Barbara Chimani
(ZAMG)
23/01/2017, 17:10
Results based on the 'FULLY COMPLICATED' synthetic dataset
Oral Presentation
The break detection of HOMOP was applied to the Easy and the Fully Complicated datasets. Different criteria for the selection of reference stations were used and a different number of missing data was allowed. The presentation will give information on the results of these tests and the influence of the different penalty criteria used.
Michal Elias
(GOP Pecny)
23/01/2017, 17:25
Results based on the 'EASY' synthetic dataset
Oral Presentation
We implemented a method of mathematical statistics for a change-point detection. The method was evaluated and the results were compared with the "Easy" synthetic time-series dataset. Even though the applied method is suggested only for a sudden change determination in the analysed series, based on the results, this method is applicable to detect the inhomogeneity in the analysed series where...
Michal Elias
(GOP Pecny)
23/01/2017, 17:30
Results based on the 'LESS COMPLICATED' synthetic dataset
Oral Presentation
We implemented a method of mathematical statistics for a change-point detection. The method was evaluated and the results were compared with the "Less-Complicated" synthetic time-series dataset. A brief report on change-point detection applied on this particular kind of series is submitted in the presentation.
Michal Elias
(GOP Pecny)
23/01/2017, 17:35
Results based on the 'FULLY COMPLICATED' synthetic dataset
Oral Presentation
We implemented a method of mathematical statistics for a change-point detection. The method was evaluated and the results were compared with the "Fully-Complicated" synthetic time-series dataset. A short summary report presents two sets of the results; first, when the gaps were not covered in the methodology process and second, when the gaps were in some way eliminated before the change-point...
Dr
Roeland Van Malderen
(Royal Meteorological Institute of Belgium)
23/01/2017, 17:40
Results based on the 'EASY' synthetic dataset
Oral Presentation
We present the break points that have been identified in the time series by applying non-parametric rank-sum tests on the daily and monthly IWV differences at the station locations. We comment on the observed weaknesses of the method, the statistical significance, and the amplitude of the offsets that might be detected.
Dr
TONG NING
(NT)
23/01/2017, 17:55
Results based on the 'FULLY COMPLICATED' synthetic dataset
Oral Presentation
Atmospheric water vapour is one of the most important climate feedback process and a very efficient greenhouse gas. The long-term trends estimated from the atmospheric water vapour is therefore important for climate monitoring as an independent data source. However the potential temporal shifts in the integrated water vapour (IWV) time series obtained from different techniques, e.g. the global...
Dr
Jose A. Guijarro
(Spanish Meteorological Agency)
23/01/2017, 18:10
Results based on the 'EASY' synthetic dataset
Oral Presentation
‘Climatol’ is a contributed R package providing some tools for climatological tasks, the most important being the homogenization of climate time series by means of its homogen function. It was originally addressed to monthly series, but direct homogenization of daily series is also possible. However, homogenization of daily climatological series is recognized as a difficult task due to their...
Dr
Eric Pottiaux
(Royal Observatory of Belgium (ROB))
24/01/2017, 09:00
Results based on the 'EASY' synthetic dataset
Oral Presentation
In the same spirit as in the Venema et al. (2012) paper, we derived statistical scores (true positive, true negative, false positive, false negative) and probability scores (probability of true detection probability of false detection...) for each synthetic dataset type, and each sub-working group member contribution (i.e. results from running their homogenization tool on the synthetic...
Dr
Anna Klos
(Military University of Technology)
24/01/2017, 09:30
Results based on the 'EASY' synthetic dataset
Oral Presentation
During this presentation, we will describe the contribution of different statistical approaches employed for synthetic datasets to a task of homogenisation. We will compare a number of offsets found by different algorithms, seasonal signals estimated when different epochs were applied and trends along with their uncertainties to the values which were simulated. We will show how different...