Analysis of global water vapour trends from satellite measurements in the visible spectral range

International audienceGlobal water vapour total column amounts have been retrieved from spectral data provided by the Global Ozone Monitoring Experiment (GOME) flying on ERS-2, which was launched in April 1995, and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT launched in March 2002. For this purpose the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) approach has been used. The combination of the data from both instruments provides us with a long-term global data set spanning more than 11 years with the potential of extension up to 2020 by GOME-2 data, on Metop. Using linear and non-linear methods from time series analysis and standard statistics the trends of H2O contents and their errors have been calculated. In this study, factors affecting the trend such as the length of the time series, the magnitude of the variability of the noise, and the autocorrelation of the noise are investigated. Special emphasis has been placed on the calculation of the statistical significance of the observed trends, which reveal significant local changes of water vapour columns distributed over the whole globe. <br

Preliminary results of GOME-2 water vapour retrievals and first applications in polar regions

International audienceGlobal total water vapour columns have been derived from measurements of the Global Ozone Monitoring Experiment 2 (GOME-2) on MetOp. For this purpose, the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) method has been adapted, having previously been applied successfully to GOME (on ERS-2) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY, on ENVISAT) data. Comparisons between the derived GOME-2 and SCIAMACHY water vapour columns show a good overall agreement. This gives confidence that the temporal series of water vapour columns from GOME-type instruments (GOME/ERS-2, SCIAMACHY/ENVISAT), which began in 1995, is successfully continued by the MetOp instrumentation until at least 2020. The enhanced temporal and spatial resolution of GOME-2 enables the analysis of diurnal variations in the polar regions. This is especially important because atmospheric data sources in the polar regions are generally sparse. As an exemplary application, daily water vapour total columns over the polar research station Ny Ålesund (78°55'19" N/11°56'33" E) are investigated. At this latitude GOME-2 yields about six data points during daylight hours at varying local times. From these data diurnal variations of water vapour have been successfully retrieved

Retrieval of global water vapour columns from GOME-2 and first applications in polar regions

International audienceGlobal total water vapour columns have been derived from measurements of the Global Ozone Monitoring Experiment 2 (GOME-2) on MetOp. For this purpose, the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) method has been adapted, which has already been applied successfully to GOME (on ERS-2) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY, on ENVISAT) data. Comparisons between the derived GOME-2 and SCIAMACHY water vapour columns show a good overall agreement. This gives confidence that the time series of water vapour columns from GOME-type instruments which started in 1995 can be continued by the MetOp instrumentation until at least 2020. The enhanced temporal and spatial resolution of GOME-2 enables the analysis of short-term variations particularly in the polar regions. This is especially important since atmospheric data sources in the polar regions are generally sparse. As an exemplary application, daily water vapour concentrations over the polar research station Ny Ålesund (78°55'19" N/11°56'33" E) are investigated. At this latitude GOME-2 gives about six data points during daylight hours at varying local times. The results of this study show that it is possible to derive information about the diurnal variability of water vapour in polar regions from GOME-2 measurements

A new estimator of heat periods for decadal climate predictions - A complex network approach

Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for eight regions in Europe and quantify the skill of the model alternatively by constructing time-evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to estimate the low-frequency dynamics of heat periods is superior for decadal predictions with respect to the typical approach of using a fixed temperature threshold for estimating the number of heat periods in Europe

Global and long-term comparison of SCIAMACHY limb ozone profiles with correlative satellite data (2002–2008)

SCIAMACHY limb scatter ozone profiles from 2002 to 2008 have been compared with MLS (2005–2008), SABER (2002–2008), SAGE II (2002–2005), HALOE (2002–2005) and ACE-FTS (2004–2008) measurements. The comparison is performed for global zonal averages and heights from 10 to 50 km in one km steps. The validation was performed by comparing monthly mean zonal means and by comparing averages over collocated profiles within a zonal band and month. Both approaches yield similar results. For most of the stratosphere SCIAMACHY agrees to within 10% or better with other correlative data. A systematic bias of SCIAMACHY ozone of up to 100% between 10 and 20 km in the tropics points to some remaining issues with regard to convective cloud interference. Statistical hypothesis testing reveals at which altitudes and in which region differences between SCIAMACHY and other satellite data are statistically significant. We also estimated linear trends from monthly mean data for different periods where SCIAMACHY has common observations with other satellite data using a classical trend model with QBO and seasonal terms in order to draw conclusions on potential instrumental drifts as a function of latitude and altitude. Since the time periods considered here are rather short these trend estimates are only used to identify potential instrumental issues with the SCIAMACHY data. As a result SCIAMACHY exhibits a statistically significant negative trend in the range of of about 1–3% per year depending on latitude during the period 2002–2005 (overlapping with HALOE and SAGE II) and somewhat less during 2002–2008 (overlapping with SABER) in the altitude range of 30–40 km, while in the period 2004–2008 (overlapping with MLS and ACE-FTS) no significant trends are observed. Since all correlative satellite instruments do not show to a very large extent statistically significant trends in any of the time periods considered here, the negative trends observed with SCIAMACHY data point at some remaining instrumental artifact which is most likely related to residual errors in the tangent height registration of SCIAMACHY

Global and long-term comparison of SCIAMACHY limb ozone profiles with correlative satellite data (2002–2008)

SCIAMACHY limb scatter ozone profiles from 2002 to 2008 have been compared with MLS (2005–2008), SABER (2002–2008), SAGE II (2002–2005), HALOE (2002–2005) and ACE-FTS (2004–2008) measurements. The comparison is performed for global zonal averages and heights from 10 to 50 km in one km steps. The validation was performed by comparing monthly mean zonal means and by comparing averages over collocated profiles within a zonal band and month. Both approaches yield similar results. For most of the stratosphere SCIAMACHY agrees to within 10% or better with other correlative data. A systematic bias of SCIAMACHY ozone of up to 100% between 10 and 20 km in the tropics points to some remaining issues with regard to convective cloud interference. Statistical hypothesis testing reveals at which altitudes and in which region differences between SCIAMACHY and other satellite data are statistically significant. We also estimated linear trends from monthly mean data for different periods where SCIAMACHY has common observations with other satellite data using a classical trend model with QBO and seasonal terms in order to draw conclusions on potential instrumental drifts as a function of latitude and altitude. Since the time periods considered here are rather short these trend estimates are only used to identify potential instrumental issues with the SCIAMACHY data. As a result SCIAMACHY exhibits a statistically significant negative trend in the range of of about 1–3% per year depending on latitude during the period 2002–2005 (overlapping with HALOE and SAGE II) and somewhat less during 2002–2008 (overlapping with SABER) in the altitude range of 30–40 km, while in the period 2004–2008 (overlapping with MLS and ACE-FTS) no significant trends are observed. Since all correlative satellite instruments do not show to a very large extent statistically significant trends in any of the time periods considered here, the negative trends observed with SCIAMACHY data point at some remaining instrumental artifact which is most likely related to residual errors in the tangent height registration of SCIAMACHY