VALIDATION OF GOMOS HIGH RESOLUTION TEMPERATURE DATA WITH THE U. BONN LIDAR AT THE ESRANGE DURING JANUARY AND FEBRUARY 2003

Transcription

1 VALIDATION OF GOMOS HIGH RESOLUTION TEMPERATURE DATA WITH THE U. BONN LIDAR AT THE ESRANGE DURING JANUARY AND FEBRUARY 03 U. Blum and K. H. Fricke Physikalisches Institut der Universität Bonn, D Bonn, Germany ABSTRACT The Bonn University lidar is located at the Esrange (68 N, 21 E) in northern Sweden, near the city of Kiruna. During January/February 03 a measurement campaign for the validation of Mipas,, and Sciamachy data was performed. During 27 measurement runs a total of nearly 0 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 km altitude. For the period August 02 to February 03 we received 261 files containing high-resolution temperature (HRT) data, processed with the ESA operational software GOPR LV2/6.0a for the Esrange location. After removing all data that are flagged as invalid by the processor, we were left with 3 files. The range of values encountered in these files are: tangent point distances from the lidar range from 55 km to 752 km, altitudes range from 5 km to 46.5 km, temperatures range from 79 K to 432 K, and temperature errors range from 3 K to 46 K. A number of these temperature values and associated errors exceed the expected extremes in the middle atmosphere. Out of these 3 temperature profiles we could use 25 profiles for validation. Selection criteria were the simultaneous spatial and temporal coincidence of the and lidar measurements. The time window was met, when the lidar measurements started or ended within one hour around the measurement time. We used two space windows. The first window comprised all data within 0 km of the Esrange (in total 21 profiles) and the second window consisted of all profiles within 00 km of the Esrange (in total 25 data-sets). We interpolated the lidar data to the altitudes. The comparison of all available - temperature pairs in the altitude range to km showed mean values for the temperature difference of.1 K and 7.4 K in the 0 km and 00 km tangent point range windows, respectively. A t-test revealed that these differences cannot be attributed to chance, but must be real. The respective median differences are 6.5 K and 4.5 K, while the modes are 4 K for both ranges. The discrepancies of mean, median, and mode values indicate that the histogram of differences is asymmetric, which hints at systematic errors as cause for the differences. The high-resolution temperatures do not agree on average with the lidar temperatures for the available data-set. 1. LIDAR EXPERIMENT 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, during summer and winter time, when extreme states occur in the polar atmosphere. The transmitter of the lidar is a solid state Nd:YAG laser, which emits a short laser pulse of ns duration or 3 m length with a repetition rate of Hz 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 set to 1µs, resulting in an electronic altitude resolution of 1 m. Above about km altitude the backscattered light is free of aerosol contribution and thus the signal strength is 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 has to be estimated, 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 % 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 falls below %. Tab. 1 shows the accuracy and precision of a typical temperature profile with two hours integration time, taken during darkness on a clear winter night for different altitudes. Proceedings of the Second Workshop on the Atmospheric Chemistry Validation of ENVISAT (ACVE-2) ESA-ESRIN, Frascati, Italy, 3-7 May 04 (ESA SP-562, August 04) EPOGOUB

2 Figure 1. Availability of and lidar data during January/February 03. On the abscissae the date of January and February 03, respectively, is consecutively given. The left ordinate describes the quality of the lidar data given by the number of counts/shot/km at km altitude. The lidar data marked by the red + -signs refer to the left ordinate. A dotted, horizontal line at counts/shot/km gives the quality-threshold for temperature calculation. The right ordinate gives the spatial distance between the footprint and the position of the lidar. This ordinate belongs to the data marked by the green -signs. The solid, blue line marks the 0 km distance. Table 1. Accuracy and precision of a typical lidar temperature profile with two hours integration time, taken during darkness conditions on a clear winter night. accuracy precision 80 % K 8.2 % 16 K 65 1 % 2 K 2.4 % 4.7 K 0.1 % 0.2 K 0.7 % 1.4 K % 0.02 K 0.2 % 0.4 K 2. DATA BASE For validation of temperature profiles a spatial and temporal differences between the and lidar measurements should be small. Due to the high variability of the middle polar atmosphere, a spatial distance of less than 00 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 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 km altitude per laser shot. For data showing more than cnts/shot/km a temperature calculation is possible. The measurement campaign lasted from January 12 to February 18, 03. During this period lidar measurements were possible on 28 days, leading to about 0 hours of accumulated data. Fig. 1 shows the data availability of and the lidar, the spatial and temporal overlap of the measurements as well as the quality of the lidar data. Fig. 2 shows all available high resolution temperatures for August 02 February 03 and the provided temperature errors in a 00 km range around the Esrange. Obviously a large number of geophysical impossible values appears. The temperature range covers values from 80 4 K and the temperature errors reach from 3 46 K. Flagging geophysically meaningless data is obviously essential.

3 Table 2. Date, time, orbit, and scan number of the validated temperature profiles as well as the start and end times of the corresponding lidar measurements. date time orbit scan # start time end time distance / km 13-JAN-03 05:44: : : JAN-03 09:11: : : JAN-03 19:05: : : JAN-03 :43: : : JAN-03 17:36: : : JAN-03 19:16: : : JAN-03 19:22: : : 1 22-JAN-03 21:00: : : JAN-03 18:51: : : JAN-03 19:26: : : JAN-03 19:28: JAN-03 21:06: : : JAN-03 18:25: : : JAN-03 :04: JAN-03 17:54: : : JAN-03 19:03: : : JAN-03 :: : : JAN-03 18:31: : : JAN-03 17:59: : : JAN-03 19:: : : FEB-03 :: : : FEB-03 18:11: : : FEB-03 19:49: : : FEB-03 :01: : : FEB-03 19:29: : : High resolution Temperature Data High resolution Temperature Data T-error / K Figure 2. Plotted are all available high resolution temperatures for August 02 February 03 (left plot) and the provided temperature errors (right plot).

4 Temperature Comparison: - U. Bonn January 03 Orbit: 4735 Star 15Rho Pup data: :04-21:42 UT February 03 Orbit: 4992 Star 15Rho Pup data: 19:01-21:00 UT Figure 3. Comparison of high resolution and lidar temperature data for two different days. The red profiles represent the data, the blue ones those of the Esrange lidar. Altogether there were 3 temperature profiles closer than 00 km to the Esrange during the campaign time with data marked as valid. For 25 out of these profiles lidar data in close temporal coincidence and of good quality are available. Reducing the accepted spatial distance to 0 km only 21 profiles are available for validation. Tab. 2 gives the date, time, orbit and scan number of the validated temperature profiles as well as the start and end times of the corresponding lidar measurements and the spatial distance between both measurements. All data were processed with the current software version GOPR LV2 6.0a. The reprocessed dataset comprised products during other times, however we did not find data for the measurement campaigns of the lidar during July/August 02, December 03, and January/February METHOD The altitude resolution of the high resolution data is 0 m and thus much better than the altitude resolution of the lidar temperature profile, which is about 1 km. To get a validation of each individual temperature point an interpolating spline is fitted to the lidar data and the respective lidar temperature value is calculated for the altitude of each measurement. For each altitude in the overlap region between both profiles the temperature difference is calculated and counted in a histogram of 1 K bin width. All differences are defined as. The mean, median, and mode of the temperature differences are calculated and a t-test calculation gives an estimate for the probability that the measured temperature difference can be attributed to chance. These statistical calculations are performed for two spatial distance regions up to 0 km and up to 00 km. 4. RESULTS Fig. 3 shows two examples for the validation of high resolution temperatures. Red lines are the data and the blue lines stand for the lidar data. Obviously the overlap region between both instruments is quite small, covering a few kilometers above km altitude. Although the temperature profiles look quite reasonable below 32 km altitude, there occur large deviations from the lidar profile in the upper most 3 5 km. Further, the high resolution temperatures contain much more structure than the lidar data (as expected from the better altitude resolution). Thus a very good agreement among both temperature profiles cannot be expected. The validation results are shown in Fig. 4. The mean deviations are.1 K in the 0 km radius and 7.4 K in the 00 km region. The median values differ with 6.5 K and 4.5 K for the two spatial regions clearly from the mean

5 Figure 4. Temperature deviations between and lidar temperatures for all available altitudes. The left plot contains data in a 0 km radius, the right plot in a 00 km radius around the Esrange. values. This indicates together with the shape of the histogram that the deviations do not satisfy a Gaussian distribution. Apparently the high resolution temperatures contain a systematic offset. Additionally the t-test reveals that the observed deviations cannot be attributed to chance, but must be real. 5. SUMMARY For the period January/February 03 there are 25 high resolution temperature profiles which we compared with lidar temperature profiles taken in close spatial and temporal distance. The spatial distance was smaller than 00 km and the lidar temperature profiles were measured within ± 1 hour around the sounding. The accuracy of the data in the km altitude range was.1 K ( 4.4 %) in the 0 km distance and 7.4 K ( 3.2 %) in the 00 km distance. A t-test revealed that the differences for both ranges are real. The comparison of mean and median of the distribution indicates, that the data do not satisfy a Gaussian distribution, therefore it is not meaningful to determine the standard deviations of the means which are a measure for the precision of the climatological mean or the standard deviations for the distributions which are a measure for the precision of an individual measurement. Although there were certain deviations expected between both instruments, the observed differences are too large. The agreement is not acceptable. However, the high resolution temperature data are not considered as valid; the algorithm needs further improvement [Fanton d Andon, 04]. 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 EE0009 from DLR-Raumfahrt, Bonn, Germany. REFERENCES Fanton d Andon, O., level 2 processor status - may 04, Proceedings of the Envisat Validation Workshop, Frascati 04, Italy (ESA-SP-562), 04. 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 , ACKNOWLEDGEMENTS