• Home
  • Marta Gruszczynska
Marta Gruszczynska

Marta Gruszczynska
Institute of Meteorology and Water Management, National Research Institute · Department of Meteorological Analyses and Long-Range Forecasts, Centre of Numerical Weather Prediction

PhD Eng.

About

31
Publications
8,569
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
156
Citations

Publications

Publications (31)
Article
Full-text available
Due to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields deri...
Article
Full-text available
Introduction: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 coronavirus. Objectives: We aimed to analyze the correlation between six different meteorological parameters and the dynamics of the COVID-19 epidemic in 16 administrative regions (voivodeships) of Poland. Patients and methods: Current analysis was...
Article
Full-text available
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel coronavirus. The role of environmental factors in COVID-19 transmission is unclear. This study aimed to analyze the correlation between meteorological conditions (temperature, relative humidity, sunshine duration, wind speed) and dynamics of the COVID-19 pandemic in Po...
Chapter
Seasonal signatures observed within the Global Navigation Satellite System (GNSS) position time series are routinely modelled as annual and semi-annual periods with constant amplitudes over time. However, in this chapter, we demonstrate that these amplitudes can vary significantly over time, by as much as 3 mm at some stations. Different methods ha...
Chapter
Full-text available
We described a spatio-temporal analysis of environmental loading models: atmospheric, continental hydrology, and non-tidal ocean changes, based on multichannel singular spectrum analysis (MSSA). We extracted the common annual signal for 16 different sections related to climate zones: equatorial, arid, warm, snow, polar and continents. We used the l...
Chapter
A reliable subtraction of seasonal signals from the Global Positioning System (GPS) position time series is beneficial for the accuracy of derived velocities. In this research, we propose a two-stage solution of the problem of a proper determination of seasonal changes. We employ environmental loading models (atmospheric, hydrological and ocean non...
Presentation
Full-text available
Detecting breaks in tropospheric data is indispensable, since these breaks directly affect the trend estimates from Zenith Total Delay (ZTD) series or Integrated Water Vapor (IWV) records. Various algorithms have been already employed to report the exact epochs of break points during the entire time span of ZTD or IWV series. This procedure is know...
Article
Full-text available
A reliable subtraction of seasonal signals from the Global Positioning System (GPS) position time series is beneficial for the accuracy of derived velocities. In this research, we propose a two-stage solution of the problem of a proper determination of seasonal changes. We employ environmental loading models (atmospheric, hydrological and ocean non...
Article
Full-text available
We described a spatio-temporal analysis of environmental loading models: atmospheric, continental hydrology, and non-tidal ocean changes, based on Multichannel Singular Spectrum Analysis (MSSA). We extracted the common annual signal for 16 different sections related to climate zones: equatorial, arid, warm, snow, polar and continents. We used the l...
Poster
Full-text available
The process of homogenization employed for tropospheric time series, e.g. Integrated Water Vapour (IWV), involves the detection of breaks or shifts in the mean value of data. This is an extremely important task since trends estimated from tropospheric data applied nowadays to monitor changes in climate are affected by these breaks. Therefore, there...
Presentation
Full-text available
Seasonal variations in GNSS position time series can be arise from real geophysical and spurious effect. This research is focused on verification of the following hypothesis: geodetic position time series are characterised by common spatio-temporal seasonal signals which are time changeable with the optimal method for their investigation being Mult...
Poster
Full-text available
In this study, Singular Spectrum Analysis (SSA) along with its multivariate extension MSSA (Multichannel SSA) were used to estimate long-term trend and gravimetric factor at the Chandler wobble frequency from superconducting gravimeter (SG) records. We have used data from seven stations located worldwide and contributing to the International Geodyn...
Presentation
Full-text available
A proper homogenization of tropospheric dataset is indispensable, as the parameters of deterministic part, e.g. trend will be influenced by undetected breaks. Different groups have already used different methods and obtained different estimates - the truth is not known. A synthetic benchmark dataset is a proper way to quantify results given by vari...
Presentation
Full-text available
An accurate removal of the seasonal signals from the Global Positioning System (GPS) position time series is beneficial for the accuracy of the derived velocities. In this research, we propose a two-stage solution of the problem of reliable subtraction of seasonal changes. Firstly, we employ the environmental loading models (atmospheric, hydrologic...
Poster
Full-text available
A synthetic benchmark dataset of Integrated Water Vapour (IWV) was created within the activity of “Data homogenisation” of sub-working group WG3 of COST ES1206 Action. The benchmark dataset was created basing on the analysis of IWV differences retrieved by Global Positioning System (GPS) International GNSS Service (IGS) stations using European Cent...
Presentation
Full-text available
Within the COST Action ES1206 “Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate” (GNSS4SWEC), there was a clear interest and need to homogenize a worldwide Integrated Water Vapour (IWV) dataset retrieved with Global Positioning System (GPS), by correcting (artificial) break points d...
Presentation
Full-text available
In this research, we explored the ability of MSSA application to separate real geophysical effects from spurious effects in GPS time series. For this purpose, we used GPS position changes and environmental loading models. We analysed the topocentric time series from 250 selected stations located worldwide, delivered from Network Solution obtained b...
Article
Full-text available
We estimated the common seasonal signal (annual oscillation) included in the Global Positioning System (GPS) vertical position time series by using Multichannel Singular Spectrum Analysis (MSSA). We employed time series from 24 International GNSS Service (IGS) stations located in Europe which contributed to the newest ITRF2014 (International Terres...
Poster
Full-text available
The seasonal variations recorded by superconducting gravimeters (SG) may stem from non-tidal ocean loading, atmosphere loading, solid Earth tides, ocean tidal loading, continental water storage loadings and various errors. In this research, we used minute gravity changes from 18 stations located worldwide. The length of SG time series ranged from 4...
Presentation
Full-text available
Environmental loading effects, such as atmospheric, hydrological, and ocean non-tidal loading, can explain about 40% of the total variance of the annual signal in GPS time series. Ideally one would like to subtract the periodic signals from the GPS observations using a geophysical model. However, the errors in the geophysical models are still signi...
Article
Full-text available
In the modern geodesy the role of the permanent station is growing constantly. The proper treatment of the time series from such station lead to the determination of the reliable velocities. In this paper we focused on some pre-analysis as well as analysis issues, which have to be performed upon the time series of the North, East and Up components...
Poster
Full-text available
Seasonal signals in the GPS-derived time series arise from real geophysical signals related to tidal (residual) or non-tidal (loadings from atmosphere, ocean and continental hydrosphere, thermo elastic strain, etc.) effects and numerical artefacts including aliasing from mismodelling in short periods or repeatability of the GPS satellite constellat...
Article
Full-text available
Nowadays, beyond the dispute we should take into account the time-varying parameters of seasonals in the GPS-derived position time series. Either real geophysical effects or system-specified artefacts can introduce non-sinusoidal changes. For this study, we used 18 daily position time series from Central European stations provided by the Jet Propul...
Presentation
Full-text available
Seasonal variations in GPS time series have significant impact on reliable determination of station’s velocity. Incorrectly defined seasonal signals for stations which data was used during reference frame processing can bias the frame realization. The aim of this research is to extract seasonal oscillations from GPS time series in order to better i...
Article
In this research, we focus on determining the quasi-annual changes in GNSS-derived 3-dimensional time series. We use the daily time series from PPP solution obtained by JPL (Jet Propulsion Laboratory) from more than 300 globally distributed IGS stations. Each of the topocentric time series were stacked into data sets according to year (from January...
Article
Full-text available
The constantly growing needs of permanent stations’ velocities users cause their stability level to increase. To this research we included more than 150 stations located across Europe operating within the EUREF Permanent Network (EPN) with weekly changes in the ITRF2005 reference frame. The obvious long-range dependencies in the stochastic part of...

Network

Cited By

Projects

Projects (3)
Project
The main goal of the GNSS alert project is to develop an off-the-shelf network of devices that would provide detection and early warning for operators of critical infrastructure, for all kind of threats related to the use of satellite navigation signals. This project will create an IT system that will allow the customer to manage data, archive and analyse it. Thus it will be possible to control potential financial losses and help to avoid life-threatening dangers. In addition, instead of one GNSS-measurement device at a site, GNSS alert may be equipped with much more (for example 30) dispersed detecting devices keeping comparable costs of system implementation and maintenance to other products available on the market. Due to obligatory standards in aviation (ICAO Annex 10 & doc. 8071), the project is primarily addressed for air transport infrastructure operators and other aeronautical services providers. The system scalability and adaptability allows to implement it for the needs of other modes of transport, as well as emergency services, energy, communication and financial sectors, which are strictly dependent on space based PNT (position, navigation and timing) systems. Project co-financed by the European Union from the European Regional Development Fund under the Smart Growth Operational Programme. Project is implemented under The National Centre for Research and Development programme: Fast Track.
Project
Due to the series length, availability of observations and density of stations (more than 20 years of observations collected at 10 000 sites on the Earth), the position time series collected at the Global Positioning System (GPS) permanent stations have become an inexhaustible source of knowledge about phenomena happening at and inside the Earth. Velocities of permanent stations are interpreted as tectonic plate movement or possible earthquakes. Beyond the linear trend, also seasonal variations arising from hydrological, atmospheric or oceanic loadings can similarly influence time series collected at the nearby stations. Having modelled the deterministic part of the GPS position time series, which was mentioned above, the residuals (or a so-called noise) are obtained. Former researches showed that the GPS position time series are best characterized by the power-law noise with spectral index close to flicker noise. However, some part of residuals corresponds to the influence that the mismodelled large scale phenomena have on the GPS observations. This mismodelled part is being transferred to the individual observations and is referred to as a Common Mode Error (CME). The existence of both noises and CME will cause the overestimation of errors of velocities. Moreover, the inefficiently modelled seasonal part will result in an increase of: an auto-correlation of series, the noise level and indirectly also in an increase of velocity error. The main goal of the proposed project is then to provide new estimates of velocity field errors, being determined when spatially and temporally correlated signals in a form of seasonal variations and CME were removed from geodetic observations. Therefore, the research hypothesis of this project reads as follows: “spatially and temporally correlated signals need to be removed from GPS position time series before the reliability of permanent station’s velocity required for creation of reference frame is achieved”. Further, the authors make use of auxiliary hypothesis which is: “probabilistic Principal Component Analysis can be successfully applied to GPS position time series”. The authors propose to employ probabilistic Principal Component Analysis (pPCA), which has never been employed before to geodetic time series. As is supposed, pPCA can bring an innovation to how the CME are estimated in a way it handles missing data. Up until now, the stations with many missing data, or those which did not overlap each other were removed from CME estimation and therefore, the values of CME were not reliable. pPCA assumes that the values are missing at random through the data set. Therefore, the GPS position time series may start and end in a different independent epochs and also, these epochs do not have to overlap with each other. At a time of increasing number of newly established GPS stations, this assumption seems to be crucial so as not to lose information or false estimates due to missing observations, removed stations or interpolation.
Project
This research focuses on verification of the main research hypothesis which states as follows: "a proper recognition of stochastic part of ZTD (Zenith Total Delay) time series is indispensable to reliably estimate the parameters of deterministic part and their uncertainties (including trend used in analyses of climate change)". This hypothesis will be verified by comparison to common approach which includes only white process and is widely used to date by geodetic community to model the GNSS-derived ZTD time series. This innovative approach based on autoregressive process, which is going to be used for homogenously reprocessed and properly homogenized ZTD series, will result in new values of ZTD trends with their uncertainties that can be further interpreted in climate studies.