References

AMT

Atmospheric Measurement Techniques

AMT

Atmos. Meas. Tech.

1867-8548

Copernicus Publications

Göttingen, Germany

10.5194/amt-2-125-2009

Intercomparison of stratospheric ozone and temperature profiles during the October 2005 Hohenpeißenberg Ozone Profiling Experiment (HOPE)

Steinbrecht

¹ McGee

T. J.

² Twigg

L. W.

² Claude

¹ Schönenborn

¹ Sumnicht

G. K.

² Silbert

Meteorologisches Observatorium, Deutscher Wetterdienst, Hohenpeißenberg, Germany

NASA Goddard Space Flight Center, Greenbelt MD, USA

27 04 2009

2 1 125 145

2009

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Thirteen clear nights in October 2005 allowed successful intercomparison of the lidar operated since 1987 by the German Weather Service (DWD) at Hohenpeißenberg (47.8° N, 11.0° E) with the Network for the Detection of Atmospheric Composition Change (NDACC) travelling standard lidar operated by NASA's Goddard Space Flight Center. Both lidars provide ozone profiles in the stratosphere, and temperature profiles in the strato- and mesosphere. Additional ozone profiles came from on-site Brewer/Mast ozonesondes, additional temperature profiles from Vaisala RS92 radiosondes launched at Munich (65 km north-east), and from operational analyses by the US National Centers for Environmental Prediction (NCEP). The intercomparison confirmed a low bias for ozone from the DWD lidar in the 33 to 43 km region, by up to 10%. This bias is caused by the DWD ozone algorithm, and is consistent with previous comparisons of the DWD lidar with SAGE, GOMOS and other instruments. During HOPE, precision (repeatability) for ozone data from both lidars was better than 5% between 20 and 40 km altitude, dropping to 10% near 45 km, and to 50% near 50 km. These results are consistent with previous NDACC intercomparisons, and confirm the reliability of the NASA NDACC travelling standard lidar. Temperature from the DWD lidar showed a 1 to 2 K cold bias from 30 to 65 km against the NASA lidar, and a 2 to 4 K cold bias against radiosondes and NCEP. This is also consistent with previous intercomparisons. Temperature precision (repeatability) for the DWD lidar was better than 2 K from 30 to 50 km, decreasing to 10 K near 70 km. For the NASA lidar, precision is expected to be better than 1 K over the 30 to 70 km range. However, due to the much lower temperature precision of the DWD lidar, this could not be checked during HOPE. It was noted that the current DWD algorithm over-estimates temperature uncertainty, which should be reduced by a factor of 2.2 (e.g. from 22 K to 10 K near 70 km). The HOPE intercomparison did uncover a 290 m range error (upward shift) of the DWD lidar data. When this shift is removed, the bias of the ozone algorithm is corrected, and a better background estimation is used, ozone profiles from the DWD lidar agree very well with both the NASA lidar and SAGE. Systematic differences are then smaller than 3% between 20 and 44 km, and smaller than 5% between 17 and 47 km. These differences are close to zero, and are not (statistically) significant. The cold temperature bias against the NASA lidar also disappears when the DWD temperature processing is corrected for the 290 m range error, and more appropriate values for the Earth's gravity acceleration are used. Compared to the radiosondes or NCEP analyses, however, both lidars show 1 to 2 K lower temperatures over the entire 15 to 35 km range. Temperature and ozone variations are tracked well by both lidars, by ozone- and radiosondes, and by NCEP analyses. Correlations exceed 0.8 to 0.9 at most stratospheric levels. They decrease at levels above 40 km, especially for ozone or NCEP temperature. The ozone and temperature bias of the DWD lidar does not appear to have changed over time. Records of ozone and temperature from the DWD lidar should be consistent over the years. Nevertheless, the HOPE intercomparison was instrumental in uncovering and repairing several long-standing errors. HOPE also confirmed the reliability of the NASA lidar as a travelling standard. Now the entire DWD lidar data record needs to be reprocessed with the improved and revised algorithms.

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