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.

Abstract. We present the new isotope-enabled model ICON-ART-Iso. The physics package of the global ICOsahedral Nonhydrostatic (ICON) modeling framework has been extended to simulate passive moisture tracers and the stable isotopologues HDO and H218O. The extension builds on the infrastructure provided by ICON-ART, which allows for high flexibility with respect to the number of related water tracers that are simulated. The physics of isotopologue fractionation follow the model COSMOiso. We first present a detailed description of the physics of fractionation that have been implemented in the model. The model is then evaluated on a range of temporal scales by comparing with measurements of precipitation and vapor. A multi-annual simulation is compared to observations of the isotopologues in precipitation taken from the station network GNIP (Global Network for Isotopes in Precipitation). ICON-ART-Iso is able to simulate the main features of the seasonal cycles in δD and δ18O as observed at the GNIP stations. In a comparison with IASI satellite retrievals, the seasonal and daily cycles in the isotopologue content of vapor are examined for different regions in the free troposphere. On a small spatial and temporal scale, ICON-ART-Iso is used to simulate the period of two flights of the IAGOS-CARIBIC aircraft in September 2010, which sampled air in the tropopause region influenced by Hurricane Igor. The general features of this sample as well as those of all tropical data available from IAGOS-CARIBIC are captured by the model. The study demonstrates that ICON-ART-Iso is a flexible tool to analyze the water cycle of ICON. It is capable of simulating tagged water as well as the isotopologues HDO and H218O.

Abstract. 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 (COSMOiso) 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 COSMOiso 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. 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 and/or short wave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument) offer higher sensitivity near 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 data. 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 is largely equivalent 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 (CH4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total column averaged CH4 product (XCH4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the upper tropospheric and lower stratospheric (UTLS) CH4 partial column information of the corresponding IASI product. As consequence, the combined product offers in addition sensitivity for the tropospheric CH4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effects are verified by comparisons to CH4 reference data obtained from collocated XCH4 measurements at six globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 24 individual AirCore soundings, and lower tropospheric CH4 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 XCH4 signals and allows to distinguish between tropospheric and UTLS CH4 partial column averaged mixing ratios, which is not possible by the individual TROPOMI and IASI products. We find indications of a weak positive bias of about +1 % of the combined lower tropospheric data product with respect to the references. For the UTLS CH4 partial columns we find no significant bias.

Abstract. The objective of this study is to derive methane (CH4) emissions from three landfills, which are found to be the most significant CH4 sources in the metropolitan area of Madrid in Spain. We derive CH4 emissions from the CH4 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 CH4 mixing ratios (XCH4). Considering the prevalent wind regimes, we calculate the wind-assigned XCH4 anomalies for two opposite wind directions. Pronounced bipolar plumes are found when applying the method to NO2, 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 CH4 emissions, the wind-assigned plume method is applied to the TROPOMI XCH4 and to the lower tropospheric CH4 / dry-air column ratio (TXCH4) of the combined TROPOMI+IASI product. As CH4 emission strength we estimate 7.4 × 1025 ± 6.4 × 1024 molec. s−1 from the TROPOMI XCH4 data and 7.1 × 1025 ± 1.0 × 1025 molec. s−1 from the TROPOMI+IASI merged TXCH4 data. We use COCCON observations to estimate the local source strength as an independent method. COCCON observations indicate a weaker CH4 emission strength of 3.7 × 1025 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.