ORCID Profile
0000-0001-7439-7862
Current Organisations
Hohai University
,
Physikalisch-Meteorologisches Observatorium Davos World Radiation Center
,
University of Beira Interior
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 31-10-2015
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-17162
Abstract: The Fengyun 3E (FY3E) spacecraft was launched on the 4th of July 2021 at 23h 28min UTC according to CASC (China Aerospace Science and Technology Corp.) on a Long March 4C vehicle from JSLC (Jiuquan Space Launch Center) in China. The orbit is a sun-synchronous near-circular with an altitude of 800 km, and an inclination of 98.7 degrees. The nominal lifetime of the satellite is eight years. The JTSIM experiments belong to the solar activities monitoring package. The solar radiation is absorbed by the black-coated cavity and the induced different heat-flux between the primary and reference cavity is measured, and the electrically calibrated differential heat-flux is used to compute the solar irradiance. SIAR has three identical channels A, B, and C, and each channel has a different solar exposure time to study the instrument& #8217 s nonlinear drift due to degradation. DARA also has three cavity radiometers and electrical substitution radiometers (Channel A, Channel B, and Channel C). The difference is that they are aligned in a triangle. Compared to VIRGO/PMO6, DARA inverts the aperture geometry to eliminate stray light. DARA and SIAR absolute radiometers are not operating at the same time due to the different designs and measurement sequences. On August 18, 2021, both instruments successfully passed the first commission phase, and they started to observe the total solar irradiance since then.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer International Publishing
Date: 17-08-2020
Publisher: Elsevier BV
Date: 09-2006
Publisher: Copernicus GmbH
Date: 03-08-2020
Publisher: Springer International Publishing
Date: 2020
Publisher: MDPI AG
Date: 12-12-2019
DOI: 10.3390/RS11242993
Abstract: This work mainly discusses an innovative teaching platform on Unmanned Aerial Vehicle digital mapping for Remote Sensing (RS) education at Wuhan University, underlining the fast development of RS technology. Firstly, we introduce and discuss the future development of the Virtual Simulation Experiment Teaching Platform for Unmanned Aerial Vehicle (VSETP-UAV). It includes specific topics such as the Systems and function Design, teaching and learning strategies, and experimental methods. This study shows that VSETP-UAV expands the usual content and training methods related to RS education, and creates a good synergy between teaching and research. The results also show that the VSETP-UAV platform is of high teaching quality producing excellent engineers, with high international standards and innovative skills in the RS field. In particular, it develops students’ practical skills with technical manipulations of dedicated hardware and software equipment (e.g., UAV) in order to assimilate quickly this particular topic. Therefore, students report that this platform is more accessible from an educational point-of-view than theoretical programs, with a quick way of learning basic concepts of RS. Finally, the proposed VSETP-UAV platform achieves a high social influence, expanding the practical content and training methods of UAV based experiments, and providing a platform for producing high-quality national talents with internationally recognized topics related to emerging engineering education.
Publisher: Authorea, Inc.
Date: 25-05-2023
Publisher: Springer International Publishing
Date: 17-08-2020
Publisher: Copernicus GmbH
Date: 26-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-616
Abstract: & & & span& The Joint Total Solar Irradiance Monitor (JTSIM) onboard the Fengyun-3E spacecraft has been launched successfully the 4& sup& th& /sup& of July 2021. It aims at measuring the Total Solar Irradiance (TSI) in orbit. The instruments on the Fengyun-3E/JTSIM include the Digital Absolute Radiometer (DARA) from the Physikalisch Meteorologisches Observatorium, Davos and World Radiation Center (PMOD/WRC) and the Solar Irradiance Absolute Radiometer (SIAR) from the Changchun Institute of Optics, Fine Mechanics and Physics Chinese Academy of Sciences (CIOMP/CAS). & /span& The JTSIM experiment will use the two different types of TSI radiometers to track the stability of TSI measurements, and to better understand instrumental degradation in space. & span& W& /span& e will present results from this new experiment& span& at first light. & /span& We & span& will & /span& compare the measurements from DARA and SIAR over the first few months and relate them to other active missions (& span& SOHO/& /span& VIRGO& span& /PMO6v& /span& , & span& SORCE/& /span& TSIS).& span& & & /span& & &
Publisher: MDPI AG
Date: 09-2022
DOI: 10.3390/RS14174339
Abstract: Previous studies have estimated the sea level rise (SLR) at various locations on the west coast of the USA and Vancouver Island in Canada. Here, we construct an entire SLR profile from Vancouver Island in the Pacific Northwest to San Diego in Southern California. First, we process global navigation satellite system (GNSS) measurements at 405 stations blanketing the whole coast to generate a profile of vertical land motion (VLM) known to bias century-long tide gauge (TG) measurements recording relative SLR (RSLR). We are then able to estimate the absolute SLR (ASLR) by correcting the SLR with the VLM. Our study emphasizes the relationship between the various tectonic movements (i.e., the Cascadia subduction zone, the San Andreas strike-slip fault system) along the Pacific coast which renders it difficult to accurately estimate the SLR. That is why we precisely model the stochastic noise of both GNSS and tide gauge time series using a combination of various models and information criterions (ICs). We also use the latest altimetry products and sea surface height (SSH) to compare it with ASLR at the same location as the TGs. This study supports previous analysis that the power law + white noise and generalized Gauss–Markov + white noise models are the best stochastic noise models for the GNSS time series. The new coastal profile confirms the large variability of VLM estimates in the Pacific Northwest around the Cascadia subduction zone in agreement with previous studies, and a similar result when the San Andreas fault comes onshore in Central California (San Francisco Bay). Negative RSLR values are mostly located in the Pacific Northwest (Vancouver Island and Olympic Peninsula). We also observe a much bigger variation (about 90–150%) of the ASLR in the Pacific Northwest which is predominantly due to glacial isostatic adjustment (GIA). Moreover, the comparison between the ASLR and the SSH estimates shows similarities in the center of the studied area (South Washington, Oregon planes, and some parts of Southern California) where the tectonic activity does not significantly influence the TG measurements. Finally, the twentieth-century satellite geocentric ocean height rates show a global mean of 1.5 to 1.9 mm/yr. Our estimates based on ASLR and SSH are within this interval.
Publisher: Springer International Publishing
Date: 2019
Publisher: Elsevier BV
Date: 02-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2013
Publisher: American Geophysical Union (AGU)
Date: 02-2018
DOI: 10.1002/2017JC013257
Publisher: Copernicus GmbH
Date: 28-09-2020
Publisher: Oxford University Press (OUP)
Date: 06-01-2015
DOI: 10.1093/GJI/GGU473
Publisher: Copernicus GmbH
Date: 15-02-2021
Abstract: Abstract. Recently, various models have been developed, including the fractional Brownian motion (fBm), to analyse the stochastic properties of geodetic time series together with the estimated geophysical signals. The noise spectrum of these time series is generally modelled as a mixed spectrum, with a sum of white and coloured noise. Here, we are interested in modelling the residual time series after deterministically subtracting geophysical signals from the observations. This residual time series is then assumed to be a sum of three stochastic processes, including the family of Lévy processes. The introduction of a third stochastic term models the remaining residual signals and other correlated processes. Via simulations and real time series, we identify three classes of Lévy processes, namely Gaussian, fractional and stable. In the first case, residuals are predominantly constituted of short-memory processes. The fractional Lévy process can be an alternative model to the fBm in the presence of long-term correlations and self-similarity properties. The stable process is here restrained to the special case of infinite variance, which can be only satisfied in the case of heavy-tailed distributions in the application to geodetic time series. Therefore, the model implies potential anxiety in the functional model selection, where missing geophysical information can generate such residual time series.
Publisher: Springer Science and Business Media LLC
Date: 14-03-2019
Publisher: Informa UK Limited
Date: 14-06-2022
Publisher: Springer International Publishing
Date: 17-08-2020
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-15391
Abstract: & & Solar radiometers are deployed in many locations on the ground and in space. The radiometers in space are measuring the solar energy input into the Earth system per time and unit area, also known as the Total Solar Irradiance (TSI). TSI radiometers are also used to calibrate Earth Observation instruments and to measure the Total Outgoing Radiation (TOR) at the top of the atmosphere, which is a key component in the Earth Radiation Budget (ERB). Ground-based solar radiometers measure the local irradiance levels, which are used for monitoring of atmospheric properties and solar energy applications.& & & & Traceability of the radiation measurements to SI units is crucial in all of these applications. However, calibrating and characterising a solar radiometer is a technically challenging task. Depending on the requirements for a specific application, different calibration concepts & span& can be employed in the calibration and characterization process.& /span& & & & & & span& We will present the currently available calibration concepts, their advantages and disadvantages, and put special focus on recent technical developments, such as the cryogenic standard radiometers for solar irradiance on the ground and in space. & /span& & &
Publisher: Wiley
Date: 13-11-2021
Publisher: IEEE
Date: 10-2012
Publisher: Elsevier BV
Date: 05-2016
Publisher: IEEE
Date: 2007
Publisher: IEEE
Date: 05-2015
Publisher: Institute of Rock Structure and Mechanics, AS CR
Date: 13-10-2017
Publisher: American Geophysical Union (AGU)
Date: 02-07-2022
DOI: 10.1029/2021JD036146
Abstract: Since the late 1970s, successive satellite missions have been monitoring the sun's activity and recording the total solar irradiance (TSI). Some of these measurements have lasted for more than a decade. In order to obtain a seamless record whose duration exceeds that of the in idual instruments, the time series have to be merged. Climate models can be better validated using such long TSI time series which can also help to provide stronger constraints on past climate reconstructions (e.g., back to the Maunder minimum). We propose a 3‐step method based on data fusion, including a stochastic noise model to take into account short and long‐term correlations. Compared with previous products scaled at the nominal TSI value of ∼1361 W/m 2 , the difference is below 0.2 W/m 2 in terms of solar minima. Next, we model the frequency spectrum of this 41‐year TSI composite time series with a Generalized Gauss‐Markov model to help describe an observed flattening at high frequencies. It allows us to fit a linear trend into these TSI time series by joint inversion with the stochastic noise model via a maximum‐likelihood estimator. Our results show that the litude of such trend is ∼−0.004 ± 0.004 W/(m 2 yr) for the period 1980–2021. These results are compared with the difference of irradiance values estimated from two consecutive solar minima. We conclude that the trend in these composite time series is mostly an artifact due to the colored noise.
Publisher: Springer Science and Business Media LLC
Date: 28-05-2014
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-7221
Abstract: The Earth Radiation Budget at the Top of the Atmosphere (ToA) governs the status of climate change on our planet. The ERB is the balance between the incoming Total Solar Irradiance (TSI) and total outgoing radiation at the ToA. If more energy is stored in the system the Earth Energy Imbalance is positive and the temperature in the system rises. The Compact Lightweight Absolute RAdiometer (CLARA) experiment onboard the Norwegian micro satellite NorSat-1 is an SI traceable radiometer with the primary science goal to measure TSI from space. Besides TSI, CLARA also measures the terrestrial Outgoing Longwave Radiation (OLR) at the ToA on the night side of Earth. We present the latest status of the data and degradation correction obtained with this SI-traceable radiometer and compare the CLARA TSI and OLR time series with other available observations and reanalysis data. The validation of these measurements is key to advance our capability to determine the Earth Energy Imbalance from space.&
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-9007
Abstract: The Project for On-Board Autonomy-3 (PROBA-3) is the fourth satellite technology development and demonstration precursor mission within ESA's GSTP (General Support Technology Program) series. The primary mission objective is to demonstrate the technologies required for formation flying of multiple spacecrafts. The PROBA-3 mission concept comprises two independent minisatellites in highly-elliptical Earth orbits in precise formation flying, close to one another with the ability to accurately control the attitude and separation of the two satellites. The mission launch is scheduled for end of 2023.PROBA-3 mission consists of a coronograph spacecraft, hosting the coronograph APIICS, and the occulter spacecraft with the Digital Absolute RAdiometer (DARA).& The radiometer to record total solar irradiance is mounted on the front satellite pointing to the Sun. DARA is& developed and manufactured in Switzerland by the PMOD/WRC. We have done two pre-flight calibration c aigns: one at the World Radiation Center in Davos, Switzerland, and one at the Total Solar Irradiance (TSI) Radiometer Facility of the Laboratory for Atmospheric and Space Physics in Boulder Colorado, USA. We report on the results of the laboratory comparisons and discuss uncertainties of several instrument parameters, which are used to transform the raw measurements, which are voltage and current, into solar irradiance values.&
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-3766
Abstract: & & & span& The modelling of the stochastic noise properties of GNSS daily coordinate time series allows to associate realistic uncertainties with the estimated geophysical parameters (e.g. tectonic rate, seasonal signal). Up to now, geodetic software based on Maximum Likelihood Estimation (MLE) jointly inverse a functional (i.e. geophysical parameters) and stochastic noise models. This method suffers from a computational time exponentially increasing & span& & & /span& with the length of the GNSS time series, which becomes an issue when considering that the first permanent stations were installed in the late 80& #8217 s & #8211 early 90& #8217 s having recorded more than 25 years of geodetic data. Combining this issue with the tremendous number of permanent stations blanketing the world (i.e. more than 20,000 stations), the processing time in the analysis of large GNSS network is a key parameter.& & /span& & & & & & span& Here, we propose an alternative to the MLE called the Generalized Method of Wavelet Moments (GMWM). This method is based on the wavelet variance, i.e. a decomposition of the time series using the Haar wavelet. We show the first results and compare them with the MLE in terms of computational efficiency and absolute error on the estimated parameters. The versatility of this new method is its flexibility of choosing various stochastic noise models (e.g., Mat& #233 rn, power law, flicker, white noise, random walk), and its robustness against outliers. Additional developments to account for deterministic components such as seasonal signal, offsets or post-seismic relaxation is easy. We explain the principle beyond the method and apply it to both simulated and real GNSS coordinate time series. Our first results are compared with the estimation using& span& & & /span& the Hector software. & /span& & &
Publisher: MDPI AG
Date: 15-09-2023
Publisher: American Geophysical Union (AGU)
Date: 02-2022
DOI: 10.1029/2021JB022489
Abstract: Several different basis functions have been used to represent the Earth's gravity field in order to generate estimates of mass variations on Earth from the analysis of data of the Gravity Recovery and Climate Experiment ( grace ) and its successor grace Follow‐On missions, including spherical harmonics, mass concentration elements (mascons) and slepian functions. Each approach depends inherently upon accurate modeling of the orbits of the pair of satellites as they revolve around the Earth, so that the observations of inter‐satellite changes in range (or, more specifically, range rate) can be exploited to identify mass variations. We have developed software using a classical orbit modeling approach, mascons and 24‐hr orbit integration, to estimate simultaneously corrections to orbital parameters and the temporal gravity field from grace data. Rather than using the range rate, we use the range acceleration as the inter‐satellite observable as it aids in localizing the mass variations. Level‐1 B range acceleration observations contain high levels of high‐frequency noise that inhibits their usefulness for this purpose. Instead, we generate range acceleration observations by numerical differentiation of the Level‐1B range rate prefit residuals. Simulations show that the gravity signal is not attenuated in this process. Our monthly estimates of mass anomalies from grace data (2003–2016) agree well with previous studies, both spatially and temporally. When converted to spherical harmonics our time series of C 2,0 , derived from grace data alone, are close to the independent estimates from satellite laser ranging, but the overall solution is improved by substituting the SLR C 2,0 .
Publisher: Wiley
Date: 17-11-2021
Publisher: Wiley
Date: 06-12-2021
Publisher: Springer International Publishing
Date: 17-08-2020
Publisher: MDPI AG
Date: 11-11-2021
DOI: 10.3390/RS13224534
Abstract: The noise in position time series of 568 GPS (Global Position System) stations across North America with an observation span of ten years has been investigated using solutions from two processing centers, namely, the Pacific Northwest Geodetic Array (PANGA) and New Mexico Tech (NMT). It is well known that in the frequency domain, the noise exhibits a power-law behavior with a spectral index of around −1. By fitting various noise models to the observations and selecting the most likely one, we demonstrate that the spectral index in some regions flattens to zero at long periods while in other regions it is closer to −2. This has a significant impact on the estimated linear rate since flattening of the power spectral density roughly halves the uncertainty of the estimated tectonic rate while random walk doubles it. Our noise model selection is based on the highest log-likelihood value, and the Akaike and Bayesian Information Criteria to reduce the probability of over selecting noise models with many parameters. Finally, the noise in position time series also depends on the stability of the monument on which the GPS antenna is installed. We corroborate previous results that deep-drilled brace monuments produce smaller uncertainties than concrete piers. However, if at each site the optimal noise model is used, the differences become smaller due to the fact that many concrete piers are located in tectonic/seismic quiet areas. Thus, for the predicted performance of a new GPS network, not only the type of monument but also the noise properties of the region need to be taken into account.
Publisher: Springer Science and Business Media LLC
Date: 24-06-2009
Publisher: AIP
Date: 2008
DOI: 10.1063/1.3037047
Publisher: MDPI AG
Date: 05-12-2022
DOI: 10.3390/RS14236164
Abstract: Geodesy is the science of accurately measuring the topography of the earth (geometric shape and size), its orientation in space, and its gravity field. With the advances in our knowledge and technology, this scientific field has extended to the understanding of geodynamical phenomena such as crustal motion, tides, and polar motion. This Special Issue is dedicated to the recent advances in modelling geodetic time series recorded using various instruments. Due to the stochastic noise properties inherent in each of the time series, careful modelling is necessary in order to extract accurate geophysical information with realistic associated uncertainties (statistically sufficient). The analyzed data have been recorded with various space missions or ground-based instruments. It is impossible to be comprehensive in the vast and dynamic field that is Geodesy, particularly so-called “Environmental Geodesy”, which intends to understand the Earth’s geodynamics by monitoring any changes in our environment. This field has gained much attention in the past two decades due to the need by the international community to understand how climate change modifies our environment. Therefore, this Special Issue collects some articles which emphasize the recent development of specific algorithms or methodologies to study particular natural phenomena related to the geodynamics of the earth’s crust and climate change.
Publisher: MDPI AG
Date: 11-12-2021
DOI: 10.3390/S21248295
Abstract: To improve the reliability of Global Positioning System (GPS) signal extraction, the traditional variational mode decomposition (VMD) method cannot determine the number of intrinsic modal functions or the value of the penalty factor in the process of noise reduction, which leads to inadequate or over-decomposition in time series analysis and will cause problems. Therefore, in this paper, a new approach using improved variational mode decomposition and wavelet packet transform (IVMD-WPT) was proposed, which takes the energy entropy mutual information as the objective function and uses the grasshopper optimisation algorithm to optimise the objective function to adaptively determine the number of modal decompositions and the value of the penalty factor to verify the validity of the IVMD-WPT algorithm. We performed a test experiment with two groups of simulation time series and three indicators: root mean square error (RMSE), correlation coefficient (CC) and signal-to-noise ratio (SNR). These indicators were used to evaluate the noise reduction effect. The simulation results showed that IVMD-WPT was better than the traditional empirical mode decomposition and improved variational mode decomposition (IVMD) methods and that the RMSE decreased by 0.084 and 0.0715 mm CC and SNR increased by 0.0005 and 0.0004 dB, and 862.28 and 6.17 dB, respectively. The simulation experiments verify the effectiveness of the proposed algorithm. Finally, we performed an analysis with 100 real GPS height time series from the Crustal Movement Observation Network of China (CMONOC). The results showed that the RMSE decreased by 11.4648 and 6.7322 mm, and CC and SNR increased by 0.1458 and 0.0588 dB, and 32.6773 and 26.3918 dB, respectively. In summary, the IVMD-WPT algorithm can adaptively determine the number of decomposition modal functions of VMD and the optimal combination of penalty factors it helps to further extract effective information for noise and can perfectly retain useful information in the original time series.
Publisher: Scientific Research Publishing, Inc.
Date: 2017
Publisher: Wiley
Date: 21-04-2022
Abstract: Elevated atmospheric [CO 2 ] (‘eCO 2 ’) may alter species composition within vegetation types by favouring the growth of some species over others. However, other related changes in climate conditions, such as increased frequency and severity of drought, may reduce eCO 2 fertilisation effects on plant growth. For many species, it is not known if responses will reflect variability in trait adaptations due to environment. We grew seedlings of nine species of eucalypts indicative of three regional vegetation types (representing a mesic–xeric ecosystem gradient) under two CO 2 concentrations (400 parts per million 640 ppm, i.e. eCO 2 ) and two watering regimes (well‐watered drought‐like conditions). Elevated CO 2 increased biomass accumulation but drought reduced this effect, with mesic species experiencing larger relative reductions. Elevated CO 2 increased the size of storage organs used during resprouting, in the absence of drought. Typical drought responses, such as increased leaf mass per unit area and root mass ratio, were more pronounced in xeric species and were reduced under eCO 2 . Seedling growth and resprouting may be enhanced by eCO 2 , suggesting continued dominance of resprouting species in disturbance‐prone ecosystems, although severe drought is likely to offset eCO 2 fertilisation. Xeric species may cope with drought more effectively under eCO 2 than mesic species due to resource acquisition and storage traits that are more responsive. Read the free Plain Language Summary for this article on the Journal blog.
Publisher: Wiley
Date: 24-12-2021
Publisher: Springer Science and Business Media LLC
Date: 12-12-2015
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-21260
Abstract: & & The analysis of daily position Global Navigation Satellite System (GNSS) time series provides information about various geophysical processes that are shaping the Earth& #8217 s crust. The goodness of fit of a trajectory model to these observations is an indication of our understanding of these phenomena. However, the fit also depends on the noise levels in the time series and in this study we investigate for 568 GNSS stations across North America the noise properties, its relation with the choice of trajectory model and if there exists a relationship with the type of monuments. We use the time series of two processing centers, namely the Central Washington University (CWU) and the New Mexico Tech (NMT), which process the data using two different complete processing strategies.& & & & We demonstrate that mismodelling slow slip events within the geodetic time series increases the percentage of selecting the Random-Walk + Flicker + White noise (RW+FN+WN) as the optimal noise model for the horizontal components, especially when the Akaike Information Criterion is used. Furthermore, the analysis of the spatial distribution of the RW component (in the FN+WN+RW) around North America takes place at stations mostly localised around tectonic active areas such as the Cascadia subduction zone (Pacific Northwest) or the San Andreas fault (South California) and coastal areas. It is in these areas that most shallow and drilled-braced monuments are also located. Therefore, the comparison of monument type with observed noise level should also take into account its location which mostly has been neglected in previous studies. In addition, the General Gauss-Markov (GGM) with white noise (GGM+WN) is often selected for the Concrete Pier monument especially on the Up component which indicates that the very long time series are experiencing this flattening of the power spectrum at low frequency. Finally, the litude of the white noise is larger for the Roof-Top/Chimney (RTC) type than for the other monument& #8217 s types. With a varying seasonal signal computed using a Wiener filter, the results show that RTC monuments have larger values in the East and North components, whereas the deep-drilled brace monuments have larger values on the vertical component.& &
Publisher: Elsevier BV
Date: 05-2017
Publisher: MDPI AG
Date: 28-10-2020
DOI: 10.3390/RS12213532
Abstract: The global navigation satellite system (GNSS) has seen tremendous advances in measurement precision and accuracy, and it allows researchers to perform geodynamics and geophysics studies through the analysis of GNSS time series. Moreover, GNSS time series not only contain geophysical signals, but also unmodeled errors and other nuisance parameters, which affect the performance in the estimation of site coordinates and related parameters. As the number of globally distributed GNSS reference stations increases, GNSS time series analysis software should be developed with more flexible format support, better human–machine interaction, and with powerful noise reduction analysis. To meet this requirement, a new software named GNSS time series noise reduction software (GNSS-TS-NRS) was written in MATLAB and was developed. GNSS-TS-NRS allows users to perform noise reduction analysis and spatial filtering on common mode errors and to visualize GNSS position time series. The functions’ related theoretical background of GNSS-TS-NRS were introduced. Firstly, we showed the theoretical background algorithms of the noise reduction analysis (empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD)). We also developed three improved algorithms based on EMD for noise reduction, and the results of the test ex le showed our proposed methods with better effect. Secondly, the spatial filtering model supported five algorithms on a separate common model error: The stacking filter method, weighted stacking filter method, correlation weighted superposition filtering method, distance weighted filtering method, and principal component analysis, as well as with batch processing. Finally, the developed software also enabled other functions, including outlier detection, correlation coefficient calculation, spectrum analysis, and distribution estimation. The main goal of the manuscript is to share the software with the scientific community to introduce new users to the GNSS time series noise reduction and application.
Publisher: American Society of Civil Engineers (ASCE)
Date: 11-2016
Publisher: IEEE
Date: 09-2011
Publisher: Springer Science and Business Media LLC
Date: 02-2023
DOI: 10.1007/S00190-023-01702-8
Abstract: The global navigation satellite system (GNSS) daily position time series are often described as the sum of stochastic processes and geophysical signals which allow to study global and local geodynamical effects such as plate tectonics, earthquakes, or ground water variations. In this work, we propose to extend the Generalized Method of Wavelet Moments (GMWM) to estimate the parameters of linear models with correlated residuals. This statistical inferential framework is applied to GNSS daily position time-series data to jointly estimate functional (geophysical) as well as stochastic noise models. Our method is called GMWMX, with X standing for eXogenous variables: it is semi-parametric, computationally efficient and scalable. Unlike standard methods such as the widely used maximum likelihood estimator (MLE), our methodology offers statistical guarantees, such as consistency and asymptotic normality, without relying on strong parametric assumptions. At the Gaussian model, our results (theoretical and obtained in simulations) show that the estimated parameters are similar to the ones obtained with the MLE. The computational performances of our approach have important practical implications. Indeed, the estimation of the parameters of large networks of thousands of GNSS stations (some of them being recorded over several decades) quickly becomes computationally prohibitive. Compared to standard likelihood-based methods, the GMWMX has a considerably reduced algorithmic complexity of order $$\\mathcal {O}\\{\\log (n) n\\}$$ O { log ( n ) n } for a time series of length n . Thus, the GMWMX appears to provide a reduction in processing time of a factor of 10–1000 compared to likelihood-based methods depending on the considered stochastic model, the length of the time series and the amount of missing data. As a consequence, the proposed method allows the estimation of large-scale problems within minutes on a standard computer. We validate the performances of our method via Monte Carlo simulations by generating GNSS daily position time series with missing observations and we consider composite stochastic noise models including processes presenting long-range dependence such as power law or Matérn processes. The advantages of our method are also illustrated using real time series from GNSS stations located in the Eastern part of the USA.
Publisher: Wiley
Date: 19-12-2005
Publisher: Wiley
Date: 24-11-2020
Publisher: Springer Science and Business Media LLC
Date: 08-06-2018
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-6437
Abstract: & & Total Solar Irradiance (TSI) is one of the Essential Climate Variables (ECV) identified by the World Meteorological Organization's Global Climate System (GCOS). The Compact Lightweight Absolute RAdiometer (CLARA) experiment onboard the Norwegian micro satellite NorSat-1 is a SI traceable radiometer and was launched July 14, 2017 with the primary science goal to measure TSI from space. We present the latest status of the data and degradation correction obtained with this SI-traceable radiometer. Besides TSI, CLARA also measures the total outgoing radiation (TOR) at the top of the Earth atmosphere on the night side of Earth, which is extremely important to understand the Earth Radiation Budget. It is to our knowledge the first time that TSI and the emitted radiation from Earth are measured simultaneously with one SI-traceable absolute radiometer. We will compare the CLARA TSI and TOR time series with other available datasets. Ultimately, we aim towards determining the Earth Energy Imbalance from space. We will discuss the achievements and limitations in direction of this goal.& &
Publisher: Springer Science and Business Media LLC
Date: 09-04-2021
DOI: 10.1038/S41598-021-87108-Y
Abstract: Various space missions have measured the total solar irradiance (TSI) since 1978. Among them the experiments Precision Monitoring of Solar Variability (PREMOS) on the PICARD satellite (2010–2014) and the Variability of Irradiance and Gravity Oscillations (VIRGO) on the mission Solar and Heliospheric Observatory , which started in 1996 and is still operational. Like most TSI experiments, they employ a dual-channel approach with different exposure rates to track and correct the inevitable degradation of their radiometers. Until now, the process of degradation correction has been mostly a manual process based on assumed knowledge of the sensor hardware. Here we present a new data-driven process to assess and correct instrument degradation using a machine-learning and data fusion algorithm, that does not require deep knowledge of the sensor hardware. We apply the algorithm to the TSI records of PREMOS and VIRGO and compare the results to the previously published results. The data fusion part of the algorithm can also be used to combine data from different instruments and missions into a composite time series. Based on the fusion of the degradation-corrected VIRGO/PMO6 and VIRGO/DIARAD time series, we find no significant change (i.e $$-0.17\\pm 0.29$$ - 0.17 ± 0.29 W/m $$^2$$ 2 ) between the TSI levels during the two most recent solar minima in 2008/09 and 2019/20. The new algorithm can be applied to any TSI experiment that employs a multi-channel philosophy for degradation tracking. It does not require deep technical knowledge of the in idual radiometers.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Authorea, Inc.
Date: 02-05-2023
DOI: 10.22541/ESSOAR.168298707.70099578/V1
Abstract: This article acts as an introduction to the JGR-Atmospheres special section titledMonitoring the Earth Radiation Budget and its Implication to Climate Simulations: RecentAdvances and Discussions. It outlines the major findings of the articles publishedin the special section as well as discusses ongoing research within the field of researchof monitoring the Earth Radiation Budget.
Publisher: Springer Science and Business Media LLC
Date: 07-06-2014
Publisher: Scientific Research Publishing, Inc.
Date: 2017
Publisher: Copernicus GmbH
Date: 03-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-4382
Abstract: & & & span& Since the late 70& #8217 s, successive satellite missions have been monitoring the sun& #8217 s activity, recording total solar irradiance observations. These measurements are important to estimate the Earth& #8217 s energy imbalance, & /span& & span& i.e. the difference of energy absorbed and emitted by our planet. Climate modelers need the solar forcing time series in their models in order to study the influence of the Sun on the Earth& #8217 s climate. With this amount of TSI data, solar irradiance reconstruction models & can be better validated which can also improve studies looking at past climate reconstructions (e.g., Maunder minimum). V& /span& & span& arious algorithms have been proposed in the last decade to merge the various TSI measurements over the 40 years of recording period. We have developed a new statistical algorithm based on data fusion.& & The stochastic noise processes of the measurements are modeled via a dual kernel including white and coloured noise.& & We show our first results and compare it with previous releases (PMOD,ACRIM, ... ).& & /span& & &
Publisher: Copernicus GmbH
Date: 25-03-2020
Publisher: Copernicus GmbH
Date: 06-12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2013
Publisher: Copernicus GmbH
Date: 07-04-2027
DOI: 10.5194/NPG-2019-48
Abstract: Abstract. Recently, various models have been developed, including the fractional Brownian motion (fBm), to analyse the stochastic properties of geodetic time series, together with the extraction of geophysical signals. The noise spectrum of these time series is generally modeled as a mixed spectrum, with a sum of white and coloured noise. Here, we are interested in modelling the residual time series, after deterministically subtracting geophysical signals from the observations. This residual time series is then assumed to be a sum of three random variables (r.v.), with the last r.v. belonging to the family of Levy processes. This stochastic term models the remaining residual signals and other correlated processes. Via simulations and real time series, we identify three classes of Levy processes: Gaussian, fractional and stable. In the first case, residuals are predominantly constituted of short-memory processes. Fractional Levy process can be an alternative model to the fBm in the presence of long-term correlations and self-similarity property. Stable process is characterized by a large variance, which can be satisfied in the case of heavy-tailed distributions. The application to geodetic time series implies potential anxiety in the functional model selection where missing geophysical information can generate such residual time series.
Publisher: IEEE
Date: 09-2014
Publisher: Copernicus GmbH
Date: 24-06-2020
DOI: 10.5194/NPG-2020-23
Abstract: Abstract. Recently, various models have been developed, including the fractional Brownian motion (fBm), to analyse the stochastic properties of geodetic time series, together with the estimated geophysical signals. The noise spectrum of these time series is generally modelled as a mixed spectrum, with a sum of white and coloured noise. Here, we are interested in modelling the residual time series, after deterministically subtracting geophysical signals from the observations. This residual time series is then assumed to be a sum of three stochastic processes, including the family of Lévy processes. The introduction of a third stochastic term models the remaining residual signals and other correlated processes. Via simulations and real time series,we identify three classes of Lévy processes: Gaussian, fractional and stable. In the first case, residuals are predominantly constituted of short-memory processes. Fractional Lévy process can be an alternative model to the fBm in the presence of long-term correlations and self-similarity property. Stable process is here restrained to the special case of infinite variance, which can be only satisfied in the case of heavy-tailed distributions in the application to geodetic time series. Therefore, it implies potential anxiety in the functional model selection where missing geophysical information can generate such residual time series.
Publisher: Scientific Research Publishing, Inc.
Date: 2018
Location: United Kingdom of Great Britain and Northern Ireland
Location: Switzerland
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2014
End Date: 2017
Funder: NASA
View Funded ActivityStart Date: 2015
End Date: 2018
Funder: Kommission für Technologie und Innovation
View Funded ActivityStart Date: 2008
End Date: 2012
Funder: Australian Research Council
View Funded Activity