COST ES1206 Sub-Working Group "Data Homogenisation": 2nd Workshop – Warsaw, Poland

A homogenisation of Integrated Water Vapour Time Series Retrieved from GPS and ERA-Interim: Building Synthetic Benchmark Datasets.

23 Jan 2017, 14:35

20m

Military University of Technology, Warsaw, Poland

Oral Presentation Opening Session Opening Session

Speaker

Dr Anna Klos (Military University of Technology)

Description

This research aims at providing the synthetic benchmark datasets that will be used by the COST Action ES1206 ‘data homogenization’ sub-working group to test the effectiveness of different statistical tools in view of the homogenization of Integrated Water Vapour (IWV) time series retrieved from GPS (Global Positioning System) and ERA-Interim. The effectiveness of these tools will be tested by their ability to properly report the epochs of offsets that were simulated along with seasonal signals, trend, gaps and two different types of coloured noises. The synthetic benchmark datasets have been generated based on the characterisation parameters (noise types and amplitudes, percentage of gaps, signals…) that were estimated from the common reference IWV time series retrieved from GPS and ERA-Interim model output (dataset shared within the working group for its activities), for a number of 120 International GNSS Service (IGS) permanent stations. Then, we simulated three flavours of 25-year long IWV time series datasets. The ‘Easy’ dataset includes seasonal signals (annual, semi-annual, 3 and 4 months if present for a particular station), offsets and only white noise. The ‘Less-complicated’ dataset includes the above-mentioned, as well as the combination of white noise and first order autoregressive processes (AR(1)+WH). The ‘Fully-complicated’ dataset includes, beyond the above characteristics, a trend and gaps. In this presentation, we focus on the deterministic parameters as well as stochastic properties that we estimated from the common IGS repro 1 reference IWV. Moreover, we describe in details the provided synthetic dataset along with possible impact of simulated but undetected offsets on trend and its uncertainty for their potential future application to the climate studies.