GLOMIR: Global MUSICA IASI Retrievals

Introduction:
At IMK-ASF, we have developed a processor for retrieving the vertical distribution of water vapour (H2O), water vapour isotopologue ratio (HDO/H2O), methane (CH4), nitrous oxide (N2O), sulphur dioxide (SO2), nitric acid (HNO3), and peroxyacetyl nitrate (PAN). Using a single processing unit the retrieval of one IASI observation takes on average about 130 seconds. We make retrievals for all spectra measured under cloud-free conditions, which are typically 0.7 million each 24 h. High performance computing (HPC) is thus indispensable for processing the satellite data.

Method:
Our processor is a full physics optimal estimation retrieval code (e.g., Rodgers 2000). This kind of retrieval approaches are computationally demanding, but they are able to simultaneously generate a variety of different products at a high and well-documented quality. The code applies a precise radiative transfer model (e.g., Hase et al., 2004), that simulates the spectra measured by the satellite instrument for a given atmospheric composition. The radiative transfer model constitutes the forward problem, which is then inverted during the atmospheric remote sensing retrieval process. Due to non-linearities involved in the radiative transfer, the inversion is achieved via several iteration steps, which is one reason for the high computational demands. On HPC systems, we process one orbit per node and use a thread pool to distribute the individual retrievals to the available number of worker threads, thus fully exploring the available computing performance. On a HoreKa “Standard Node”, one orbit (about 25000 observations) is processed in less than 6h, and with 7 standard nodes we would be able to process the about 0.7 million cloud-free observations made each 24 h in 24 h (near-real time processing). The processor and the generated data sets are described in detail in Schneider at el. (2022a).

Results:
Our data make important contributions to international research activities and projects in different fields. The unique water vapour isotopologue product has a demonstrated potential to reduce atmospheric model uncertainties on weather time scales (e.g., Toride et al., 2021; Schneider et al., 2024) and furthermore, it  enables the monitoring of atmospheric moisture transport (e.g., Diekmann et al., 2024) and cloud processes (e.g., Bailey et al., 2023; Galewsky et al., 2023), which are essential for better understanding and predicting the changing climate. Methane (CH4) and nitrous oxide (N2O) are important greenhouse gases, and our respective products contribute to an improved assessment of the anthropogenic sources (e.g., Tu et al., 2022a;b) and the natural sinks.

Ongoing Work and Outlook:
We are evaluating the potential of IASI for detecting stratospheric concentrations of water vapour and sulphur dioxide (SO2), and for bridging an upcoming observation gap: the limb-sounding satellite instruments (MIPAS, ACE-FTS, or Aura/MLS, e.g., Hegglin et al., 2021) -- generally used for this kind of monitoring -- have already ended or are expected to end several years before the next-generation limb-sounding missions might be operative (e.g., CAIRT, Rhode et al., 2024). 
The diversity of satellite data is steadily increasing. We can show that a synergetic combination of different data sets has a stronger scientific impact than the two individual data sets, and we work on the development of efficient synergetic combination methods (Schneider et al., 2022b).
The IASI successor instrument IASI-NG (IASI-Next Generation) is scheduled for launch in 2025 and will offer a further improved spectral resolution and potential enable retrievals of products with increased quality (but also computational demands). We are preparing an efficient IASI-NG processing.

References:
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