Retrieval of water vapor in the atmosphere and its spectral content

From OLCI to GPS

authored by: G. Kermarrec, X. Calbet, Z. Deng, C. Carbajal Henken, R. Preusker
Abstract: Understanding the tropospheric diabatic heating is essential for predicting Earth’s weather and climate. To reach that goal, information on water vapor (WV) in the atmosphere is mandatory. Unfortunately, monitoring WV is challenging, because of its high variability in both space and time. Particularly, advanced knowledge and modeling of its fine scale behavior would be beneficial to improve forecasting applications. In this contribution, we propose to compare and discuss the spectral content of dataset from two instruments recording WV content of the atmosphere, focusing on small scales: Ocean Land Color Instrument (OLCI) on board of Copernicus Sentinel-3 and Zenith wet delay (ZWD) retrieved from Global Navigation Satellite System (GNSS) observations. Kolmogorov’s theory states that the structure function of passive scalar, or equivalently the temporal power spectrum (assuming taylor frozen turbulence), should follow a given power law within the inertial range. Using the von Karman modelling, it is possible to assess the outer scale length of turbulence defined as the frequency where the spectrum saturates. For our analysis on WV small scales, we have selected a region around Lindenberg in Germany. We will discuss the spectral content of the retrieved observations and their specificity. We will highlight the potential of ZWD from GNSS observations to study daily variations of turbulence parameters.
Organisation(s): Institute of Meteorology and Climatology
External Organisation(s): State Meteorological Agency (AEMET)
Helmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)
Freie Universität Berlin (FU Berlin)
Type: Conference contribution
Publication date: 2023
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Electronic, Optical and Magnetic Materials, Condensed Matter Physics, Computer Science Applications, Applied Mathematics, Electrical and Electronic Engineering
Sustainable Development Goals: SDG 13 - Climate Action
Electronic version(s): https://doi.org/10.1117/12.2678381 (Access: Closed)