Preprints
https://doi.org/10.5194/essd-2021-87
https://doi.org/10.5194/essd-2021-87

  30 Mar 2021

30 Mar 2021

Review status: this preprint is currently under review for the journal ESSD.

The MUSICA IASI {H2O, δD} pair product

Christopher J. Diekmann1, Matthias Schneider1, Benjamin Ertl1,2, Frank Hase1, Omaira García3, Farahnaz Khosrawi1, Eliezer Sepúlveda3, Peter Knippertz1, and Peter Braesicke1 Christopher J. Diekmann et al.
  • 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 2Steinbuch Centre for Computing, Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 3Izaña Atmospheric Research Center, Agencia Estatal de Meteorología, Santa Cruz de Tenerife, Spain

Abstract. We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard 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 Schneider et al. (2021b). From the independently retrieved H2O and δD 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 δD. Here, this standard MUSICA method for deriving {H2O, δD} 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, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021).

Christopher J. Diekmann et al.

Status: open (until 25 May 2021)

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Christopher J. Diekmann et al.

Data sets

MUSICA IASI water isotopologue pair product (a posteriori processing version 2) Diekmann, C. J., Schneider, M., and Ertl, B. https://doi.org/10.35097/415

Christopher J. Diekmann et al.

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Short summary
The joint analysis of different stable water isotopes in water vapour is a powerful tool for investigating
atmospheric moisture pathways. This paper presents a novel global and multi-annual dataset of H2O and
HDO in mid-tropospheric water vapour by using data from the satellite sensor Metop/IASI. Due to its unique
combination of coverage and resolution in space and time, this dataset is highly promising for studying the
hydrological cycle and its representation in weather and climate models.