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Validating time series of a combined GPS and MERIS Integrated Water Vapor product

Roderik Lindenbergh(1), Maxim Keshin(2), Hans Van der Marel(1) and Siebren De Haan(3)

(1) Delft University of Technology, P.O. Box 5058, 2600 GB Delft, Netherlands
(2) Finnish Geodetic Institute, Geodeetinrinne 2, FI-02431 Masala, Finland
(3) KNMI Royal Meteorological Institute, P.O.Box 201, 3730 AE De Bilt, Netherlands


Water vapor is the atmosphere's dominant greenhouse gas, but it is still a challenge to determine its spatial-temporal distribution at sufficient resolution from one single type of contemporary meteorological instrument. It is possible however to retrieve and consecutively combine water vapor estimates from complementary satellite systems. At ground stations from the world wide Global Positioning System (GPS), the zenith Integrated Water Vapor (IWV) is derived from estimates of GPS signal travel time delay in troposphere. This derivation results in relative good measurements with high temporal, e.g. 1 hour, but low spatial resolution, e.g. tenths of kilometers over Western Europe. The Medium Resolution Imaging Spectrometer (MERIS) on the Envisat satellite retrieves IWV by comparing radiances in two spectral bands in the near infrared, with a maximum spatial resolution of 300 m. Its temporal resolution is restricted to 3 days. Moreover, MERIS only provides useful IWV observations under clear sky conditions.

The topic of the proposed paper is the validation of a method that creates time series of hourly IWV predictions by combining complementary MERIS and GPS IWV observations, [1]. For this purpose a region of interest is considered of about 300 by 400 km covering The Netherlands. The method takes GPS and MERIS observations of the period March-May 2006 as input and creates a two months time series of hourly IWV maps at about 10 km spatial resolution. The quality of the integrated water vapour product is assessed by cross-validation: at each GPS ground station location two time series of IWV values are compared. One time series consists of the direct GPS IWV observations from that ground station; the other time series is extracted from a combined GPS-MERIS IWV product, created using all available observations, except for the GPS IWV observations from the ground station at hand.

For the proposed data combination, GPS IWV estimates of about 40 ground stations in the region of interest will be used. These IWV estimates, available at at least hourly intervals, were processed by the KNMI Royal Meteorological Institute. The MERIS data product used here is MER_RRC_2P, the Level 2 Reduced Resolution Cloud and Water vapor product. There are about 60 MER_RRC_2P data sets available in the period half March - half May 2006 that have at least partial overlap with the region of interest.

The method of GPS and MERIS data fusion has been described in detail in [2]. In short, spatial and temporal correlations between the different available IWV observations are taken into account in a Co-Kriging approach. It has been shown that such an approach not only leads to a, in a specific mathematical sense, optimal spatio-temporal interpolation result, but also to a description of the quality of each interpolated value in the space-time domain in the form a Kriging variance. The proposed cross-validation method will also give insight in the applicability of this Kriging variance as variance values can be compared to differences between interpolated and directly observed IWV estimates. Finally, the additional value of incorporating MERIS IWV will be quantified by comparing time series of interpolated IWV estimated based on GPS IWV observations only to time series that incorporate MERIS IWV as well.

[1] R. Lindenbergh, M. Keshin, H. van der Marel and S. de Haan, (2007). Towards sequential water vapor predictions based on time series of GPS and MERIS observations. In: Proceedings ESA Envisat Symposium, Montreux, Switzerland, 2007.

[2] R. Lindenbergh, M. Keshin, H. van der Marel and R. Hanssen, (2008). High resolution spatio-temporal water vapor mapping using GPS and MERIS observations. International Journal of Remote Sensing, 29(8), pp. 2393-2409.


Workshop presentation

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry