scholarly journals Total water vapour columns derived from Sentinel 5p using the AMC-DOAS method

2021 ◽  
Author(s):  
Tobias Küchler ◽  
Stefan Noël ◽  
Heinrich Bovensmann ◽  
John Philip Burrows ◽  
Thomas Wagner ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Independent Data ◽  
Total Water ◽  
Max Planck ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Spatial Coverage

Abstract. Water vapour is the most abundant natural greenhouse gas in the Earth's atmosphere and global data sets are required for meteorological applications and climate research. The Tropospheric Ozone Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) launched on 13 October 2017 has a very high spatial resolution of around 5 km and a daily global coverage. Currently, there is no operational total water vapour product for S5P measurements. Here, we present first results of a new scientific total column water vapour (TCWV) product for S5P using the so-called Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) scheme. This method analyses spectral data between 688 and 700 nm and has already been successfully applied to measurements from the Global Monitoring Experiment (GOME) on ERS-2, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) on Envisat and GOME-2 on MetOp. The adaptation of the AMC-DOAS method to S5P data especially includes an additional post-processing procedure to correct the influences of surface albedo, cloud height and cloud fraction. The quality of the new S5P AMC-DOAS water vapour product is assessed by comparisons with data from GOME-2 on MetOp-B retrieved also with the AMC-DOAS algorithm and with four completely independent data sets, namely re-analysis data from the European Centre for Medium range Weather Forecast (ECMWF ERA5), data obtained by the Special Sensor Microwave Imager and Sounder (SSMIS) flown on the Defense Meteorological Satellite Program (DMSP) platform 16 and two scientific S5P TCWV products derived from TROPOMI measurements. Both are recently published TCWV products for S5P provided by the Max Planck Institute for Chemistry (MPIC) in Mainz and the Netherlands Institute for Space Research (SRON), Utrecht. The SRON TCWV is limited to clear sky scenes over land. These comparisons reveal a good agreement between the various data sets but also some systematic deviations between all of them. On average, the derived offset between AMC-DOAS S5P TCWV and AMC-DOAS GOME-2B TCWV is negative (around −1.5 kg m−2) over land and positive over ocean surfaces (more than 1.5 kg m−2). In contrast, SSMIS TCWV is on average lower than AMC-DOAS S5P TCWV by about 3 kg m−2. TCWV from ERA5 and S5P AMC-DOAS TCWV comparison shows spatial differences over both land and water surface. Over land there are systematical spatial structures with enhanced discrepancies between S5P AMC-DOAS TCWV and ERA5 TCWV in tropical regions. Over sea, S5P AMC-DOAS TCWV is slightly lower than ERA5 TCWV by around 2 kg m−2. The S5P AMC-DOAS TCWV and S5P TCWV from MPIC agree on average within 1 kg m−2 over both land and ocean. TCWV from SRON shows differences to AMC-DOAS S5P TCWV of around 1.2 kg m−2. All of these deviations are in line with the accuracy of these products and with the typical range of deviations of 5 kg m−2 obtained when comparing different TCWV data sets. The AMC-DOAS TCWV product for S5P provides therefore a valuable new and independent data set for atmospheric applications which also shows a better spatial coverage than the other S5P TCWV products.

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2014 ◽  
Vol 7 (3) ◽  
pp. 3021-3073 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Data Processor ◽  
Climate Analysis ◽  
Total Column

Abstract. The knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors and perform an extensive inter-comparison and validation in order to estimate their absolute accuracy and long-term stability. We use the recently reprocessed data sets retrieved by the GOME-2 instruments aboard EUMETSAT's MetOp-A and MetOp-B satellites and generated by DLR in the framework of the O3M-SAF using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines H2O/O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. We evaluate the overall consistency between about 8 months measurements from the newer GOME-2 instrument on the MetOp-B platform with the GOME-2/MetOp-A data in the overlap period. Furthermore, we compare GOME-2 results with independent TCWV data from ECMWF and with SSMIS satellite measurements during the full period January 2007–August 2013 and we perform a validation against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project. We find global mean biases as small as ± 0.03 g cm−2 between GOME-2A and all other data sets. The combined SSM/I-MERIS sample is typically drier than the GOME-2 retrievals (−0.005 g cm−2), while on average GOME-2 data overestimate the SSMIS measurements by only 0.028 g cm−2. However, the size of some of these biases are seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, but are not as evident in the validation with the ECMWF and the SSM/I + MERIS data. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three independent data sets, especially for land areas, although some discrepancies over ocean and over land areas with high humidity and a relatively large surface albedo are also present.

scholarly journals Validation of SCIAMACHY AMC-DOAS water vapour columns

2005 ◽  
Vol 5 (7) ◽  
pp. 1835-1841 ◽  
Author(s):  
S. Noël ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Water Vapour ◽  
Visible Spectral Region ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Monthly Means ◽  
Data Set ◽  
Weather Forecasts ◽  
Microwave Imager ◽  
Scanning Imaging

Abstract. A first validation of water vapour total column amounts derived from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the visible spectral region has been performed. For this purpose, SCIAMACHY water vapour data have been determined for the year 2003 using an extended version of the Differential Optical Absorption Spectroscopy (DOAS) method, called Air Mass Corrected (AMC-DOAS). The SCIAMACHY results are compared with corresponding water vapour measurements by the Special Sensor Microwave Imager (SSM/I) and with model data from the European Centre for Medium-Range Weather Forecasts (ECMWF). In confirmation of previous results it could be shown that SCIAMACHY derived water vapour columns are typically slightly lower than both SSM/I and ECMWF data, especially over ocean areas. However, these deviations are much smaller than the observed scatter of the data which is caused by the different temporal and spatial sampling and resolution of the data sets. For example, the overall difference with ECMWF data is only -0.05 g/cm2 whereas the typical scatter is in the order of 0.5 g/cm2. Both values show almost no variation over the year. In addition, first monthly means of SCIAMACHY water vapour data have been computed. The quality of these monthly means is currently limited by the availability of calibrated SCIAMACHY spectra. Nevertheless, first comparisons with ECMWF data show that SCIAMACHY (and similar instruments) are able to provide a new independent global water vapour data set.

scholarly journals The SPARC water vapour assessment II: comparison of stratospheric and lower mesospheric water vapour time series observed from satellites

2018 ◽  
Vol 11 (7) ◽  
pp. 4435-4463 ◽  
Author(s):  
Farahnaz Khosrawi ◽  
Stefan Lossow ◽  
Gabriele P. Stiller ◽  
Karen H. Rosenlof ◽  
Joachim Urban ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Data Sets ◽  
Data Set ◽  
Spatial Coverage ◽  
Modelling Studies ◽  
The Difference ◽  
The Tropics ◽  
The Antarctic ◽  
Satellite Instruments

Abstract. Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 different satellite instruments were compared in the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II). This comparison aimed to provide a comprehensive overview of the typical uncertainties in the observational database that can be considered in the future in observational and modelling studies, e.g addressing stratospheric water vapour trends. The time series comparisons are presented for the three latitude bands, the Antarctic (80∘–70∘ S), the tropics (15∘ S–15∘ N) and the Northern Hemisphere mid-latitudes (50∘–60∘ N) at four different altitudes (0.1, 3, 10 and 80 hPa) covering the stratosphere and lower mesosphere. The combined temporal coverage of observations from the 15 satellite instruments allowed the consideration of the time period 1986–2014. In addition to the qualitative comparison of the time series, the agreement of the data sets is assessed quantitatively in the form of the spread (i.e. the difference between the maximum and minimum volume mixing ratios among the data sets), the (Pearson) correlation coefficient and the drift (i.e. linear changes of the difference between time series over time). Generally, good agreement between the time series was found in the middle stratosphere while larger differences were found in the lower mesosphere and near the tropopause. Concerning the latitude bands, the largest differences were found in the Antarctic while the best agreement was found for the tropics. From our assessment we find that most data sets can be considered in future observational and modelling studies, e.g. addressing stratospheric and lower mesospheric water vapour variability and trends, if data set specific characteristics (e.g. drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.

scholarly journals Validation of SCIAMACHY AMC-DOAS water vapour columns

2005 ◽  
Vol 5 (2) ◽  
pp. 1925-1942 ◽  
Author(s):  
S. Noël ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Water Vapour ◽  
Visible Spectral Region ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Monthly Means ◽  
Data Set ◽  
Weather Forecasts ◽  
Microwave Imager ◽  
Scanning Imaging

Abstract. A first validation of water vapour total column amounts derived from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the visible spectral region has been performed. For this purpose, SCIAMACHY water vapour data have been determined for the year 2003 using an extended version of the Differential Optical Absorption Spectroscopy (DOAS) method, called Air Mass Corrected (AMC-DOAS). The SCIAMACHY results are compared with corresponding water vapour measurements by the Special Sensor Microwave Imager (SSM/I) and with model data from the European Centre for Medium-Range Weather Forecasts (ECMWF). In confirmation of previous results it could be shown that SCIAMACHY derived water vapour columns are typically slightly lower than both SSM/I and ECMWF data, especially over ocean areas. However, these deviations are much smaller than the observed scatter of the data which is caused by the different temporal and spatial sampling and resolution of the data sets. For example, the overall difference with ECMWF data is only −0.05 g/cm2 whereas the typical scatter is in the order of 0.5 g/cm2. Both values show almost no variation over the year. In addition, first monthly means of SCIAMACHY water vapour data have been computed. The quality of these monthly means is currently limited by the availability of calibrated SCIAMACHY spectra. Nevertheless, first comparisons with ECMWF data show that SCIAMACHY (and similar instruments) are able to provide a new independent global water vapour data set.

scholarly journals Long term NO<sub>2</sub> measurements in Hong Kong using LED based Long Path Differential Optical Absorption Spectroscopy

2011 ◽  
Vol 4 (6) ◽  
pp. 6615-6642
Author(s):  
K. L. Chan ◽  
D. Pöhler ◽  
G. Kuhlmann ◽  
A. Hartl ◽  
U. Platt ◽  
...  
Keyword(s):  
Hong Kong ◽  
Optical Absorption ◽  
Absorption Spectroscopy ◽  
Differential Optical Absorption Spectroscopy ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Weekly Cycle

Abstract. In this study we present the first long term measurements of atmospheric nitrogen dioxide (NO2) using a LED based Long Path Differential Optical Absorption Spectroscopy (LP-DOAS) instrument. This instrument is measuring continuously in Hong Kong since December 2009, first in a setup with a 550 m absorption path and then with a 3820 m path at about 30 m to 50 m above street level. The instrument is using a high power blue light LED with peak intensity at 450 nm coupled into the telescope using a Y-fibre bundle. The LP-DOAS instrument measures NO2 concentrations in the Kowloon Tong and Mong Kok district of Hong Kong and we compare the measurement results to concentrations reported by monitoring stations operated by the Hong Kong Environmental Protection Department in that area. Hourly averages of coinciding measurements are in reasonable agreement (R = 0.74). Furthermore, we used the long-term data set to validate the Ozone Monitoring Instrument (OMI) NO2 data product. Monthly averaged LP-DOAS and OMI measurements correlate well (R = 0.84) when comparing the data for the OMI overpass time. We analyzed weekly patterns in both data sets and found that the LP-DOAS detects a clear weekly cycle with a reduction on weekends during rush hour peaks, whereas OMI is not able to observe this weekly cycle due to its fix overpass time.

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2015 ◽  
Vol 8 (3) ◽  
pp. 1111-1133 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Temporal Stability ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Climate Analysis ◽  
Total Column

Abstract. Knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform an extensive inter-comparison in order to evaluate their consistency and temporal stability. For the analysis, the GOME-2 data sets are generated by DLR in the framework of the EUMETSAT O3M-SAF project using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines a H2O and O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O total column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. The overall consistency between measurements from the newer GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A data is evaluated in the overlap period (December 2012–June 2014). Furthermore, we compare GOME-2 results with independent TCWV data from the ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the full period January 2007–June 2014 and against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically drier than the GOME-2 retrievals, while on average GOME-2 data overestimate the SSMIS measurements by only 0.006 g cm−2. However, the size of these biases is seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, which include only data over ocean. The seasonal behaviour is not as evident when comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets, since the different biases over land and ocean surfaces partly compensate each other. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three data sets, especially for land areas, although some discrepancies (bias larger than ±0.5 g cm−2) over ocean and over land areas with high humidity or a relatively large surface albedo are observed.

scholarly journals Individual Tree Volume Equations for Red Pine in Michigan

1997 ◽  
Vol 14 (2) ◽  
pp. 53-58 ◽  
Author(s):  
Gary W. Fowler
Keyword(s):  
Red Pine ◽  
Data Sets ◽  
Regression Equations ◽  
Independent Data ◽  
Data Set ◽  
Individual Tree ◽  
Standing Trees ◽  
Pine Stands ◽  
Volume Estimates ◽  
Volume Equations

Abstract New total, pulpwood, sawtimber, and residual pulpwood cubic foot individual tree volume equations were developed for red pine in Michigan using nonlinear and multiple linear regression. Equations were also developed for Doyle, International 1/4 in., and Scribner bd ft volume, and a procedure for estimating pulpwood and residual pulpwood rough cord volumes from the appropriate cubic foot equations was described. Average ratios of residual pulpwood (i.e., topwood, cubic foot or cords) to mbf were developed for 7.6 and 9.6 in. sawtimber. Data used to develop these equations were collected during May-August 1983-1985 from 3,507 felled and/or standing trees from 27 stands in Michigan. Sixteen and 11 stands were located in the Upper and Lower Peninsulas, respectively. All equations were validated on an independent data set. Rough cord volume estimates based on the new pulpwood equation were compared with contemporary tables for 2 small cruise data sets. The new equations can be used to more accurately estimate total volume and volume per acre when cruising red pine stands. North. J. Appl. For. 14(2):53-58.

scholarly journals Long-term MAX-DOAS network observations of NO<sub>2</sub> in Russia and Asia (MADRAS) during the period 2007–2012: instrumentation, elucidation of climatology, and comparisons with OMI satellite observations and global model simulations

2014 ◽  
Vol 14 (15) ◽  
pp. 7909-7927 ◽  
Author(s):  
Y. Kanaya ◽  
H. Irie ◽  
H. Takashima ◽  
H. Iwabuchi ◽  
H. Akimoto ◽  
...  
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Satellite Observations ◽  
Global Model ◽  
Optical Absorption Spectroscopy ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Data Set ◽  
Model Simulations

Abstract. We conducted long-term network observations using standardized Multi-Axis Differential optical absorption spectroscopy (MAX-DOAS) instruments in Russia and ASia (MADRAS) from 2007 onwards and made the first synthetic data analysis. At seven locations (Cape Hedo, Fukue and Yokosuka in Japan, Hefei in China, Gwangju in Korea, and Tomsk and Zvenigorod in Russia) with different levels of pollution, we obtained 80 927 retrievals of tropospheric NO2 vertical column density (TropoNO2VCD) and aerosol optical depth (AOD). In the technique, the optimal estimation of the TropoNO2VCD and its profile was performed using aerosol information derived from O4 absorbances simultaneously observed at 460–490 nm. This large data set was used to analyze NO2 climatology systematically, including temporal variations from the seasonal to the diurnal scale. The results were compared with Ozone Monitoring Instrument (OMI) satellite observations and global model simulations. Two NO2 retrievals of OMI satellite data (NASA ver. 2.1 and Dutch OMI NO2 (DOMINO) ver. 2.0) generally showed close correlations with those derived from MAX-DOAS observations, but had low biases of up to ~50%. The bias was distinct when NO2 was abundantly present near the surface and when the AOD was high, suggesting a possibility of incomplete accounting of NO2 near the surface under relatively high aerosol conditions for the satellite observations. Except for constant biases, the satellite observations showed nearly perfect seasonal agreement with MAX-DOAS observations, suggesting that the analysis of seasonal features of the satellite data were robust. Weekend reduction in the TropoNO2VCD found at Yokosuka and Gwangju was absent at Hefei, implying that the major sources had different weekly variation patterns. While the TropoNO2VCD generally decreased during the midday hours, it increased exceptionally at urban/suburban locations (Yokosuka, Gwangju, and Hefei) during winter. A global chemical transport model, MIROC-ESM-CHEM (Model for Interdisciplinary Research on Climate–Earth System Model–Chemistry), was validated for the first time with respect to background NO2 column densities during summer at Cape Hedo and Fukue in the clean marine atmosphere.

scholarly journals The SPARC water vapour assessment II: Profile-to-profile and climatological comparisons of stratospheric <i>δ</i>D(H<sub>2</sub>O) observations from satellite

2018 ◽  
Author(s):  
Charlotta Högberg ◽  
Stefan Lossow ◽  
Ralf Bauer ◽  
Kaley A. Walker ◽  
Patrick Eriksson ◽  
...  
Keyword(s):  
Water Vapour ◽  
Atmospheric Chemistry ◽  
Lower Stratosphere ◽  
Isotopic Ratio ◽  
Michelson Interferometer ◽  
Data Sets ◽  
Data Set ◽  
Spectroscopic Database ◽  
Temporal And Spatial ◽  
Chemistry Experiment

Abstract. Within the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), we have evaluated five data sets of δD(H2O) obtained from observations of Odin/SMR (Sub-Millimetre Radiometer), Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding) and SCISAT/ACE-FTS (Science Satellite/Atmospheric Chemistry Experiment-Fourier Transform Spectrometer) using profile-to-profile and climatological comparisons. Our focus is on stratospheric altitudes, but results from the upper troposphere to the lower mesosphere are provided. There are clear quantitative differences in the measurements of the isotopic ratio, which primarily concerns the comparisons to the SMR data set. In the lower stratosphere, this data set shows a higher depletion than the MIPAS and ACE-FTS data sets. The differences maximise close to 50 hPa and exceed 200 per mille. With increasing altitude, the biases typically decrease. Above 4 hPa, the SMR data set shows a lower depletion than the MIPAS data sets, on occasion exceeding 100 per mille. Overall, the δD biases of the SMR data set are driven by HDO biases in the lower stratosphere and by H2O biases in the upper stratosphere and lower mesosphere. In between, in the middle stratosphere, the biases in δD are a combination of deviations in both HDO and H2O. These biases are attributed to issues with the calibration, in particular in terms of the sideband filtering for H2O, and uncertainties in spectroscopic parameters. The MIPAS and ACE-FTS data sets agree rather well between about 100 hPa and 10 hPa. The MIPAS data sets show less depletion below about 15 hPa (up to about 30 per mille), due to differences in both HDO and H2O. Higher up the picture is reversed, and towards the upper stratosphere the biases typically increase. This is driven by increasing biases in H2O and on occasion the differences in δD exceed 80 per mille. Below 100 hPa, the differences between the MIPAS and ACE-FTS data sets are even larger. In the climatological comparisons, the MIPAS data sets continue to show less depletion than the ACE-FTS data sets below 15 hPa during all seasons, with some variations in magnitude. The differences between the MIPAS and ACE-FTS data come from different aspects, such as differences in the temporal and spatial sampling (except for the profile-to-profile comparisons), cloud influence, vertical resolution, and the microwindows and spectroscopic database chosen. Differences between data sets from the same instrument are typically small in the stratosphere.

scholarly journals Statistical analysis of water vapour and ozone in the UT/LS observed during SPURT and MOZAIC

2008 ◽  
Vol 8 (22) ◽  
pp. 6603-6615 ◽  
Author(s):  
A. Kunz ◽  
C. Schiller ◽  
F. Rohrer ◽  
H. G. J. Smit ◽  
P. Nedelec ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Water Vapour ◽  
Trace Gases ◽  
Distribution Functions ◽  
Variance Analysis ◽  
Trace Gas ◽  
Data Sets ◽  
Data Set ◽  
Atmospheric Processes ◽  
Passenger Aircraft

Abstract. A statistical analysis for the comparability of water (H2O) and ozone (O3) data sets sampled during the SPURT aircraft campaigns and the MOZAIC passenger aircraft flights is presented. The Kolmogoroff-Smirnoff test reveals that the distribution functions from SPURT and MOZAIC trace gases differ from each other with a confidence of 95%. A variance analysis shows a different variability character in both trace gas data sets. While the SPURT H2O data only contain atmospheric processes variable on a diurnal or synoptical timescale, MOZAIC H2O data also reveal processes, which vary on inter-seasonal and seasonal timescales. The SPURT H2O data set does not represent the full MOZAIC H2O variance in the UT/LS for climatological investigations, whereas the variance of O3 is much better represented. SPURT H2O data are better suited in the stratosphere, where the MOZAIC RH sensor looses its sensitivity.

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