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  • 1
  • 2
    Publication Date: 2017-12-01
    Description: Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over years it is still commonly observed that Zenith Tropospheric Delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double difference processing are most of the time caused by sub-daily data gaps at reference stations which cause disconnections of clusters of stations from the reference network and common–mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and coincide usually with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely-used strategy maximising the number of observations which available in many GNSS software. The reason is that observations are maximised before processing whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of one year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 3
  • 4
    Publication Date: 2019-07-29
    Description: This study analyzes the characteristics of GPS tropospheric estimates (zenith wet delays – ZWDs, gradients, and post-fit phase residuals) during the passage of mesoscale convective systems (MCSs) and evaluates their sensitivity to the research-level GPS data processing strategy implemented. Here, we focus on MCS events observed during the monsoon season of West Africa. This region is particularly well suited for the study of these events due to the high frequency of MCS occurrences in the contrasting climatic environments between the Guinean coast and the Sahel. This contrast is well sampled with data generated by six African Monsoon Multidisciplinary Analysis (AMMA) GPS stations. Tropospheric estimates for a 3-year period (2006–2008), processed with both the GAMIT and GIPSY-OASIS software packages, were analyzed and intercompared. First, the case of a MCS that passed over Niamey, Niger, on 11? August 2006 demonstrates a strong impact of the MCS on GPS estimates and post-fit residuals when the GPS signals propagate through the convective cells as detected on reflectivity maps from the MIT C-band Doppler radar. The estimates are also capable of detecting changes in the structure and dynamics of the MCS. However, the sensitivity is different depending on the tropospheric modeling approach adopted in the software. With GIPSY-OASIS, the high temporal sampling (5 min) of ZWDs and gradients is well suited for detecting the small-scale, short-lived, convective cells, while the post-fit residuals remain quite small. With GAMIT, the lower temporal sampling of the estimated parameters (hourly for ZWDs and daily for gradients) is not sufficient to capture the rapid delay variations associated with the passage of the MCS, but the post-fit phase residuals clearly reflect the presence of a strong refractivity anomaly. The results are generalized with a composite analysis of 414 MCS events observed over the 3-year period at the six GPS stations with the GIPSY-OASIS estimates. A systematic peak is found in the ZWDs coincident with the cold pool crossing time associated with the MCSs. The tropospheric gradients reflect the path of the MCS propagation (generally from east to west). This study concludes that ZWDs, gradients, and post-fit phase residuals provide relevant and complementary information on MCSs passing over or in the vicinity of a GPS station.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 5
    Publication Date: 2019-01-23
    Description: To study key processes of the water cycle, two special observation periods (SOPs) of the Hydrological cycle in the Mediterranean experiment (HyMeX) took place during the autumn 2012 and winter 2013. The first SOP aimed to study high precipitation systems and flash-flooding in the Mediterranean area. The AROME-WMED (West-Mediterranean) model (Fourrié et al., 2015) is a dedicated version of the mesoscale Numerical Weather Prediction (NWP) AROME-France model 5 which covers the western Mediterranean basin providing the HyMeX operational centre with daily real-time analyses and forecasts. These products allowed adequate decision-making for the field campaign observation deployment and the instrument operation. Shortly after the end of the campaign, a first re-analysis with more observations was performed with the first SOP operational software. An ensuing comprehensive second re-analysis of the first SOP which included field research observations (not assimilated in real-time), and some reprocessed observation datasets, was made with AROME-WMED. Moreover, a more recent version of the AROME model was used with updated background error statistics for the assimilation process. This paper depicts the main differences between the real-time version and the benefits brought by HyMeX re-analyses with AROME-WMED. The first re-analysis used 9 % of additional data and the second one 24 % more compared to the real-time version. The second re-analysis is found to be closer to observations than the previous AROME-WMED analyses. The second re-analysis forecast errors of surface parameters are reduced up to the 18-h or 24-h forecast range. In the mid and in the upper troposphere, upper-level fields are also improved up to the 48-h forecast range when compared to radiosondes. Integrated Water Vapour comparisons indicate a positive benefit for at least 24 hours. Precipitation forecasts are found to be improved with the second re-analysis for a thresholds up to 10 mm/24-h. For higher thresholds, the frequency bias is degraded. Finally, improvement brought by the second re-analysis is illustrated with the Intensive Observation Period (IOP 8) associated with heavy precipitation over Eastern Spain and South of France.
    Print ISSN: 1991-9611
    Electronic ISSN: 1991-962X
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 6
    Publication Date: 2019-07-08
    Description: To study key processes of the water cycle, two special observation periods (SOPs) of the Hydrological cycle in the Mediterranean experiment (HyMeX) took place during autumn 2012 and winter 2013. The first SOP aimed to study high precipitation systems and flash flooding in the Mediterranean area. The AROME-WMED (western Mediterranean) model (Fourrié et al., 2015) is a dedicated version of the mesoscale Numerical Weather Prediction (NWP) AROME-France model, which covers the western Mediterranean basin providing the HyMeX operational center with daily real-time analyses and forecasts. These products allowed for adequate decision-making for the field campaign observation deployment and the instrument operation. Shortly after the end of the campaign, a first reanalysis with more observations was performed with the first SOP operational software. An ensuing comprehensive second reanalysis of the first SOP, which included field research observations (not assimilated in real time) and some reprocessed observation datasets, was made with AROME-WMED. Moreover, a more recent version of the AROME model was used with updated background error statistics for the assimilation process. This paper depicts the main differences between the real-time version and the benefits brought by HyMeX reanalyses with AROME-WMED. The first reanalysis used 9 % additional data and the second one 24 % more compared to the real-time version. The second reanalysis is found to be closer to observations than the previous AROME-WMED analyses. The second reanalysis forecast errors of surface parameters are reduced up to the 18 and 24 h forecast range. In the middle and upper troposphere, fields are also improved up to the 48 h forecast range when compared to radiosondes. Integrated water vapor comparisons indicate a positive benefit for at least 24 h. Precipitation forecasts are found to be improved with the second reanalysis for a threshold up to 10 mm (24 h)−1. For higher thresholds, the frequency bias is degraded. Finally, improvement brought by the second reanalysis is illustrated with the Intensive Observation Period (IOP8) associated with heavy precipitation over eastern Spain and southern France.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 7
    Publication Date: 2017-07-28
    Description: Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total Column Water Vapour (TCWV) data set derived from ground-based GPS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectrometer (MODIS), the Atmospheric Infrared System (AIRS), and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GPS and satellite data are carried out for three reference Arctic observation sites (Sodankyla, Ny-Alesund and Thule) where long homogeneous GPS time series are available. We select hourly GPS data that are coincident with overpasses of the different satellites over the 3 sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GPS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GPS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high latitude stations during fall and winter). SCIAMACHY TCWV data are generally drier than GPS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Alesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankyla during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankyla. The MODIS bias at Sodankyla is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally-dependent surface albedo and a better consideration of vertically-resolved cloud cover are recommended if biases in satellite measurements are to be reduced in polar regions.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 8
    Publication Date: 2019-03-06
    Description: This study analyzes the characteristics of GPS tropospheric estimates (Zenith Wet Delays, and gradients, and post-fit phase residuals) during the passage of Mesoscale Convective Systems (MCSs) and evaluates their sensitivity to the research-level GPS data processing strategy implemented. Here, we focus on MCS events observed during the monsoon seasons of West Africa. This region is particularly well suited because of the high frequency of occurrence of MCSs in contrasting climatic environments between the Guinean coast and the Sahel. This contrast is well sampled data with the six AMMA GPS stations. Tropospheric estimates for 3-year period (2006–2008), processed with both GAMIT and GIPSY-OASIS software packages, were analyzed and inter-compared. First, the case an MCS which passed over Niamey, Niger, on 11 August 2006, demonstrates a strong impact of the MCS on GPS estimates and post-fit residuals when the GPS signals propagate through convective cells as detected on reflectivity maps from MIT’s C-band Doppler radar. The estimates are also capable of detecting changes in the structure and dynamics of the MCS. The sensitivity is however different depending on the tropospheric modeling approach adopted in the software. With GIPSY-OASIS, the high temporal sampling (5 min) of Zenith Wet Delays and gradients is well suited for detecting the small-scale, short-lived, convective cells, while the post-fit residuals remain quite small. With GAMIT, the lower temporal sampling of the estimated parameters (hourly for Zenith Wet Delays and daily for gradients) is not sufficient to capture the rapid delay variations associated with the passage of the MCS, but the post-fit phase residuals clearly reflect the presence of a strong refractivity anomaly. The results are generalized with a composite analysis of 414 MCS events observed over the 3-year period at the six GPS stations with the GIPSY-OASIS estimates. A systematic peak is found in the Zenith Wet Delays coincident with the cold-pool crossing time associated to the MCSs. The tropospheric gradients are reflecting the path of the MCS propagation (generally from East to West). This study concludes that Zenith Wet Delays, gradients, and post-fit phase residuals provide relevant and complementary information on MCSs passing over or in the vicinity of a GPS station.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 9
    Publication Date: 2019-01-22
    Description: This study examines the consistency and representativeness differences of daily IWV data from ERA-Interim reanalysis and GPS observations at 120 global sites over a 16-year period (1995–2010). Various comparison statistics are analysed as a function of geographic, topographic, and climatic features. A small (±1 kg m−2) bias is found in the reanalysis across latitudes (moist in northern and southern mid-latitudes and dry in the tropics). The standard deviation of daily IWV differences is generally below 2 kg m−2 but peaks in the northern and southern storm-tracks regions. In general, the larger IWV differences are explained by increased representativeness errors, when GPS observations capture some small-scale variability that is not resolved by the reanalysis. A representativeness error statistic is proposed which measures the spatiotemporal variability in the vicinity of the GPS sites, based on reanalysis data at the four surrounding grid points. It allows to predict the standard deviation of daily IWV differences with a correlation of 0.73. In general, representativeness differences can be reduced by temporal averaging and spatial interpolation from the four surrounding grid points. A small number of outlying cases (15 sites) which don’t follow the general tendencies are further examined. It is found that their special topographic and climatic features strongly enhance the representativeness errors (e.g. steep topography and coast-lines, strong seasonal cycle in monsoon regions). Discarding these sites significantly improves the global ERA-Interim and GPS comparison results. The selection of site a priori, based on the representativeness error statistic, is able to detect 11 out of the 15 sites and improve the comparison results by 20 to 30 %.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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  • 10
    Publication Date: 2016-07-05
    Description: A detailed investigation of calibration variation sources in the instrumental part of the detection-fibered, water vapor Raman lidar, Rameau, is presented. This lidar has been developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) and aims at calibrating GNSS wet delay signals and thus at improving vertical positioning. Several measurements campaigns enabled to validate the capacity of the instrument to retrieve high accuracy water vapor measurements. However, in order to insure a good stability, regular calibrations were necessary and led us to seek for instability sources in each sub-system of the instrument. The calibration variations are shown to be induced by fiber mode fluctuations and spatial non-uniformity of the photomultiplier photocathodes, and are responsible for significant calibration coefficient drifts. Such drifts are incompatible with both the long term stability required for applications such as climatology and the absolute accuracy needed for wet path delay correction of GNSS signals. We show by means of experimental tests that variation sources can be mitigated by means of an optimization and re-design of the optical detection system, a careful alignment procedure, and the operational monitoring of the system with dedicated measurements. In order to validate the modifications of the system and the new procedure, measurements were repeated over a period of 5 months. The detection subsystem stability was monitored from lidar profiles measured with a unique nitrogen filter used for detecting the signal in the two measurement channels. Compared to the previous campaign (Development of Methodologies for Water Vapor Measurement, Demevap), we observe an improvement in the stability of the system based on the nitrogen measurements which showed a drift of less than 3 % per month and a standard deviation of about 3 % during the campaign. The water vapor calibration coefficients were determined from capacitive humidity sensor measurements and from GPS zenith wet delays measurements. They show a similar small drift of 3 % per month and a standard deviation of ~ 6 %. Thanks to the N2 measurements, the drift can be completely removed. Lower standard deviation can be achieved by increasing the Signal to Noise Ratio and/or spatial and temporal integration window.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union (EGU).
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