VALIDATION OF MIPAS TEMPERATURE DATA WITH THE U. BONN LIDAR AT THE ESRANGE DURING JULY AND AUGUST 2002

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1 VALIDATION OF MIPAS TEMPERATURE DATA WITH THE U. BONN LIDAR AT THE ESRANGE DURING JULY AND AUGUST 2002 U. Blum and K. H. Fricke Physikalisches Institut der Universität Bonn, D Bonn, Germany ABSTRACT 1. LIDAR EXPERIMENT The Bonn University lidar is located at the Esrange (68 N, 21 E) in northern Sweden, near the city of Kiruna. During July/August 2002 a measurement campaign for the validation of Mipas, Gomos, and Sciamachy data was performed. During 41 measurement runs a total of nearly 350 hours integration time was accumulated. Most of the measurements could be used for the calculation of temperature profiles in the aerosol-free part of the atmosphere, which is above 30 km altitude. For the period July/August 2002 we received 56 Mipas files containing temperature data, processed with the software MIPAS/4.61 for the Esrange location. The range of values encountered in these files are: tangent point distances from the lidar range from 60 km to 995 km, altitudes range from 7 km to 70 km, temperatures range from 207 K to 283 K, and temperature errors range from 0.3 K to 2.7 K. These data ranges look quite reasonable and self-consistent. Out of these 56 Mipas temperature profiles we could use 33 profiles for validation. Selection criteria were the simultaneous spatial and temporal coincidence of the Mipas and lidar measurements. The time window was met, when the lidar measurements started or ended within one hour about the Mipas measurement time. We used two space windows. The first window comprised all data within 500 km of the Esrange (in total 11 profiles) and the second window consisted of all profiles within 1000 km of the Esrange (in total 33 data-sets). We interpolated the lidar data to each Mipas corrected altitude. The comparison of all available Mipas-Lidar temperature pairs in the altitude range 30 to 70 km showed mean values (a measure for the accuracy) for the temperature difference of 0.3 % ( 0.7 K) and 0.7 % ( 1.6 K) in the 500 km and 1000 km tangent point range windows, respectively. A t-test revealed that these differences cannot be attributed to chance, but must be real. The standard deviations of the distributions (a measure for the precision) are of the order of 2 % ( 5 K) for both range groups. While the Mipas temperatures do not agree on average with the lidar temperatures for the available data-set, the deviation is very small and fits well with the targeted accuracy for the Mipas temperature data. The Bonn University backscatter lidar [Müller et al., 1997] is located at the Esrange (68 N, 21 E), north of the Arctic circle, near the Swedish city of Kiruna. The lidar is operated on a campaign basis primarily, during summer and winter, when extreme states of the polar atmosphere occur. The transmitter of the lidar is a solid state Nd:YAG laser, which emits a short laser pulse of 10 ns duration or 3 m length with 20 Hz repetition rate on 532 nm wavelength. The backscattered light from the atmosphere is collected by a telescope system, detected by photomultipliers, and recorded by counting electronics. The elapsed time between the emission of a light pulse and the detection of the echo determines the scattering altitude. The altitude resolution is given by the width of the range gates taken for integration of the backscattered signal. In our case these range gates are 1µs wide, resulting in an electronic altitude resolution of 150 m. Above about 30 km altitude the backscattered light is free of any aerosol contribution and thus direct proportional to the molecular density of the atmosphere. Assuming hydrostatic equilibrium, the integration of the range corrected lidar net signal yields the temperature profile. At the upper end of the profile (i.e. at about km altitude) a seed temperature is required, which we take from the MSISE90 model [Hedin, 1991]. Smoothing of the raw data before temperature calculation reduces the altitude resolution to about one kilometer. The accuracy of the lidar temperature is determined only by the seed temperature as long as the measurement is not affected by aerosol contribution. The effect of the seed temperature decreases exponentially with altitude. Assuming an accuracy of 10 % of the temperature in the seed altitude results in an accuracy of 1 % in an altitude two scaleheights below the seed altitude. The precision of the temperature is determined by the measurement statistics and varies with altitude and integration time as well as with the daylight and weather conditions. The starting altitude of the temperature integration is chosen where the statistical error exceeds 10 %. Tab. 1 shows the accuracy and precision of a typical temperature profile with two hours integration time, taken during twilight on a clear summer evening in different altitudes. Proceedings of the Second Workshop on the Atmospheric Chemistry Validation of ENVISAT (ACVE-2) ESA-ESRIN, Frascati, Italy, 3-7 May 2004 (ESA SP-562, August 2004)

2 Figure 1. Availability of Mipas and lidar data during July/August On the abscissae the date of July and August 2002, respectively, is consecutively given. The left ordinate describes the quality of the lidar data given by the number of counts/shot/km at 30 km altitude. The lidar data marked by the red + -signs refer to the left ordinate. A dotted, horizontal line at 10 counts/shot/km gives the quality-threshold for temperature calculation. The right ordinate gives the spatial distance between the Mipas footprint and the position of the lidar. This ordinate belongs to the Mipas data marked by the green -signs. The solid, blue line marks the 500 km distance. Table 1. Accuracy and precision of a typical lidar temperature profile with two hours integration time, taken during twilight conditions on a clear summer evening. altitude / km accuracy precision % 20 K 10 % 20 K 60 1 % 2 K 2.2 % 4.4 K % 0.2 K 0.7 % 1.4 K % 0.02 K 0.1 % 0.2 K 2. DATA BASE For validation of Mipas temperature profiles the spatial and temporal difference between the Mipas and lidar measurements should be small. Due to the high variability of the middle polar atmosphere, a spatial distance of less than 1000 km and a small temporal interval of maximum ± 1 hour is required. The spatial distance of the measurements is determined by the footprint of the Mipas measurement, whereas the temporal spacing is given by the lidar measurements. During the campaign time the lidar is continuously operated as long as weather conditions permit. Overcast skies prevent lidar measurements and partly cloudy skies decrease the quality of the lidar measurements. The quality of the lidar data is given by the number of counts received from an one kilometer wide interval at 30 km altitude per laser shot. For data showing more than 10 cnts/shot/km a temperature calculation is possible. The measurement campaign lasted from July 15 to August 31, During this period lidar measurements were possible on 30 days, leading to about 350 hours of accumulated data. Fig. 1 shows the data availability of Mipas and the lidar, the spatial and temporal overlap of the measurements as well as the quality of the lidar data. Altogether there were 56 Mipas temperature profiles closer than 1000 km to the Esrange during the campaign time. For 33 out of these profiles lidar data in close temporal coincidence and of good quality are available. Reducing the accepted spatial distance to 500 km only 11 profiles are available for validation. Tab. 2 gives the date, time, orbit, and scan number of the validated Mipas temperature profiles as well as the start and end times of the corresponding lidar measurements and the spatial distance between both measurements. All Mipas data were

3 Table 2. Date, time, orbit, and scan number of the validated Mipas temperature profiles as well as the start and end times of the corresponding lidar measurements. Mipas Lidar date time orbit scan # start time end time distance / km 18-JUL :09: ; 20: ; 21: JUL :10: JUL :11: JUL :54: ; 19: ; 21: JUL :56: JUL :57: JUL :58: JUL :51: ; 09: ; 11: JUL :53: JUL :54: JUL :32: JUL :05: ; 21: ; 23: JUL :06: JUL :20: ; 07: ; 09: JUL :21: JUL :22: JUL :00: JUL :01: JUL :03: JUL :00: ; 20: ; 22: JUL :02: JUL :03: AUG :11: ; 21: ; 23: AUG :30: ; 07: ; 09: AUG :32: AUG :33: AUG :35: AUG :29: ; 19: ; 21: AUG :30: AUG :08: AUG :10: AUG :11: AUG :12: processed with the current software version MIPAS/4.61. The reprocessed data-set comprised Mipas products during other times, however there were no Mipas data available for additional measurement campaigns of the lidar during January/February 2003, December 2003, and January/February that the measured temperature difference is attributed to chance. These statistical calculations are performed for all coincidences in each altitude as well as for all altitudes together and for both spatial distance regions up to 500 km and up to 1000 km. Additionally the temperature difference for all measurements are counted in a histogram of 1 K bin width and the statistical calculations are performed. 3. METHOD The lidar altitude resolution of 1 km is much better than the altitude resolution of the Mipas temperature profile, which differs with altitude from 3 to 5 km. To get a validation of each individual Mipas temperature point an interpolating spline is fitted to the lidar data and the respective lidar temperature value is calculated for the corrected altitude of each Mipas measurement. For each Mipas altitude in the overlap region between both profiles the relative temperature difference is calculated. All differences are defined as Mipas Lidar. The mean and the standarddeviation of the temperature differences is calculated for each altitude. A t-test calculation gives the probability 4. RESULTS The validation results are shown in Fig. 2. The overlap between both instruments comprised the uppermost nine pointing directions of Mipas reaching from 32 to 70 km altitude. The mean deviations reach from 0.0 % to 1.5 % in the 500 km radius and from -0.2 % to 3.0 % in the 1000 km region. However, the deviations increase rapidly from 50 km on upward which represents the large influence of the seed temperature and the poorer precision in the upper part of the lidar temperature profile. Be-

4 Figure 2. Relative temperature deviation between Mipas and lidar data for the individual Mipas pointing altitudes. Shown are the extreme as well as the mean deviations for each altitude. The mean and 1-σ together with the t-test values and the probability that the observed deviation is attributed to chance is given for each altitude as well as for all data. In the left plot all data closer than 500 km to Esrange are used, in the right plot all data within 1000 km maximum distance. low 50 km altitude the agreement between Mipas and lidar is very good independent of the spatial distance. The temperatures in the two lowermost altitudes show again a small increase of the temperature deviation which might be attributed to an aerosol contribution in the atmosphere, leading to colder lidar temperatures. However, an aerosol load of less than 1 % is not determinable directly by the lidar. It can be seen clearly that the observed deviations in the individual altitudes are most probably caused by chance in the 500 km data set, whereas this cannot be stated for the data in a 1000 km spatial distance. The overall temperature deviation is 0.3 % ( 0.7 K) and 0.7 % ( 1.6 K) for 500 km and 1000 km distance regime, respectively, with 1-σ errors of 2.1 % ( 4.5 K) and 2.4 % ( 5.5 K). The data set containing all altitudes is sufficient to detect a real temperature deviation which can not be attributed to chance at least for the 1000 km distance. The comparison of all temperature values is given in the histograms in Fig. 3. The overall agreement between Mipas and lidar is quite good. In 500 km distance from the Esrange the mean temperature deviation is 0.7 K and in 1000 km distance the mean is 1.6 K. The median as well as the mode of both distributions are quite similar which is consistent with the symmetric Gaussian shape of the distribution. 5. SUMMARY For the period July/August 2002 there are 33 Mipas temperature profiles which we compared with lidar temperature profiles taken in close spatial and temporal distance. The spatial distance was smaller than 1000 km and the lidar temperature profiles were measured within ± 1 hour around the Mipas sounding. The accuracy of the Mipas data in the km altitude range was 0.7 % ( 1.6 K) in the 1000 km distance and 0.3 % ( 0.7 K) in the 500 km distance. A t-test revealed that the differences for ranges up to 500 km can be attributed to chance at the 10 % level, whereas the differences are real for larger distances. The standard deviations of the means (a measure for the precision of the climatological mean) are of the order of 0.2 % ( 0.4 K) for both range groups. The standard deviations for the distributions (a measure for the precision of an individual measurement) are close to 2.2 % ( 5 K). While the Mipas temperatures are warmer on average than the lidar temperatures for the available data-set, the deviation is small and fits well with the targeted accuracy for the Mipas temperature data.

5 Figure 3. Temperature deviations between Mipas and lidar temperatures for all available altitudes. The left plot contains data in a 500 km radius, the right plot in a 1000 km radius around the Esrange. ACKNOWLEDGEMENTS We thank the entire staff of the Esrange for the always quick and uncomplicated support during the measurement campaigns. This project is supported by grant 50EE0009 from DLR-Raumfahrt, Bonn, Germany. REFERENCES Hedin, A. E., Neutral atmosphere empirical model from the surface to the lower exosphere MSISE90, J. Geophys. Res., 96, , Müller, K.-P., G. Baumgarten, J. Siebert, and K. H. Fricke, The new lidar facility at Esrange, Kiruna, Proceedings of the 13th ESA symposium on European Rocket and Ballon Programmes and Related Research, Öland 1997, Sweden, ESA-SP-397, pp , 1997.