Search

Satellite-based observations of free-tropospheric water vapour isotopologue ratios (HDO / H 2 O, expressed in form of the δ value δ D) with good global and temporal coverage have become available recently. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses fields of specific humidity (q), temperature (T), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity (ω), the latent heating rate (Q2), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations relative to the impact achieved by the observation of q and T , which are much more easily observed by satellites and are routinely in use for atmospheric analyses. For our investigations we use an Observing System Simulation Experiment; i.e. we simulate the satellite observations of q , T , and δ D with known uncertainties and coverage (e.g. observations are not available for cloudy conditions, i.e. at locations where the atmosphere is vertically unstable). Then we use the simulated observations within a Kalman-filter-based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes (30° S to 30° N) and for 40 d between mid-July and the end of August 2016. We find that q observations generally have the largest impacts on the analyses' quality and that T observations have stronger impacts overall than δ D observations. We show that there is no significant impact of δ D observations for stable atmospheric conditions; however, for very unstable conditions, the impact of δ D observations is significant and even slightly stronger than the respective impact of T observations. Very unstable conditions are rare but are related to extreme events (e.g. storms, flooding); i.e. the δ D observations significantly impact the analyses' quality of the events that have the largest societal consequences. The fact that no satellite observations are available at the location and time of the unstable conditions indicates a remote impact of δ D observations that are available elsewhere. Concerning real-world applications, we conclude that the situation of δ D satellite observations is very promising but that further improving the model's linkage between convective processes and the larger-scale δ D fields might be needed for optimizing the assimilation impact of real-world δ D observations. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH 4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH 4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the progress made, the consistent acquisition of independent CH 4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH 4 observations from May 2018 to May 2023, coupled with ERA5 wind and a bottom-up inventory dataset based on the IPCC (Intergovernmental Panel on Climate Change) Tier 2 approach covering the Changzhi, Jincheng, and Yangquan regions of the Shanxi province. The derived emission strengths are 8.4 × 10 26 molec. s -1 (0.706 Tg yr -1 , ± 25 %), 1.4 × 10 27 molec. s -1 (1.176 Tg yr -1 , ± 20 %), and 4.9 × 10 26 molec. s -1 (0.412 Tg yr -1 , ± 21 %), respectively. Our results exhibit biases of - 18 %, 8 %, and 14 %, respectively, when compared to the IPCC Tier 2 bottom-up inventory. Larger discrepancies are found when comparing the estimates to the Copernicus Atmosphere Monitoring Service global anthropogenic emissions (CAMS-GLOB-ANT) and Emissions Database for Global Atmospheric Research (EDGARv7.0) inventories (64 %–176 %), suggesting that the two inventories may be overestimating CH 4 emissions from the studied coal mining regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and provide additional insights into CMM emission mitigation. [ABSTRACT FROM AUTHOR]

Satellite-based observations of free tropospheric water vapour isotopologue ratios (δ D) with good global and temporal coverage have become recently available. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses fields of specific humidity (q), temperature (T), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity (ω), the latent heating rate (Q 2), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations if used in addition to the observation of q and T , which are much easier to be observed by satellites and routinely in use for atmospheric analyses. For our investigations we use an Observing System Simulation Experiment, i.e. simulate the satellite observations of q , T , and δ D with known uncertainties, then use them within a Kalman filter based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes (30° S to 30° N) and for 40 days between mid-July and end of August 2016. We find that the assimilation of q and T observations alone well constrains the atmospheric q and T fields (analyses skills in the free troposphere of up to 60 %), and moderately constrains the fields of δ D, ω , Q 2, and Prcp (analyses skills of 20 %–40 %). The additional assimilation of δ D observations further improves the quality of the analyses of all variables. We use Q 2 as proxy for the presence of condensation and evaporation processes, and we show that the additional improvement is rather weak when evaporation or condensation are negligible (additional analyses skills of generally below 5 %), and strongest for high condensation rates (additional skills of about 15 % and above). The very high condensation rates (identified by large positive Q 2 values) are rare, but related to extreme events (very high ω and Prcp) that are not well captured in the analyses (for these extreme events also the analyses uncertainties of ω , Q 2, and Prcp are very large), i.e. the additional assimilation of δ D observations significantly improves the analyses of the water cycle related variables for the events when an improvement is most important. In real world satellite datasets δ D observations affected by such strong latent heating events are frequently available, suggesting that the here demonstrated additional δ D impact for the simulated world is also a realistic scenario for a real world data assimilation. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the process made, the consistent acquisition of independent CH4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH4 observations from May 2018 to May 2023, coupled with ERA5 wind covering the Changzhi, Jincheng and Yangquan regions. The derived emission strengths are 8.4× 1026 ± 1.6 × 1025 molec. s-1 (0.706 ± 0.013 Tg yr-1), 1.4 × 1027 ± 1.9 × 1025 molec. s-1 (1.176 ± 0.016 Tg yr-1), and 4.9 × 1026± 1.8 × 1025 molec. s-1 (0.412 ± 0.015 Tg yr-1), respectively. Our results exhibit biases of -18 %, 8 %, and 14 % when compared to the bottom-up inventory. Larger discrepancies are found when comparing the estimates to the CAMS-GLOB-ANT and EDGARv7.0 inventories. This suggests that the two inventories may be overestimating the CH4 emissions in the Jincheng and Yangquan regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and help to develop climate mitigation strategies. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the process made, the consistent acquisition of independent CH4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH4 observations from May 2018 to May 2023, coupled with ERA5 wind covering the Changzhi, Jincheng and Yangquan regions. The derived emission strengths are 8.4× 1026 ± 1.6 × 1025 molec. s-1 (0.706 ± 0.013 Tg yr-1), 1.4 × 1027 ± 1.9 × 1025 molec. s-1 (1.176 ± 0.016 Tg yr-1), and 4.9 × 1026± 1.8 × 1025 molec. s-1 (0.412 ± 0.015 Tg yr-1), respectively. Our results exhibit biases of -18%, 8%, and 14% when compared to the bottom-up inventory. Larger discrepancies are found when comparing the estimates to the CAMS-GLOB-ANT and EDGARv7.0 inventories. This suggests that the two inventories may be overestimating the CH4 emissions in the Jincheng and Yangquan regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and help to develop climate mitigation strategies. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO 2) air pollution provides valuable information for quantifying NO x (NO x = NO + NO 2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO 2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s -1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO 2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s -1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory. Weekly variations in NO 2 emission are highly related to anthropogenic activities, such as the transport sector. The NO 2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO 2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO 2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO 2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget. [ABSTRACT FROM AUTHOR]

The strong coupling between atmospheric circulation, moisture pathways and atmospheric diabatic heating is responsible for most climate feedback mechanisms and controls the evolution of severe weather events. However, diabatic heating rates obtained from current meteorological reanalysis show significant inconsistencies. Here, we theoretically assess with an Observation System Simulation Experiment (OSSE) the potential of the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) Infrared Atmospheric Sounding interferometer (IASI) mid-tropospheric water isotopologue data for constraining uncertainties in meteorological analysis fields. For this purpose, we use the Isotope-incorporated General Spectral Model (IsoGSM) together with a Local Ensemble Transform Kalman Filter (LETKF) and assimilate synthetic MUSICA IASI water vapour isotopologue observations. We perform four ensemble simulations, three where synthetic IASI isotopologue and humidity data are assimilated and another one where no observational data at all are assimilated. By comparing the ensemble simulations with data assimilation with water isotopologues to the one without any data assimilation we can, in contrast to the former study by Toride et al. (2021) where additionally conventional observations where considered, assess the direct impact of the IASI δD and water vapour data on the meteorological variables, especially on the heating rates and vertical velocity. The assessment is performed for the tropics in the latitude range from 10° S to 10° N. When the synthetic isotopologue data are assimilated, we derive reduced Root-Mean-Square Deviations (RMSDs) and improved skills with respect to meteorological variables (improvement by about 11–17%). When only IASI δD is assimilated the improvement in vertical velocity and heating rate is minor (up to a few percent) and restricted to the mid-troposphere. However, when water vapour alone or δD is assimilated additionally to water vapour, heating rates and vertical motion can be improved throughout the troposphere. The highest improvements, however, are derived when δD is assimilated additionally to water vapour confirming that water isotopologues hold different aspects of information than water vapour. Thus, in consequence δD offers, especially when assimilated additionally to water vapour, potential for improving diabatic heating and precipitation and thus meteorological analysis, weather forecasts and climate predictions in the tropical regions. [ABSTRACT FROM AUTHOR]

Retrieving high-precision concentrations of atmospheric trace gases from FTIR (Fourier transform infrared) spectrometry requires a precise knowledge of the instrumental performance. In this context, this paper examines the impact on the ozone (O 3) retrievals of several approaches used to characterize the instrumental line shape (ILS) function of ground-based FTIR spectrometers within NDACC (Network for the Detection of Atmospheric Composition Change). The analysis has been carried out at the subtropical Izaña Observatory (IZO, Spain) by using the 20-year time series of the high-resolution FTIR solar absorption spectra acquired between 1999 and 2018. The theoretical quality assessment and the comparison to independent O 3 observations available at IZO (Brewer O 3 total columns and electrochemical concentration cell, ECC, sondes) reveal consistent findings. The inclusion of a simultaneous retrieval of the ILS parameters in the O 3 retrieval strategy allows, on the one hand, a rough instrumental characterization to be obtained and, on the other hand, the precision of the FTIR O 3 products to be slightly improved. The improvement is of special relevance above the lower stratosphere, where the cross-interference between the O 3 vertical distribution and the instrumental performance is more significant. However, it has been found that the simultaneous ILS retrieval leads to a misinterpretation of the O 3 variations on daily and seasonal scales. Therefore, in order to ensure the independence of the O 3 retrievals and the instrumental response, the optimal approach to deal with the FTIR instrumental characterization is found to be the continuous monitoring of the ILS function by means of independent observations, such as gas cell measurements. [ABSTRACT FROM AUTHOR]

The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near-infrared and/or shortwave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument), offer higher sensitivity near the ground and are used for the retrieval of total-column-averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total-column level 2 retrieval products. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach has strong theoretical similarities to applying the spectra of the different sensors together in a single retrieval procedure but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH 4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total-column-averaged CH 4 product (XCH 4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the high-quality upper troposphere–lower stratosphere (UTLS) CH 4 partial-column information of the corresponding IASI product. As a consequence, the combined product offers additional sensitivity for the tropospheric CH 4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effect is verified by comparisons to CH 4 reference data obtained from collocated XCH 4 measurements at 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH 4 profile measurements made by 36 individual AirCore soundings, and tropospheric CH 4 data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect the actual variations of atmospheric XCH 4 , CH 4 in the UTLS, and CH 4 in the troposphere. A similar good reliability for the latter is not achievable by the individual TROPOMI and IASI products. [ABSTRACT FROM AUTHOR]

Intensive coal mining activities in the Upper Silesian Coal Basin (USCB) in southern Poland are resulting in large amounts of methane (CH4) emissions. Annual CH4 emissions reached 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hotspot in Europe, it is of importance to investigate its emission sources and make accurate emission estimates. In this study, we use satellite-based total column-averaged dry-air mole fraction of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI). In addition, the high-resolution model forecasts, XCH4 and TXCH4 , from the Copernicus Atmosphere Monitoring Service (CAMS) are used to estimate the CH4 emission rate averaged over 3 years (November 2017–December 2020) in the USCB region (49.3–50.8 ∘ N and 18–20 ∘ E). The wind-assigned anomaly method is first validated using the CAMS forecast data (XCH4 and TXCH4), showing a good agreement with the CAMS GLOBal ANThropogenic emission (CAMS-GLOB-ANT) inventory. It indicates that the wind-assigned method works well. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI + IASI TXCH4 by using the Carbon dioxide and Methane (CoMet) inventory derived for the year 2018. The calculated averaged total CH4 emissions over the USCB region is about 496 kt yr -1 (5.9×1026 molec. s -1) for TROPOMI XCH4 and 437 kt yr -1 (5.2×1026 molec. s -1) for TROPOMI + IASI TXCH4. These values are very close to the ones given in the E-PRTR inventory (448 kt yr -1) and the ones in the CoMet inventory (555 kt yr -1), and are thus in agreement with these inventories. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region are of secondary importance. Uncertainties from different error sources (background removal and noise in the data, vertical wind shear, wind field segmentation, and angle of the emission cone) are approximately 14.8 % for TROPOMI XCH4 and 11.4 % for TROPOMI + IASI TXCH4. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions. [ABSTRACT FROM AUTHOR]

Accurate observations of atmospheric ozone (O 3) are essential to monitor in detail its key role in atmospheric chemistry. The present paper examines the performance of different O 3 retrieval strategies from FTIR (Fourier transform infrared) spectrometry by using the 20-year time series of the high-resolution solar spectra acquired from 1999 to 2018 at the subtropical Izaña Observatory (IZO, Spain) within NDACC (Network for the Detection of Atmospheric Composition Change). In particular, the effects of two of the most influential factors have been investigated: the inclusion of a simultaneous atmospheric temperature profile fit and the spectral O 3 absorption lines used for the retrievals (the broad spectral region of 1000–1005 cm -1 and single micro-windows between 991 and 1014 cm -1). Additionally, the water vapour (H 2 O) interference in O 3 retrievals has been evaluated, with the aim of providing an improved O 3 strategy that minimises its impact and, therefore, could be applied at any NDACC FTIR station under different humidity conditions. The theoretical and experimental quality assessments of the different FTIR O 3 products (total column (TC) amounts and volume mixing ratio (VMR) profiles) provide consistent results. Combining a simultaneous temperature retrieval with the optimal selection of single O 3 micro-windows results in superior FTIR O 3 products, with a precision of better than 0.6 %–0.7 % for O 3 TCs as compared to coincident NDACC Brewer observations taken as a reference. However, this improvement can only be achieved provided the FTIR spectrometer is properly characterised and stable over time. For unstable instruments, the temperature fit is found to exhibit a strong negative influence on O 3 retrievals due to the increase in the cross-interference between the temperature retrieval and instrumental performance (given by the instrumental line shape function and measurement noise), which leads to a worsening of the precision of FTIR O 3 TCs of up to 2 %. This cross-interference becomes especially noticeable beyond the upper troposphere/lower stratosphere, as documented theoretically as well as experimentally by comparing FTIR O 3 profiles to those measured using electrochemical concentration cell (ECC) sondes within NDACC. Consequently, it should be taken into account for the reliable monitoring of the O 3 vertical distribution, especially over long-term timescales. [ABSTRACT FROM AUTHOR]

This work employs ground- and space-based observations, together with model data, to study columnar abundances of atmospheric trace gases (XH2O , XCO2 , XCH4 and XCO) in two high-latitude Russian cities, St. Petersburg and Yekaterinburg. Two portable COllaborative Column Carbon Observing Network (COCCON) spectrometers were used for continuous measurements at these locations during 2019 and 2020. Additionally, a subset of data of special interest (a strong gradient in XCH4 and XCO was detected) collected in the framework of a mobile city campaign performed in 2019 using both instruments is investigated. All studied satellite products (TROPOMI, OCO-2, GOSAT, MUSICA IASI) show generally good agreement with COCCON observations. Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous Copernicus Atmosphere Monitoring Service (CAMS) model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite validation, showing good agreement in both Peterhof and Yekaterinburg. The gradients between the two study sites (Δ Xgas) are similar between CAMS and CAMS-COCCON datasets, indicating that the model gradients are in agreement with the gradients observed by COCCON. This is further supported by a few simultaneous COCCON and satellite Δ Xgas measurements, which also agree with the model gradient. With respect to the city campaign observations recorded in St Petersburg, the downwind COCCON station measured obvious enhancements for both XCH4 (10.6 ppb) and XCO (9.5 ppb), which is nicely reflected by TROPOMI observations, which detect city-scale gradients of the order 9.4 ppb for XCH4 and 12.5 ppb for XCO. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 - March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory. Weekly variations of NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 24% at weekends in Riyadh, and high reductions are found near the city center and the areas along the highway. An average weekend reduction estimate of 30% in Madrid is found. The regions with dominant sources are located in the east of Madrid, where the residential areas and the Madrid-Barajas airport are located. Additionally, the NO2 emissions decreased by 21% in March-June 2020 compared to the same period in 2019 induced by the COVID-19 lockdowns in Riyadh. A much higher reduction (60%) is estimated for Madrid where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas and cover smaller areas during weekdays than at weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Though our analysis is limited to two cities as testing examples, the method has proved to provide reliable and consistent results. Therefore, it is expected to be suitable for other trace gases and other target regions. [ABSTRACT FROM AUTHOR]

Intensive coal mining activities are in the Upper Silesian Coal Basin (USCB) in southern Poland, resulting in large amounts of methane (CH4) emissions. Annual CH4 emission reached to 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hot spot in Europe, it is of importance to investigate its emission sources and accurate emission estimates. In this study, we use satellite-based column-averaged dry-air molar fraction observations of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI), together with the high-resolution model forecast XCH4 and TXCH4 from the Copernicus Atmosphere Monitoring Service (CAMS) to estimate the CH4 emission rate averaged over three years in the USCB region (49.3° - 50.8° N and 18° - 20° E). Using the CAMS inventory as the a priori knowledge of the sources, together with ERA5 wind at 330 m, the wind-assigned XCH4 anomalies for two opposite wind directions are calculated, which yields an estimated CH4 emission of 9.6E26 ± 1.4E25 molec./s for CAMS XCH4 and 9.1E26 ± 1.2E25 molec./s for CAMS TXCH4. These values are very close to the total emission of the CAMS inventory (9.7E26 molec./s). Very good agreements between CAMS and the wind-assigned model results (R²=0.89 for XCH4 and TXCH4) indicate that our wind-assigned method is quite robust. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region is of secondary importance. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI+IASI TXCH4 with using the Carbon dioxide and Methane (CoMet) inventory performed in 2018. The calculated averaged total CH4 emission over the USCB region is about 5.7E26 ± 4.9E24 molec./s for TROPOMI XCH4 and 5.2E26 ± 2.2E25 molec./s for TROPOMI+IASI TXCH4. These results are very close and thus in agreement to the emissions given in the E-PRTR inventory (5.33E26 molec./s) and the CoMet inventory (6.6E26 molec./s). Since the wind speed is increasing with altitude, sensitivity tests show that higher CH4 emission strengths are yielded with increasing altitude and vice versa. About 23% lower and 13% higher estimates are obtained when using lower wind information at 10 m and higher wind information at 500 m instead of 330 m, respectively. When using different wind coverage and different wind segmentation, an uncertainty of 4.2% and -2.1% is obtained, respectively. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions. [ABSTRACT FROM AUTHOR]

IASI (Infrared Atmospheric Sounding Interferometer) is the core instrument of the currently three Metop (Meteorological operational) satellites of EUMETSAT (European Organization for the Exploitation of Meteorological Satellites). The MUSICA IASI processing has been developed in the framework of the European Research Council project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor performs an optimal estimation of the vertical distributions of water vapour (H 2 O), the ratio between two water vapour isotopologues (the HDO/H2O ratio), nitrous oxide (N 2 O), methane (CH 4), and nitric acid (HNO 3) and works with IASI radiances measured under cloud-free conditions in the spectral window between 1190 and 1400 cm -1. The retrieval of the trace gas profiles is performed on a logarithmic scale, which allows the constraint and the analytic treatment of ln⁡[HDO]-ln⁡[H2O] as a proxy for the HDO/H2O ratio. Currently, the MUSICA IASI processing has been applied to all IASI measurements available between October 2014 and June 2021 and about two billion individual retrievals have been performed. Here we describe the MUSICA IASI full retrieval product data set. The data set is made available in the form of netCDF data files that are compliant with version 1.7 of the CF (Climate and Forecast) metadata convention. For each individual retrieval these files contain information on the a priori usage and constraint, the retrieved atmospheric trace gas and temperature profiles, profiles of the leading error components, and information on vertical representativeness in the form of the averaging kernels as well as averaging kernel metrics, which are more handy than the full kernels. We discuss data filtering options and give examples of the high horizontal and continuous temporal coverage of the MUSICA IASI data products. For each orbit an individual standard output data file is provided with comprehensive information for each individual retrieval, resulting in a rather large data volume (about 40 TB for the almost 7 years of data with global daily coverage). This, at a first glance, apparent drawback of large data files and data volume is counterbalanced by multiple possibilities of data reuse, which are briefly discussed. Examples of standard data output files and a README.pdf file informing users about access to the total data set are provided via https://doi.org/10.35097/408. In addition, an extended output data file is made available via https://doi.org/10.35097/412. It contains the same variables as the standard output files together with Jacobians (and spectral responses) for many different uncertainty sources and gain matrices (due to this additional variables it is called the extended output). We use these additional data for assessing the typical impact of different uncertainty sources – like surface emissivity or spectroscopic parameters – and different cloud types on the retrieval results. The extended output file is limited to 74 example observations (over a polar, mid-latitudinal, and tropical site); its data volume is only 73 MB, and it is thus recommended to users for having a quick look at the data. [ABSTRACT FROM AUTHOR]

The objective of this study is to derive methane (CH 4) emissions from three landfills, which are found to be the most significant CH 4 sources in the metropolitan area of Madrid in Spain. We derive CH 4 emissions from the CH 4 enhancements observed by spaceborne and ground-based instruments. We apply satellite-based measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) together with measurements from the ground-based COllaborative Carbon Column Observing Network (COCCON) instruments. In 2018, a 2-week field campaign for measuring the atmospheric concentrations of greenhouse gases was performed in Madrid in the framework of Monitoring of the Greenhouse Gases Concentrations in Madrid (MEGEI-MAD) project. Five COCCON instruments were deployed at different locations around the Madrid city center, enabling the observation of total column-averaged CH 4 mixing ratios (XCH 4). Considering the prevalent wind regimes, we calculate the wind-assigned XCH 4 anomalies for two opposite wind directions. Pronounced bipolar plumes are found when applying the method to NO 2 , which implies that our method of wind-assigned anomaly is suitable to estimate enhancements of trace gases at the urban level from satellite-based measurements. For quantifying the CH 4 emissions, the wind-assigned plume method is applied to the TROPOMI XCH 4 and to the lower tropospheric CH 4 / dry-air column ratio (TXCH 4) of the combined TROPOMI + IASI product. As CH 4 emission strength we estimate 7.4 × 10 25 ± 6.4 × 10 24 molec. s -1 from the TROPOMI XCH 4 data and 7.1 × 10 25 ± 1.0 × 10 25 molec. s -1 from the TROPOMI + IASI merged TXCH 4 data. We use COCCON observations to estimate the local source strength as an independent method. COCCON observations indicate a weaker CH 4 emission strength of 3.7 × 10 25 molec. s -1 from a local source (the Valdemingómez waste plant) based on observations from a single day. This strength is lower than the one derived from the satellite observations, and it is a plausible result. This is because the analysis of the satellite data refers to a larger area, covering further emission sources in the study region, whereas the signal observed by COCCON is generated by a nearby local source. All emission rates estimated from the different observations are significantly larger than the emission rates provided via the official Spanish Register of Emissions and Pollutant Sources. [ABSTRACT FROM AUTHOR]

We present a global and multi-annual space-borne dataset of tropospheric { H2O , δ D } pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in. From the independently retrieved H2O and δ D proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δ D. Here, this standard MUSICA method for deriving { H2O , δ D } pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a { H2O , δ D } pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in { H2O , δ D } pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the { H2O , δ D } pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI { H2O , δ D } pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI { H2O , δ D } pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered { H2O , δ D } pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI 10.35097/415 and the Level-3 dataset with DOI 10.35097/495. [ABSTRACT FROM AUTHOR]

Due to its dryness, the subtropical free troposphere plays a critical role in the radiative balance of the Earth's climate system. But the complex interactions of the dynamical and physical processes controlling the variability in the moisture budget of this sensitive region of the subtropical atmosphere are still not fully understood. Stable water isotopes can provide important information about several of the latter processes, namely subsidence drying, turbulent mixing, and dry and moist convective moistening. In this study, we use high-resolution simulations of the isotope-enabled version of the regional weather and climate prediction model of the Consortium for Small-Scale Modelling (COSMO iso) to investigate predominant moisture transport pathways in the Canary Islands region in the eastern subtropical North Atlantic. Comparison of the simulated isotope signals with multi-platform isotope observations (aircraft, ground- and space-based remote sensing) from a field campaign in summer 2013 shows that COSMO iso can reproduce the observed variability of stable water vapour isotopes on timescales of hours to days, thus allowing us to study the mechanisms that control the subtropical free-tropospheric humidity. Changes in isotopic signals along backward trajectories from the Canary Islands region reveal the physical processes behind the synoptic-scale isotope variability. We identify four predominant moisture transport pathways of mid-tropospheric air, each with distinct isotopic signatures: air parcels originating from the convective boundary layer of the Saharan heat low (SHL) – these are characterised by a homogeneous isotopic composition with a particularly high δD (median mid-tropospheric δD=-122‰), which results from dry convective mixing of low-level moisture of diverse origin advected into the SHL; air parcels originating from the free troposphere above the SHL – although experiencing the largest changes in humidity and δD during their subsidence over West Africa, these air parcels typically have lower δD values (median δD=-148‰) than air parcels originating from the boundary layer of the SHL; air parcels originating from outside the SHL region, typically descending from tropical upper levels south of the SHL, which are often affected by moist convective injections from mesoscale convective systems in the Sahel – their isotopic composition is much less enriched in heavy isotopes (median δD=-175‰) than those from the SHL region; air parcels subsiding from the upper-level extratropical North Atlantic – this pathway leads to the driest and most depleted conditions (median δD=-255‰) in the middle troposphere near the Canary Islands. The alternation of these transport pathways explains the observed high variability in humidity and δD on synoptic timescales to a large degree. We further show that the four different transport pathways are related to specific large-scale flow conditions. In particular, distinct differences in the location of the North African mid-level anticyclone and of extratropical Rossby wave patterns occur between the four transport pathways. Overall, this study demonstrates that the adopted Lagrangian isotope perspective enhances our understanding of air mass transport and mixing and offers a sound interpretation of the free-tropospheric variability of specific humidity and isotope composition on timescales of hours to days in contrasting atmospheric conditions over the eastern subtropical North Atlantic. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel 5 Precursor (S5P) satellite, launched in October 2017, provides a wealth of atmospheric composition data, including total columns of carbon monoxide (TCCO) at high horizontal resolution (5.5 km × 7 km). Near-real-time TROPOMI TCCO data have been monitored in the global data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS) since November 2018 to assess the quality of the data. The CAMS system already routinely assimilates TCCO data from the Measurement of Pollution in the Troposphere (MOPITT) instrument and the Infrared Atmospheric Sounding Interferometer (IASI) outside the polar regions. The assimilation of TROPOMI TCCO data in the CAMS system was tested for the period 6 July to 31 December 2021, i.e. after the TROPOMI algorithm update to version 02.02.00 in July 2021. By assimilating TROPOMI TCCO observations, the CAMS CO columns increase by on average 8 %, resulting in an improved fit to independent observations (IAGOS aircraft profiles and NDACC Fourier transform infrared (FTIR) tropospheric and total-column CO data) compared to a version of the CAMS system where only TCCO from MOPITT and IASI is assimilated. The largest absolute and relative changes from the assimilation of TROPOMI CO are found in the lower and middle troposphere, i.e. that part of the atmosphere that is not already well constrained by the assimilated TIR MOPITT and IASI data. The largest impact near the surface comes from clear-sky TROPOMI data over land, and additional vertical information comes from the retrievals of measurements in cloudy conditions. July and August 2021 saw record numbers of boreal wildfires over North America and Russia, leading to large amounts of CO being released into the atmosphere. The paper assesses the impact of TROPOMI CO assimilation on selected CO plumes more closely. While the CO column can be well constrained by the assimilation of TROPOMI CO data, and the fit to individual IAGOS CO profiles in the lower and middle troposphere is considerably improved, the TROPOMI CO columns do not provide further constraints on individual plumes that are transported across continents and oceans at altitudes above 500 hPa. [ABSTRACT FROM AUTHOR]