases. 2.2 MethodsBefor

10、e applying the spectral analysis, seasonal cycles will be removed from ozonesondes and model simulations. To obtain the statistical significance of signals in a power spectrum, we will compare the amplitude of a spectral peak to the red noise spectrum. The red noise spectrum used in constructing nul

11、l hypothesis for significance is the spectrum associated with the autocorrelation function, (Gilman et al., 1963). in the function is the average of one-lag autocorrelation and the square-root of the two-lag autocorrelation. The red noise spectrum associated with the autocorrelation function is Here

12、, is frequency and is the maximum lag (Gilman et al., 1963). The 15%, 10%, and 5% significance level for the power spectrum are found using F-statistics to compare the spectrum to the red noise spectrum.Empirical mode decomposition (EMD) analysis (Huang et al. 1998) method will be applied to ozoneso

13、ndes and model simulation for separating 3.5-yr signal from raw data. EMD method is a simple technique that decomposes time series into natural modes or intrinsic mode functions (IMFs). IMF has a symmetric envelope defined by the local maxima and minima so that its mean amplitude is zero everywhere.

14、 Its mean period can be determined by counting the number of peaks (maxima). ResultsWe first detrended the monthly mean column ozone data, then calculated the power spectrums for the ozonesondes. We choose 21 observation stations that have long time record. Only eight stations have significant 3.5-y

15、ear signal. The eight stations are Potsdam, Belsk, Hradec, Hohenpeissenberg, Arosa, Toronto, Sappor, Nashiville. We layout the observation stations and their positions, and found the signal has no preference for the spatial distributions. Power spectra and statistical significances of the peaks are

16、shown in Figure1 for the eight stations. Dotted lines are the mean red-noise spectra. Dash-dot lines and dashed lines correspond to 10% and 5% significance levels, respectively. In fig.1a, there are about three kind of significant spectral peak: residual annual cycle, Quasi-Biennial Oscillation and

17、3.5-yr cycle. Since there is already many research about the first two spectral peaks, we only focus on the third one in this paper. Among these 8 stations, we can find significant peaks between 3-4 years. The power spectra of Fig. 1a-Potsdam, d- Hohenpeissenberg, and g-Sappor are within 10% to 5% s

18、ignificance levels. The other 5 stations such as Fig. 1b-Belsk, c-Hradec, e- Arosa, f-Toronto, h-Nashiville have the power spectra within 5%. The 3.5-yr signal was found in Jiang et al. 2008. However, the mechanism for the signal is not known. In order to reveal the mechanism for the 3.5-yr cycle an

19、d explain the results from the above, we will investigate the signal in GEOS-CCM. GEOS-CCM is forced by realistic sea surface temperature and sea ice. The ENSO signal is well captured at the model surface. There is no QBO and solar cycle in the model. We applied same spectral analysis to the model o

20、utput. Results for model column ozone are shown in figure 2. There are significant 3.5-yr signals (within 10%-5% significance levels) from figure 2a to e and g. Two stations, Toronto and Nashiville, have 3.5-yr signals within 5% significance level. It is obvious that the 3.5-y signal could also be f

21、ound in the model column ozone and is significant. Since the model only has realistic interannual variability from ENSO, no other interannual variability is available, it suggests that the 3.5-yr signal in ozone might origin from ENSO signal from surface. As we know, there are many kinds of cycles t

22、hat mixed in the data, which could affect the results. So we further apply the Empirical Mode Decomposition (EMD) technique (Huang et al., 1998) to analysis the data. This method is designed for separating different signals from time series. The results of EMD can help to improve our understanding a

23、bout the 3.5-yr oscillation. We found that the fourth IMF corresponds to the 3.5-yr signal in ozone for each station. Figure 3 shows the results of the fourth IMFs of observation column ozone data. The amplitudes for the fourth IMFs are within 15 DU to -10 DU. Power spectra for the fourth IMFs revea

24、l that the signals are between 3-4 years and it is significant. Similarly, we applied EMD to model column ozone. The fourth IMFs are shown in Figure 4. 3.5-yr signals at Potsdam, Hohenpeissenberg, Arosa and Toronto are the quite significant as those in observation data. However, the 3.5-yr signals a

25、t Belsk, Hradec, Sappor and Nashiville are not so strong compared with other signals in the fourth IMFs of model ozone. This may because the limitation of the models accuracy and resolution.ConclusionsWe investigated the observation data of monthly mean column ozone and found the 3.5-year signal in

26、the eight stations. The 3.5-y signal was found in the GEOS-CCM model ozone, which suggests that the 3.5-yr signal might be related to the ENSO. EMD method was also used to analysis the data. The same result was found in the observation data. The EMD result of the model data is good, though in some s

27、tations the power spectra were not as strong as in the observation data according to the limitation of the models resolution and accuracy. In summary, the relationship between the 3.5-y ozone period and ENSO exists. And the ozone 3.5-y period might be a part of ENSO signal. The linkage between 3.5-y

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