Ozone time series and trends Various groups compute trends in different ways. One goal of the workshop is to be able to compare time series and trends.

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Presentation transcript:

Ozone time series and trends Various groups compute trends in different ways. One goal of the workshop is to be able to compare time series and trends from different groups. Therefore we are requesting that participants compute trends for common time periods in a common manner, to facilitate intercomparison of results. This is not mandatory, but is highly desirable. This does not preclude participants presenting trends computed in other ways for other time periods (e.g., their entire record).

Recommendations for trend intercomparison. The template is a guide, to be followed as much as possible for the trend intercomparison. Comparing trends is only one aspect of the « Tropospheric O3 Changes » issue. Key points are: to show the entire time-series in ppb, as there is often non-linear behavior to analyse trends to check the regional consistency within different datasets.

General recommendations: Please calculate all trends as the slope of the linear regression line and give the corresponding 95% confidence interval for the trend (2σ) and r 2 for the fit. Also give the intercept (with a confidence limit) for a selected reference year (e.g. 2000) or give the average mixing ratio for the record. ALL trends (including seasonal trends) should be calculated based on monthly mean anomalies (i.e. deseasonalized trends) and reported in ppb/year +/- 2σ. Specific recommendations for surface stations : Monthly means are calculated using original data resolution (e.g. hourly means). Monthly mean is considered valid if less than 33% of points are missing.

Specific recommendations for vertical profiles : 1.Monthly means should be reported for the following vertical layers: A: surface layer (ground-1 km) B: lower free troposphere (1-3 km) C: mid free troposphere (3-8 km) D: upper troposphere (8 km - tropopause) : E: UTLS 2.Or use vertical resolution of ~1 km from ground to the tropopause 3.Or if you use some other vertical grid, it would be helpful to report trends on the recommended altitude ranges.

Recommended time intervals Three time periods should be investigated if your data covers these periods: , and If these are not available, just use the data range you have e.g, for MOZAIC Compute trends for if you wish to compare to MOZAIC trends.

Data presentations talks (no more than 10 slides) Description of station/data set : 1 slide as suggested below (#7 or #9 for either surface or vertical profile station) Display of entire time series (in ppb) and highlight of special features. 1 slide Display of time series anomalies (in ppb) over and/or and/or if possible and include a linear fit with indications on slope/2σ/r 2 and intercept or average concentration over the record. (max 3 slides) Display of summary tables : 1 slide as suggested below (#8 or #10 for either surface or vertical profile station) Discussion points (1 slide). Comparison with neighboring sites and/or alternative statistical approaches. (max. 2 slides) Summary and open issues. 1 slide

General information about surface station: 1) The station : Name, Latitude, Longitude, Altitude, Surrounding (possible sources of precursors/ anthropogenic impact), Systematic changes in environment 2) Instrument (general performance/calibration) 3) Data set: Period: % of missing points: Particularities (e.g. years of the general tendency change)

From monthly mean anomalies based on all available data From night data only (11 p.m. – 4 a.m. local time) From day data only (11 a.m.- 4p.m. local time) Annual trends Seasonal trends (for day and night values) DJFMAMJJASON « Night / Day » can be replaced by « Baseline / Non-Baseline » or « Regional / Local » influence

General information about the vertical profile station: 1) The station: Name, Latitude, Longitude, launch altitude, Launch time and frequency surrounding (possible sources of precursors/ anthropogenic impact), systematic changes in environment 2) Instrument (general performance/calibration) 3) Data set: Period Big data gaps Particularities (e.g. years of the general tendency change)

From monthly mean anomalies (in ppb) based on all available data ABCDE Annual trends for the five altitude layers (or whatever is convenient with your dataset) Seasonal trends DJFMAMJJASON A, B, C, D, E altitude levels can be replaced by plots of profile trends

Model evaluation talks (no more than 12 slides – focus on reanalysis simulations) Description of model and simulation set-up : 1 slide General characterization of simulation results (e.g. maps or “Stevenson-plot” (multi-panel regional averages): 1 slide Up to 4 slides with time series comparisons for surface sites. Use monthly mean anomalies as the data people; individual stations or regional averages: all graphs should have time axes and/or and/or and include a linear fit with indications on slope/2σ/r 2 and intercept or average concentration over the record. Up to 4 slides to analyze modeled vertical profiles versus MOZAIC and/or sondes. For MOZAIC use and , for sondes and Show time series at standard pressure levels (850, 500, 250 hPa) plus summary slide for trend (ppbv/year) versus altitude. Discussion points (1 slide) Summary and open issues: 1slide