References of "Klos, Anna"
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See detailTracking Hurricanes using GPS atmospheric precipitable water vapor field
Ejigu, Yohannes Getachew; Teferle, Felix Norman UL; klos, Anna et al

in Beyond 100: The Next Century in Geodesy (2020)

Tropical cyclones are one of the most powerful severe weather events that produce devastating socioeconomic and environmental impacts in the areas they strike. Therefore, monitoring and tracking of the ... [more ▼]

Tropical cyclones are one of the most powerful severe weather events that produce devastating socioeconomic and environmental impacts in the areas they strike. Therefore, monitoring and tracking of the arrival times and path of the tropical cyclones are extremely valuable in providing early warning to the public and governments. Hurricane Florence struck the East cost of USA in 2018 and offers an outstanding case study. We employed Global Positioning System (GPS) derived precipitable water vapor (PWV) data to track and investigate the characteristics of storm occurrences in their spatial and temporal distribution using a dense ground network of permanent GPS stations. Our findings indicate that a rise in GPS-derived PWV occurred several hours before Florence’s manifestation. Also, we compared the temporal distribution of the GPS-derived PWV content with the precipitation value for days when the storm appeared in the area under influence. The study will contribute to quantitative assessment of the complementary GPS tropospheric products in hurricane monitoring and tracking using GPS-derived water vapor evolution from a dense network of permanent GPS stations [less ▲]

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See detailUsing the Vertical Land Movement estimates from the IGS TIGA combined solution to derive Global Mean Sea Level changes
Bogusz, Janusz; Hunegnaw, Addisu UL; Teferle, Felix Norman UL et al

Scientific Conference (2019, December 13)

Global mean sea level (GMSL) is now widely recognized to have risen between 1 to 2 mm/yr depending on location since the 20th century. Prior to the satellite altimetry era, GMSL was primarily estimated ... [more ▼]

Global mean sea level (GMSL) is now widely recognized to have risen between 1 to 2 mm/yr depending on location since the 20th century. Prior to the satellite altimetry era, GMSL was primarily estimated from a set of secular tide gauge records relative to coastal benchmarks. Recent measurements of GPS (Global Positioning System) have been demonstrated as a useful tool of a direct estimate of Vertical Land Motion (VLM) induced by both long and short-term geophysical and human-induced processes in a geocentric reference frame. This presentation will provide the results of a combination performed using the CATREF software of three independent GPS daily solutions provided by British Isles continuous GNSS Facility – University of Luxembourg consortium (BLT), German Research Centre for Geosciences (GFZ) and University of La Rochelle (ULR) under the auspices of the Tide Gauge Benchmark Monitoring (TIGA) Working Group (WG), that results in a spatially comprehensive map of VLM near or close to tide gauge benchmarks. The combination was performed in accordance with the second re-processing campaign (repro2) of the IGS (International GNSS Service). Long coastal tide gauge records from the archives maintained at the Permanent Service for Mean Sea Level (PSMSL) were extracted for relative sea level estimates. To cross-compare the sea level rates over the years, we employed observations between 1900-2016. Then, the time series were cut and analyzed separately, ceteris paribus, for the period 1960-2016. This analysis was aimed at a cross-comparison of relative sea level trends and their changes over the years. The stochastic part of the tide gauge records was analyzed with Maximum Likelihood Estimation (MLE) and assumed several different combinations of noise models with the Bayesian Information Criterion (BIC) providing a means to identify the preferred one. The relative sea level estimates were corrected by the inverted barometric effect to the tide-gauge records using data from the 20th century Reanalysis project version V2C, the effect of wind stress on the surface of the ocean in both, zonal and meridional components, as well as Pacific Decadal Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO) influencing Pacific tide gauge records. The GPS-based velocities were corrected by Glacial Isostatic Adjustment (GIA) effect using ICE-6G(VM5a) model with associated geoid rate and post seismic decays using ITRF2014 estimates. Also, environmental loading models were employed to account for present-day elastic loading in VLM. The Mean Sea Level (MSL) trends from tide gauges and VLM-corrected MSL trends using GIA model (TG+GIA) and the TIGA combination (TG+TIGA) were determined. Our final reconstruction of GMSL based on the MSL records from 1900 to 2016 where the VLM uncertainty is smaller than 0.7 mm/yr indicate a long-term trend of 1.75 +/- 0.2 mm/yr and is in good agreement with several similar determinations. [less ▲]

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See detailStatistical significance of trends in Zenith Wet Delay from re-processed GPS solutions
Klos, Anna; Hunegnaw, Addisu UL; Teferle, Felix Norman UL et al

in GPS Solutions (2018)

Long series of Zenith Wet Delay (ZWD) obtained as part of a homogeneous re-processing of Global Positioning System solutions constitute a reliable set of data to be assimilated into climate models. The ... [more ▼]

Long series of Zenith Wet Delay (ZWD) obtained as part of a homogeneous re-processing of Global Positioning System solutions constitute a reliable set of data to be assimilated into climate models. The correct stochastic properties, i.e. the noise model of these data, have to be identified to assess the real value of ZWD trend uncertainties since assuming an inappropriate noise model may lead to over- or underestimated error bounds leading to statistically insignificant trends. We present the ZWD time series for 1995–2017 for 120 selected globally distributed stations. The deterministic model in the form of a trend and significant seasonal signals were removed prior to the noise analysis. We examined different stochastic models and compared them to widely assumed white noise (WN). A combination of the autoregressive process of first-order plus WN (AR(1) + WN) was proven to be the preferred stochastic representation of the ZWD time series over the generally assumed white-noise-only approach. We found that for 103 out of 120 considered stations, the AR(1) process contributed to the AR(1) + WN model in more than 50% with noise amplitudes between 9 and 68 mm. As soon as the AR(1) + WN model was employed, 43 trend estimates became statistically insignificant, compared to 5 insignificant trend estimates for a white-noise-only model. We also found that the ZWD trend uncertainty may be underestimated by 5–14 times with median value of 8 using the white-noise-only assumption. Therefore, we recommend that AR(1) + WN model is employed before tropospheric trends are to be determined with the greatest reliability. [less ▲]

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See detailOn the combined effect of periodic signals and colored noise on velocity uncertainties
Klos, Anna; Olivares Pulido, German UL; Teferle, Felix Norman UL et al

in GPS Solutions (2017)

The velocity estimates and their uncertainties derived from position time series of Global Navigation Satellite System stations are affected by seasonal signals and their harmonics, and the statistical ... [more ▼]

The velocity estimates and their uncertainties derived from position time series of Global Navigation Satellite System stations are affected by seasonal signals and their harmonics, and the statistical properties, i.e., the stochastic noise, contained in the series. If the deterministic model in the form of linear trend and periodic terms is not accurate enough to describe the time series, it will alter the stochastic model, and the resulting effect on the velocity uncertainties can be perceived as a result of a misfit of the deterministic model. The effects of insufficiently modeled seasonal signals will propagate into the stochastic model and falsify the results of the noise analysis, in addition to velocity estimates and their uncertainties. We provide the general dilution of precision (GDP) of velocity uncertainties as the ratio of uncertainties of velocities determined from to two different deterministic models while accounting for stochastic noise at the same time. In this newly defined GDP, the first deterministic model includes a linear trend, while the second one includes a linear trend and seasonal signals. These two are tested with the assumption of white noise only as well as the combinations of power-law and white noise in the data. The more seasonal terms are added to the series, the more biased the velocity uncertainties become. With increasing time span of observations, the assumption of seasonal signals becomes less important, and the power-law character of the residuals starts to play a crucial role in the determined velocity uncertainties. With reference frame and sea level applications in mind, we argue that 7 and 9 years of continuous observations is the threshold for white and flicker noise, respectively, while 17 years are required for random-walk to decrease GDP below 5% and to omit periodic oscillations in the GNSS-derived time series taking only the noise model into consideration. [less ▲]

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See detailNoise characteristics in Zenith Total Delay from homogeneously reprocessed GPS time series
Klos, Anna; Hunegnaw, Addisu UL; Teferle, Felix Norman UL et al

Scientific Conference (2017, February 22)

Zenith Total Delay (ZTD) time series, derived from the re-processing of Global Positioning System (GPS) data, provide valuable information for the evaluation of global atmospheric reanalysis products such ... [more ▼]

Zenith Total Delay (ZTD) time series, derived from the re-processing of Global Positioning System (GPS) data, provide valuable information for the evaluation of global atmospheric reanalysis products such as ERA-Interim. Identifying the correct noise characteristics in the ZTD time series is an important step to assess the ’true’ magnitude of ZTD trend uncertainties. The ZTD residual time series for 1995-2015 are generated from our homogeneously re-processed and homogenized GPS time series from over 700 globally distributed stations classified into five major climate zones. The annual peak of ZTD data ranges between 10 and 150 mm with the smallest values for the polar and Alpine zone. The amplitudes of daily curve fall between 0 and 12 mm with the greatest variations for the dry zone. The autoregressive process of fourth order plus white noise model were found to be optimal for ZTD series. The tropical zone has the largest amplitude of autoregressive noise (9.59 mm) and the greatest amplitudes of white noise (13.00 mm). All climate zones have similar median coefficients of AR(1) (0.80±0.05) with a minimum for polar and Alpine, which has the highest coefficients of AR(2) (0.27±0.01) and AR(3) (0.11±0.01) and clearly different from the other zones considered. We show that 53 of 120 examined trends became insignificant, when the optimum noise model was employed, compared to 11 insignificant trends for pure white noise. The uncertainty of the ZTD trends may be underestimated by a factor of 3 to 12 compared to the white noise only assumption. [less ▲]

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See detailA New Vertical Land Movements Data Set from a Reprocessing of GNSS at Tide Gauge Stations
Hunegnaw, Addisu UL; Klos, Anna; Hansen, Dionne et al

Scientific Conference (2016, July 30)

The main objective of the International GNSS Service (IGS) Tide Gauge Benchmark Monitoring (TIGA) Working Group is to provide accurate coordinates and changes in them in the form of long-term trends for ... [more ▼]

The main objective of the International GNSS Service (IGS) Tide Gauge Benchmark Monitoring (TIGA) Working Group is to provide accurate coordinates and changes in them in the form of long-term trends for globally distributed Global Navigation Satellite System (GNSS) stations at or close to tide gauges (TGs). Mean sea level (MSL) records derived from TG observations measure sea level relative to benchmarks on the land and structures supporting the TGs. Therefore, any changes in land levels affect the MSL records and the computed estimates of sea level change, ie. the MSL trends. In order to compute regionally or globally averaged MSL required for climate studies, these MSL trends have to be corrected for the vertical land movements (VLMs) derived from the GNSS observations. In this study, we have estimated a new set of VLMs at or close to TGs from the recent reprocessing campaign “repro2” undertaken by British Isles continuous GNSS Facility and University of Luxembourg TIGA Analysis Center (BLT). The position time series of more than 700 stations distributed around the world have been reprocessed for the period 1994 to 2015 using the latest bias models and processing strategies following the conventions of the International Earth Rotation and Reference Frame Service (IERS). It is well known that position time series are affected by discontinuities, which stem from different sources such as earthquakes, hardware changes and other artificial offsets that do not reflect real geophysical events. Since uncorrected discontinuities adversely affect the trend estimates, we have, after applying all known offset epochs, inspected the time series of all stations manually and added any further offset epochs required during the analysis. We have included a total of 2500+ discontinuities of which two-thirds are from hardware changes, 4% from earthquakes and 9% from unknown sources. We fit a deterministic model (sum of linear trend and seasonal terms) to the position time series using the Hector software package. As expected the annual terms show the highest power with amplitudes of a few millimeters. The stochastic model for estimating trend and associated uncertainties follows a power-law noise process as has previously been described as optimal for GNSS-derived position time series. The new set of VLM estimates from our repro2 solution is evaluated through comparison with a published GNSS solution, the recent ICE-6G model of glacial isostatic adjustment and by application to the latest release of MSL trends from the Permanent Service For Mean Sea Level. [less ▲]

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See detailOn the Properties of Zenith Total Delay Time Series from Reprocessed GPS Solutions
Klos, Anna; Teferle, Felix Norman UL; Hunegnaw, Addisu UL et al

Poster (2016, July 29)

Global Positioning System observations from stations in regional and global networks have proven to sense the conditions of the atmosphere, especially the water vapour content of the troposphere. Zenith ... [more ▼]

Global Positioning System observations from stations in regional and global networks have proven to sense the conditions of the atmosphere, especially the water vapour content of the troposphere. Zenith Total Delay (ZTD) derived during the processing of GPS data is a measure of the total atmospheric delay along the signal path between satellite and receiver antennas and arises mostly from the hydrostatic and wet parts of the atmosphere. Having taken surface pressure and temperature into account, ZTD can be converted into an estimate of the Integrated Water Vapour (IWV) content of the atmosphere, which when derived from homogenously reprocessed GPS observations, is emerging as an important parameter in the monitoring of climate change. Especially, the long-term trend and variations in IWV together with their associated uncertainties are of high interest as atmospheric water vapour is the dominant greenhouse gas. To date the trend estimates and their uncertainties are widely determined with assumption that the stochastic properties of the time series follow a random, ie. white noise, process. However, if ZTD and IWV are directly linked to climate processes, one would expect that the underlying noise process has similar character to that found in other climate parameters, which have been modelled by means of an autoregressive process. If this proves to be true, the trend estimates and their uncertainties in ZTD and IWV may have been underestimated up to this day of an order of magnitude. In this research, we examine the properties of both deterministic and stochastic parameters of the ZTDs that were estimated by the consortium of the British Isles continuous GNSS Facility (BIGF) and the University of Luxembourg TIGA Analysis Centres (BLT) for GPS data collected by a global tracking network of more than 700 stations (repro2 solution). The analysis has been started with the homogenisation of the ZTD time series, which is an important task to provide homogeneity over the long-term. Here we used all previously reported discontinuities for a single station along with those added after manually inspecting the time series. This procedure did lead to a total number of 2505 discontinuities for this data set. Next, all significant oscillations were identified with spectral analysis and thereafter modelled with a Least-Squares Method. The residuals were subjected to noise analysis with different stochastic models. The results showed that an autoregressive model of fourth order combined with a white noise process is the optimal model for the ZTD time series. Finally, we provide an optimum evaluation of the ZTD trends and their uncertainties for selected climate zones, which were established according to the Köppen-Geiger climate classification. [less ▲]

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See detailThe Combined Effect of Periodic Signals and Noise on the Dilution of Precision of GNSS Station Velocity Uncertainties
Klos, Anna; Olivares Pulido, German UL; Teferle, Felix Norman UL et al

Poster (2016, April 05)

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series ... [more ▼]

Station velocity uncertainties determined from a series of Global Navigation Satellite System (GNSS) position estimates depend on both the deterministic and stochastic models applied to the time series. While the deterministic model generally includes parameters for a linear and several periodic terms, the stochastic model is a representation of the noise character of the time series in form of a power-law process. For both of these models the optimal model may vary from one time series to another while the models also depend, to some degree, on each other. In the past various power-law processes have been shown to fit the time series and the sources for the apparent temporally-correlated noise were attributed to, for example, mismodelling of satellites orbits, antenna phase centre variations, troposphere, Earth Orientation Parameters, mass loading effects and monument instabilities. [less ▲]

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See detailTotal Impact of Periodic Terms and Coloured Noise on Velocity Estimates
Klos, Anna; Olivares, German; Teferle, Felix Norman UL et al

Poster (2016, February 05)

The uncertainties of velocity estimates for position time series of Global Navigation Satellite System (GNSS) stations are mainly affected by a misfit of the deterministic model applied to this data ... [more ▼]

The uncertainties of velocity estimates for position time series of Global Navigation Satellite System (GNSS) stations are mainly affected by a misfit of the deterministic model applied to this data. Insufficiently modelled seasonal signals will propagate into the stochastic model and falsify the results of the noise analysis besides the velocity estimates and their uncertainties. In this presentation we derived the General Dilution of Precision (GDP) of velocity uncertainties. We define this dilution as the ratio between the uncertainties of velocities determined when different deterministic and stochastic models are applied. In this way we discuss, referring to previously published results, how insufficiently modelled seasonal signals influence station velocity uncertainties with white and coloured noise. Using simulated and real data from selected (115) IGS (International GNSS Service) stations we show that the noise character affects GNSS data more than seasonals for time series longer than 9 years. [less ▲]

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