ALBERT

Description: The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) has shown that the sensor IASI aboard the satellite MetOp can measure the free tropospheric {H2O,δD} pair distribution twice per day on a quasi-global scale. Such data are very promising for investigating tropospheric moisture pathways, however, the complex data characteristics compromise their usage in the context of model evaluation studies. Here we present a tool that allows for simulating MUSICA MetOp/IASI {H2O,δD} pair remote sensing data for a given model atmosphere, thereby creating model data that have the remote sensing data characteristics assimilated. This model data can then be compared to the MUSICA data. The retrieval simulation method is based on the physical principles of radiative transfer and we show that the uncertainty of the simulations is within the uncertainty of the MUSICA MetOp/IASI products, i.e. the retrieval simulations are reliable enough. We demonstrate the working principle of the simulator by applying it to ECHAM5-wiso model data. The few case studies clearly reveal the large potential of the MUSICA MetOp/IASI {H2O,δD} data pairs for evaluating modelled moisture pathways. The tool is made freely available in form of MATLAB and Python routines and can be easily connected to any atmospheric water vapour isotopologue model.

Description: 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.

Description: This paper presents upper tropospheric methane (CH4) and nitrous oxide (N2O) concentrations retrieved from thermal infrared spectra as observed by the remote sensor IASI (Infrared Atmospheric Sounding Interferometer) on-board the EUMETSAT/MetOp meteorological satellites. The CH4 and N2O mixing ratios are retrieved as side products of the MetOp/IASI retrieval developed for the European Research Council project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The MUSICA/IASI CH4 and N2O retrieval strategy is described in detail as well as their characterisation in terms of the vertical resolution and expected errors. Theoretically, we document that MUSICA/IASI products can capture the upper tropospheric CH4 and N2O variability (at ≈ 300–350 hPa) with a precision better than 2 %. We compare the remote sensing data to coincident high precision aircraft vertical profiles taken within the HIAPER Pole-to-Pole Observations (HIPPO) project and empirically estimate a precision of 2.1 % (38.2 ppbv) for each individual IASI CH4 observation. The precision is improved to 1.7 % (32.1 ppbv) for IASI data that have been averaged within 2° × 2° boxes. For N2O the empirically estimated precision is 2.7 % (8.7 ppbv) for each individual observation and 2.1 % (6.9 ppbv) for the 2° × 2° averages. The empirical study works with data from the missions HIPPO1 and HIPPO5, which cover latitudes between 67º S and 80º N during typical winter and summer conditions in both hemispheres, thus being reasonably representative for global observation during different seasons. In addition, we present a product that combines the CH4 and N2O retrieval estimates. The combination is made a-posteriori and we theoretically and empirically show that the combined product has a much better precision than the individual CH4 and N2O products. For the combined product the theoretical precision is 0.8 % and the comparison with HIPPO data gives an empirical precision estimate of 1.5 % (26.3 ppbv) when considering all individual IASI observations and of 1.2 % (21.8 ppbv) for the 2° ×2° averages. In the case that the horizontal, vertical and temporal variation of N2O can be robustly modeled, we can easily reconstruct CH4 from the combined product and generate high quality IASI CH4 data.

Description: This paper presents the tools and methodology for performing a routine comprehensive monitoring of consistency and quality of IASI (Infrared Atmospheric Sounding Interferometer) trace gas Level 2 (L2) products (O3, CO, N2O, CH4, and CO2) generated at EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) using ground-based observations at the Izaña Atmospheric Observatory (IZO, Tenerife). As a demonstration the period 2010–2014 was analysed, covering the version 5 of the IASI L2 processor. Firstly, we assess the consistency between the total column (TC) observations from the IASI sensors on board the EUMETSAT Metop-A and Metop-B meteorological satellites (IASI-A and IASI-B respectively) in the subtropical North Atlantic region during the first 2 years of IASI-B operations (2012–2014). By analysing different timescales, we probe the daily and annual consistency of the variability observed by IASI-A and IASI-B and thereby assess the suitability of IASI-B for continuation of the IASI-A time series. The continuous intercomparison of both IASI sensors also offers important diagnostics for identifying inconsistencies between the data records and for documenting their temporal stability. Once the consistency of IASI sensors is documented we estimate the overall accuracy of all the IASI trace gas TC products by comparing to coincident ground-based Fourier transform infrared spectrometer (FTS) measurements performed at IZO from 2010 to 2014. The IASI L2 products reproduce the ground-based FTS observations well at the longest temporal scales, i.e. annual cycles and long-term trends for all the trace gases considered (Pearson correlation coefficient, R, larger than 0.95 and 0.75 for long-term trends and annual cycles respectively) with the exception of CO2. For CO2 acceptable agreement is only achieved for long-term trends (R ∼ 0.70). The differences observed between IASI and FTS observations can be in part attributed to the different vertical sensitivities of the two remote sensing instruments and also to the degree of maturity of the IASI products: O3 and CO are pre-operational, while N2O, CH4, and CO2 are, for the period covered by this study, aspirational products only and are not considered mature. Regarding shorter timescales (single or daily measurements), only the O3 product seems to show good sensitivity to actual atmospheric variations (R ∼ 0.80), while the CO product is only moderately sensitive (R ∼ 0.50). For the remainder of the trace gases, further improvements would be required to capture the day-to-day real atmospheric variability.

Description: In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.

Description: We present two years of in situ measurements of water vapour (H2O) and its isotopologue ratio (δD, the standardized ratio between H216O and HD16O), made at two remote mountain sites on Tenerife in the subtropical North Atlantic. We show that the data – if measured during night-time – are well representative for the lower/middle free troposphere. We use the measured H2O-δD pairs, together with dust measurements and back trajectory modelling for analysing the moisture pathways to this region. We can identify four principally different transport pathways. The air mass transport from high altitudes and high latitudes shows two different scenarios. The first scenario brings dry air masses to the stations, as the result of condensation events occurring at low temperatures. The second scenario brings humid air masses to the stations, due to cross-isentropic mixing with lower-level and more humid air during transport since last condensation (LC). The third pathway is transportation from lower latitudes and lower altitudes, whereby we can identify rain re-evaporation as an occasional source of moisture. The fourth pathway is linked to the African continent, where during summer, dry convection processes over the Sahara very effectively inject humidity from the boundary layer to higher altitudes. This so-called Saharan Air Layer (SAL) is then advected westward over the Atlantic and contributes to moisten the free troposphere. We demonstrate that the different pathways leave distinct fingerprints on the measured H2O-δD pairs.

Description: The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) has shown that the sensor IASI aboard the satellite MetOp can measure the free tropospheric {H2O,δD} pair distribution twice per day on a quasi global scale. Such data are very promising for investigating tropospheric moisture pathways, however, the complex data characteristics compromises their usage in the context of model evaluation studies. Here we present a tool that allows for simulating MUSICA MetOp/IASI {H2O,δD} pair remote sensing data for a given model atmosphere, thereby creating model data that have the remote sensing data characteristics assimilated. This model data can then be compared to the MUSICA data. The retrieval simulation method is based on the physical principles of radiative transfer and we show that the uncertainty of the simulations is within the uncertainty of the MUSICA MetOp/IASI products, i.e. the retrieval simulations are reliable enough. We demonstrate the working principle of the simulator by applying it to ECHAM5-wiso model data. The exemplary model study clearly reveals the large potential of the MUSICA MetOp/IASI {H2O,δD} data pairs for evaluating modeled moisture pathways. The tool is made freely available in form of MATLAB and Python routines and can be easily connected to any atmospheric water vapour isotopologue model.

Description: The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) has shown that the sensor IASI aboard the satellite MetOp can measure the free tropospheric {H2O,δD} pair distribution twice per day on a quasi-global scale. Such data are very promising for investigating tropospheric moisture pathways, however, the complex data characteristics compromise their usage in the context of model evaluation studies. Here we present a tool that allows for simulating MUSICA MetOp/IASI {H2O,δD} pair remote sensing data for a given model atmosphere, thereby creating model data that have the remote sensing data characteristics assimilated. This model data can then be compared to the MUSICA data. The retrieval simulation method is based on the physical principles of radiative transfer and we show that the uncertainty of the simulations is within the uncertainty of the MUSICA MetOp/IASI products, i.e. the retrieval simulations are reliable enough. We demonstrate the working principle of the simulator by applying it to ECHAM5-wiso model data. The few case studies clearly reveal the large potential of the MUSICA MetOp/IASI {H2O,δD} data pairs for evaluating modelled moisture pathways. The tool is made freely available in form of MATLAB and Python routines and can be easily connected to any atmospheric water vapour isotopologue model.