Airborne Multi AXis DOAS instrument and measurements of two-dimensional tropospheric trace gas distributions

The Airborne Multi AXis DOAS instrument was developed and successfully operated during four measurement campaigns. Depending on the purpose the instrument was installed on two different aeroplanes flying either close to the tropopause or in the mixing layer. In a detailed sensitivity study the possibilities of the measurements were investigated. For a qualitatively good observation of tropospheric trace gases (e.g. NO2 and HCHO) additional information about the mixing layer height and the aerosol extinction is essential. This information can be gained from either independent measurements or retrieved from the measurements themselves. For example based on the O4 observation from different lines of sight the aerosol extinction can be estimated. A very good agreement between tropospheric vertical NO2 columns for AMAXDOAS and SCIAMACHY measurements will be derived, if the AMF calculation is based on independent observation. The linear correlation between the datasets results in a slope of 1 ± 0.07. Due to the measurement system the AMAXDOAS instrument is ideal for flux estimations. For one flight just above the mixing layer the total HCHO production of Milano is estimated to 3.5*10^24 molec/s. In total the plume was 20 km wide. A detailed plume study in lee of a power plant was performed. Here the different NO2 slant column densities were used for the reconstruction of a 2-dimensional trace gas distribution. The estimated flux originating from the power plant equals 2.5*10^24 molec/s

Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements

The retrieval of trace gas, cloud, and aerosol measurements from ultraviolet, visible, and near-infrared (UVN) sensors requires precise information on surface properties that are traditionally obtained from Lambertian equivalent reflectivity (LER) climatologies. The main drawbacks of using LER climatologies for new satellite missions are that (a) climatologies are typically based on previous missions with significantly lower spatial resolutions, (b) they usually do not account fully for satellite-viewing geometry dependencies characterized by bidirectional reflectance distribution function (BRDF) effects, and (c) climatologies may differ considerably from the actual surface conditions especially with snow/ice scenarios. In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors; the algorithm is based on the full-physics inverse learning machine (FP_ILM) retrieval. Radiances are simulated using a radiative transfer model that takes into account the satellite-viewing geometry, and the inverse problem is solved using machine learning techniques to obtain the GE_LER from satellite measurements. The GE_LER retrieval is optimized not only for trace gas retrievals employing the DOAS algorithm, but also for the large amount of data from existing and future atmospheric Sentinel satellite missions. The GE_LER can either be deployed directly for the computation of air mass factors (AMFs) using the effective scene approximation or it can be used to create a global gapless geometry-dependent LER (G3_LER) daily map from the GE_LER under clear-sky conditions for the computation of AMFs using the independent pixel approximation. The GE_LER algorithm is applied to measurements of TROPOMI launched in October 2017 on board the EU/ESA Sentinel-5 Precursor (S5P) mission. The TROPOMI GE_LER/G3_LER results are compared with climatological OMI and GOME-2 LER datasets and the advantages of using GE_LER/G3_LER are demonstrated for the retrieval of total ozone from TROPOMI

Trends of tropical tropospheric ozone from 20 years of European satellite measurements and perspectives for the Sentinel-5 Precursor

In preparation of the TROPOMI/S5P launch in early 2017, a tropospheric ozone retrieval based on the convective cloud differential method was developed. For intensive tests we applied the algorithm to the total ozone columns and cloud data of the satellite instruments GOME, SCIAMACHY, OMI, GOME-2A and GOME-2B. Thereby a time series of 20 years (1995–2015) of tropospheric column ozone was generated. To have a consistent total ozone data set for all sensors, one common retrieval algorithm, namely GODFITv3, was applied and the L1 reflectances were also soft calibrated. The total ozone columns and the cloud data were input into the tropospheric ozone retrieval. However, the tropical tropospheric column ozone (TCO) for the individual instruments still showed small differences and, therefore, we harmonised the data set. For this purpose, a multilinear function was fitted to the averaged difference between SCIAMACHY's TCO and those from the other sensors. The original TCO was corrected by the fitted offset. GOME-2B data were corrected relative to the harmonised data from OMI and GOME-2A. The harmonisation leads to a better agreement between the different instruments. Also, a direct comparison of the TCO in the overlapping periods proves that GOME-2A agrees much better with SCIAMACHY after the harmonisation. The improvements for OMI were small. Based on the harmonised observations, we created a merged data product, containing the TCO from July 1995 to December 2015. A first application of this 20-year record is a trend analysis. The tropical trend is 0.7 ± 0.12 DU decade−1. Regionally the trends reach up to 1.8 DU decade−1 like on the African Atlantic coast, while over the western Pacific the tropospheric ozone declined over the last 20 years with up to 0.8 DU decade−1. The tropical tropospheric data record will be extended in the future with the TROPOMI/S5P data, where the TCO is part of the operational products

Tropospheric ozone retrieval by a combination of TROPOMI/S5P measurements with BASCOE assimilated data

We present a new tropospheric ozone dataset based on TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P) total ozone measurements combined with stratospheric ozone data from the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by assimilating ozone observations from the Microwave Limb Sounder (MLS). The BASCOE stratospheric data are interpolated to the S5P observations and subtracted from the TROPOMI total ozone data. The difference is equal to the tropospheric ozone residual column from the surface up to the tropopause. The tropospheric ozone columns are retrieved at the full spatial resolution of the TROPOMI sensor (5.5×3.5 km2) with daily global coverage. Compared to the Ozone Mapping and Profiler Suite Modern-Era Retrospective analysis for Research and Applications 2 (OMPS-MERRA-2) data, a global mean positive bias of 3.3 DU is found for the analysed period April 2018 to June 2020. A small negative bias of about −0.91 DU is observed in the tropics relative to the operational TROPOMI tropical tropospheric data based on the convective cloud differential (CCD) algorithm throughout the same period. The new tropospheric ozone data (S5P-BASCOE) are compared to a set of globally distributed ozonesonde data integrated up to the tropopause level. We found 2254 comparisons with cloud-free TROPOMI observations within 25 km of the stations. In the global mean, S5P-BASCOE deviates by 2.6 DU from the integrated ozonesondes. Depending on the latitude the S5P-BASCOE deviate from the sondes and between −4.8 and 7.9 DU, indicating a good agreement. However, some exceptional larger positive deviations up to 12 DU are found, especially in the northern polar regions (north of 70∘). The monthly mean tropospheric column and time series for selected areas showed the expected spatial and temporal pattern, such as the wave one structure in the tropics or the seasonal cycle, including a summer maximum, in the mid-latitudes.</p

MAX-DOAS measurements of tropospheric NO2 and HCHO in Nanjing and a comparison to ozone monitoring instrument observations

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by similar to 30% with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %-50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies

Two decades of homogenized satellite ozone measurements for climate services

Since the launch of GOME onboard ERS-2 in 1995 total and tropospheric ozone have been derived from European satellite instruments. In the framework of the ESA CCI and the EU ECMWF C3S projects, BIRA generates total ozone products from the satellite sensors GOME, SCIAMACHY, OMI, and GOME-2 using the GODFIT algorithm and DLR is responsible for harmonizing the total column data from all these sensors and generating a merged product, which encompasses more than two decades of global total ozone observations. Additionally, tropospheric ozone columns form the European sensors are generated by DLR using the convective cloud differential algorithm. Total and tropospheric ozone from GOME-2 onboard MetOp-A and -B are operational products from the EUMETSAT AC-SAF and within the ESA CCI project the tropical tropospheric ozone products from GOME, SCIAMACHY, OMI, and GOME-2 were harmonized and a merged data product was delivered and has been updated regularly. On a global scale a slight increase in total ozone columns is observed over the years since 1995 until today indicating that the total ozone starts to emerge into the expected recovery phase. Tropospheric data from the last 22 years show a slightly increasing trend with strong regional variations especially in the tropical eastern Pacific and Atlantic Ocean. These unique ozone datasets will be extended during the next two decades with measurements from the EU Copernicus missions Sentinel-5 Precursors (successfully launched in October 2017) and the future Sentinel-4 and Sentinel-5 missions

Tropospheric ozone column data records based on total columns from GOME, SCIAMACHY, GOME-2, OMI and TROPOMI using CCD algorithm or in combination with BASCOE/MLS

A long-term tropospheric ozone time series has been generated for the tropical band (20°S to 20°N) based on convective cloud differential algorithm (CCD). Tropical tropospheric ozone columns were retrieved from several European sensors starting with observations by GOME in 1995 and including data from SCIAMACHY, OMI, GOME-2A and GOME-2B. It has now been extended by DLR with data from GOME-2C and TROPOMI and now encompasses 25 years. The tropospheric ozone retrieval for all data sets is based on the total columns retrieved with the GODFIT algorithm and associated cloud products. There are however some differences between the different tropospheric columns from the different sensors which have to be corrected for. For the CCD time series, we used SCIAMACHY data as reference and fitted an offset and a trend correction to the data of the other sensors. We estimated the trend based on the long-term time series. For the tropics an overall trend of +0.7 DU/decade was found in the data set until 2019, varying locally between -0.5 and 1.8 DU/decade. The second data record combines total ozone columns from TROPOMI with BASCOE stratospheric ozone profiles. BASCOE stratospheric ozone data is constrained by assimilated Aura MLS observation and it is provided with 3-hour time resolutions in NRT. We used the BASCOE NRT data set to calculate the stratospheric ozone columns for every day from April 2018 to December 2020 and subtracted it from the respective NRT total columns observed by TROPOMI. The TROPOMI NRT total ozone product was updated recently including a new surface albedo retrieval algorithm. An internal reanalysis of the NRT data was used to create a consistent tropospheric ozone data set. A comparison to ozone sondes showed a good agreement for most part of the world. For the GEMS validation the TROPOMI total ozone NRT algorithm is applied to selected the GEMS data. Also, the tropospheric ozone column might be retrieved based on the TROPOMI-BASCOE algorithm described above. Both the CCD and the TROPOMI-BASCOE tropospheric ozone data will be presented. Furthermore, first results for total and troposheric ozone columns of GEMS data using the TROPOMI algorithms might be shown

Almost one year of TROPOMI/S5P total ozone column data: global ground-based validation

Póster presentado en: ATMOS 2018, celebrado en Salzburgo (Austria) del 26 al 29 de noviembre de 2018.In this work we present the validation results of almost one year of TROPOMI Near Real Time (NRTI) and OFFLine (OFFL) data against ground-based quality-assured Brewer and Dobson total ozone column (TOC) measurements deposited in the World Ozone and Ultraviolet Radiation Data Center (WOUDC). Additionally, comparisons to Brewer measurements from the European Brewer Network (EUBREWNET) and the Canadian Network are performed, as well as to twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, that form part of the SAOZ network (Système d'Analyse par Observation Zénitale) of the Network for the Detection of Atmospheric Composition Change (NDACC). Through the comparison of the TROPOMI measurements to the total ozone ground-based measurements from stations that are distributed globally, as the background truth, the dependence of the new instrument on latitude, cloud properties, solar zenith and viewing angles, among others, is examined. Validation results show that the mean bias and the standard deviation of the percentage difference between TROPOMI and QA ground TOC meet the product requirements

TROPOMI/S5P total ozone column data: global ground-based validation and consistency with other satellite missions

In this work, the TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are presented and compared to daily ground-based quality-assured Brewer and Dobson TOC measurements deposited in the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Additional comparisons to individual Brewer measurements from the Canadian Brewer Network and the European Brewer Network (Eubrewnet) are performed. Furthermore, twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, which form part of the SAOZ network (Système d'Analyse par Observation Zénitale), are used for the validation. The quality of the TROPOMI TOC data is evaluated in terms of the influence of location, solar zenith angle, viewing angle, season, effective temperature, surface albedo and clouds. For this purpose, globally distributed ground-based measurements have been utilized as the background truth. The overall statistical analysis of the global comparison shows that the mean bias and the mean standard deviation of the percentage difference between TROPOMI and ground-based TOC is within 0 –1.5 % and 2.5 %–4.5 %, respectively. The mean bias that results from the comparisons is well within the S5P product requirements, while the mean standard deviation is very close to those limits, especially considering that the statistics shown here originate both from the satellite and the ground-based measurements.This research has been supported by the European Space Agency “Preparation and Operations of the Mission Performance Centre (MPC) for the Copernicus Sentinel-5 Precursor Satellite” (contract no. 4000117151/16/1-LG)