scholarly journals Studying tropospheric turbulence with GNSS

2021 ◽  
Author(s):  
Steffen Schön ◽  
Gaël Kermarrec
Keyword(s):  
Refractive Index ◽  
Power Spectrum ◽  
Carrier Phase ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atomic Clock ◽  
Three Dimensional ◽  
Satellite System ◽  
Free Atmosphere ◽  
Phase Measurements

<p>Long-term variations of the tropospheric refractive index delay the carrier phase measurements from Global Navigation Satellite System (GNSS). This information is now operationally integrated in Weather prediction models. Random fluctuations of the refractive index correlate the phase measurements and induces non-stationary noise processes. The correlation structure and spectral properties of observation residuals from GNSS relative positioning provide a unique opportunity to study specific properties of the turbulent atmosphere. In this contribution, we will give a short overview on turbulent processes and their impact on GNSS carrier phase measurements. We will discuss our data analysis concepts to separate the tropospheric fluctuations from other temporally varying error sources such as GNSS receiver clock errors or multipath. The analysis is based on the power spectrum of single or double differences of carrier phase measurements. This approach enables a determination of the cut-off frequencies of the atmospheric noise and the associated power law processes with their typical slopes. The obtained values are compared with theoretical expectations. We will show results for GPS from the Seewinkel network (Austria), as well as from a small network at Physikalisch-Technische Bundesanstalt (PTB, Germany) where all receivers are connected to a common highly stable atomic clock. We show that (i) a two slopes power spectrum can be reliably determined and (ii) that the outer scale length can be taken to a constant value, close to the physically expected one and in relation with the size of the eddies at tropospheric height. The study of their dependencies with the satellite geometry, the Day of the Year (DOY) or the time of the day provides a new insight on the two- and three-dimensional atmospheric turbulence in the free atmosphere.</p>

scholarly journals Removing day-boundary discontinuities on GNSS clock estimates: methodology and results

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Adrià Rovira-Garcia ◽  
José Miguel Juan ◽  
Jaume Sanz ◽  
Guillermo González-Casado ◽  
Javier Ventura-Traveset ◽  
...  
Keyword(s):  
Carrier Phase ◽  
Atomic Clock ◽  
Satellite System ◽  
Daily Basis ◽  
Integer Ambiguity ◽  
Atomic Clocks ◽  
International Gnss Service ◽  
Present Contribution ◽  
Statistical Characterization ◽  
Phase Measurements

AbstractGlobal navigation satellite system (GNSS) satellites are equipped with very stable atomic clocks that can be used for assessing the models and strategies involved in the estimation processes, where the clock estimates should present high stability. For instance, GNSS products (including satellite and receiver clocks) are computed on daily basis, i.e., with the data of each day being processed independently from other days. This choice produces the well-known day-boundary discontinuities (DBDs) on clock estimates that stem from the estimation process, rather than to the nature of the atomic clock itself. The aim of the present contribution is to propose a strategy to estimate the satellite and receiver clock offsets that is capable to reduce the DBDs observed in the products of different analysis centers (ACs) within the International GNSS Service (IGS), ultimately improving the accuracy of clock estimates. Our approach relies on the use of unambiguous, undifferenced and uncombined carrier phase measurements collected by a network of permanent receivers on ground. The strategy considers the carrier phase hardware delays and assumes their possible variations along time. Our daily data processing aims to maintaining the natural continuity over days of the carrier phase measurements after integer ambiguity resolution (IAR), even if IAR is performed on daily batches. We compare our clock estimations with those computed by different IGS ACs, evaluating the linear behavior of the satellite atomic clocks on the day change. The results show the removal of DBD on clock estimates computed with the continuous and unambiguous carrier phase measurements. This DBD improvement may benefit the statistical characterization of long-term phenomena correlated with the on-board clocks.

scholarly journals Improving DGNSS Performance through the Use of Network RTK Corrections

2021 ◽  
Vol 13 (9) ◽  
pp. 1621
Author(s):  
Duojie Weng ◽  
Shengyue Ji ◽  
Yangwei Lu ◽  
Wu Chen ◽  
Zhihua Li
Keyword(s):  
Carrier Phase ◽  
Local Area ◽  
Satellite System ◽  
High Accuracy ◽  
Single Frequency ◽  
Baseline Length ◽  
Low Latitude ◽  
Phase Measurements ◽  
Network Rtk ◽  
Global Navigation Satellite

The differential global navigation satellite system (DGNSS) is an enhancement system that is widely used to improve the accuracy of single-frequency receivers. However, distance-dependent errors are not considered in conventional DGNSS, and DGNSS accuracy decreases when baseline length increases. In network real-time kinematic (RTK) positioning, distance-dependent errors are accurately modelled to enable ambiguity resolution on the user side, and standard Radio Technical Commission for Maritime Services (RTCM) formats have also been developed to describe the spatial characteristics of distance-dependent errors. However, the network RTK service was mainly developed for carrier-phase measurements on professional user receivers. The purpose of this study was to modify the local-area DGNSS through the use of network RTK corrections. Distance-dependent errors can be reduced, and accuracy for a longer baseline length can be improved. The results in the low-latitude areas showed that the accuracy of the modified DGNSS could be improved by more than 50% for a 17.9 km baseline during solar active years. The method in this paper extends the use of available network RTK corrections with high accuracy to normal local-area DGNSS applications.

Development of a Fast Three-Dimensional Dynamic Radiative Transfer Solver for Numerical Weather Prediction Models


2021 ◽  
Author(s):  
Richard Maier ◽  
Bernhard Mayer ◽  
Claudia Emde ◽  
Aiko Voigt
Keyword(s):  
Radiative Transfer ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Transfer Model ◽  
Heating Rates ◽  
Time Step ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models

<div> <div> <div> <div> <p>The increasing resolution of numerical weather prediction models makes 3D radiative effects more and more important. These effects are usually neglected by the simple 1D independent column approximations used in most of the current models. On top of that, these 1D radiative transfer solvers are also called far less often than the model’s dynamical core.</p> <p>To address these issues, we present a new „dynamic“ approach of solving 3D radiative transfer. Building upon the existing TenStream solver (Jakub and Mayer, 2015), radiation in this 3D model is not solved completely in each radiation time step, but is rather only transported to adjacent grid boxes. For every grid box, outgoing fluxes are then calculated from the incoming fluxes from the neighboring grid cells of the previous time step. This allows to reduce the computational cost of 3D radiative transfer models to that of current 1D solvers.</p> <p>Here, we show first results obtained with this new solver with a special emphasis on heating rates. Furthermore, we demonstrate issues related to the dynamical treatment of radiation as well as possible solutions to these problems.</p> <p>In the future, the speed of this newly developed 3D dynamic TenStream solver will be further increased by reducing the number of spectral bands used in the radiative transfer calculations with the aim to get a 3D solver that can be called even more frequently than the 1D two-stream solvers used nowadays.</p> <p>Reference:<br><span>Jakub, F. and Mayer, B. (2015), A three-dimensional parallel radiative transfer model for atmospheric heating rates for use in cloud resolving models—The TenStream solver, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 163, 2015, Pages 63-71, ISSN 0022-4073, . </span></p> </div> </div> </div> </div>

scholarly journals A multiscale approach for precipitation verification applied to the FORALPS case studies

2008 ◽  
Vol 16 ◽  
pp. 3-9 ◽  
Author(s):  
A. Lanciani ◽  
S. Mariani ◽  
M. Casaioli ◽  
C. Accadia ◽  
N. Tartaglione
Keyword(s):  
Power Spectrum ◽  
Prediction Models ◽  
Weather Prediction ◽  
Power Spectra ◽  
Multiscale Methods ◽  
Precipitation Forecast ◽  
Diagnostic Tools ◽  
Small Scale ◽  
Multiscale Approach ◽  
Skill Scores

Abstract. Multiscale methods, such as the power spectrum, are suitable diagnostic tools for studying the second order statistics of a gridded field. For instance, in the case of Numerical Weather Prediction models, a drop in the power spectrum for a given scale indicates the inability of the model to reproduce the variance of the phenomenon below the correspondent spatial scale. Hence, these statistics provide an insight into the real resolution of a gridded field and must be accurately known for interpolation and downscaling purposes. In this work, belonging to the EU INTERREG IIIB Alpine Space FORALPS project, the power spectra of the precipitation fields for two intense rain events, which occurred over the north-eastern alpine region, have been studied in detail. A drop in the power spectrum at the shortest scales (about 30 km) has been found, as well as a strong matching between the precipitation spectrum and the spectrum of the orography. Furthermore, it has also been shown how the spectra help understand the behavior of the skill scores traditionally used in Quantitative Precipitation Forecast verification, as these are sensitive to the amount of small scale detail present in the fields.

scholarly journals Kriging Interpolation in Modelling Tropospheric Wet Delay

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1125
Author(s):  
Hongyang Ma ◽  
Qile Zhao ◽  
Sandra Verhagen ◽  
Dimitrios Psychas ◽  
Han Dun
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Satellite System ◽  
Kriging Interpolation ◽  
Seasonal Effect ◽  
Dense Network ◽  
Sparse Network ◽  
Average Value ◽  
Global Navigation Satellite ◽  
Mean Square Errors

This contribution implements the Kriging interpolation in predicting the tropospheric wet delays using global navigation satellite system networks. The predicted tropospheric delays can be used in strengthening the precise point positioning models and numerical weather prediction models. In order to evaluate the performances of the Kriging interpolation, a sparse network with 8 stations and a dense network with 19 stations from continuously operating reference stations (CORS) of the Netherlands are selected as the reference. In addition, other 15 CORS stations are selected as users, which are divided into three blocks: 5 stations located approximately in the center of the networks, 5 stations on the edge of the networks and 5 stations outside the networks. The zenith tropospheric wet delays are estimated at the network and user stations through the ionosphere-free positioning model; meanwhile, the predicted wet delays at the user stations are generated by the Kriging interpolation in the use of the tropospheric estimations at the network. The root mean square errors (RMSE) are calculated by comparing the predicted wet delays and estimated wet delays at the same user station. The results show that RMSEs of the stations inside the network are at a sub-centimeter level with an average value of 0.74 cm in the sparse network and 0.69 cm in the dense network. The stations on edge and outside the network can also achieve 1-cm level accuracy, which overcomes the limitation that accurate interpolations can only be attained inside the network. This contribution also presents an insignificant improvement of the prediction accuracy from the sparse network to the dense network over 1-year’s data processing and a seasonal effect on the tropospheric wet delay predictions.

Estimation of the scale lengths of turbulence from GPS single difference phase observations 

2021 ◽  
Author(s):  
Gaël Kermarrec ◽  
Steffen Schön
Keyword(s):  
Satellite System ◽  
Index Of Refraction ◽  
Empirical Modeling ◽  
Free Atmosphere ◽  
Phase Measurements ◽  
Power Spectral ◽  
Satellite Geometry ◽  
Global Navigation Satellite ◽  
Kolmogorov Theory ◽  
Single Differences

<p>Signals from the Global Navigation Satellite System (GNSS) travel through the whole atmosphere and encounter fluctuations of the index of refraction. The long-term variations of the tropospheric refractive index delay the signals, whereas its random variations correlate with the phase measurements. The power spectral density of microwave phase difference can be derived from physical considerations by combining results from the Kolmogorov theory and electromagnetic wave propagation. Four different dominant noise regimes are expected. Their cutoff frequencies can be estimated with the unbiased Whittle Maximum Likelihood estimator; They provide information about the scale lengths of turbulence which are directly linked with the size of the eddies or swirling motion present in the free atmosphere. Dependencies of these parameters with the satellite geometry or the time of the day pave the way for a better comprehension of how tropospheric turbulence acts as correlating GNSS phase observations. The result is less empirical modeling of GNSS phase correlations to improve the positioning results and avoid an overestimation of their precision. We use GPS single differences from 290 m distant antenna positions recorded during two days in 2013 in a common clock experiment at the Physikalisch Technische Bundesanstalt in Braunschweig Germany to explain our methodology, based on adequate filtering of the residuals to mitigate multipath effects.</p>

scholarly journals Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models

2012 ◽  
Vol 140 (8) ◽  
pp. 2706-2719 ◽  
Author(s):  
Gemma V. Bennitt ◽  
Adrian Jupp
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Total Delay ◽  
Numerical Weather ◽  
Zenith Total Delay ◽  
Nwp Model ◽  
The Impact ◽  
Numerical Weather Prediction Models

Abstract Zenith total delay (ZTD) observations derived from ground-based GPS receivers have been assimilated operationally into the Met Office North Atlantic and European (NAE) numerical weather prediction (NWP) model since 2007. Assimilation trials were performed using the Met Office NAE NWP model at both 12- and 24-km resolution to assess the impact of ZTDs on forecasts. ZTDs were found generally to increase relative humidity in the analysis, increasing the humidity bias compared to radiosonde observations, which persisted through the forecasts at some vertical levels. Improvements to cloud forecasts were also identified. Assimilation of ZTDs using both three-dimensional and four-dimensional variational data assimilation (3D-Var/4D-Var) was investigated, and it is found that assimilation at 4D-Var does not deliver any clear benefit over 3D-Var in the periods studied with the NAE model. This paper summarizes the methods used to assimilate ZTDs at the Met Office and presents the results of impact trials performed prior to operational assimilation. Future improvements to the assimilation methods are discussed.

scholarly journals Diurnal Valley Winds in a Deep Alpine Valley: Observations

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 54
Author(s):  
Fabienne Schmid ◽  
Juerg Schmidli ◽  
Maxime Hervo ◽  
Alexander Haefele
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Warm Season ◽  
Ground Level ◽  
Weather Conditions ◽  
Wind Profiler ◽  
Fair Weather ◽  
Wind Maximum ◽  
Alpine Valley

Diurnal valley winds frequently form over complex topography, particularly under fair weather conditions, and have a significant impact on the local weather and climate. Since diurnal valley winds result from complex and multi-scale interactions, their representation in numerical weather prediction models is challenging. Better understanding of these local winds based on observations is crucial to improve the accuracy of the forecasts. This study investigates the diurnal evolution of the three-dimensional mean wind structure in a deep Alpine valley, the Rhone valley at Sion, using data from a radar wind profiler and a surface weather station operated continuously from 1 September 2016 to 17 July 2017. In particular, the wind profiler data was analyzed for a subset of days on which fair weather conditions allowed for the full development of thermally driven winds. A pronounced diurnal cycle of the wind speed, as well as a reversal of the wind direction twice per day is documented for altitudes up to about 2 km above ground level (AGL) in the warm season and less than 1 km AGL in winter. The diurnal pattern undergoes significant changes during the course of the year. Particularly during the warm-weather months of May through to September, a low-level wind maximum occurs, where mean maximum up-valley velocities of 8–10 m s−1 are found between 15–16 UTC at altitudes around 200 m AGL. In addition, during nighttime, a down-valley jet with maximum wind speeds of 4–8 m s−1 around 1 km AGL is found. A case study of a three-day period in September 2016 illustrates the occurrence of an elevated layer of cross-valley flow around 1–1.5 km AGL.

scholarly journals Satellite Data Assimilation in Numerical Weather Prediction Models. Part II: Uses of Rain-Affected Radiances from Microwave Observations for Hurricane Vortex Analysis

2007 ◽  
Vol 64 (11) ◽  
pp. 3910-3925 ◽  
Author(s):  
Fuzhong Weng ◽  
Tong Zhu ◽  
Banghua Yan
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Forecast Model ◽  
Background Information ◽  
Radiative Transfer Model ◽  
Asymmetric Structure ◽  
Transfer Model ◽  
Surface Parameters

Abstract A hybrid variational scheme (HVAR) is developed to produce the vortex analysis associated with tropical storms. This scheme allows for direct assimilation of rain-affected radiances from satellite microwave instruments. In the HVAR, the atmospheric temperature and surface parameters in the storms are derived from a one-dimension variational data assimilation (1DVAR) scheme, which minimizes the cost function of both background information and satellite measurements. In the minimization process, a radiative transfer model including scattering and emission is used for radiance simulation (see Part I of this study). Through the use of 4DVAR, atmospheric temperatures from the Advanced Microwave Sounding Unit (AMSU) and surface parameters from the Advanced Microwave Scanning Radiometer (AMSR-E) are assimilated into global forecast model outputs to produce an improved analysis. This new scheme is generally applicable for variable stages of storms. In the 2005 hurricane season, the HVAR was applied for two hurricane cases, resulting in improved analyses of three-dimensional structures of temperature and wind fields as compared with operational model analysis fields. It is found that HVAR reproduces detailed structures for the hurricane warm core at the upper troposphere. Both lower-level wind speed and upper-level divergence are enhanced with reasonable asymmetric structure.

Analysis of chaotic behavior of three-dimensional dynamical systems by a B-spline differential quadrature algorithm

2021 ◽  
pp. 2250077
Author(s):  
Rajni Rohila ◽  
R. C. Mittal
Keyword(s):  
Dynamical Systems ◽  
Prediction Models ◽  
Numerical Solutions ◽  
Chaotic Behavior ◽  
Weather Prediction ◽  
Dynamical Behavior ◽  
Three Dimensional ◽  
Differential Quadrature ◽  
Lorenz Attractor ◽  
Novel Approach

A novel approach based on cubic [Formula: see text]-spline functions has been developed to find solutions of three-dimensional chaotic dynamical systems. Interesting dynamical behavior has been illustrated in figures. We observed that dynamical systems depend very sensitively on the initial condition and corresponding behavior has been captured in numerical simulations. The Butterfly effect is used in the development of weather prediction models and has been depicted graphically. This paper deals with the numerical solutions of Lorenz attractor, Chen, Genesio and a combination of Lorenz and Rossler attractors. The computed solutions are quite accurate, consistent and confirm that the cubic [Formula: see text]-spline differential quadrature is a very efficient method to portray complex dynamical behaviors of dynamical systems.

Sign in / Sign up

Export Citation Format

Share Document