Inter-technique validation of tropospheric slant total delays

An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was -0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm +/- 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm +/- 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at intertechnique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.Web of Science1062208218

Residuals of Tropospheric Delays from GNSS Data and Ray-Tracing as a Potential Indicator of Rain and Clouds

The Global Navigation Satellite System (GNSS) is commonly recognized by its all-weather capability. However, observations depend on atmospheric conditions which requires the induced tropospheric delay to be estimated as an unknown parameter. In the following study, we investigate the impact of intense weather events on GNSS estimates. GNSS slant total delays (STD) in Precise Point Positioning technique (PPP) strategy were calculated for stations in southwest Poland in a 56 days period covering several heavy precipitation cases. The corresponding delays retrieved from Weather Research and Forecasting (WRF) model by a ray-tracing technique considered only gaseous parts of the atmosphere. The discrepancies are correlated with rain rates and cloud type products from remote sensing platforms. Positive correlation is found as well as GNSS estimates tend to be systematically larger than modeled delays. Mean differences mapped to the zenith direction are showed to vary between 10 mm and 30 mm. The magnitude of discrepancies follows the intensity of phenomena, especially for severe weather events. Results suggest that effects induced by commonly neglected liquid and solid water terms in the troposphere modeling should be considered in precise GNSS applications for the atmosphere monitoring. The state-of-art functional model applied in GNSS processing strategies shows certain deficits. Estimated tropospheric delays with gradients and post-fit residuals could be replaced by a loosely constrained solution without loss of quality

Cloud Detection from Radio Occultation Measurements in Tropical Cyclones

Tropical cyclones (TC) are one of the main producers of clouds in the tropics and subtropics. Hence, most of the clouds in TCs are dense, with large water and ice content, and provide conditions conducive to investigate clouds’ impact on Radio Occultation (RO) measurements. Although the RO technique is considered insensitive to clouds, recent studies show a refractivity positive bias in cloudy conditions. In this study, we analyzed the RO bending angle sensitivity to cloud content during tropical cyclone seasons between 2007 and 2010. Thermodynamic parameters were obtained from the ERA-Interim reanalysis, whereas the water and ice cloud contents were retrieved from the CloudSat profiles. Our experiments confirm the positive mean RO refractivity bias in cloudy conditions that reach up to more than 0.5% at the geometric height of around 7 km. A similar bias but larger and shifted up is visible in bending angle anomaly (1.6%). Our results reveal that the influence of clouds is significant and can exceed the RO bending angle standard deviation for 21 out of 50 (42%) investigated profiles. Mean clouds’ impact is detectable between 9.0 and 10.5 km, while, in the case of single events, clouds in most of the observations are significant between 8 and 14 km. Almost 15% of the detectable clouds reach 16 km height, while the influence of the clouds below 5 km is insignificant. For more than half of the significant cases, the detection range is less than 3 km but for one observation this range spreads to 7⁻8 km

GNSS radio occultation profiles in the neutral atmosphere from inversion of excess phase data

Long-term stability, global coverage and high resolution are characteristics that make the Global Navigation Satellite System (GNSS) radio occultation (RO) technique well-suitable to serve as anchor measurements for observing the Earth’s atmosphere. The concept of occultation soundings utilizes a receiver placed on a low Earth orbit to measure the accumulated atmospheric contribution along the limb in terms of a phase delay. A high sampling rate allows to reconstruct profiles of geophysical parameters through an inversion process of occultation signals. However, such measurements require a careful processing in order to provide accurate retrievals in the neutral atmosphere. The following development describes specific aspects in radio occultation methodology implemented in the retrieval chain from phase data to profiles of dry pressure and dry temperature. Independent retrievals from nearreal time measurements are compared with occultation products provided by official processing centers to demonstrate reliability of the solution. The region within the upper troposphere and lower stratosphere (UTLS) is particularly represented by a low uncertainty being within 0.5% (K). A comparison with radiosondes shows a significant contribution of a water vapor term in the lower troposphere that comes from the dry air assumption in occultation profiles of pressure and temperature. Radiosonde measurements reproduced to refractivity profiles show very high agreement with occultation soundings, which is generally below 5%. A superior accuracy of RO refractivity is observed in the upper troposphere, where retrievals are consistent with radiosondes to 1%

RMIT University's Practical Space Weather Prediction Laboratory

Space weather is a key component in the daily operation of many technological systems and applications; including large-scale power grids, high-frequency radio systems and satellite systems. As the international space sector continues to boom, accessible space weather products, tools and education are increasingly important to ensure that space actors (both old and new) are equipped with the knowledge of how space weather influences their activities and applications.    At RMIT University, the initiative was taken to develop a Space Weather Prediction Laboratory exercise for students as part of its new offering of a Bachelor Degree in Space Science in 2020. This new Space Weather Prediction Lab exercise is offered as part of an undergraduate course on `Space Exploration', which has a diverse student in-take, including students with no background in physics; a key detail in the design of the Lab. The aims of the Space Weather Prediction Lab were to: (1) Provide a short and intense introduction to the near-Earth space environment and its impact on various human technologies; (2) Give students `hands-on' training in data analysis, interpretation and communication; and (3) Create an immersive space science experience for students that encourages learning, scientific transparency and teamwork. The format of the lab that was developed can be easily scaled in difficulty to suit the students' technical level, either by including more/less space weather datasets in the analysis or by analyzing more/less complicated space weather events. The details of the Space Weather Prediction Lab developed and taught at RMIT in 2020, in both face-to-face and online formats, are presented