ALBERT

Description: The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenith-scattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of ∼0.2 Pmolec.cm-2 (5 %–10 %) and a dispersion of 0.2 to 1 Pmolec.cm-2 with respect to the ZSL-DOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec.cm-2) up to −10 Pmolec.cm-2 (−40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (−1 to −4 Pmolec.cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.

Description: In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Description: 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.

Description: Zenith-Sky scattered light Differential Optical Absorption Spectroscopy (ZS-DOAS) has been used widely to retrieve total column ozone (TCO). ZS-DOAS measurements have the advantage of being less sensitive to clouds than direct-sun measurements. However, the presence of clouds still affects the quality of ZS-DOAS TCO. Clouds are thought to be the largest contributor to random uncertainty in ZS-DOAS TCO, but their impact on data quality still needs to be quantified. This study has two goals: (1) to investigate whether clouds have a significant impact on ZS-DOAS TCO, and (2) to develop a cloud-screening algorithm to improve ZS-DOAS measurements in the Arctic under cloudy conditions. To quantify the impact of weather, 8 years of measured and modelled TCO have been used, along with information about weather conditions at Eureka, Canada (80.05∘ N, 86.41∘ W). Relative to direct-sun TCO measurements by Brewer spectrophotometers and modelled TCO, a positive bias is found in ZS-DOAS TCO measured in cloudy weather, and a negative bias is found for clear conditions, with differences of up to 5 % between clear and cloudy conditions. A cloud-screening algorithm is developed for high latitudes using the colour index calculated from ZS-DOAS spectra. The quality of ZS-DOAS TCO datasets is assessed using a statistical uncertainty estimation model, which suggests a 3 %–4 % random uncertainty. The new cloud-screening algorithm reduces the random uncertainty by 0.6 %. If all measurements collected during cloudy conditions, as identified using the weather station observations, are removed, the random uncertainty is reduced by 1.3 %. This work demonstrates that clouds are a significant contributor to uncertainty in ZS-DOAS TCO and proposes a method that can be used to screen clouds in high-latitude spectra.

Description: The long-term evolution of total ozone column inside the Antarctic polar vortex is investigated over the 1980–2017 period. Trend analyses are performed using a multilinear regression (MLR) model based on various proxies for the evaluation of ozone interannual variability (heat flux, quasi-biennial oscillation, solar flux, Antarctic oscillation and aerosols). Annual total ozone column measurements corresponding to the mean monthly values inside the vortex in September and during the period of maximum ozone depletion from 15 September to 15 October are used. Total ozone columns from the Multi-Sensor Reanalysis version 2 (MSR-2) dataset and from a combined record based on TOMS and OMI satellite datasets with gaps filled by MSR-2 (1993–1995) are considered in the study. Ozone trends are computed by a piece-wise trend (PWT) proxy that includes two linear functions before and after the turnaround year in 2001 and a parabolic function to account for the saturation of the polar ozone destruction. In order to evaluate average total ozone within the vortex, two classification methods are used, based on the potential vorticity gradient as a function of equivalent latitude. The first standard one considers this gradient at a single isentropic level (475 or 550 K), while the second one uses a range of isentropic levels between 400 and 600 K. The regression model includes a new proxy (GRAD) linked to the gradient of potential vorticity as a function of equivalent latitude and representing the stability of the vortex during the studied month. The determination coefficient (R2) between observations and modelled values increases by ∼ 0.05 when this proxy is included in the MLR model. Highest R2 (0.92–0.95) and minimum residuals are obtained for the second classification method for both datasets and months. Trends in September over the 2001–2017 period are statistically significant at 2σ level with values ranging between 1.84 ± 1.03 and 2.83 ± 1.48 DU yr−1 depending on the methods and considered proxies. This result confirms the recent studies of Antarctic ozone healing during that month. Trends from 2001 are 2 to 3 times smaller than before the turnaround year, as expected from the response to the slowly ozone-depleting substances decrease in polar regions. For the first time, significant trends are found for the period of maximum ozone depletion. Estimated trends from 2001 for the 15 September–15 October period over 2001–2017 vary from 1.21 ± 0.83 to 1.96 DU ± 0.99 yr−1 and are significant at 2σ level. MLR analysis is also applied to the ozone mass deficit (OMD) metric for both periods, considering a threshold at 220 DU and total ozone columns south of 60∘ S. Significant trend values are observed for all cases and periods. A decrease of OMD of 0.86 ± 0.36 and 0.65 ± 0.33 Mt yr−1 since 2001 is observed in September and 15 September–15 October, respectively. Ozone recovery is also confirmed by a steady decrease of the relative area of total ozone values lower than 175 DU within the vortex in the 15 September–15 October period since 2010 and a delay in the occurrence of ozone levels below 125 DU since 2005.

Description: Long-term variability in ozone trends was assessed over eight Southern Hemisphere tropical and subtropical sites (Natal, Nairobi, Ascension Island, Java, Samoa, Fiji, Reunion and Irene), using total column ozone data (TCO) and vertical ozone profiles (altitude range 15–30 km) recorded during the period January 1998–December 2012. The TCO datasets were constructed by combination of satellite data (OMI and TOMS) and ground-based observations recorded using Dobson and SAOZ spectrometers. Vertical ozone profiles were obtained from balloon-sonde experiments which were operated within the framework of the SHADOZ network. The analysis in this study was performed using the Trend-Run model. This is a multivariate regression model based on the principle of separating the variations of ozone time series into a sum of several forcings (annual and semi-annual oscillations, QBO (Quasi-Biennial Oscillation), ENSO, 11-year solar cycle) that account for most of its variability. The trend value is calculated based on the slope of a normalized linear function which is one of the forcing parameters included in the model. Three regions were defined as follows: equatorial (0–10∘ S), tropical (10–20∘ S) and subtropical (20–30∘ S). Results obtained indicate that ozone variability is dominated by seasonal and quasi-biennial oscillations. The ENSO contribution is observed to be significant in the tropical lower stratosphere and especially over the Pacific sites (Samoa and Java). The annual cycle of ozone is observed to be the most dominant mode of variability for all the sites and presents a meridional signature with a maximum over the subtropics, while semi-annual and quasi-biannual ozone modes are more apparent over the equatorial region, and their magnitude decreases southward. The ozone variation mode linked to the QBO signal is observed between altitudes of 20 and 28 km. Over the equatorial zone there is a strong signal at ∼26 km, where 58 % ±2 % of total ozone variability is explained by the effect of QBO. Annual ozone oscillations are more apparent at two different altitude ranges (below 24 km and in the 27–30 km altitude band) over the tropical and subtropical regions, while the semi-annual oscillations are more significant over the 27–30 km altitude range in the tropical and equatorial regions. The estimated trend in TCO is positive and not significant and corresponds to a variation of ∼1.34±0.50 % decade−1 (averaged over the three regions). The trend estimated within the equatorial region (0–15∘ S) is less than 1 % per decade, while it is assessed at more than 1.5 % decade−1 for all the sites located southward of 17∘ S. With regard to the vertical distribution of trend estimates, a positive trend in ozone concentration is obtained in the 22–30 km altitude range, while a delay in ozone improvement is apparent in the UT–LS (upper troposphere–lower stratosphere) below 22 km. This is especially noticeable at approximately 19 km, where a negative value is observed in the tropical regions.

Description: This paper assesses the quality of IASI (Infrared Atmospheric Sounding Interferometer)/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3; v20151001) software for 9 years (2008–July 2017) through an extensive intercomparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). Compared with the previous version of FORLI-O3 (v20140922), several improvements have been introduced in FORLI-O3 v20151001, including absorbance look-up tables recalculated to cover a larger spectral range, with additional numerical corrections. This leads to a change of ∼4 % in the total ozone column (TOC) product, which is mainly associated with a decrease in the retrieved O3 concentration in the middle stratosphere (above 30 hPa/25 km). IASI-A and IASI-B TOCs are consistent, with a global mean difference of less than 0.3 % for both daytime and nighttime measurements; IASI-A is slightly higher than IASI-B. A global difference of less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A is lower than IASI-B), which is partly due to a temporary issue related to the IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2 (Global Ozone Monitoring Experiment-2), Dobson, Brewer, SAOZ (Système d'Analyse par Observation Zénithale) and FTIR (Fourier transform infrared) TOCs, with global mean differences in the range of 0.1 %–2 % depending on the instruments compared. The worst agreement with UV–vis retrieved TOC (satellite and ground) is found at the southern high latitudes. The IASI-A and ground-based TOC comparison for the period from 2008 to July 2017 shows the long-term stability of IASI-A, with insignificant or small negative drifts of 1 %–3 % decade−1. The comparison results of IASI-A and IASI-B against smoothed FTIR and ozonesonde partial O3 columns vary with altitude and latitude, with the maximum standard deviation being seen for the 300–150 hPa column (20 %–40 %) due to strong ozone variability and large total retrievals errors. Compared with ozonesonde data, the IASI-A and IASI-B O3 TROPO column (defined as the column between the surface and 300 hPa) is positively biased in the high latitudes (4 %–5 %) and negatively biased in the midlatitudes and tropics (11 %–13 % and 16 %–19 %, respectively). The IASI-A-to-ozonesonde TROPO comparison for the period from 2008 to 2016 shows a significant negative drift in the Northern Hemisphere of -8.6±3.4 % decade−1, which is also found in the IASI-A-to-FTIR TROPO comparison. When considering the period from 2011 to 2016, the drift value for the TROPO column decreases and becomes statistically insignificant. The observed negative drifts of the IASI-A TROPO O3 product (8 %–16 % decade−1) over the 2008–2017 period might be taken into consideration when deriving trends from this product and this time period.

Description: Subpolar regions in the southern hemisphere are influenced by the Antarctic polar vortex during austral spring, which induces high and short term ozone variability at different altitudes mainly into the stratosphere. This variation may affect considerably the total ozone column changing the harmful UV radiation that reaches the surface. With the aim to study ozone with high time resolution at different altitudes in subpolar regions, a Millimeter Wave Radiometer (MWR) was installed at the Observatorio Atmosférico de la Patagonia Austral (OAPA), Río Gallegos, Argentina, (51.6° S; 69.3° W) by 2011. This instrument provides ozone profiles with time resolution of ~ 1 hour which enables studies of short term ozone mixing ratio variability from 25 to 70 km in altitude. This work presents the MWR ozone observations between October 2014 and 2015 focusing on an atypical event of polar vortex and ozone hole influence over Río Gallegos detected from the MWR measurements at 27 and 37 km during November of 2014. The advected potential vorticity (APV) calculated from the high-resolution advection model MIMOSA (Modélisation Isentrope du transport Méso-échelle de l'Ozone Stratosphérique par Advection) was also analysed at 675 and 950 K to understand and explain the dynamic at both altitudes and correlate the ozone rapid variation during the event with the passage of the polar vortex. In addition, the MWR dataset were compared for first time with measurements obtained from Microwave Limb Sounder (MLS) at individual altitude levels (27 km, 37 km and 65 km) and with the Differential Absorption Lidar (DIAL) installed in OAPA to analyse the correspondence between the MWR and independent instruments. The MWR-MLS comparison presents reasonable correlation with a mean bias error of +5 %, −11 % and −7 % at 27 km, 37 km and 65 km, respectively. The MWR-DIAL comparison at 27 km presents also good agreement with a mean bias error of −1 %.