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4 Some Remarks on Intercomparison with other Data Series

4.1 Lower Stratospheric Temperature Differences between Meteorological Analyses in two cold Arctic Winters and their Impact on Polar Processing Studies. (Manney et al., 2002)

4.2 SPARC Stratospheric Temperature Trend Assessment (STTA) (Ramaswamy et al., 2001)

4.3 Intercomparison of two Stratospheric Analyses:
Temperatures Relevant to Polar Stratospheric Cloud Formation.
(Pawson et al., 1999)

4.4 References


4 Some Remarks on Intercomparison with other Data Series

The intercomparison of different stratospheric analyses is an important issue for the understanding of any trends, but also for the evaluation of, e.g., the tropopause temperatures in the tropics or the potential for the formation of "polar stratospheric clouds" (PSCs), to name a few of the questions. Over the years and with the advent of different satellite data and recently the re-analyses by NCEP/NCAR and the data assimilations by different groups, this problem has been studied by several groups, dealing with different aspects. Here, we refer to a few studies where "Berlin Data" have participated. But this is not a complete list of such studies.

4.1 Lower Stratospheric Temperature Differences between Meteorological Analyses in two cold Arctic Winters and their Impact on Polar Processing Studies. (Manney et al., 2002)

A quantitative comparison of six meteorological analyses is presented for the cold 1999-2000 and 1995-1996 Arctic winters. Using different analyzed data sets to obtain temperatures and temperature histories can have significant consequences. The area below a polar stratospheric cloud (PSC) formation threshold commonly varies by about 25% between the analyses, with some differences over 50%......

Freie Universität analyses are often colder than others at temperatures below 205 K but warmer than others at temperatures above about 210-215 K. The FUB analyses are closely matched to radiosonde observations and consequently may capture local variations in the vicinity of radiosonde stations that are smoothed over in the other systems that also give weight to low vertical resolution satellite data; however, away from the radiosonde locations they are more poorly constrained than the other analyses, and may miss or severely smooth temperature variations that occur between observation locations.... (Manney et al., 2002)

As also other comparisons have shown, the hand analyses done by experienced meteorologists are catching the extremes usually better than the computer analyses. And if there are few radiosonde stations, when interpolated into data sparse region, they can go a long way. Figure 27 is shown here as one example of the comparisons, and the much larger scatter of the "Berlin Data" is consistent with the above.

[Scatter Plots of different Temperature Analysis]

Figure 27: Scatter plots of the difference between temperatures from each analysis and the ensemble mean temperature (average over all analyses at each grid point) as a function of the ensemble mean, for all grid points on a 5 x 5 grid from 60 to 90N, at 50 hPa, for January and February 2000 and 1996. The shaded region shows the area filled by the individual scattered points. The solid triangles show the average difference (analysis temperature - ensemble mean temperature) in each 1-K average temperature bin. The thin line is the zero line. (Figure 1 in Manney et al., 2002)

4.2 SPARC Stratospheric Temperature Trend Assessment (STTA) (Ramaswamy et al., 2001)

Under the auspices of the World Climate Research Program (WCRP) the sub-program SPARC (Stratospheric Processes and Their Role in Climate) initiated the STTA Group. The charter was (1) to bring together all available data sets of stratospheric temperatures and (2) to analyse the trends in a consistent manner. The results of this work are published in Ramaswamy et al. (2001). The "Berlin Data" participated in this major intercomparison and one Figure is given here as an example, Fig.28. The report deals carefully with all the problems arising from the various, very diverse data sets and their trends.

[Zonal-mean decadal temperature trends at 50 hPa]

Figure 28: Zonal-mean decadal temperature trends at 50 hPa over the 1966-1994 period from different radiosonde data sets. Ramaswamy et al., 2001, Plate 2

4.3 Intercomparison of two Stratospheric Analyses:
Temperatures Relevant to Polar Stratospheric Cloud Formation.
(Pawson et al., 1999)

Abstract

"Two independent daily stratospheric data sets are compared for 16 northern winters. The objective is to assess the consistency of temperatures low enough for polar stratospheric cloud (PSC) formation at 50 hPa. The first data set is the subjective [historic] analysis [of temperatures and geopotential heights] produced from the radiosonde network at the "Freie Universität Berlin" (FUB), which is constrained by hydrostatic and thermal wind balance. The second is the satellite-based analysis of geopotential height, compiled from the TIROS Operational Vertical Sounding system by the United Kingdom Meteorological Office; temperatures are derived from the hypsometric equation. The Stratospheric Sounding Units (SSU) provide most of the stratospheric data in that system. The FUB data are generally colder, particularly at low temperatures, but there is a large dispersion about the mean difference. The uncertainties of the values of the lowest temperatures are around 1 K and 2 K in the mean and rms, respectively. There may be a geographical bias in the data sets. There is a clear relationship between the vertical temperature gradient and the difference between the two data sets, the satellite-derived values becoming relatively colder when the temperature decreases at pressures lower than 50 hPa. Regarding PSC formation: adequately low temperatures occur more often in the FUB data, but on 25% of winter days the Area A where PSCs might form where larger in the SSU data. Seasonally integrated values of A show a fairly good agreement between the two data sets, the satellite-derived values generally being smaller. Both systems give stable and consistent estimates of the areas of low temperature at 50 hPa. On the basis of data quality alone, it is not possible to recommend either analysis system in preference to the other for studies of the coldness of the polar stratosphere."

Out of this very detailed comparison only one figure is shown here, (Fig.29), which is Fig.2 in the report. The text describing the figure is cited here:

"Fig.2a shows a histogram illustrating the number of recorded T values at all gridpoints poleward of 40N in the FUB analyses on all days in the 16 winters (November - March). The data were binned into 1K wide intervals for this presentation. The display is cut off at the lowest analyzed TFUB = 183K and at 220K, which is well above Tnat. There are few occurrences of extremely low T but the number begins to increase quickly for T larger than 189K, before levelling off near T = 212K. The second histogram in Fig.2a shows the number of records of each TFUB at times when the SSU data were available. Although the sample is clearly smaller the missing days do not change the shape of the distribution, so the SSU sampling is adequate for this intercomparison. There is evidence of peaks at 5K intervals in the number of records; this is presumably because the FUB analyses are made with a contour interval of 5K and the digitizing mechanism cannot extrapolate to local minima inside closed isotherms.

The rms difference in T remains remarkably constant, close to 3K, at all TFUB (Fig.2b). There is some hint of a temperature dependence in the bias, since the mean difference [T] decreases slowly with increasing TFUB, from about -1.5K near TFUB = 190K to around zero at TFUB = 220K; the envelope of extreme differences moves towards stronger positive and weaker negative values as TFUB increases.

These differences must be attributed to the two observation and analysis systems: they are consistent with the "local" nature of radiosonde measurements and the "vertically smoothed" character of temperatures derived from satellite-based radiance measurements, at least with retrievals of the kind used in the SSU data set."

[Statistics for the 50-hPa Temperature]

Figure 29: Statistics for T at 50 hPa, binned into 1K intervals, at all gridpoints poleward of 40N, and for T <= 220K. (a) Histogram showing the frequency of occurrence of TFUB on all days (gray) and on days with coincident SSU data (black); (b) Plot showing TFUB against T (K). The envelope is shaded; the mean and rms differences are depicted by thick solid and dashed lines. All days in November through March, 1979 until 1996, were used

4.4 References

Manney, G.L., J. L. Sabutis, S. Pawson, M. L. Santee, B. Naujokat, R. Swinbank, M. E. Gelman, and W. Ebisuzaki, 2002: Lower stratospheric temperature differences between meteorological analyses in two cold Arctic winters and theirimpact on polar processing studies. J. Geophys. Res., 107, in press.

Ramaswamy, V., M. L. Chanin, J. Angell, J. Barnett, D. Gaffen, M. Gelman, P. Keckhut, Y. Koshelkov, K. Labitzke, J. J. R. Lin, A. O'Neil, J. Nash, W. Randel, R. Rood, K. Shine, M. Shiotani, and R. Swinbank, 2001: Stratospheric temperature trends: Observations and model simulations. Review of Geophysics, 39, 71-122.

Pawson, S., K. Krüger, R. Swinbank, M. Bailey and A. O'Neill, 1999: Intercomparison of two stratospheric analyses: temperatures relevant to polar stratospheric cloud formation. J. Geophys. Res., 104, 2041-2050.


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