IWV observations in the Caribbean Arc from a network of ground-based GNSS receivers during EUREC4A
- 1Université de Paris, Institut de physique du globe de Paris, CNRS, IGN, F-75005 Paris, France
- 2ENSG-Géomatique, IGN, F-77455 Marne-la-Vallée, France
- 3Lab-STICC UMR 6285 CNRS/PRASYS, ENSTA Bretagne/HOP, F-29200 Brest, France
- 4LATMOS/IPSL, UMR 8190 CNRS-SU-UVSQ, Paris, France
- 5Géosiences Montpellier UMR 5243, Université Montpellier - CNRS, Montpellier, France
- 6Max-Planck-Institut für Meteorologie, Hamburg, Germany
- 7IGN, Saint-Mandé, France
- 8LMD/IPSL, UMR 8539 CNRS, Sorbonne Université, Paris, France
- 9Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
Abstract. Ground-based Global Navigation Satellite System (GNSS) measurements from nearly fifty stations distributed over the Caribbean Arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality Integrated Water Vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the Tradewinds and their feedback on the large-scale circulation and energy budget.
This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD) to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a colocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS derived IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated.
We classified the cloud organisation for five representative GNSS stations across the Caribbean Arc and found that the environment of Fish cloud patterns to be moister than that of Flowers cloud patterns which, in turn, is moister than the environment of Gravel cloud patterns. The differences in the IWV means between Fish and Gravel were assessed to be significant. Finally, the Gravel moisture environment was found to be similar to that of clear, cloud-free conditions. The moisture environment associated with the Sugar cloud pattern has not been assessed because it was hardly observed during the first two months of 2020.
The reprocessed ZTD and IWV data set from 49 GNSS stations used in this study are available from the AERIS data center (https://doi.org/10.25326/79; Bock (2020b)).
Olivier Bock et al.
Status: open (until 21 Apr 2021)
Olivier Bock et al.
Reprocessed IWV data from ground-based GNSS network during EUREC4A campaign https://doi.org/10.25326/79
Olivier Bock et al.
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