Observations performed with ground-based space geodetic and remote sensing techniques are sensitive to the amount of water vapour in the neutral atmosphere. Corresponding parameters that describe the signal delay in the troposphere can be derived for example from the analysis of data collected from geodetic Very Long Baseline Interferometry (VLBI), Global Navigation Satellite System (GNSS), as well as microwave radiometers. The latter instruments are often referred to as water vapour radiometers (WVR).

The Onsala Space Observatory (OSO) operates a number of such instruments for VLBI, GNSS and WVR measurements, all co-located within about 600 m. Among these are the Onsala twin telescopes (OTT), two modern 13.2~m diameter radio telescopes performing observations in the VLBI Global Observing System (VGOS) of the International VLBI Service for Geodesy and Astrometry (IVS). The OTT are the first operational VGOS twin telescopes worldwide and are contributing with observations to the IVS since 2019. OSO also operates eight permanently installed GNSS stations, of which two are official stations in the International GNSS Service (IGS) network. Furthermore, OSO operates ground-based microwave radiometers, which are used for atmospheric research and perform continuous observations of the water vapour content in the neutral atmosphere. Data analysis of all three techniques, VLBI, GNSS and WVR, allows to derive information on the temporal and spatial variations of water vapour in the neutral atmosphere. Using co-located instrumentation within a few hundred metres distance thus offers a perfect opportunity for comparisons and assessments of the results.

We focus on data recorded at OSO during 2022 and compare the parameters describing the signal delay in the neutral atmosphere, i.e. the so-called equivalent zenith total delays and the linear horizontal delay gradients. The temporal resolution of the derived parameters is 15 min or less. Out of more than 40 VGOS experiments in 2022, each of a duration of 24 h, we have WVR data covering at least half of the session in all except one.  We have examples where the equivalent zenith wet delay only varies by 2--3 cm over an experiment during rather stable atmospheres.  When the atmosphere is more variable the zenith wet delay can vary by more than 10 cm over 24 h.

How to cite: Haas, R. and Elgered, G.: Tropospheric Parameters Derived From Co-located Instrumentation at the Onsala Space Observatory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17013, https://doi.org/10.5194/egusphere-egu24-17013, 2024.

Modelling of the microwave signal delay in the neutral atmosphere (i.e., the tropospheric delay) is a crucial part of GNSS observations processing. The design of observation-modelling algorithms is based on signal ray tracing. Considering advancements in modern Numerical Weather Prediction (NWP) models and high standards of GNSS product quality, it is necessary to revise the existing ray-tracing algorithms. We developed an improved least-travel time (LTT) ray-tracer with robust physics assumptions, based on the original LTT algorithm. Both new and original LTT implementations, along with the state-of-the-art VieVS Ray-tracer (RADIATE), are supplied with numerical weather data by the Open Integrated Forecasting System model (OpenIFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). These three ray tracers are justly compared in the setup of modelling the skyview delays for 256 GNSS stations during one month (December 2016). The skill of these delay products is assessed as the quality of GNSS precise orbit determination (POD) products of the GPS constellation made by the orbit solver GROOPS (Gravity Recovery Object Oriented Programming System) software toolkit of the Graz University of Technology. The GNSS POD metrics which have been analysed are orbit midnight discontinuities (MD) and precise point positioning (PPP) error. In the context of these metrics, the usage of the new LTT algorithm leads to better orbit products, compared to the original LTT and the RADIATE ray tracers.

How to cite: Vasiuta, M., Navarro Trastoy, A., Tuppi, L., Motlaghzadeh, S., and Järvinen, H.: Improved Least Travel Time ray-tracing operator for GNSS tropospheric delays, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14710, https://doi.org/10.5194/egusphere-egu24-14710, 2024.

We have initiated a new research project to analyze the behaviors of precipitable water vapor with high spatial and temporal resolutions using a dense global navigation satellite system (GNSS) network and next-generation microwave radiometers. Recently, line-shaped rainbands with extreme and hazardous characteristics have been occurring frequently in Japan, leading to disasters such as severe flooding and landslides. However, there is insufficient knowledge regarding the generation mechanism of cumulonimbus clouds within these rainbands. Our project has four research subobjectives: (1) to develop a novel microwave radiometer for use in millimeter-wave spectroscopy, enabling high-resolution and high-precision monitoring of water vapor behavior, and conduct field measurements using this radiometer for proof of concept; (2) to conduct high-resolution water vapor measurements using a dense network of low-cost GNSS receivers; (3) to conduct GNSS water vapor tomography for estimating precise temporal and spatial variations; and (4) to numerically predict weather precisely using dense-measurement water vapor datasets and fine GNSS tomography results. Our project is aimed at not only the advancement of mesoscale meteorology but also application to space geodetic techniques such as very long baseline interferometry (VLBI) and GNSS. Regarding the first subobjective, significant progress has been achieved in the development of a next-generation microwave radiometer utilizing millimeter-wave spectroscopy since 2018. To date, we have successfully engineered a new front-end module equipped with an orthomode transducer (OMT) and a wideband feed. The prototype of the complete receiver system has a wide bandwidth feed spanning from 16 to 58 GHz, facilitating the measurement of two frequency bands: 16-28 GHz (H₂O) and 50-58 GHz (O₂). We plan to integrate this system into a 40-meter-class dish telescope to assess its performance in detecting water vapor variability this summer. For the observation of GNSS precipitable water vapor, we first installed a low-cost GNSS receiver and a commercial-based microwave radiometer at Kagoshima University in early November 2023 as a preliminary observation to understand the variability of water vapor in the southern Kyushu area. In addition to the precipitable water vapor information obtained from this observation, we plan to investigate the variability of water vapor in this area based on the information obtained from the GNSS Earth observation network (GEONET) system of the Geospatial Information Authority of Japan (GSI) and a commercial-based GNSS observation network. Our presentation will include preliminary results and an outlook on future developments. This work received support through JSPS KAKENHI Grant Numbers JP21H04524 and 23H00221.

How to cite: Ichikawa, R., Ohta, Y., Araki, K., Tajiri, T., Fujita, M., Ujihara, H., Yamada, T., Jike, T., Imai, H., Minowa, M., and Takashima, Y.: Novel Real-time Observation of High-resolution Water Vapor Behavior for Detection of Precursors of Cumulonimbus Clouds and Investigation of Their Evolution: - Preliminary Results -, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6211, https://doi.org/10.5194/egusphere-egu24-6211, 2024.

The variometric approach has been demonstrated effective in GNSS seismology and GNSS ionospheric seismology to estimate ground shaking (VADASE) and earthquake/tsunami induced ionospheric disturbances (VARION) in real time for years. In this study the same variometric approach has been utilized to appraise the potential for real-time tracking of tropospheric delay (VARTROPO): this investigation holds significance for timely enhancements in weather forecasting, by incorporating this data into numerical weather models.
In contrast to the prevailing method of tracking tropospheric delay, which relies on employing a mapping function and estimating a singular zenith tropospheric delay (ZTD) for all satellites within a specific time interval, the proposed approach is based on the estimation of single-epoch variation of the slant tropospheric delay (VSTD) for individual satellite. The low-pass filtering process and the integration of this variation over time, starting from a known initial value of the STD, allows to estimate the STD in near (due to low-pass filtering) real time for each satellite. It is noteworthy that the proposed approach allows to highlight the azimuthal anisotropy of the troposphere, valuable during periods of intense weather fronts.
The preliminary research focuses on evaluating how the estimates derived from the proposed approach, in near real-time scenario, match with both the official ZTD estimates provided by CDDIS and those obtained through Precise Point Positioning (PPP) technique. In this respect, it has to be underlined that the assessment hereafter illustrated has been developed: (i) using 1-second rate GNSS data; (ii) in both terms of ZTDs and STDs, using a standard 1/sin(elevation) mapping function for conversion; (iii) with fixed position of the GNSS permanent station (only the receiver clock variation has been estimated in the variometric approach); (iv) without multipath mapping and removal. The first presented comparison is between VARTROPO and PPP (MATE station; satellite G03; 1st October 2023) (Figure 1).

Fig. 1

VARTROPO derived VSTD and VZTD exhibits higher noise level; therefore, to mitigate the highfrequency noise, a simple low-pass filter (moving median) with different moving windows (from 5 seconds to 2 minutes) has been applied. Then, the different low-pass filtered VZTDs have been integrated over time, starting from the ZTD at the initial epoch as derived from PPP, and compared to the ZTDs estimated by PPP (Figure 2).

 Fig2

The differences between the reconstructed VARTROPO ZTDs trends and the PPP ZTDs have been represented (Figure 3).

  Fig.3

The second comparison is between VARTROPO and CDDIS, to substantiate the aforementioned findings (Figures 4, 5).

     Fig4

 Fig5

In conclusion, it has been understood that simple moving medians are able to effectively low-pass filter the VARTROPO ZTDs: with 2-minute moving window the agreement with PPP ZTDs and CDDIS ZTDs are at within 1-2 millimeters, what preliminarily demonstrate that near real-time track of the tropospheric delay is feasible. Next research steps will involve: (i) enhancing the VSTDs estimates (e.g. with multipath mitigation); (ii) investigating the possibility to estimate troposphere azimuthal anisotropy in presence of weather fronts.

How to cite: De Pace, A. M., Fratini, R., Mazzoni, A., and Crespi, M.: Near real-time GNSS meteorology: a preliminary feasibility demonstration based on the variometric approach , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19978, https://doi.org/10.5194/egusphere-egu24-19978, 2024.

MAP-IO (Marion Dufresne Atmospheric Program Indian Ocean) is a research project that aims to collect long-term atmospheric, biological and marine observations to document the under-instrumented areas of the Indian and Southern Oceans. To achieve this, the French Research Vessel (R/V) Marion-Dufresne, based in Réunion Island in the Indian Ocean, has been equipped with around twenty autonomous instruments to take measurements along its route.

Among the instruments deployed on this R/V, a GNSS antenna has been in operation since autumn 2020, providing unique and continuous measurements of atmospheric water vapour in this part of the world. The data were initially transmitted daily to shore for ultra-rapid (day +1) and rapid (day +3) routine analysis. The quality of the retrieved tropospheric delays and integrated water vapour contents was highlighted in a previous study. With more reliable transmission facilities, raw GNSS data are now transmitted hourly and can be analysed with a latency of less than 30 minutes.

In this study, we provide an initial assessment of the near real-time (h+20min) processing performed as part of this project. This evaluation is based on GNSS raw data collected in August 2023 during a rotation of the R/V Marion-Dufresne in the French Austral Islands (Crozet, Kerguelen, Saint-Paul and Amsterdam Islands). Processing is performed every hour over a 24-hour window, using the raw hourly data transmitted by the R/V and the cumulative real-time ephemerides and clocks provided by JPL / GDGPS. Only the last hour of each analysis is then considered. Over this period, the estimated tropospheric delays are in good agreement with the rapid routine solution, with differences of less than 1 cm RMS. The comparison with the analysis and the 6h forecast of the Météo-France's global numerical weather prediction model Arpège highlight the benefits of these shipborne GNSS measurements for numerical weather prediction.

The medium-term objective of this work is to establish an operational procedure for the assimilation of these near real-time GNSS tropopheric solutions into numerical weather prediction models.

How to cite: Bosser, P. and Tulet, P.: Near real-time water vapour monitoring with shipborne GNSS for numerical weather prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8726, https://doi.org/10.5194/egusphere-egu24-8726, 2024.

Recently, the University of Luxembourg (UL), in collaboration with the United Kingdom Met Office, has started providing accurate near real-time (NRT) Zenith Total Delays (ZTDs) from networks of GNSS ground stations. This initiative is in alignment with the operational meteorological products from various analysis centers available at the EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) and the team in Luxembourg envisages to re-start its contributions in the near future. Active in Europe, E-GVAP coordinates NRT GNSS-based atmospheric content monitoring to support Numerical Weather Prediction (NWP) modelling with products that are crucial for mesoscale models throughout Europe, for example, for the Met Office. GNSS technology is essential for accurately measuring atmospheric parameters such as ZTD and Integrated Water Vapor (IWV) at high frequencies, regardless of weather conditions. In addition, GNSS data are low-cost when compared to conventional meteorological systems. Ensuring the NRT availability of these data for NWP assimilation systems requires numerous methods in GNSS data handling and processing, quality assurance, and distribution.  The study details the collaborative work between the UK Met Office and the University of Luxembourg in providing accurate and rapidly available meteorological data through GNSS technology. This collaboration has led to the development and update of various systems for the processing of GNSS observations to produce advanced NRT ZTD products at UL and the Met Office. These products are generated at 1-hour intervals on both global and regional scales, and at sub-hourly intervals regionally. This study primarily aims to provide a thorough review and accuracy assessment of NRT ZTD products from the UL, comparing their precision with benchmark data from both post-processed and NRT ZTD estimates from various EGVAP analysis centres. The NRT GNSS processing systems at UL use the Bernese GNSS Software (BSW) versions 5.2 and 5.4 with a double-differencing (DD) approach, and similarly, the post-processed benchmark ZTD estimates employs the DD positioning strategy using the same software packages.

How to cite: Hunegnaw, A., Teferle, N., and Jones, J.: New Developments in Near Real-Time GNSS Zenith Total Delay Estimates at the University of Luxembourg, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21040, https://doi.org/10.5194/egusphere-egu24-21040, 2024.

We present findings from an ongoing investigation into the evaluation of long-term trends in ground-based GNSS-derived Zenith Total Delay (ZTD) for potential integration into climate models, either for assimilation or validation purposes. Our analysis focuses on ZTD time series obtained from six REPRO3 IGS Analysis Centers (ACs) – COD, ESA, GFZ, GRG, JPL, and TUG – spanning 20 years or more. Thirty stations from the IGS global network were selected for this study. The ZTD time series underwent a homogenization process, utilizing ERA-5 derived ZTDs as a reference, followed by daily value averaging to minimize potential discrepancies arising from diverse estimation strategies employed by individual ACs. Similar averaging procedures were applied to ERA-5 ZTDs and the IGS tropo-product if already reprocessed in REPRO3. Two combinations, employing weighted mean and a robust least median of squares, were generated from the six homogenized ACs, serving as quality control measures for each AC. Analysis of trends in each of the nine ZTD time series was conducted in both time and frequency domains, revealing geographical variations in results. For instance, at station ALBH in Canada, the inter-AC scatter was 0.47 mm/decade for trends, 0.11 mm for annual amplitudes, and 0.29 degrees for annual phases.

How to cite: C. Santos, M., Balidakis, K., Kloss, A., Pacione, R., and Rees, J.: Climate trends derived from long-term ground-based GNSS-derived Zenith Total Delay (ZTD), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22538, https://doi.org/10.5194/egusphere-egu24-22538, 2024.

Homogenized atmospheric water vapour data is an important prerequisite for climate analysis. Compared with other techniques, GPS has inherent homogeneity advantage, but it still requires reprocessing and homogenization to eliminate impacts of applied strategy and observation environmental changes where a selection of proper processing strategies is critical. Here, we reprocess GPS observations at 44 IGS stations during 1995 to 2014. We focus on the influence of the mapping function, the elevation cut-off angle and homogenization on long-term reprocessing results, in particular for Zenith Tropospheric Delays (ZTD) products. Moreover, for the first time, we include the mapping function (VMF3) and exploit homogenized radiosonde data as a reference for ZTD trend evaluations. Our analysis shows that both site position and ZTD solutions achieved the best accuracy when using VMF3 and 3° elevation cut-off angle. Regarding the long-term ZTD trends, we find that homogenization can reduce the trend inconsistency among different elevation cut-off angles. ZTD trend results show that the impact of mapping functions is very small. On the other hand, the discrepancy can reach 0.60 mm/year by using different elevation cut-off angles. We suggest the low elevation cut-off angles (3° or 7°) for the best estimates of ZTD reprocessing time series when compared to homogenized radiosonde data or ERA5 reference time series.

How to cite: Bai, J., Lou, Y., Zhang, W., Zhou, Y., Zhang, Z., Shi, C., and Liu, J.: Impact analysis of processing strategies for long-term GPS zenith tropospheric delay (ZTD), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15082, https://doi.org/10.5194/egusphere-egu24-15082, 2024.

The Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign was conducted between June and September 2023 in the southeastern Black Forest, the Neckar Valley and the Swabian Alb in southwestern Germany. It focused on hydro-meteorological extreme events, including the initiation and intensification of convective events which are accompanied by heavy rain and can lead to local flooding. As a part of the observing system the GFZ installed eight additional GNSS stations in the region of interest and operated them in near real time during the measurement campaign. The precise point positioning technique was utilized to provide Integrated Water Vapor (IWV) estimates with a temporal resolution of 15 min. In this contribution we provide a first comparison of these IWV estimates with those derived from atmospheric (re-) analysis datasets. We utilize the atmospheric reanalysis ERA5 (horizontal resolution 31 km) and the operational analysis ICON-D2 (horizontal resolution 2 km) provided by the German Weather Service. Ground-based GNSS data are not assimilated into ERA5 and ICON-D2. In general, we find good agreement between GNSS and (re-)analysis estimates: the root mean square error is 1-2 kg/m². Our goal is to better understand the remaining station specific systematic and random deviations. For example, for all stations, the random deviations are smaller for the high compared to the low resolution model data. We attribute this to smaller representative errors and smaller forward model (interpolation) errors. However, for the systematic deviations the result is not too obvious. Comparisons with measurements from instruments which are collocated with the GNSS stations are envisaged to better understand the issue.  

How to cite: Zus, F., Oertel, A., Muraleedharan Thundathil, R., Dick, G., Knippertz, P., and Wickert, J.: Validation of GNSS-based Integrated Water Vapor for the Swabian MOSES 2023 field campaign, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8792, https://doi.org/10.5194/egusphere-egu24-8792, 2024.

The INGV operates a network of about 60 permanent GNSS stations to monitor the Neapolitan volcanic area (southern Italy), which includes three active volcanoes: Somma Vesuvio, Campi Flegrei and the island of Ischia. In this study we consider only the GPS constellation, whose signals are transmitted in the microwave band. Therefore, they suffer a delay while propagating in the troposphere. Bearing in mind that the refractive index in the atmosphere is a function of the water vapour content, pressure and temperature, tropospheric delay can be assimilated into short-term weather forecast models and used in long-term climate studies. We analyse a data set ranged about 14 years (2006-2019) of continuous GPS data, to evaluate the tropospheric delay to be used as a probe tool to quantify precipitable water and track its spatial-temporal evolution. We limit the analysis to the area of Somma Vesuvio, a strato-vulcano that covers an area of 165 km² and is about 1200 meters high, to study also the effect of the steep topography on the spatial distribution of the precipitable water content. The data are analysed in terms of empirical functions (IMF), organised in ascending order with a parameter ranging from 0 to 15, plus the trend. The trend found is not a linear growth, but grows to a maximum that is in the middle of the time range of about 11 years and then decreases. It is very interesting that the correlation with the solar cycle is high. Therefore, the next developments will be to analyze other data sets to verify the generality of this result.

How to cite: Tammaro, U., Carbone, V., Capparelli, V., Lepreti, F., and Martino, C.: The tropospheric delay of the GPS signal and its correlation with the solar cycle, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13449, https://doi.org/10.5194/egusphere-egu24-13449, 2024.

Coastal water monitoring is of increasing importance for applications such as sea level monitoring and urban planning. Currently, traditional tide gauge by radar measurement remains the most widely used method, but it involves placing a sensor close to the water surface, which can lead to its destruction, particularly in hostile maritime environments.

Sea level measurement by GNSS-R offers a promising alternative to traditional tide gauge methods by enabling continuous and global sea level measurements (e.g., Larson et al., 2013). It has the significant advantage of limiting the constraints linked to the installation of sensors physically close to the water surface, as a GNSS antenna can be placed away from the coast or on a high structure. Furthermore, this technique takes advantage of the high availability of existing GNSS installations around the globe, which would make it possible to considerably extend the scope of tide gauge measurements on a global scale.

Most of the methods used in GNSS-R are based on the analysis of the signal/noise ratio (SNR). They generally use a spectral analysis based on a Lomb-Scargle periodogram and are effective for monitoring mean sea level at the centimeter level (e.g., Larson et al., 2013; Santamaría-Gómez and Watson, 2017; Peng et al., 2021). However, they require a relatively long portion of the SNR series to obtain a precise estimate of the oscillation frequency of the SNR signal. This has the effect of limiting the sampling rate of the measurement series and limits spectral methods to the observation of slow variations in sea level such as the tide. Other approaches use Kalman filtering and show that it is possible to achieve an accuracy of less than 5cm in near real time (e.g., Strandberg, Hobiger and Haas, 2019; Liu et al., 2023). Furthermore, these methods show that it is possible to considerably increase the data sampling rate and thus monitor rapid variations in sea level. This extends the scope of GNSS-R techniques to all applications requiring real-time sea level measurement.

We present a novel approach for measuring sea level by analyzing SNR signals with Kalman filtering. This approach relies on the estimation of the oscillation frequency and amplitude of SNR signals using an extended Kalman filter. It has the advantage of providing sea level height estimates at a sampling rate as high as the SNR measurements. The major constraint linked to the method lies essentially in the estimation of the initial phase of the SNR signals, which particularly affects the fit of the SNR signals from setting satellites.

GNSS-R measurements were carried out with a sampling frequency of 1 second and compared to those of a tide gauge colocated on the Aix Island ILDX site (France). By combining data from different existing GNSS systems (GPS, GLONASS, Galileo, BDS) and considering all available carriers, we estimate that it is possible to obtain an RMS error of less than 5cm on sites with high tidal ranges (± 6m).

How to cite: Pira, A., Santamaría-Gómez, A., and Woppelmann, G.: Extended Kalman filtering applied to high-rate GNSS-R sea level measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14947, https://doi.org/10.5194/egusphere-egu24-14947, 2024.

One of the dominant error sources for Global Navigation Satellite System (GNSS) measurements is the correction for delay of an electromagnetic wave as it traverses the neutral atmosphere, which is usually shorted as tropospheric delay. Generally, tropospheric delay must be calculated or estimated since refractivity along ray path is not easily or economically measured. Empirically, the line of sight delay for either hydrostatic or wet component is modeled as product of zenith delay and a mapping function. The accuracy of estimated geodetic parameters for GNSS could be limited due to the indeterminacy of mapping function, when observations are typically made to low elevation angles. Nowadays, there are many different empirical tropospheric delay mapping functions are generated and used in GNSS applications, the sensitivity of mapping functions to height above the geoid of point of observations are mostly corrected with method and formulas proposed in Niell (1996), in which the height corrections are only concerned in hydrostatic delay mapping function. In Niell (1996), the adopted form of height correction for hydrostatic delay mapping function is linearly dependent on height, and the linear coefficient is empirically chosen for fitting precision purpose. In this work, similar to many current works about modelling mapping factors to operational mapping functions, with the help of ERA-Interim reanalysis data set from the European Centre for Medium-range Weather Forecasts (ECMWF), the sensitivity of both hydrostatic and wet delay mapping factors to height are calculated and preliminary analyzed. As an important part of the work, the needed data set sources, i.e., the tropospheric delays at some ground-based stations along some previously set ray paths with different elevation angles, azimuth angles, heights and time epochs, are generated with a self-generated tropospheric delay ray-tracing package named GTRATS (Gnss Tropospheric delay RAy Tracing Software). The first results show that for a specific not low elevation angle, the variations of both hydrostatic and wet mapping factors to the height are not too obvious; the hydrostatic mapping factors change linearly to height with different performances, while wet mapping factors are not with linearly change, especially for low elevation angles; height corrections with method in Niell (1996) for hydrostatic mapping factors actually perform well in some cases, while maybe correct too much or too less in some stations at some time epochs, thus maybe new correction strategy can be accounted; the height correction should also be concerned for wet delay mapping functions, while there is no obvious, regular and reliable relation or appearance can be observed according to our first results, and more efforts should be made for the examination and investigation of this problem.

How to cite: Wang, M., Li, P., Lu, R., Wang, S., and Zhang, F.: First results about height correction of tropospheric delay mapping function in GNSS applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2522, https://doi.org/10.5194/egusphere-egu24-2522, 2024.

The rapidly changing climate is escalating the frequency and intensity of extreme weather events in the Azores, Portugal. It is crucial to comprehend the dynamics of these events to mitigate them. Atmospheric water vapor data from the Global Navigation Satellite System (GNSS) and reanalysis products from an atmospheric general circulation model can be utilized to investigate the dynamics of weather fronts in the Azores Islands. A primary goal of our study is to conduct a comprehensive comparison between GNSS and MERRA2-based atmospheric reanalysis data and derive small-scale atmospheric structures with high-temporal resolution. Using statistical analysis, we will unveil the similarities and discrepancies between the two approaches in capturing atmospheric water vapor patterns. Emphasizing an exploratory methodology, we will showcase our findings using a restricted dataset that centers on specific instances of extreme precipitation witnessed in the Azores Islands.

How to cite: Mondal, D. R., Elosegui, P., Brock, L., Paine, S., Mateus, P., and Mendes, V.: Probing the Dynamics of Extreme Weather Events in the Azores, Portugal, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5929, https://doi.org/10.5194/egusphere-egu24-5929, 2024.