Network For The Detection Of Atmospheric Composition Change Research Articles

Atmospheric HCFC-22 total columns near St. Petersburg: stabilization with start of a decrease

ABSTRACTWe study the changes in the growth rate of atmospheric HCFC-22 (CHClF2, or chlorodifluoromethane) total column (TC) in the vicinity of St. Petersburg, Russia (60° N). Although HCFC-22 surface concentrations at the two nearest sites of the Halocarbons and other Atmospheric Trace Species group (HATS) (53.3° N and 71.3° N) and mean HCFC-22 mixing ratios in the upper troposphere measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE FTS) in the latitude range of 55‒65° N continue to increase, their growth rate is slowing down, especially in the last three years. Analysis of the temporal variability of HCFC-22 TCs measured at the St. Petersburg site of Network for the Detection of Atmospheric Composition Change (NDACC) shows that its total atmospheric abundancy reached a maximum in 2016‒2017 and is currently decreasing. Thus, the measurements in the atmosphere above St. Petersburg have detected a local decrease of the HCFC-22 content, which demonstrates the effectiveness of restrictions on the production of HCFC-22.

Temperature and water vapour measurements in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC)

Abstract. The BASIL Raman lidar system entered the International Network for the Detection of Atmospheric Composition Change (NDACC) in 2012. Since then, measurements have been carried out routinely on a weekly basis. This paper reports specific measurement results from this effort, with a dedicated focus on temperature and water vapour profile measurements. The main objective of this research effort is to provide a characterisation of the system performance. The results illustrated in this publication demonstrate the ability of BASIL to perform measurements of the temperature profile up to 50 km and of the water vapour mixing ratio profile up to 15 km, when considering an integration time of 2 h and a vertical resolution of 150–600 m; the mean measurement accuracy, determined based on comparisons with simultaneous and co-located radiosondes, is 0.1 K (for the temperature profile) and 0.1 g kg−1 (for the water vapour mixing ratio profile) up to the upper troposphere. The relative humidity profiling capability up to the tropopause is also demonstrated by combining simultaneous temperature and water vapour profile measurements. Raman lidar measurements are compared with measurements from additional instruments, such as radiosondes and satellite sensors (IASI and AIRS), as well as with model reanalyses data (ECMWF and ECMWF-ERA). We focused our attention on six case studies collected during the first 2 years of system operation (November 2013–October 2015). Comparisons between BASIL and the different sensor/model data in terms of the water vapour mixing ratio indicate biases in the altitudinal interval between 2 and 15 km that are always within ±1 g kg−1 (or ±50 %), with minimum values being observed in the comparison between BASIL and radiosonde measurements (±20 % up to 15 km). Results also indicate a vertically averaged mean mutual bias of −0.026 g kg−1 (or −3.8 %), 0.263 g kg−1 (or 30.0 %), 0.361 g kg−1 (or 23.5 %), −0.297 g kg−1 (or −25 %) and −0.296 g kg−1 (or −29.6 %) when comparing BASIL with radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The vertically averaged mean absolute mutual biases are somewhat higher, i.e. 0.05 g kg−1(or 16.7 %), 0.39 g kg−1 (or 23.0 %), 0.57 g kg−1 (or 23.5 %), 0.32 g kg−1 (or 29.6 %) and 0.52 g kg−1 (or 53.3 %), when comparing BASIL with radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The comparisons in terms of temperature measurements indicate mutual biases in the altitudinal interval between 3 and 30 km that are always within ±3 K, with minimum values being observed in the comparison between BASIL and radiosonde measurements (±2 K within this same altitudinal interval). Results also reveal mutual biases within ±3 K up to 50 km for most sensor/model pairs. Furthermore, a vertically averaged mean mutual bias of −0.03, 0.21, 1.95, 0.14 and 0.43 K is found between BASIL and the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively. The vertically averaged absolute mean mutual biases between BASIL and the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA are 1.28, 1.30, 3.50, 1.76 and 1.63 K respectively. Based on the available dataset and benefiting from the fact that the BASIL Raman lidar could be compared with all other sensor/model data, it was possible to estimate the overall bias of all sensors/datasets: −0.04 g kg−1 ∕ 0.19 K, 0.20 g kg−1 ∕ 0.22 K, −0.31 g kg−1 ∕ −0.02 K, −0.40 g kg−1 ∕ −1.76 K, 0.25 g kg−1 ∕ 0.04 K and 0.25 g kg−1 ∕ −0.24 K for the water vapour mixing ratio/temperature profile measurements carried out by BASIL, the radiosondes, IASI, AIRS, ECMWF and ECMWF-ERA respectively.

Water Vapour and Temperature Measurements by Raman Lidar in the Frame of the NDACC

In November 2012, the University of BASILicata Raman Lidar system (BASIL) was approved to enter the International Network for the Detection of Atmospheric Composition Change (NDACC). Since then measurements were routinely carried out on a once per week basis. This paper illustrates specific measurement examples from this effort, with a dedicated focus on temperature and water vapour measurements, with the ultimate goal to provide a characterization of the system performance. Case studies illustrated in this paper demonstrate the ability of BASIL to perform measurements of the temperature profile up to 50 km and of the water vapour mixing ratio profile up to 15 km, based on an integration time of 2 hours and a vertical resolution of 150 m, with measurement bias not exceeding 0.1 K and 0.1 g kg−1, respectively. Raman lidar measurements are compared with measurements from additional instruments, such as radiosondings and satellite sensors (IASI and AIRS), and with model re-analyses data (ECMWF and ECMWF-ERA). Comparisons in this paper cover the altitude interval up to 15 km for water vapour mixing ratio and up to 50 km for the temperature. Comparisons between BASIL and the different sensor/model data in terms of water vapour mixing ratio indicate a mean absolute/relative bias of -0.024 g kg−1(or -3.9 %), 0.342 g kg−1(or 36.8 %), 0.346 g kg−1 (or 37.5 %), -0.297 g kg−1 (or -25 %), -0.381 g kg−1 (or -31 %), when compared with radisondings, AIRS, IASI, ECMWF, ECMWF-ERA, respectively. For what concerns the comparisons in terms of temperature measurements, these indicate a mean absolute bias between BASIL and the radisondings, AIRS, IASI, ECMWF, ECMWF-ERA of -0.04, 1.99, 0.48, 0.14, 0.62 K, respectively. Based on the available dataset and benefiting from the circumstance that the Raman lidar BASIL could be compared with all other sensor/model data, it has been possible to estimate the absolute bias of all sensors/datasets, this being 0.004 g kg−1/0.30 K, 0.021 g kg−1/-0.34 K, -0.35 g kg−1/0.18 K, -0.346 g kg−1/-1.63 K, 0.293 g kg−1/-0.16 K and 0.377 g kg−1/0.32 K in terms of water vapour mixing ratio/temperature for BASIL, the radisondings, IASI, AIRS, ECMWF, ECMWF-ERA, respectively.

TCCON and NDACC X<sub>CO</sub> measurements: difference, discussion and application

Abstract. Column-averaged dry-air mole fraction of CO (XCO) measurements are obtained from two ground-based Fourier transform infrared (FTIR) spectrometer networks: the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). In this study, the differences between the TCCON and NDACC XCO measurements are investigated and discussed based on six NDACC–TCCON sites using data over the period 2007–2017. A direct comparison shows that the NDACC XCO measurements are about 5.5 % larger than the TCCON data at Ny-Ålesund, Bremen, and Izaña (Northern Hemisphere), and the absolute bias between the NDACC and TCCON data is within 2 % at Saint-Denis, Wollongong and Lauder (Southern Hemisphere). The hemispheric dependence of the bias is mainly attributed to their smoothing errors. The systematic smoothing error of the TCCON XCO data varies in the range between 0.2 % (Bremen) and 7.9 % (Lauder), and the random smoothing error varies in the range between 2.0 % and 3.6 %. The systematic smoothing error of NDACC data is between 0.1 % and 0.8 %, and the random smoothing error of NDACC data is about 0.3 %. For TCCON data, the smoothing error is significant because it is higher than the reported uncertainty, particularly at Southern Hemisphere sites. To reduce the influence from the a priori profiles and different vertical sensitivities, the scaled NDACC a priori profiles are used as the common a priori profiles for comparing TCCON and NDACC retrievals. As a result, the biases between TCCON and NDACC XCO measurements become more consistent (5.6 %–8.5 %) with a mean value of 6.8 % at these sites. To determine the sources of the remaining bias, regular AirCore measurements at Orléans and Sodankylä are compared to co-located TCCON measurements. It is found that TCCON XCO measurements are 6.1 ± 1.6 % and 8.0 ± 3.2 % smaller than the AirCore measurements at Orléans and Sodankylä, respectively, indicating that the scaling factor of TCCON XCO data should be around 1.0000 instead of 1.0672. Further investigations should be carried out in the TCCON community to determine the correct scaling factor to be applied to the TCCON XCO data. This paper also demonstrates that the smoothing error must be taken into account when comparing FTIR XCO data, and especially TCCON XCO data, with model or satellite data.

Investigation of Arctic middle-atmospheric dynamics using 3 years of H<sub>2</sub>O and O<sub>3</sub> measurements from microwave radiometers at Ny-Ålesund

Abstract. We used 3 years of water vapour and ozone measurements to study the dynamics in the Arctic middle atmosphere. We investigated the descent of water vapour within the polar vortex, major and minor sudden stratospheric warmings and periodicities at Ny-Ålesund. The measurements were performed with the two ground-based microwave radiometers MIAWARA-C and GROMOS-C, which have been co-located at the AWIPEV research base at Ny-Ålesund, Svalbard (79∘ N, 12∘ E), since September 2015. Both instruments belong to the Network for the Detection of Atmospheric Composition Change (NDACC). The almost continuous datasets of water vapour and ozone are characterized by a high time resolution of the order of hours. A thorough intercomparison of these datasets with models and measurements from satellite, ground-based and in situ instruments was performed. In the upper stratosphere and lower mesosphere the MIAWARA-C water vapour profiles agree within 5 % with SD-WACCM simulations and ACE-FTS measurements on average, whereas AuraMLS measurements show an average offset of 10 %–15 % depending on altitude but constant in time. Stratospheric GROMOS-C ozone profiles are on average within 6 % of the SD-WACCM model, the AuraMLS and ACE-FTS satellite instruments and the OZORAM ground-based microwave radiometer which is also located at Ny-Ålesund. During these first 3 years of the measurement campaign typical phenomena of the Arctic middle atmosphere took place, and we analysed their signatures in the water vapour and ozone measurements. Two major sudden stratospheric warmings (SSWs) took place in March 2016 and February 2018 and three minor warmings were observed in early 2017. Ozone-rich air was brought to the pole and during the major warmings ozone enhancements of up to 4 ppm were observed. The reversals of the zonal wind accompanying a major SSW were captured in the GROMOS-C wind profiles which are retrieved from the ozone spectra. After the SSW in February 2018 the polar vortex re-established and the water vapour descent rate in the mesosphere was 355 m d−1. Inside of the polar vortex in autumn we found the descent rate of mesospheric water vapour from MIAWARA-C to be 435 m d−1 on average. We find that the water vapour descent rate from SD-WACCM and the vertical velocity w‾* of the residual mean meridional circulation from SD-WACCM are substantially higher than the descent rates of MIAWARA-C. w‾* and the zonal mean water vapour descent rate from SD-WACCM agree within 10 % after the SSW, whereas in autumn w‾* is up to 40 % higher. We further present an overview of the periodicities in the water vapour and ozone measurements and analysed seasonal and interannual differences.

Calibration of a water vapour Raman lidar using GRUAN-certified radiosondes and a new trajectory method

Abstract. Raman lidars have been designated as potential candidates for trend studies by the Network for the Detection of Atmospheric Composition Change (NDACC) and GCOS (Global Climate Observing System) Reference Upper Air Network (GRUAN); however, for such studies improved calibration techniques are needed as well as careful consideration of the calibration uncertainties. Trend determinations require frequent, accurate, and well-characterized measurements. However, water vapour Raman lidars produce a relative measurement and require calibration in order to transform the measurement into a mixing ratio, a conserved quantity when no sources or sinks for water vapour are present. Typically, the calibration is done using a reference instrument such as a radiosonde. We present an improved trajectory technique to calibrate water vapour Raman lidars based on the previous work of Whiteman et al. (2006), Leblanc and Mcdermid (2008), Adam et al. (2010), and Herold et al. (2011), who used radiosondes as an external calibration source and matched the lidar measurements to the corresponding radiosonde measurement. However, they did not consider the movement of the radiosonde relative to the air mass and fronts. Our trajectory method is a general technique which may be used for any lidar and only requires that the radiosonde report wind speed and direction. As calibrations can be affected by a lack of co-location with the reference instrument, we have attempted to improve their technique by tracking the air parcels measured by the radiosonde relative to the field of view of the lidar. This study uses GRUAN Vaisala RS92 radiosonde measurements and lidar measurements taken by the MeteoSwiss RAman Lidar for Meteorological Observation (RALMO), located in Payerne, Switzerland, from 2011 to 2016 to demonstrate this improved calibration technique. We compare this technique to the traditional radiosonde–lidar calibration technique which does not involve tracking the radiosonde and uses the same integration time for all altitudes. Both traditional and our trajectory methods produce similar profiles when the water vapour field is homogeneous over the 30 min calibration period. We show that the trajectory method reduces differences between the radiosonde and lidar by an average of 10 % when the water vapour field is not homogeneous over a 30 min calibration period. We also calculate a calibration uncertainty budget that can be performed on a nightly basis. The calibration uncertainty budget includes the uncertainties due to phototube paralysis, aerosol extinctions, the assumption of the Ångström exponent, and the radiosonde. The study showed that the radiosonde was the major source of uncertainty in the calibration at 4 % of the calibration value. This trajectory method showed small improvements for RALMO's calibration but would be more useful for stations in different climatological regions or when non-co-located radiosondes are the only available calibration source.

Variability in the Gas Composition of the Popocatépetl Volcanic Plume

Long term time series of volcanic plumes composition constitute valuable indicators of the evolution of the magmatic and volcanic systems. We present here a 4 years long time series of molecular ratios of HF/HCl, HCl/SO2 , SiF4 /SO2 , HF/SiF4 measured in the Popocat epetl 's volcanic plume using ground-based solar absorption FTIR spectroscopy. The instrument based in the NDACC (Network for the Detection of Atmospheric Composition Change) station of Altzomoni site, facing the Popocatepetl volcano, provides an unrivalled precision. The computed mean and standard deviation of the HF/HCl and HCl/SO2 ratios for this period were found to be 0.24±0.03 and 0.11±0.03, respectively. SiF4 was detected in three occasions and the SiF4 /SO2 ratios ranged between (1.9±0.5) x 10e−3 and (9.9±0.4) x 10e−3. The HBr/HCl and HBr/SO2 ratios remained below their detection limit (1.25 x 10e−4 and 1.25 x 10e−5, respectively), given that a part of the HBr has already been converted to other bromine species (e.g.: BrO, Br2 ) a few kilometers downwind of the crater. Combining our time-series with satellite SO2 fluxes and seismic data, we explain the significant long-term HCl/SO2 variations by changes in the conduit and edifice permeabilities, impacting the deep and shallow degassing processes. The high temporal resolution of the data also allows capturing the variation of the volcanic plume composition preceding and induced by a common moderate explosion at Popocatepetl volcano. We interpret the observed variations of the HCl/SO2 ratio during the explosion as a progressive decompression and release of the gas (Taquet et al. 2017) stored in the deep conduit. SiF4 /HCl versus HF/HCl is found to have a linear relation with a slope of -1/4 during the explosions, which implies a conservation of fluorine.

Significant decline of mesospheric water vapor at the NDACC site near Bern in the period 2007 to 2018

Abstract. The middle atmospheric water vapor radiometer MIAWARA is located close to Bern in Zimmerwald (46.88∘ N, 7.46∘ E; 907 m) and is part of the Network for the Detection of Atmospheric Composition Change (NDACC). Initially built in the year 2002, a major upgrade of the instrument's spectrometer allowed middle atmospheric water vapor to be continuously measured since April 2007. Thenceforward to May 2018, a time series of more than 11 years has been gathered, that makes a first trend estimate possible. For the trend estimation, a robust multilinear parametric trend model has been used. The trend model encompasses a linear term, a solar activity tracker, the El Niño–Southern Oscillation (ENSO) index and the Quasi-Biennial Oscillation (QBO) as well as the annual and semi-annual oscillation. In the time period April 2007 to May 2018 we find a significant decline in water vapor by -0.6±0.2 ppm per decade between 61 and 72 km. Below the stratopause level (∼48 km) a smaller reduction of H2O of up to -0.3±0.1 ppm per decade is detected.

Increase of Atmospheric Methane Observed from Space-Borne and Ground-Based Measurements

It has been found that the concentration of atmospheric methane (CH4) has rapidly increased since 2007 after a decade of nearly constant concentration in the atmosphere. As an important greenhouse gas, such an increase could enhance the threat of global warming. To better quantify this increasing trend, a novel statistic method, i.e. the Ensemble Empirical Mode Decomposition (EEMD) method, was used to analyze the CH4 trends from three different measurements: the mid–upper tropospheric CH4 (MUT) from the space-borne measurements by the Atmospheric Infrared Sounder (AIRS), the CH4 in the marine boundary layer (MBL) from NOAA ground-based in-situ measurements, and the column-averaged CH4 in the atmosphere (XCH4) from the ground-based up-looking Fourier Transform Spectrometers at Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). Comparison of the CH4 trends in the mid–upper troposphere, lower troposphere, and the column average from these three data sets shows that, overall, these trends agree well in capturing the abrupt CH4 increase in 2007 (the first peak) and an even faster increase after 2013 (the second peak) over the globe. The increased rates of CH4 in the MUT, as observed by AIRS, are overall smaller than CH4 in MBL and the column-average CH4. During 2009–2011, there was a dip in the increase rate for CH4 in MBL, and the MUT-CH4 increase rate was almost negligible in the mid-high latitude regions. The increase of the column-average CH4 also reached the minimum during 2009–2011 accordingly, suggesting that the trends of CH4 are not only impacted by the surface emission, however that they also may be impacted by other processes like transport and chemical reaction loss associated with [OH]. One advantage of the EEMD analysis is to derive the monthly rate and the results show that the frequency of the variability of CH4 increase rates in the mid–high northern latitude regions is larger than those in the tropics and southern hemisphere.

Ground-based ozone profiles over central Europe: incorporating anomalous observations into the analysis of stratospheric ozone trends

Abstract. Observing stratospheric ozone is essential to assess whether the Montreal Protocol has succeeded in saving the ozone layer by banning ozone depleting substances. Recent studies have reported positive trends, indicating that ozone is recovering in the upper stratosphere at mid-latitudes, but the trend magnitudes differ, and uncertainties are still high. Trends and their uncertainties are influenced by factors such as instrumental drifts, sampling patterns, discontinuities, biases, or short-term anomalies that may all mask a potential ozone recovery. The present study investigates how anomalies, temporal measurement sampling rates, and trend period lengths influence resulting trends. We present an approach for handling suspicious anomalies in trend estimations. For this, we analysed multiple ground-based stratospheric ozone records in central Europe to identify anomalous periods in data from the GROund-based Millimetre-wave Ozone Spectrometer (GROMOS) located in Bern, Switzerland. The detected anomalies were then used to estimate ozone trends from the GROMOS time series by considering the anomalous observations in the regression. We compare our improved GROMOS trend estimate with results derived from the other ground-based ozone records (lidars, ozonesondes, and microwave radiometers), that are all part of the Network for the Detection of Atmospheric Composition Change (NDACC). The data indicate positive trends of 1 % decade−1 to 3 % decade−1 at an altitude of about 39 km (3 hPa), providing a confirmation of ozone recovery in the upper stratosphere in agreement with satellite observations. At lower altitudes, the ground station data show inconsistent trend results, which emphasize the importance of ongoing research on ozone trends in the lower stratosphere. Our presented method of a combined analysis of ground station data provides a useful approach to recognize and to reduce uncertainties in stratospheric ozone trends by considering anomalies in the trend estimation. We conclude that stratospheric trend estimations still need improvement and that our approach provides a tool that can also be useful for other data sets.

The role and performance of ground-based networks in tracking the evolution of the ozone layer

In the 1980s, ground-based monitoring of the ozone layer played a key role in the discovery of the Antarctic Ozone Hole as well as in the first documentation of significant winter and spring long-term downward trends in the populated mid-latitude regions. The article summarizes the close-to-hundred-year-long history of ground-based measurements of stratospheric ozone, and more recent observations of constituents that influence its equilibrium. Ozone observations began long before the recognition of the impact of increasing emissions of manmade ozone-depleting substances on ozone and therefore on UV levels, human health, ecosystems and the Earth climate. The historical ozone observations prior to 1980s are used as a reference for the assessments of the state of the ozone layer linked to the enforcement of the Montreal Protocol. In this paper, we describe the worldwide monitoring networks and their ozone observations used to determine long-term trends with an accuracy of a few percent per decade. Since 1989, the ground-based monitoring activities have provided support for the amendments of the Montreal Protocol (MP). They include monitoring of (a) the ozone total column and the vertical distribution at global scale, (b) the ozone-depleting substances (ODS) related to the MP such as chlorofluorocarbons (CFCs), and their decomposition products in the stratosphere, and (c) the atmospheric species playing a role in ozone depletion, e.g., nitrogen oxides, water vapor, aerosols, polar stratospheric clouds. We highlight important accomplishments in the atmospheric monitoring performed by the Global Atmosphere Watch program (GAW) run under the auspices of the World Meteorological Organization (WMO) and by the Network for the Detection of Atmospheric Composition Change (NDACC). We also address the complementary roles of ground-based networks and satellite instruments. High-quality ground-based measurements have been used to evaluate ozone variabilities and long-term trends, assess chemistry climate models, and check the long-term stability of satellite data, including more recently the merged satellite time-series developed for the detection of ozone recovery at global scale, which might be further modified by climate change.

Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars

Abstract. The objective of this paper and its companion (Wing et al., 2018) is to show that ground-based lidar temperatures are a stable, accurate, and precise data set for use in validating satellite temperatures at high vertical resolution. Long-term lidar observations of the middle atmosphere have been conducted at the Observatoire de Haute-Provence (OHP), located in southern France (43.93∘ N, 5.71∘ E), since 1978. Making use of 20 years of high-quality co-located lidar measurements, we have shown that lidar temperatures calculated using the Rayleigh technique at 532 nm are statistically identical to lidar temperatures calculated from the non-absorbing 355 nm channel of a differential absorption lidar (DIAL) system. This result is of interest to members of the Network for the Detection of Atmospheric Composition Change (NDACC) ozone lidar community seeking to produce validated temperature products. Additionally, we have addressed previously published concerns of lidar–satellite relative warm bias in comparisons of upper-mesospheric and lower-thermospheric (UMLT) temperature profiles. We detail a data treatment algorithm which minimizes known errors due to data selection procedures, a priori choices, and initialization parameters inherent in the lidar retrieval. Our algorithm results in a median cooling of the lidar-calculated absolute temperature profile by 20 K at 90 km altitude with respect to the standard OHP NDACC lidar temperature algorithm. The confidence engendered by the long-term cross-validation of two independent lidars and the improved lidar temperature data set is exploited in Wing et al. (2018) for use in multi-year satellite validations.

Atmospheric CO and CH<sub>4</sub> time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements

Abstract. Atmospheric carbon monoxide (CO) and methane (CH4) mole fractions are measured by ground-based in situ cavity ring-down spectroscopy (CRDS) analyzers and Fourier transform infrared (FTIR) spectrometers at two sites (St Denis and Maïdo) on Reunion Island (21∘ S, 55∘ E) in the Indian Ocean. Currently, the FTIR Bruker IFS 125HR at St Denis records the direct solar spectra in the near-infrared range, contributing to the Total Carbon Column Observing Network (TCCON). The FTIR Bruker IFS 125HR at Maïdo records the direct solar spectra in the mid-infrared (MIR) range, contributing to the Network for the Detection of Atmospheric Composition Change (NDACC). In order to understand the atmospheric CO and CH4 variability on Reunion Island, the time series and seasonal cycles of CO and CH4 from in situ and FTIR (NDACC and TCCON) measurements are analyzed. Meanwhile, the difference between the in situ and FTIR measurements are discussed. The CO seasonal cycles observed from the in situ measurements at Maïdo and FTIR retrievals at both St Denis and Maïdo are in good agreement with a peak in September–November, primarily driven by the emissions from biomass burning in Africa and South America. The dry-air column averaged mole fraction of CO (XCO) derived from the FTIR MIR spectra (NDACC) is about 15.7 ppb larger than the CO mole fraction near the surface at Maïdo, because the air in the lower troposphere mainly comes from the Indian Ocean while the air in the middle and upper troposphere mainly comes from Africa and South America. The trend for CO on Reunion Island is unclear during the 2011–2017 period, and more data need to be collected to get a robust result. A very good agreement is observed in the tropospheric and stratospheric CH4 seasonal cycles between FTIR (NDACC and TCCON) measurements, and in situ and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite measurements, respectively. In the troposphere, the CH4 mole fraction is high in August–September and low in December–January, which is due to the OH seasonal variation. In the stratosphere, the CH4 mole fraction has its maximum in March–April and its minimum in August–October, which is dominated by vertical transport. In addition, the different CH4 mole fractions between the in situ, NDACC and TCCON CH4 measurements in the troposphere are discussed, and all measurements are in good agreement with the GEOS-Chem model simulation. The trend of XCH4 is 7.6±0.4 ppb yr−1 from the TCCON measurements over the 2011 to 2017 time period, which is consistent with the CH4 trend of 7.4±0.5 ppb yr−1 from the in situ measurements for the same time period at St Denis.

Global spectral irradiance array spectroradiometer validation according to WMO

Solar spectral irradiance measured by two recently developed array spectroradiometers (called UV-BTS and VIS-BTS) are compared to the results of a scanning double monochromator system which is certified as a travelling reference instrument by the Network for the detection of atmospheric composition change (NDACC) and fulfils the specifications of S-2 UV instruments of the world meteorological organization (WMO). The comparison took place between 15 and 18 May 2017 at the Institute of Meteorology and Climatology of the University of Hanover (IMuK) between 4:00 and 17:00UTC. The UV-BTS array spectroradiometer is equipped with special hardware to significantly reduce internal stray light which has been the limiting factor of many array spectroradiometers in the past. It covers a wavelength range of 200 nm–430 nm. The VIS-BTS covers a wider spectral range from 280 nm up to 1050 nm, and stray light reduction is achieved by mathematical methods. For the evaluation, wavelength integrated quantities and spectral global irradiance are compared. The deviation for UV index measured by the UV-BTS, is within ±1% for solar zenith angles (SZA) below 70° and increased to a maximum of ±3% for SZA between 70° and 85° when synchronisation between measurements was possible. The deviation of global spectral irradiance is smaller ±2.5% in the spectral range from 300 nm to 420 nm (evaluated for SZA < 70°). The VIS-BTS achieved the same deviation for blue light hazard as the UV-BTS for the UV index. The evaluations of global spectral irradiance data of the VIS-BTS show a deviation smaller than ±2% in the spectral range from 365 nm to 900 nm (evaluated for SZA < 70°). Below 365 nm, the deviation rises up to ±7% at 305 nm due to remaining stray light. The agreement within the limited time of the intercomparison is considered to be satisfactory for a number of applications and provides a good basis for further investigations.

NDACC harmonized formaldehyde time series from 21 FTIR stations covering a wide range of column abundances

Abstract. Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50 % can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations.For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12 % and 27 % and between 1 and 11×1014 molec cm−2, respectively. The median values among all stations are 13 % and 2.9×1014 molec cm−2 for the total systematic and random uncertainties.This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013 molec cm−2) to highly polluted levels (7×1016 molec cm−2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions.

The MUSICA IASI CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; and N&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;O products and their comparison to HIPPO, GAW and NDACC FTIR references

Abstract. This work presents the methane (CH4) and nitrous oxide (N2O) products as generated by the IASI (Infrared Atmospheric Sounding Interferometer) processor developed during the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor retrieves CH4 and N2O with different water vapour and water vapour isotopologues (as well as HNO3) and uses a single a priori data set for all the retrievals (no variation in space and time). Firstly, the characteristics and errors of the products are analytically described. Secondly, the products are comprehensively evaluated by comparisons to the following reference data measured by different techniques and from different platforms as follows: (1) aircraft CH4 and N2O profiles from the five HIAPER Pole-to-Pole Observation (HIPPO) missions; (2) continuous in situ CH4 and N2O observations performed between 2007 and 2017 at subtropical and mid-latitude high-mountain observatories (Izaña Atmospheric Observatory and Jungfraujoch, respectively) in the framework of the WMO–GAW (World Meteorological Organization–Global Atmosphere Watch) programme; (3) ground-based FTIR (Fourier-transform infrared spectrometer) measurements made between 2007 and 2017 in the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) at the subtropical Izaña Atmospheric Observatory, the mid-latitude station of Karlsruhe and the Kiruna polar site.The theoretical estimations and the comparison studies suggest a precision for the N2O and CH4 retrieval products of about 1.5–3 % and systematic errors due to spectroscopic parameters of about 2 %. The MUSICA IASI CH4 data offer a better sensitivity than N2O data. While for the latter the sensitivity is mainly limited to the UTLS (upper troposphere–lower stratosphere) region, for CH4 we are able to prove that at low latitudes the MUSICA IASI processor can detect variations that take place in the free troposphere independently from the variations in the UTLS region. We demonstrate that the MUSICA IASI data qualitatively capture the CH4 gradients between low and high latitudes and between the Southern Hemisphere and Northern Hemisphere; however, we also find an inconsistency between low- and high-latitude CH4 data of up to 5 %. The N2O latitudinal gradients are very weak and cannot be detected. We make comparisons over a 10-year time period and analyse the agreement with the reference data on different timescales. The MUSICA IASI data can detect day-to-day signals (only in the UTLS), seasonal cycles and long-term evolution (in the UTLS and for CH4 also in the free troposphere) similar to the reference data; however, there are also inconsistencies in the long-term evolution connected to inconsistencies in the used atmospheric temperature a priori data.Moreover, we present a method for analytically describing the a posteriori-calculated logarithmic-scale difference of the CH4 and N2O retrieval estimates. By correcting errors that are common in the CH4 and N2O retrieval products, the a posteriori-calculated difference can be used for generating an a posteriori-corrected CH4 product with a theoretically better precision than the original CH4 retrieval products. We discuss and evaluate two different approaches for such a posteriori corrections. It is shown that the correction removes the inconsistencies between low and high latitudes and enables the detection of day-to-day signals also in the free troposphere. Furthermore, they reduce the impact of short-term atmospheric dynamics, which is an advantage, because respective signals are presumably hardly comparable to model data. The approach that affects the correction solely on the scales on which the errors dominate is identified as the most efficient, because it reduces the inconsistencies and errors without removing measurable real atmospheric signals. We give a brief outlook on a possible usage of this a posteriori-corrected MUSICA IASI CH4 product in combination with inverse modelling.

Quality assessment of the Ozone_cci Climate Research Data Package (release 2017) – Part 2: Ground-based validation of nadir ozone profile data products

Abstract. Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically resolved ozone observations with both stratospheric and tropospheric sensitivity, on both global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV–visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonized in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone_cci). To verify their fitness for purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical, and temporal domains of validity; (b) quantification of their potential bias, noise, and drift and their dependences on major influence quantities; and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone_cci Climate Research Data Package (CRDP) released in 2017 the versatile QA and validation system Multi-TASTE, which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone_cci validation papers, reports for the first time on data content studies, information content studies and ground-based validation for both the GOME- and IASI-type climate data records combined. The ground-based reference measurements have been provided by the Network for the Detection of Atmospheric Composition Change (NDACC), NASA's Southern Hemisphere Additional Ozonesonde programme (SHADOZ), and other ozonesonde and lidar stations contributing to the World Meteorological Organisation's Global Atmosphere Watch (WMO GAW). The nadir ozone profile CRDP quality assessment reveals that all nadir ozone profile products under study fulfil the GCOS user requirements in terms of observation frequency and horizontal and vertical resolution. Yet all L2 observations also show sensitivity outliers in the UTLS and are strongly correlated vertically due to substantial averaging kernel fluctuations that extend far beyond the kernel's 15 km FWHM. The CRDP typically does not comply with the GCOS user requirements in terms of total uncertainty and decadal drift, except for the UV–visible L4 dataset. The drift values of the L2 GOME and OMI, the L3 IASI, and the L4 assimilated products are found to be overall insignificant, however, and applying appropriate altitude-dependent bias and drift corrections make the data fit for climate and atmospheric composition monitoring and modelling purposes. Dependence of the Ozone_cci data quality on major influence quantities – resulting in data screening suggestions to users – and perspectives for the Copernicus Sentinel missions are additionally discussed.

The Network for the Detection of Atmospheric Composition Change (NDACC): history, status and perspectives

Abstract. The Network for the Detection of Atmospheric Composition Change (NDACC) is an international global network of more than 90 stations making high-quality measurements of atmospheric composition that began official operations in 1991 after 5 years of planning. Apart from sonde measurements, all measurements in the network are performed by ground-based remote-sensing techniques. Originally named the Network for the Detection of Stratospheric Change (NDSC), the name of the network was changed to NDACC in 2005 to better reflect the expanded scope of its measurements. The primary goal of NDACC is to establish long-term databases for detecting changes and trends in the chemical and physical state of the atmosphere (mesosphere, stratosphere, and troposphere) and to assess the coupling of such changes with climate and air quality. NDACC's origins, station locations, organizational structure, and data archiving are described. NDACC is structured around categories of ground-based observational techniques (sonde, lidar, microwave radiometers, Fourier-transform infrared, UV-visible DOAS (differential optical absorption spectroscopy)-type, and Dobson–Brewer spectrometers, as well as spectral UV radiometers), timely cross-cutting themes (ozone, water vapour, measurement strategies, cross-network data integration), satellite measurement systems, and theory and analyses. Participation in NDACC requires compliance with strict measurement and data protocols to ensure that the network data are of high and consistent quality. To widen its scope, NDACC has established formal collaborative agreements with eight other cooperating networks and Global Atmosphere Watch (GAW). A brief history is provided, major accomplishments of NDACC during its first 25 years of operation are reviewed, and a forward-looking perspective is presented.

Validation of Carbon Monoxide Total Column Retrievals from SCIAMACHY Observations with NDACC/TCCON Ground-Based Measurements

The objective was to validate the carbon monoxide (CO) total column product inferred from Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) full-mission (2003–2011) short-wave infrared (SWIR) nadir observations using the Beer InfraRed Retrieval Algorithm (BIRRA). Globally distributed Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) ground-based (g-b) measurements were used as a true reference. Weighted averages of SCIAMACHY CO observations within a circle around the g-b observing system were utilized to minimize effects due to spatial mismatch of space-based (s-b) and g-b observations, i.e., disagreements due to representation errors rather than instrument and/or algorithm deficiencies. In addition, temporal weighted averages were examined and then the unweighted (classical) approach was compared to the weighted (non-classical) method. The delivered distance-based filtered SCIAMACHY data were in better agreement with respect to CO averages as compared to square-shaped sampling areas throughout the year. Errors in individual SCIAMACHY retrievals have increased substantially since 2005. The global bias was determined to be in the order of − 10 parts per billion in volume (ppbv) depending on the reference network and validation strategy used. The largest negative bias was found to occur in the northern mid-latitudes in Europe and North America, and was partly caused by insufficient a priori estimates of CO and cloud shielding. Furthermore, no significant trend was identified in the global bias throughout the mission. The global analysis of the CO columns retrieved by the BIRRA shows results that are largely consistent with similar investigations in previous works.

Ultraviolet radiation modelling from ground-based and satellite measurements on Reunion Island, southern tropics

Abstract. Surface ultraviolet radiation (SUR) is not an increasing concern after the implementation of the Montreal Protocol and the recovery of the ozone layer (Morgenstern et al., 2008). However, large uncertainties remain in the prediction of future changes of SUR (Bais et al., 2015). Several studies pointed out that UV-B impacts the biosphere (Erickson et al., 2015), especially the aquatic system, which plays a central part in the biogeochemical cycle (Hader et al., 2007). It can affect phytoplankton productivity (Smith and Cullen, 1995). This influence can result in either positive or negative feedback on climate (Zepp et al., 2007). Global circulation model simulations predict an acceleration of the Brewer-Dobson circulation over the next century (Butchart, 2014), which would lead to a decrease in ozone levels in the tropics and an enhancement at higher latitudes (Hegglin and Shepherd, 2009). Reunion Island is located in the tropics (21° S, 55° E), in a part of the world where the amount of ozone in the ozone column is naturally low. In addition, this island is mountainous and the marine atmosphere is often clean with low aerosol concentrations. Thus, measurements show much higher SUR than at other sites at the same latitude or at midlatitudes. Ground-based measurements of SUR have been taken on Reunion Island by a Bentham DTMc300 spectroradiometer since 2009. This instrument is affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC). In order to quantify the future evolution of SUR in the tropics, it is necessary to validate a model against present observations. This study is designed to be a preliminary parametric and sensitivity study of SUR modelling in the tropics. We developed a local parameterisation using the Tropospheric Ultraviolet and Visible Model (TUV; Madronich, 1993) and compared the output of TUV to multiple years of Bentham spectral measurements. This comparison started in early 2009 and continued until 2016. Only clear-sky SUR was modelled, so we needed to sort out the clear-sky measurements. We used two methods to detect cloudy conditions: the first was based on an observer's hourly report on the sky cover, while the second was based on applying Long and Ackerman (2000)'s algorithm to broadband pyranometer data to obtain the cloud fraction and then discriminating clear-sky windows on SUR measurements. Long et al. (2006)'s algorithm, with the co-located pyranometer data, gave better results for clear-sky filtering than the observer's report. Multiple model inputs were tested to evaluate the model sensitivity to different parameters such as total ozone column, aerosol optical properties, extraterrestrial spectrum or ozone cross section. For total column ozone, we used ground-based measurements from the SAOZ (Système d'Analyse par Observation Zénithale) spectrometer and satellite measurements from the OMI and SBUV instruments, while ozone profiles were derived from radio-soundings and the MLS ozone product. Aerosol optical properties came from a local aerosol climatology established using a Cimel photometer. Since the mean difference between various inputs of total ozone column was small, the corresponding response on UVI modelling was also quite small, at about 1 %. The radiative amplification factor of total ozone column on UVI was also compared for observations and the model. Finally, we were able to estimate UVI on Reunion Island with, at best, a mean relative difference of about 0.5 %, compared to clear-sky observations.