Christopher Johannes Diekmann

The Copernicus Sentinel-4/UVN and Sentinel-5/UVNS imaging spectrometers, hosted on EUMETSAT’s Meteosat Third Generation - Sounder (MTG-S) and EUMETSAT Polar System - Second Generation A (EPS-SG A) satellites, are in space since the summer of 2025. Sentinel-4/UVN is designed to monitor atmospheric trace gases - such as ozone, nitrogen dioxide, sulphur dioxide, formaldehyde and glyoxal - as well as aerosol and cloud properties from hyperspectral measurements in the UV, Visible and Near-Infrared (UVN). Observing from a geostationary orbit, it provides high spatial resolution and hourly coverage over Europe and northern Africa. Sentinel-5/UVNS has a similar scope but additionally covers spectral bands in the Shortwave-Infrared and therefore allows measuring additional species, such as carbon monoxide and methane. Flying in a polar orbit, it provides high spatial resolution and near-daily global coverage. Both instruments provide essential data for tracking atmospheric composition and support the Copernicus Atmosphere Monitoring Service (CAMS). The innovative instruments are completing the European contribution to the constellation of geostationary and polar orbiting atmospheric composition missions, including the existing geostationary GEMS and TEMPO over Asia and North America, respectively, as well as the fleet of Low Earth Orbit air quality missions operating in similar spectral ranges, such as GOME-2, OMI, TROPOMI and OMPS. This presentation will cover the mission status during the ongoing commissioning and Cal/Val activities, including insights into level-2 product status.

The West African Monsoon (WAM) is crucial for rainfall in West Africa, impacting socio-economic conditions. Its complexity arises from interactions between large-scale circulation, convective dynamics, and microphysical processes, making it challenging to disentangle individual contributions to the hydrological cycle. Recent advances in retrieving the isotopic composition of tropospheric water vapour from space promote the paired analysis of H₂O and HDO to study atmospheric moisture pathways and processes. Using data from the satellite instruments IASI (Infrared Atmospheric Sounding Interferometer), AIRS (Atmospheric Infrared Sounder) and TROPOMI (Tropospheric Monitoring Instrument), along with the IMERG (Integrated Multi-Satellite Retrievals for GPM) precipitation product, we analyse the variability of H₂O and HDO (given as δD) over West Africa at convective and seasonal scales. Key findings include the following: (1) monsoon convection over the Sahel induces an anti-correlation between H₂O and δD in the mid-troposphere. This is due to dry intrusions from the Saharan upper troposphere into Sahelian squall lines, fostering rain evaporation and mid-tropospheric δD depletion. (2) Over the Guinea coast, convective precipitation is associated with moist and enriched signals, with surface evaporation from the tropical Atlantic reducing rain evaporation and δD depletion. (3) During the Sahelian monsoon peak, an anti-correlation between precipitation and δD forms year to year, indicating the amount effect in tropospheric water vapour. (4) In the Sahelian winter, when precipitation is minimal, {H₂O, δD} signals point to mixing of dry air masses of different origins. This study is the first to apply comprehensive isotopic datasets from IASI, TROPOMI and AIRS to the WAM, demonstrating the utility of satellite-based {H₂O, δD} pairs in detecting impacts of microphysical and dynamical processes on water vapour isotopic composition.

The West African Monsoon (WAM) represents the main source of rainfall over West Africa and thus has important socio-economic impacts. However, the complex interactions of the large-scale circulation, convective dynamics and microphysical processes pose a substantial challenge to reliably quantify the atmospheric branches of the hydrological cycle in observations and models. Making use of recent advances in retrieving the isotopic composition of tropospheric water vapour from space, we promote the paired analysis of H₂O and HDO to investigate the moisture pathways and processes associated with the WAM. Data from the state-of-the-art satellite sensors IASI, AIRS and TROPOMI, together with the multi-satellite IMERG precipitation product, serve to characterize the variability of H₂O and HDO (with their ratio product δD) over West Africa from a convective as well as seasonal perspective and with respect to impacts from dynamical and microphysical processes. In particular, we find: (1) Monsoon convection over the Sahel leads to a marked anti-correlation between increasing H₂O and decreasing δD in the free troposphere. This is due to strong dry air intrusions from the Saharan upper troposphere that feed into Sahelian squall line systems, foster rain evaporation and, hence, lead to δD depletion; (2) Over the Guinea Coast, convective precipitation is associated with overall moist and enriched signals without showing significant δD depletion. Here, surface evaporation from the Tropical Atlantic moistens the troposphere, reducing the efficiency of the rain evaporation and the corresponding δD depletion; (3) During the Sahelian monsoon peak, an anti-correlation between increasing precipitation amount and decreasing δD becomes apparent. Thus, this provides observational evidence for the amount effect in tropospheric water vapour, similar to what is known for the isotopic composition in precipitation; (4) When no considerable precipitation occurs, e.g. during the Sahelian winter, the {H₂O, δD} signals point to dry air mass mixing from large-scale circulation. This study demonstrates that different microphysical and dynamical processes occurring over West Africa leave distinct features in the isotopic composition of water vapour, and, hence, underlines the overall value of using paired H₂O and δD observations from space to study effects of processes that control tropical convection.

The West African Monsoon (WAM) represents the main source of rainfall over West Africa and thus has important socio-economic impacts. However, the complex interactions of the large-scale circulation, convective dynamics and microphysical processes pose a substantial challenge to reliably quantify the atmospheric branches of the hydrological cycle in observations and models. Making use of recent advances in retrieving the isotopic composition of tropospheric water vapour from space, we promote the paired analysis of H₂O and HDO to investigate the moisture pathways and processes associated with the WAM. Data from the state-of-the-art satellite sensors IASI, AIRS and TROPOMI, together with the multi-satellite IMERG precipitation product, serve to characterize the variability of H₂O and HDO (with their ratio product δD) over West Africa from a convective as well as seasonal perspective and with respect to impacts from dynamical and microphysical processes. In particular, we find: (1) Monsoon convection over the Sahel leads to a marked anti-correlation between increasing H₂O and decreasing δD in the free troposphere. This is due to strong dry air intrusions from the Saharan upper troposphere that feed into Sahelian squall line systems, foster rain evaporation and, hence, lead to δD depletion; (2) Over the Guinea Coast, convective precipitation is associated with overall moist and enriched signals without showing significant δD depletion. Here, surface evaporation from the Tropical Atlantic moistens the troposphere, reducing the efficiency of the rain evaporation and the corresponding δD depletion; (3) During the Sahelian monsoon peak, an anti-correlation between increasing precipitation amount and decreasing δD becomes apparent. Thus, this provides observational evidence for the amount effect in tropospheric water vapour, similar to what is known for the isotopic composition in precipitation; (4) When no considerable precipitation occurs, e.g. during the Sahelian winter, the {H₂O, δD} signals point to dry air mass mixing from large-scale circulation. This study demonstrates that different microphysical and dynamical processes occurring over West Africa leave distinct features in the isotopic composition of water vapour, and, hence, underlines the overall value of using paired H₂O and δD observations from space to study effects of processes that control tropical convection.

The West African Monsoon (WAM) represents the main source of rainfall over West Africa and thus has important socio-economic impacts. However, the complex interactions of the large-scale circulation, convective dynamics and microphysical processes pose a substantial challenge to reliably quantify the atmospheric branches of the hydrological cycle in observations and models. Making use of recent advances in retrieving the isotopic composition of tropospheric water vapour from space, we promote the paired analysis of H₂O and HDO to investigate the moisture pathways and processes associated with the WAM. Data from the state-of-the-art satellite sensors IASI, AIRS and TROPOMI, together with the multi-satellite IMERG precipitation product, serve to characterize the variability of H₂O and HDO (with their ratio product δD) over West Africa from a convective as well as seasonal perspective and with respect to impacts from dynamical and microphysical processes. In particular, we find: (1) Monsoon convection over the Sahel leads to a marked anti-correlation between increasing H₂O and decreasing δD in the free troposphere. This is due to strong dry air intrusions from the Saharan upper troposphere that feed into Sahelian squall line systems, foster rain evaporation and, hence, lead to δD depletion; (2) Over the Guinea Coast, convective precipitation is associated with overall moist and enriched signals without showing significant δD depletion. Here, surface evaporation from the Tropical Atlantic moistens the troposphere, reducing the efficiency of the rain evaporation and the corresponding δD depletion; (3) During the Sahelian monsoon peak, an anti-correlation between increasing precipitation amount and decreasing δD becomes apparent. Thus, this provides observational evidence for the amount effect in tropospheric water vapour, similar to what is known for the isotopic composition in precipitation; (4) When no considerable precipitation occurs, e.g. during the Sahelian winter, the {H₂O, δD} signals point to dry air mass mixing from large-scale circulation. This study demonstrates that different microphysical and dynamical processes occurring over West Africa leave distinct features in the isotopic composition of water vapour, and, hence, underlines the overall value of using paired H₂O and δD observations from space to study effects of processes that control tropical convection.

The West African Monsoon (WAM) represents the main source of rainfall over West Africa and thus has important socio-economic impacts. However, the complex interactions of the large-scale circulation, convective dynamics and microphysical processes pose a substantial challenge to reliably quantify the atmospheric branches of the hydrological cycle in observations and models. Making use of recent advances in retrieving the isotopic composition of tropospheric water vapour from space, we promote the paired analysis of H₂O and HDO to investigate the moisture pathways and processes associated with the WAM. Data from the state-of-the-art satellite sensors IASI, AIRS and TROPOMI, together with the multi-satellite IMERG precipitation product, serve to characterize the variability of H₂O and HDO (with their ratio product δD) over West Africa from a convective as well as seasonal perspective and with respect to impacts from dynamical and microphysical processes. In particular, we find: (1) Monsoon convection over the Sahel leads to a marked anti-correlation between increasing H₂O and decreasing δD in the free troposphere. This is due to strong dry air intrusions from the Saharan upper troposphere that feed into Sahelian squall line systems, foster rain evaporation and, hence, lead to δD depletion; (2) Over the Guinea Coast, convective precipitation is associated with overall moist and enriched signals without showing significant δD depletion. Here, surface evaporation from the Tropical Atlantic moistens the troposphere, reducing the efficiency of the rain evaporation and the corresponding δD depletion; (3) During the Sahelian monsoon peak, an anti-correlation between increasing precipitation amount and decreasing δD becomes apparent. Thus, this provides observational evidence for the amount effect in tropospheric water vapour, similar to what is known for the isotopic composition in precipitation; (4) When no considerable precipitation occurs, e.g. during the Sahelian winter, the {H₂O, δD} signals point to dry air mass mixing from large-scale circulation. This study demonstrates that different microphysical and dynamical processes occurring over West Africa leave distinct features in the isotopic composition of water vapour, and, hence, underlines the overall value of using paired H₂O and δD observations from space to study effects of processes that control tropical convection.

The West African Monsoon (WAM) represents the main source of rainfall over West Africa and thus has important socio-economic impacts. However, the complex interactions of the large-scale circulation, convective dynamics and microphysical processes pose a substantial challenge to reliably quantify the atmospheric branches of the hydrological cycle in observations and models. Making use of recent advances in retrieving the isotopic composition of tropospheric water vapour from space, we promote the paired analysis of H₂O and HDO to investigate the moisture pathways and processes associated with the WAM. Data from the state-of-the-art satellite sensors IASI, AIRS and TROPOMI, together with the multi-satellite IMERG precipitation product, serve to characterize the variability of H₂O and HDO (with their ratio product δD) over West Africa from a convective as well as seasonal perspective and with respect to impacts from dynamical and microphysical processes. In particular, we find: (1) Monsoon convection over the Sahel leads to a marked anti-correlation between increasing H₂O and decreasing δD in the free troposphere. This is due to strong dry air intrusions from the Saharan upper troposphere that feed into Sahelian squall line systems, foster rain evaporation and, hence, lead to δD depletion; (2) Over the Guinea Coast, convective precipitation is associated with overall moist and enriched signals without showing significant δD depletion. Here, surface evaporation from the Tropical Atlantic moistens the troposphere, reducing the efficiency of the rain evaporation and the corresponding δD depletion; (3) During the Sahelian monsoon peak, an anti-correlation between increasing precipitation amount and decreasing δD becomes apparent. Thus, this provides observational evidence for the amount effect in tropospheric water vapour, similar to what is known for the isotopic composition in precipitation; (4) When no considerable precipitation occurs, e.g. during the Sahelian winter, the {H₂O, δD} signals point to dry air mass mixing from large-scale circulation. This study demonstrates that different microphysical and dynamical processes occurring over West Africa leave distinct features in the isotopic composition of water vapour, and, hence, underlines the overall value of using paired H₂O and δD observations from space to study effects of processes that control tropical convection.

Satellite-based observations of free tropospheric water vapour isotopologue ratios (δD) 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 δD 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 δD 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 δD 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 δD, ω, Q₂, and Prcp (analyses skills of 20 %–40 %). The additional assimilation of δD observations further improves the quality of the analyses of all variables. We use Q₂ 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 Q₂ 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, Q₂, and Prcp are very large), i.e. the additional assimilation of δD 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 δD observations affected by such strong latent heating events are frequently available, suggesting that the here demonstrated additional δD impact for the simulated world is also a realistic scenario for a real world data assimilation.

Satellite-based observations of free tropospheric water vapour isotopologue ratios (δD) 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 δD 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 δD 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 δD 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 δD, ω, Q₂, and Prcp (analyses skills of 20 %–40 %). The additional assimilation of δD observations further improves the quality of the analyses of all variables. We use Q₂ 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 Q₂ 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, Q₂, and Prcp are very large), i.e. the additional assimilation of δD 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 δD observations affected by such strong latent heating events are frequently available, suggesting that the here demonstrated additional δD impact for the simulated world is also a realistic scenario for a real world data assimilation.