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In recent years, the significant growth of positioning applications has come with the development of low-cost dual frequency Global Navigation Satellite Systems (GNSS) receivers. Such receivers allow high precision positioning to be achieved. They are becoming increasingly popular for geosciences as they allow for large numbers of equipment at affordable prices. Founded in 2019, the Centipede network is a collaborative permanent GNSS network that aims to offer free real-time centimetric positioning to any user. The network is currently made up of more than 330 low-cost reference stations located mainly in France and has nearly 500 regular users. Since July 2022, the GNSS raw data acquired by the stations forming this network have been archived by the Réseau National GNSS (RENAG) scientific network data centre in order to evaluate their suitability for geosciences applications such as tectonic, sea-level monitoring, troposphere and ionosphere studies. In this study, we present a first evaluation of the use of this dataset for the retrieval of integrated water vapour content (IWV) over five months in 2022. Troposphere delays are estimated from a PPP analysis and are converted to IWV using a standard procedure. Then, the IWV are compared with those retrieved for GNSS stations from the “conventional” French permanent GNSS networks, the Réseau GNSS Permanent (RGP) and RENAG. The results of these comparisons are conclusive, with root mean square differences in the range of 0.5-2 kg/m2 and high correlations of the time series registered by nearby low-cost and geodetic-class receivers. These results confirm the high potential of low-cost GNSS networks. The development of such network is a real opportunity for geoscience applications, particularly in poorly instrumented areas. In such areas, their contribution could be especially significant for meteorological or climatological applications for which the monitoring of water vapour by GNSS is widely used.

International audience; The representation of a high-impact weather (HIW) event over southern France is evaluated in Météo-France forecasts, and the sensitivity of the HIW forecast to the upstream upper-level flow and the Mediterranean and North Atlantic humidity structure prior to the event is quantified. The event occurred in October 2016 during the international field experiment NAWDEX. The approach of an upper-level potential vorticity (PV) cut-off, referred to as cut-off Sanchez, triggered extreme precipitation over southern France. Many 2- to 7-day ensemble forecasts predicted the maximum of the extreme precipitation and the location of the upper-level PV cut-off too far to the east. This eastward shift primarily resulted from an underestimation of the cut-off intensity two days before the HIW and the subsequent downstream propagation and amplification of these errors in the vicinity of Sanchez. Improving the representation of the cut-off two days before the event significantly improved the forecast quality. Another error source were inaccuracies in the moisture structure in the eastern North Atlantic. Specifically, an underestimation of the moisture in the warm conveyor belt inflow led to errors in the low- and upper-level circulation that eventually contributed to the eastward shift of the HIW two days later. Corrections in the eastern North Atlantic humidity structure further improved the forecast quality. On the other hand, corrections in the Mediterranean humidity structure had only a small impact on the accuracy of the forecast. The findings illustrate the importance of downstream error propagation and moist diabatic processes for the prediction of extreme weather over Europe, and demonstrate how targeted changes in the PV and humidity field a few days in advance can improve the quality of the forecasts.

In the framework of the EUREC 4 A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases ( −1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2 . The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2 , which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2 , reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre ( https://en.aeris-data.fr/ , last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 ( Bosser et al. , 2020 a ) and https://doi.org/10.25326/74 ( Bosser et al. , 2020 d ) , respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 ( Bosser et al. , 2020 b ) and https://doi.org/10.25326/75 ( Bosser et al. , 2020 e ) , respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 ( Bosser et al. , 2020 c ) and https://doi.org/10.25326/76 ( Bosser et al. , 2020 f ) , respectively.

Integrated water vapour (IWV) measurements from similar or different techniques are often inter-compared for calibration and validation purposes. Results are usually assessed in terms of bias (difference of the means), standard deviation of the differences, and linear fit slope and offset (intercept) estimates. When the instruments are located at different elevations, a correction must be applied to account for the vertical displacement between the sites. Empirical formulations are traditionally used for this correction. In this paper we show that the widely used correction model based on a standard, exponential, profile for water vapour cannot properly correct the bias, slope, and offset parameters simultaneously. Correcting the bias with this model degrades the slope and offset estimates and vice versa. This paper proposes an improved correction method that overcomes these limitations. It implements a multiple linear regression method where the slope and offset parameters are provided from a radiosonde climatology. It is able to predict monthly mean IWVs with a bias smaller than 0.1 kg m−2 and a root-mean-square error smaller than 0.5 kg m−2 for height differences up to 500 m. The method is applied to the inter-comparison of GPS IWV data in a tropical mountainous area and to the inter-validation of GPS and satellite microwave radiometer data. This paper also emphasizes the need for using a slope and offset regression method that accounts for errors in both variables and for correctly specifying these errors.

In recent years, the significant growth of positioning applications has come with the development of low-cost dual frequency Global Navigation Satellite Systems (GNSS) receivers. The accuracy of these receivers in terms of positioning has been proved. Various studies have also highlighted the ability of these receivers to precisely monitor the atmospheric water vapour. The low cost of such receivers enables large deployment, thus presenting an advantage for many geoscience applications.In this context, we have developed a hydrographic buoy prototype, equipped with low-cost GNSS receiver and antenna. This buoy was first aimed to be used for the monitoring in delayed time of offshore tides and currents, by a precise point positioning analysis of the GNSS raw data. In addition, the ability of this low-cost GNSS buoy for the water vapour monitoring was also investigated through the assessment of Zenith Tropospheric Delay (ZTD) estimates from the post-processing of the raw data. The comparisons with ZTD estimates from a nearby ground-based GNSS geodetic antenna and the ECMWF fifth ReAnalysis (ERA5), provide pretty good results with RMS differences lower than 10 mm. These conclusive results highlight the opportunities for the use of such low-cost systems for meteorology and climatology applications over the Oceans.

The aim of this work is to study the impact of the processing parameterization on the estimation of the zenith total delay (ZTD) from a shipborne GNSS antenna measurement. For this purpose, we used a simplified observation model, and simulated a realistic configuration of measurements (ephemerids, troposphere, motion of the shipborne antenna). Different sources of error that could affect the measurement were also simulated. The impact of these errors was then evaluated on the estimation by Kalman filtering, using different parameterizations (multi-constellation, solution sampling, random walk process noise for the ZTD estimates, observation weighting, cut-off angle). As it could have been expected, low cut-off angle (in the range of 3 to 7 degrees) and multi-constellation provide more accurate results. The choice of the data weighting is shown to significantly impact the difference on the estimates, and the use of a square-root of sine function, or uniform weighting of elevation gives the most conclusive results. High value of random walk process noise for ZTD estimates should also be avoided. Globally, the accuracy of the ZTD estimation can be improved up to more than 90% according to the configuration. The results of this work will be helpful to set up an optimal parameterization for the processing of massive dataset of GNSS measurements acquired from shipborne antennas.

Water vapor is a key variable in meteorology and climate studies. Since the late 90s, Global Navigation Satellite System (GNSS) estimates from ground antennas are commonly used for its description. Indeed, propagation delays are due to the transit of the signal through the atmosphere. The correction of these delays is a crucial step that is needed for the precise GNSS positioning. Integrated Water Vapor (IWV) contents are derived from these delays and are used to describe the distribution of water vapour in the atmosphere.However, severe meteorological phenomena often originate over the oceans and could strongly affect coastal regions. These phenomena are less well described or forecasted because of the small number of observations available in these regions. In this context, the potential of shipborne GNSS measurements has already been highlighted.This work aims at investigating the impact of some GNSS processing parameters on IWV retrieval from a shipborne antenna in PPP mode. The studied parameters are cutoff angle, random walk of the estimated delays, and observation weighting. Data were collected for 2 months in 2018 by the GNSS antenna of a vessel operating in the Bay of Brest, France. The impact of the parameters is assessed by comparing the shipborne GNSS-derived IWV to the IWV estimated from a close GNSS ground station, and those computed by the ERA5 reanalysis and operational radiosonde profiles from the nearest Météo-France station. The most satisfying parameterization is shown to have Root Mean Squared (RMS) differences of 0.5 kg m−2, 0.9 kg m−2, and 1.2 kg m−2 compared to GNSS ground station, ERA5, and radiosonde respectively. These conclusive results are also confirmed by comparing the GNSS height estimates to the measurements from the Brest tide gauge, with an RMS difference of 4.9 cm.

In the framework of the research project “Marion Dufresne Atmospheric Program – Indian Ocean” (MAP-IO), which is aiming at collecting long-term atmospheric and marine biology observations in the under-instrumented Indian and Austral Oceans, a Global Navigation Satellite System (GNSS) receiver was installed on the research vessel (RV) Marion Dufresne in October 2020 to describe, and monitor, global moisture changes in these areas. GNSS raw data are recorded continuously and used to retrieve integrated water vapor contents (IWV) along the RV route.After a data quality check that confirmed that a wise choice of location of the GNSS antenna on the RV is crucial to avoid mask, signal reflection and interference from other instruments that may degrade IWV retrieval, a first assessment of the GNSS analysis performances was carried out by comparing the vertical component of the estimated positions to sea surface height model. The differences are on the order of 20 to 30 cm; they are consistent with both the error budget for sea surface height determination using GNSS and the sea surface height model formal errors.An evaluation of GNSS-derived IWV was conducted using IWV estimates from the ECMWF fifth ReAnalysis (ERA5) and ground-based GNSS reference stations located nearby the tracks of RV Marion Dufresne. Preliminary analyses show encouraging results with a mean root mean square error of ~2-3 kg m-2 between ERA5 and GNSS-derived IWV. The use of ultra-rapid GNSS orbit and clock product was also investigated to assess the performance of near real-time GNSS-derived IWV estimation for numerical weather prediction purposes.

IWV data were retrieved from a network of nearly fifty Global Navigation Satellite System (GNSS) stations distributed over the Caribbean arc for the period 1 January-29 February 2020 encompassing the EUREC4A field campaign. Two of the stations had been installed at the Barbados Cloud Observatory (BCO) during fall 2019 in the framework of the project and are still running. All other stations are permanent stations operated routinely from various geodetic and geophysical organisations in the region. High spatial and temporal Integrated Water Vapour (IWV) observations will be used to investigate the atmospheric environment during the life cycle of convection and its feedback on the large-scale circulation and energy budget.This paper describes the ground-based GNSS data processing details and assesses the quality of the GNSS IWV retrievals as well as the IWV estimates from radiosoundings, microwave radiometer measurements and ERA5 reanalysis.The GNSS results from five different processing streams run by IGN and ENSTA-B/IPGP are first intercompared. Four of the streams were run operationally, among one was in near-real time, and one was run after the campaign in a reprocessing mode. The uncertainties associated with each of the data sets, including the zenith tropospheric delay to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the BCO and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (-2.9 kg/m2) and the GNSS results (-1.2 kg/m2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg/m2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The HATPRO IWV estimates agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to GNSS and BCO sondes before that date. ERA5 IWV estimates are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated.

Ground-based Global Navigation Satellite System (GNSS) measurements from nearly fifty stations distributed over the Caribbean Arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality Integrated Water Vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the Tradewinds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD) to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a colocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS derived IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organisation for five representative GNSS stations across the Caribbean Arc and found that the environment of Fish cloud patterns to be moister than that of Flowers cloud patterns which, in turn, is moister than the environment of Gravel cloud patterns. The differences in the IWV means between Fish and Gravel were assessed to be significant. Finally, the Gravel moisture environment was found to be similar to that of clear, cloud-free conditions. The moisture environment associated with the Sugar cloud pattern has not been assessed because it was hardly observed during the first two months of 2020. The reprocessed ZTD and IWV data set from 49 GNSS stations used in this study are available from the AERIS data center (https://doi.org/10.25326/79; Bock (2020b)).

The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.

For the documentation of time and space variations of water vapor in atmosphere during the Nawdex campaign (North Atlantic, Autumn 2016), a ground network of more than 1200 coastal continuously operation reference GNSS stations has been analyzed. This network spreads from Caribbeans to Morocco through Greenland. Retrieved IWV have been used to evaluate ERAI and ERA5 reanalysis and highlight improvements made by ERA5 (-0.2 +/- 1.6 kg/m2 vs -0.3 +/- 2.1 kg/m2 overall). They are also used to describe high impact weather events that took place during the experiment.The analysis of this ground GNSS network has been completed with the IWV retrieved from GPS data acquired by the French RV Atalante which cruises in the area during the experiment. IWV from shipborne receiver are consistent with both ERAI and ERA5 reanalysis (1.0 +/- 3.2 kg/m2 and 1.3 +/- 2.0 kg/m2 respectively) ; shipborne IWV also agree with IWV from nearby ground GNSS stations (-0.4 +/- 0.9 kg/m2). These results confirm the quality of shipborne IWV retrievals and opens up prospects for use in climatology and meteorology.

This work aims to provide a quick review of different experiments conducted in the past for the estimation of integrated water vapor content from shipborne GNSS receiver. This state of the art will be confronted with results obtained using GPS data acquired by the French Hydrographic Ship Borda on a cruise over Atlantic Ocean and Mediterranean Sea, from Brest to Toulon in August 2015; the estimated IWV are compared with satellite observations (MODIS) and outputs from numerical weather prediction models (ERAI, ERA5, Arpege, Arome); while differences between GPS and MODIS retrievals reach almost 4 kg/m2 in terms of RMS, agreement is generally much better with numerical models (2 up to 3 kg/m2 in terms of RMS). Use of real-time orbit and clocks product is also investigated in order to assess the performance of near real-time GPS-IWV estimation for NWP purposes. We will draw out the prospects in terms of possibilities and opportunities for the use of shipborne GNSS IWV for meteorology and climatology.

International audience; This article presents a coupled system consisting of a single-frequency GPS receiver and a light photogrammetric quality camera embedded in an Unmanned Aerial Vehicle (UAV). The aim is to produce high quality data that can be used in metrology applications. The issue of Integrated Sensor Orientation (ISO) of camera poses using only GPS measurements is presented and discussed. The accuracy reached by our system based on sensors developed at the French Mapping Agency (IGN) Opto-Electronics, Instrumentation and Metrology Laboratory (LOEMI) is qualified. These sensors are specially designed for close-range aerial image acquisition with a UAV. Lever-arm calibration and time synchronization are explained and performed to reach maximum accuracy. All processing steps are detailed from data acquisition to quality control of final products. We show that an accuracy of a few centimeters can be reached with this system which uses low-cost UAV and GPS module coupled with the IGN-LOEMI home-made camera.

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.

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.

In the framework of the HyMeX project, measurements from more than one thousand ground-based GPS receivers located in the north-western Mediterranean area are reprocessed using a single GPS software for the period from 1st September 2012 to 31 March 2013. A special screening procedure is developed for the removal of outliers in the GPS ZTD data. ZTD data are converted to IWV using surface pressure information from AROME-WMED operational analysis. The reprocessed ZTD and IWV data are used to assess the accuracy of the near real time E-GVAP ZTD data assimilated in operational NWP systems and to validate the IWV data from AROME-WMED operational analysis and AROME-WMED reanalysis 1, and from radiosonde observations. The mean differences between E-GVAP and reprocessed ZTD data are not negligible and lie in the range from −3 to +3 mm. The standard deviations of differences are between 4 and 8 mm. The comparisons of IWV from AROME-WMED analyses and the reprocessed GPS data show high quality of the analyses where operational GPS data are assimilated and lower quality where no GPS data are assimilated. Small but significant biases are found in the radiosonde data at daytime (−0.5 to +1.4 kg m−2), but their origin is not determined so far. Thanks to the high spatial density of the reprocessed GPS stations, both the large scale and small scale variations in IWV can be documented. The case of HyMeX Intensive Observing Period 8 is presented as an example of heavy precipitation event. This work suggests that improved quality of the humidity fields can be expected of the future AROME-WMED reanalysis 2 as a result of the assimilation of the reprocessed GPS data.

L’Armee de terre est pleinement engagee sur le territoire national avec l’operation Sentinelle. S’appuyant sur sa culture operationnelle, les forces terrestres disposent de capacites reelles pour contribuer a la securite des populations, tout en poursuivant ses engagements a l’exterieur et en adaptant son organisation.

Over the last decade, Unmanned Airbone Vehicles (UAVs) have been largely used for civil applications. Airborne photogrammetry has found place in these applications not only for 3D modeling but also as a measurement tool. Vinci-Construction-Terrassement is a private company specialized in public works sector and uses airborn photogrammetry as a mapping solution and metrology investigation tool on its sites. This technology is very efficient for the calculation of stock volumes for instance, or for time tracking of specific areas with risk of landslides. The aim of the present work is to perform a direct georeferencing of images acquired by the camera leaning on an embedded GPS receiver. UAV, GPS receiver and camera used are low-cost models and therefore data processing is adapted to this particular constraint.

L’Armee de terre est dans un processus permanent d’adaptation aux enjeux strategiques. S’appuyant sur la maturite de ses soldats et l’experience operationnelle acquises, le nouveau modele « Au contact » lui permettra d’etre plus efficace et de repondre a l’accroissement des menaces pour defendre les Francais.

We have investigated calibration variations in the Rameau water vapor Raman lidar. This lidar system was developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS). It aims at calibrating Global Navigation Satellite System (GNSS) measurements for tropospheric wet delays and sounding the water vapor variability in the lower troposphere. The Rameau system demonstrated good capacity in retrieving water vapor mixing ratio (WVMR) profiles accurately in several campaigns. However, systematic short-term and long-term variations in the lidar calibration factor pointed to persistent instabilities. A careful testing of each subsystem independently revealed that these instabilities are mainly induced by mode fluctuations in the optic fiber used to couple the telescope to the detection subsystem and by the spatial nonuniformity of the photomultiplier photocathodes. Laboratory tests that replicate and quantify these instability sources are presented. A redesign of the detection subsystem is presented, which, combined with careful alignment procedures, is shown to significantly reduce the instabilities. Outdoor measurements were performed over a period of 5 months to check the stability of the modified lidar system. The calibration changes in the detection subsystem were monitored with lidar profile measurements using a common nitrogen filter in both Raman channels. A short-term stability of 2–3 % and a long-term drift of 2–3 % per month are demonstrated. Compared to the earlier Development of Methodologies for Water Vapour Measurement (DEMEVAP) campaign, this is a 3-fold improvement in the long-term stability of the detection subsystem. The overall water vapor calibration factors were determined and monitored with capacitive humidity sensor measurements and with GPS zenith wet delay (ZWD) data. The changes in the water vapor calibration factors are shown to be fairly consistent with the changes in the nitrogen calibration factors. The nitrogen calibration results can be used to correct the overall calibration factors without the need for additional water vapor measurements to within 1 % per month.

International audience; In this work, we compare IASI-retrieved vertical water vapour profiles and related precipitable water over a complex region, namely the Rhine Valley area, during the pre-operational period of IASI exploitation (June?August 2007). Both IASI water vapour mixing ratio profiles and integrated water vapour content are retrieved from L1C radiances spectra using two techniques and compared with water vapour related observations acquired during the Convective and Orographically-induced Precipitation Study (COPS) field campaign that took place in this area at that time (i.e. lidars, radiosoundings and a global positioning system - GPS - station network). This work addresses the issue of IASI vertical spatial resolution and its capability to detect two-layer water vapour structures such as those observed in a mountainous area and which play an important role in convective initiation or inhibition. We found that this capability mostly relies on the type of a-priori background vector (climatology or space-time colocated ECMWF analysis), which is used within the retrieval scheme. Systematic comparison of water vapour products derived from 71 IASI spectra confirms that IASI can retrieve water vapour amounts in 2 km width layers, in the lower troposphere, with an accuracy of approximately 10%.

altitude region 0.5 –3.5 km, while comparisons between BASIL and the airborne DLR DIAL lead to a mean relative bias of 1.87% (0.018 g kg −1 ) in this same altitude region. Comparisons between the ground-based UHOH DIAL and the CNRS DIAL indicate a bias of −3.2% (−0.37 × 10 22 m −3 ) in the altitude range 1.5 –4.5 km, while comparisons between the UHOH DIAL and the DLR DIAL indicate a bias of 0.83% (0.06 × 10 22 m −3 ) in this same altitude range. Based on the available comparisons between the groundbased Raman lidar BERTHA and the CNRS DIAL, the mean relative bias is found to be −4.37% (−0.123 g kg −1 ) in the altitude region 0.5 –4.5 km. Comparisons between the ground-based IGN Raman lidar and the CNRS DIAL indicate a bias of 3.18% (0.55 g kg −1 ) in the altitude range from 0.5 to 4.5 km, while comparisons between the CNRS DIAL and DLR DIAL result in a mean relative bias of 3.93% (1.1 × 10 22 m −3 ) in the altitude interval 0.5 –4.0 km. Based on the available statistics of comparisons, benefiting from the fact that the CNRS DIAL was able to be compared with all other lidar systems, and putting equal weight on the data reliability of each instrument, overall relative values for BASIL, BERTHA, IGN Raman lidar, UHOH DIAL, DLR DIAL, and CNRS DIAL, with respect to the mean value, are found to be −0.38, −2.60, 4.90, −1.43, −2.23 and 1.72%, respectively. Copyright c

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.

The Development of Methodologies for Water Vapour Measurement (DEMEVAP) project aims at assessing and improving humidity sounding techniques and establishing a reference system based on the combination of Raman lidars, ground-based sensors and GPS. Such a system may be used for climate monitoring, radiosonde bias detection and correction, satellite measurement calibration/validation, and mm-level geodetic positioning with Global Navigation Satellite Systems. A field experiment was conducted in September–October 2011 at Observatoire de Haute Provence. Two Raman lidars, a stellar spectrometer (SOPHIE), a differential absorption spectrometer (SAOZ), a sun photometer (AERONET), 5 GPS receivers and 4 types of radiosondes (Vaisala RS92, MODEM M2K2-DC and M10, and Meteolabor Snow-White) participated in the campaign. A total of 26 balloons with multiple radiosondes were flown during 16 clear nights. This paper presents preliminary findings from the analysis of all these datasets. Several classical Raman lidar calibration methods are evaluated which use either Vaisala RS92 measurements, point capacitive humidity measurements, or GPS integrated water vapour (IWV) measurements. A novel method proposed by Bosser et al. (2010) is also tested. It consists in calibrating the lidar measurements during the GPS data processing. The methods achieve a repeatability of 4–5%. A drift in the IGN-LATMOS Raman lidar calibration of 15% over the 45 days of the experiment is evidenced but not yet explained. When this drift is removed, the precision of the calibration factors improves to 2–3%. However, the variations in the absolute calibration factor between methods and types of reference data remain at the level of 7%. The intercomparison of radiosonde measurements shows good agreement between RS92 and Snow-White measurements up to 12 km. An overall dry bias is found in the measurements from both MODEM radiosondes. Investigation of situations with low RH values (

International audience; Doppler Orbitography Radiopositioning Integrated by Satellite (DORIS) and Global Positioning System (GPS) techniques are similarly affected by propagation delays in the neutral atmosphere (troposphere) and hence make use of similar data processing strategies for reducing this effect. We compare Zenith Tropospheric Delays (ZTDs) estimated from 52 DORIS and GPS station pairs co-located at 35 sites over the 2005-2008 period. We find an overall systematic negative mean bias of -4 mm and a median bias of -2 mm, with a large site-to-site scatter and especially stronger biases over South America, potentially linked to remaining problems related to the South Atlantic Anomaly (SAA) in the current DORIS data processing. The standard deviation of ZTD differences is in the range 4-12 mm over the globe (8 mm on average), with larger values located in the southern hemisphere. The spatial variability of differences is consistent with previous work but remains largely unexplained. DORIS is shown to be much less sensitive to instrumental changes than GPS (only the switch from Alcatel to Starec antenna at Toulouse is detected as an offset of -4 mm in the ZTD time series). On the opposite, discontinuities and spurious annual signals are found in the GPS ZTD solutions. A discontinuity of +5 mm is found on 5 November 2006, linked to the switch from relative to absolute GPS antenna models used in the data processing. The use of modified GPS antennas (e.g. at GODE) or improved antenna models is shown to reduce the spurious annual signal (e.g. from 5 mm to 2 mm at METS). Overall, the agreement between both techniques is good, though DORIS shows a significantly larger random scatter. The high stability and good spatial and temporal coverage make DORIS a potential candidate technique for meteorology and climate studies as long as reasonable time averaging can be applied (e.g. differences are reduced from 8.6 to 2.4 mm with 5-day averages) and no real-time application is considered. This technique could be considered as a potential contributor to Global Geodetic Observing System (GGOS) for climatology.

International audience; This paper investigates the impact of rapid small-scale water vapor fluctuations on GPS height determination. Water vapor measurements from a Raman lidar are used for documenting the water vapor heterogeneities and correcting GPS signal propagation delays in clear sky conditions. We use data from four short observing sessions (6 h) during the VAPIC experiment (15 May–15 June 2004). The retrieval of wet delays from our Raman lidar is shown to agree well with radiosonde retrievals (bias and standard deviation (SD) were smaller than 1 and 2.8 mm, respectively) and microwave radiometers (from two different instruments, bias was 6.0/−6.6 mm and SD 1.3/3.8 mm). A standard GPS data analysis is shown to fail in accurately reproducing fast zenith wet delay (ZWD) variations. The ZWD estimates could be improved when mean post-fit phase residuals were removed. Several methodologies for integrating zenith lidar observations into the GPS data processing are also presented. The final method consists in using lidar wet delays for correcting a priori the GPS phase observations and estimating a scale factor for the lidar wet delays jointly with the GPS station position. The estimation of this scale factor allows correcting for a mis-calibration in the lidar data and provides in the same way an estimate of the Raman lidar instrument constant. The agreement of this constant with an independent determination using radiosonde data is at the level of 1–4%. The lidar wet delays were derived by ray-tracing from zenith pointing measurements: further improvement in GPS positioning is expected from slant path lidar measurements that would properly account for water vapor anisotropy.

International audience; Water vapor measurements from a Raman lidar developed conjointly by the IGN and the LATMOS/CNRS are used for documenting the water vapor heterogeneities and correcting GPS signal propagation delays in clear sky conditions. We use data from four 6 h-observing sessions during the VAPIC experiment (15 May-15 June 2004). The retrieval of zenith wet delays (ZWDs) from our Raman lidar is shown to agree well with radiosonde (0.6 ± 2.5 mm) and microwave radiometers (−6.6 ± 1.2 and 6.0 ± 3.8 mm) retrievals. ZWDs estimated from GPS data present a good consistency too (−2.0 ± 2.7 mm) but they are still shown to not represent properly the fast evolutions with high frequency variations correlation about 0.12. Part of the errors is also due to multipath and antenna phase center variations. Within this framework, methodologies for integrating of zenith lidar observations into the GPS processing are described. They include also a correction for multipath and antenna phase center variation. The best results are obtained when the lidar ZWDs are used for a priori correcting the GPS phase observations: discrepancies between lidar and GPS estimates are then reduced to −1.1 ± 1.4 mm. It is shown also that mapping function derived from the lidar vertical profiles performs nearly as well as the VMF1 mapping function.

International audience; The Convective and Orographically- induced Precipitation Study (COPS) is a coordinated international project, comprised of an observational field campaign and a research programme aiming to advance the quality of fore- casts of orographically-induced pre- cipitation by four-dimensional obser- vations and modelling of its life cycle. The COPS field campaign took place during June-July-August 2007 over eastern France and south-western Germany. Its main objective was to provide an unprecedented comprehen- sive set of in situ and remotely-sensed meteorological observations of the entire depth of the troposphere. After a short overview of the project, the paper focuses on the French contribution to the COPS field phase, describes the experimental setup and highlights some key observations.; L’étude des précipitations convectives induites par l’orographie (Cops selon l’acronyme anglais) est un projet inter- national coordonné qui comprend une campagne d’observations de terrain et un programme scientifique et qui vise à améliorer la qualité des prévisions des précipitations orographiques convectives à la fois par l’observation quadridimensionnelle et la modélisa- tion de leur cycle de vie. La campagne de terrain s’est déroulée en juin-juillet- août 2007 sur l’est de la France et le sud-ouest de l’Allemagne. Son objectif majeur était de fournir un jeu d’obser- vations météorologiques, in situ et à distance, aussi complet que possible et sur toute la profondeur de la colonne troposphérique.Après une brève revue d’ensemble du projet, l’article se concentre sur la contribution française à la campagne Cops, décrit le dispositif expérimental mis en œuvre et met en valeur quelques observations clés.

The statistical properties of atmospheric water vapor mixing ratio (WVMR) determined as the ratio of Raman lidar signals backscattered from water vapor and nitrogen molecules are studied. It is shown that WVMR estimates can be biased by a small percentage at low signal photon-counting rates due to fluctuations in the nitrogen signal in the denominator of the ratio, the magnitude of the bias being linked to the signal-to-noise ratio of the nitrogen signal. This is particularly important when unbiased estimates are required as in the case of climate studies and global positioning system (GPS) signal calibration. Different bias corrections and a modified ratio formulation are proposed in order to correct or eliminate this bias. The method is successfully applied in processing signals obtained with an experimental Raman lidar system devoted to calibrate GPS signals for slant path delays. It is shown to reduce biases into negligible values in both WVMR and wet path delay estimates in the range interval of 0-7 km.

The determination of global positioning system (GPS) heights with submillimeter accuracy needs proper correction of tropospheric delay. In this letter, the modeling of zenith hydrostatic delay (ZHD) was addressed, considering that wet delay must be treated separately. ZHD is traditionally estimated from Saastamoinen's formula using a mean-gravity model and surface pressure observations. The uncertainty in ZHD associated with the mean-gravity model is about 0.3 mm. An improved parametric model is derived here, which yields an uncertainty in the ZHD less than 0.1 mm when the surface altitude lies in the range of 0-9 km. A second parametric model is derived for higher altitudes (such as above radiosonde observations or atmospheric models). Both parametric models depend on latitude, height, and time variables. This dependence is due to the link between the mean gravity and temperature profiles between the surface and ~80-km altitude. The uncertainty in the parametric models due to short-term temporal variability of the temperature profiles is shown to produce an uncertainty in ZHD smaller than 0.1 mm

Les attentats de janvier 2015 a Paris ont confirme l’existence d’une menace terroriste sur la France, incitant le president de la Republique a prolonger la mission de protection du territoire national par les armees. Une inflexion qui, pour l’armee de terre, souleve de nombreux defis d’ordre notamment ethique, juridique, conceptuel et doctrinal. L’armee est redevenue indispensable pour proteger nos concitoyens et tout ce qui fait l’essence de la nation, un element fondamental de la cohesion nationale.

Les attentats de janvier 2015 a Paris ont confirme l’existence d’une menace terroriste sur la France, incitant le president de la Republique a prolonger la mission de protection du territoire national par les armees. Une inflexion qui, pour l’armee de terre, souleve de nombreux defis d’ordre notamment ethique, juridique, conceptuel et doctrinal. L’armee est redevenue indispensable pour proteger nos concitoyens et tout ce qui fait l’essence de la nation, un element fondamental de la cohesion nationale.

Ground-based Global Navigation Satellite System (GNSS) measurements from nearly 50 stations distributed over the Caribbean arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality integrated water vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the trade winds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD)-to-IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams International Airport (GAIA), Bridgetown, Barbados. A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2), where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a collocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth-generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS-derived IWV peaks. Two successive peaks are observed on 22 January and 23–24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organization for five representative GNSS stations across the Caribbean arc using visible satellite images. A statistically significant link was found between the cloud patterns and the local IWV observations from the GNSS sites as well as the larger-scale IWV patterns from the ECMWF ERA5 reanalysis. The reprocessed ZTD and IWV data sets from 49 GNSS stations used in this study are available from the French data and service centre for atmosphere (AERIS) (https://doi.org/10.25326/79; Bock, 2020b).

Autonomous Underwater Vehicles (AUVs) represent a very promising tool for high resolution bathymetric surveys. In this context, this article presents a state-of-the-art of precise underwater navigation. While classical acoustic underwater positioning systems (USBL, LBL) provide a sufficient level of precision, they suffer from deployment difficulties: beacons immersion, need for support vessel, etc... Therefore these methods are not further developed in this article and a conventional underwater navigation method consists in inertial navigation. However, position accuracy of inertial systems drifts over time, making it incompatible with bathymetric survey quality requirements for long missions. To limit this drift, external speed sensors (a Doppler Velocity Log -DVL- most of the time) are used: this is called Aided Inertial Navigation System (AINS). AINS performances depend on sensor performances, data fusion algorithms and mission pattern followed by the AUV. These considerations are presented in this paper and illustrated by two sea trials conducted in the bay of Brest (France). Finally, Terrain Based Navigation (TBN), Simultaneous Localization And Mapping (SLAM) and Synthetic Aperture Sonar (SAS) micronavigation are presented as emerging methods that could help to reduce or bound the position uncertainty drift.

International audience; The main objective of this work is to provide accurate error estimates for the different water vapour profiling sensors based on an intensive inter-comparison effort. The inter-comparison, performed in the framework of COPS--Convective and Orographically-induced Precipitation Study (01 June-31 August 2007), involves airborne and ground-based water vapour lidar systems, radiosondes with different humidity sensors, GPS and Microwave radiometers (MWR). Simultaneous and co-located data from different sensors are used to compute relative bias and root-mean square (RMS) deviations as a function of altitude

In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.

Nowadays, GPS positioning tends to become a scientific research tool used in meteorology for the determination of the atmospheric water cycle. The GPS wet tropospheric delay can be used as an input to initialize numerical weather models and thus make better weather forecasts. The objective of this work is to evaluate the quality of the ZTD series of a network of more than 1300 GNSS stations to be used in numerical weather prediction. This is to provide a clean and reliable set of ZTD data that can be used in numerical weather prediction. To do this, several analyzes wereperformed. First, an analysis of the intrinsic quality of the GPS treatment was carried out in order to eliminate residual errors after adjusting the parameters. Second, ZTD data from the NAWDEX network was compared with conventional meteorological data to validate their adequacy. An optimization of PPP treatment under Gipsy-Oasis II was also performed. Finally, a study of the distribution and the spatio-temporal variations was carried out using the visualization tools developed under Python.; De nos jours, le positionnement GPS a tendance à devenir un outil de recherche scientifique utilisé en météorologie pour la détermination du cycle de l’eau atmosphérique. La partie humide des délais troposphériques GPS peut servir d’intrant pour initialiser les modèles de prévision numérique du temps et ainsi faire de meilleures prévisions météorologiques. L’objectif visé par ce travail, est d’évaluer la qualité des séries ZTD d’un réseau de plus de 1300 stations GNSS à être utilisées dans la prévision numérique du temps. Il s‘agit de fournir un ensemble des données ZTD propre et fiable qui peut être utilisé en prévision numérique du temps. Pour ce faire, plusieurs analyses ont été réalisées. En premier lieu, une analyse de la qualité intrinsèque du traitement GPS a été réalisé dans le but d’éliminer les erreurs grossières résiduelles après ajustement des paramètres. En second lieu, les données ZTD du réseau NAWDEX ont été comparées aux données classiques météorologiques afin de valider leur adéquation. Une optimisation du traitement PPP sous Gipsy-Oasis II a été également réalisée. Enfin, une étude de la distribution et des variations spatio-temporelles a été réalisée à l’aide des outils de visualisation développés sous Python.

Over the last decade, drones have been largely used for civil applications. Airborne photogrammetry has found place in these applications as a modeling and a measuring tool. Vinci-Construction-Terrassement is a private company of public building and works sector that integrates drones and photogrammetry as a mapping solution and metrology investigation on its sites. This tool is very efficient for the calculation of stock volumes for instance, or for time tracking of specific areas with risk of landslides. The aim of the present work is to do direct georeferencing of images acquired by the camera leaning on an embedded GPS receiver. The UAS used needs to be low cost and therefore data processing is adapted to this constraint, Au cours de la dernière décennie, les drones ont été largement utilisés dans les domaines des applications civiles. La photogrammétrie aéroportée a trouvé place dans ces applications comme une solution efficace de modélisation 3D mais aussi comme un outil de mesure. Vinci-Construction-Terrassement est une entreprise privée spécialisée dans le secteur des Travaux Publics qui intègre les drones et la photogrammétrie comme une solution de cartographie et de métrologie de ses chantiers. Cet outil est très efficace, par exemple, pour le calcul des volumes de stocks ou pour le suivi temporel de zones spécifiques avec un risque de glissement de terrain. Le but de ce travail est d’arriver à un géo-référencement direct des images acquises par la caméra lors du vol en s’appuyant uniquement sur un récepteur GPS embarqué. Le système utilisé doit être de faible coût et par conséquent le traitement des données est adapté à cette contrainte

Over the last decade, drones have been largely used for civil applications. Airborne photogrammetry has found place in these applications as a modeling and a measuring tool. Vinci-Construction-Terrassement is a private company of public building and works sector that integrates drones and photogrammetry as a mapping solution and metrology investigation on its sites. This tool is very efficient for the calculation of stock volumes for instance, or for time tracking of specific areas with risk of landslides. The aim of the present work is to do direct georeferencing of images acquired by the camera leaning on an embedded GPS receiver. The UAS used needs to be low cost and therefore data processing is adapted to this constraint, Au cours de la dernière décennie, les drones ont été largement utilisés dans les domaines des applications civiles. La photogrammétrie aéroportée a trouvé place dans ces applications comme une solution efficace de modélisation 3D mais aussi comme un outil de mesure. Vinci-Construction-Terrassement est une entreprise privée spécialisée dans le secteur des Travaux Publics qui intègre les drones et la photogrammétrie comme une solution de cartographie et de métrologie de ses chantiers. Cet outil est très efficace, par exemple, pour le calcul des volumes de stocks ou pour le suivi temporel de zones spécifiques avec un risque de glissement de terrain. Le but de ce travail est d’arriver à un géo-référencement direct des images acquises par la caméra lors du vol en s’appuyant uniquement sur un récepteur GPS embarqué. Le système utilisé doit être de faible coût et par conséquent le traitement des données est adapté à cette contrainte