D20    Impact of spatial error correlation model


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SMHI
30
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Public
This is part of work-package 3200, the purpose of which is modelling and correction of GPS spatial error correlations.

ObjectivesTo develop and test models for the spatial correlation of ground-based GPS observation errors to be applied in variational data assimilation.

Methodology/Work Description: The design of the ground-based measurement and pre-processing system implies theoretically the measurements to be affected by spatially correlated errors. Simulation studies by Jarlemark et al. (2001) and studies of empirical spatial correlations by Stoew et al. (2001) support this theory. These early studies suggest that the length scale of the GPS observation error correlation may be significantly larger than the length scale of the forecast error. This separation of length scales can possibly be utilised for a determination of the spatial (horizontal) correlation of GPS observations errors from innovation vectors, i.e. the differences between GPS observations and the model data. Other observations of the atmospheric moisture could in principle serve as references for the estimation of the GPS observation errors, but the limited spatial resolution and relatively poor quality of radiosonde moisture measurements do not make this approach meaningful. It will furthermore be investigated whether the observation error and forecast error contributions to the spatial correlation of the GPS data innovation vectors can be separated through a separate modelling of the forecast error correlation by simulation techniques, based on ensemble assimilation experiments.

The efficiency of the developed spatial error correlation model will be implemented and tested through data assimilation and forecast experiments with and without application of the spatial error correlation model. The implementation of the spatial error correlation may cause coding design difficulties, since the present design of computer codes for operational variational data assimilation schemes does, in principle, not allow for such spatially correlated errors.

Since the errors in the ZTD estimates from the GPS data are strongly correlated with the errors in the estimated site positions in the local vertical coordinate, we will also investigate the spatial error correlation of these residuals in the vertical site positions using both archived GPS data and near real-time data acquired within the proposed project. The point is that the true site position is significantly less variable than is the true ZTD. It is, therefore, in this case much easier to separate the signal from the error for long time series of data. Here we can also assess possible differences in spatial error correlation using the post processed and the near real time processed GPS data

Partner SMHI has been implementing a model for the spatial error correlations of the GPS ZTD in the HIRLAM model which enables correction for the errors during data assimilation. The model has
been tested in an impact study. The work of SMH is described in the following two reports:

 Report-200501

 Report-200509

For questions contact Martin Ridal at martin.ridal@smhi.se