ALBERT

Description: The thermosphere causes by far the largest non-gravitational perturbing acceleration of near-Earth orbiting satellites. Especially between 80 km and 1,000 km, the thermospheric density distribution and variations are required to model accurately this acceleration for precise orbit determination (POD), ephemeris computation and re-entry prediction of the Low-Earth Orbiting (LEO) satellites. So far, mostly on-board accelerometers are used to measure the thermospheric density. However, such type of satellite is usually of complex shape and any error or mismodelling in the satellite drag coefficient and satellite effective cross-sectional area will directly propagate into the derived thermospheric density values. At GFZ, an empirical model of the thermospheric mass density denoted as “CH-Therm-2018” has been developed by using 9 years (2001–2009) of CHAMP observations. A completely different approach for thermospheric density determination is based on using satellite laser ranging (SLR) measurements to LEO satellites equipped with retro-reflectors to determine an accurate satellite orbit. These measurements are sensitive to small perturbations acting on the satellite. In order to minimize the error induced by imprecise satellite macro-models, we use in our investigation SLR observations to satellites with a simple spherical shape and thus, relate estimated scaling factors to the thermospheric density. In this paper, we use SLR observations to two ANDE-2 satellites – ANDE-Castor and ANDE-Pollux – as well as SpinSat with altitudes between 248 km and 425 km to calibrate the CH-Therm-2018 model, as well as four other empirical models of thermospheric density, namely CIRA86, NRLMSISE00, JB2008 and DTM2013. For our tests, we chose a period from 16 August 2009 to 26 March 2010 of low solar activity and a period from 29 December 2014 to 29 March 2015 of high solar activity. Using data of a few geodetic satellites obtained at the same and different time intervals allows us to investigate the reliability of the scaling factors of the thermospheric densities provided by the models. We have found that CIRA86 and NRLMSISE00 most significantly overestimate the thermospheric density at the period of low solar activity among the models tested. The JB2008 model is the least scaled model and provides reliable values of the thermospheric density for the periods of both low and high solar activity. The GFZ CH-Therm-2018 model, on the contrary, underestimates the thermospheric density at the time interval of low solar activity. Using SLR observations at longer time intervals should allow to investigate temporal evolution of the scaling factors of these models more precisely.

Description: In this study, we present an empirical model, named CH-Therm-2018, of the thermospheric mass density derived from 9-year (from August 2000 to July 2009) accelerometer measurements from the CHAllenging Mini-satellite Payload (CHAMP) satellite at altitudes from 460 to 310km. The CHAMP dataset is divided into two 5-year periods with 1-year overlap (from August 2000 to July 2005 and from August 2004 to July 2009) to represent the high-to-moderate and moderate-to-low solar activity conditions, respectively. The CH-Therm-2018 model describes the thermospheric density as a function of seven key parameters, namely the height, solar flux index, season (day of year), magnetic local time, geographic latitude and longitude, as well as magnetic activity represented by the solar wind merging electric field. Predictions of the CH-Therm-2018 model agree well with CHAMP observations (within 20%) and show different features of thermospheric mass density during the two solar activity levels, e.g., the March–September equinox asymmetry and the longitudinal wave pattern. From the analysis of satellite laser ranging (SLR) observations of the ANDE-Pollux satellite during August–September 2009, we estimate 6h scaling factors of the thermospheric mass density provided by our model and obtain the median value equal to 1.267±0.60. Subsequently, we scale up our CH-Therm-2018 mass density predictions by a scale factor of 1.267. We further compare the CH-Therm-2018 predictions with the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar Extended (NRLMSISE-00) model. The result shows that our model better predicts the density evolution during the last solar minimum (2008–2009) than the NRLMSISE-00 model.

Description: Integrated observation platforms have been set up to investigate consequences of global change within a terrestrial network of observatories (TERENO) in Germany. The aim of TERENO is to foster the understanding of water, energy, and matter fluxes in terrestrial systems, as well as their biological and physical drivers. Part of the Lower Rhine Valley-Eifel observatory of TERENO is located within the Eifel National Park. Recently, the National Park forest management started to promote the natural regeneration of near-natural beech forest by removing a significant proportion of the spruce forest that was established for timber production after World War II. Within this context, the effects of such a disturbance on forest ecosystem functioning are currently investigated in a deforestation experiment in the Wustebach catchment, which is one of the key experimental research sites within the Lower Rhine Valley-Eifel observatory. Here, we present the integrated observation system of the Wustebach test site to exemplarily demonstrate the terrestrial observatory concept of TERENO that allows for a detailed monitoring of changes in hydrological and biogeochemical states and fluxes triggered by environmental disturbances. We present the observation platforms and the soil sampling campaign, as well as preliminary results including an analysis of data consistency. We specifically highlight the capability of integrated datasets to enable improved process understanding of the post-deforestation changes in ecosystem functioning.

Description: The high-quality dual-frequency phase measurements of Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) system provide valuable opportunities to examine the Earth’s ionosphere. DORIS data from the Jason-3 satellite has also been available in Near-Real-Time (NRT) with a delay of a few hours. Such data are perfectly suited for independent validation and combination of Real-Time Global Ionospheric Maps (RT-GIM) derived from GNSS measurements. In this work, we analyzed the feasibility of using DORIS data to estimate the accuracy of GNSS-generated ionospheric models. To this end, the concept of DORIS differential Slant Total Electron Content (dSTEC) assessment is proposed. The consistency between DORIS and GNSS dSTEC assessments in the quality analysis of RT-GIMs was checked, and the overall Pearson correlation coefficient reaches 0.81 during the one-year test period. The DORIS dSTEC assessment can be used not only to estimate the accuracy of individual GIMs, but also to determine their weighting within a combination strategy. The performance of DORIS-dSTEC and GNSS-dSTEC combined GIMs is assessed by comparison to Jason-3 VTEC from the mission altimeter. The standard deviations are 4.71 TECu and 4.80 TECu for DORIS-dSTEC and GNSS-dSTEC combined GIMs, indicating the slightly better performance of DORIS-dSTEC combined RT-GIM in Jason-3 VTEC assessment. Overall, NRT DORIS data can be used to independently validate and combine GNSS-derived ionospheric maps. In the future, it is also envisaged that DORIS data can be directly incorporated into ionosphere modeling. To this end, the provision of NRT data from other DORIS missions is planned (e.g., Sentinel-3).

Description: Space weather is an up-to-date and interdisciplinary field of research. It describes physical processes in space mainly caused by the Sun’s radiation of energy. The manifestations of space weather are variations of the Earth’s magnetic field or changes of the neutral and ionized states of the thermosphere and the ionosphere.The main objectives of the Focus Area on Geodetic Space Weather Research (FA GSWR) are the development of (1) improved ionosphere models and (2) improved thermosphere models, (3) coupled processes between magnetosphere, ionosphere, plasmasphere and thermosphere and (4) understanding of space weather events and their monitoring.Objective (1) aims at high-precision and high-resolution (spatial and temporal) modelling of the electron density. This allows to compute a signal propagation delay, which will be used in many geodetic applications, in particular in positioning, navigation and timing. Concerning objective (2), satellite geodesy will obviously benefit when working on precise orbit determination, but there are further technical matters such as collision analysis or re-entry calculation. Objective (3) links the magnetosphere with the first two objectives by introducing physical laws and principles such as continuity, energy and momentum equations and solving partial differential equations. Finally, objective (4) connects the results of (1), (2) and (3) to the monitoring techniques and vice versa. To arrive at these objectives one Joint Study Group and three Joint Working Groups have been installed and are successfully running since 2019. In this presentation, we provide an overview about the status of the FA GSWR and provide future perspectives.

Description: The four dimensional (4D) space and time dependent electron density within the ionosphere and plasmasphere needs to be accurately known for precise point positioning and satellite navigation because it strongly influences the propagation of electromagnetic waves. The electron density is a highly variable function reflecting, e.g. plasma fluctuations with periods of less than a few minutes, diurnal and seasonal variations, long-period changes corresponding to the solar cycle of 11 years as well as the impact of space weather events. If the 4D electron density would be known everywhere within the ionosphere and plasmasphere at any time moment, each measurement of space-geodetic observation techniques such as GNSS, Satellite Altimetry or DORIS could be corrected independently if single or multi-frequency measurements are used. Vice versa, all these observations including Ionospheric Radio Occultations, Langmuir probe and GRACE K-band measurement provide valuable information on the state of the ionosphere and the plasmasphere and thus, for modeling the electron density. The Multi-Layer Chapman Model developed at DGFI-TUM consists of 14 key parameters. The joint estimation of all of them means an unsolvable task. It is well-known that unrealistic estimates such as negative values for the maximum electron density value of the L2 layer, may appear in the parameter estimation procedure. To avoid this, inequality constraints must be incorporated in the estimation process. This is mathematically equivalent to solving a constrained optimization problem. We developed in this context a procedure based on the active-set method. Several numerical examples are presented mostly based on simulated input data.

Description: Low-resolution global satellite gravity observations can be combined with medium-resolution satellite altimetry data and high-resolution regional gravity data from airborne, shipborne, or terrestrial measurements for a refined, high-resolution geoid modeling. Current studies based on spherical radial basis functions (SRBFs) majorly consider a single-level approach for data combination. Despite the promising results reported in numerous publications, it has been suspected that the single-level model may fail to extract the full information contained in the gravity data. In this study, a spectral combination based on the SRBFs is applied through the multi-resolution representation (MRR), which allows to decompose the gravity signal into series expansion in terms of spherical harmonics for the global long-wavelength part, and a number of detail signals in terms of wavelet functions for the regional medium and high frequency parts. An innovative MRR scheme is developed based on the pyramid algorithm and sequential parameter estimation. Instead of estimating the coefficients for calculating the detail signals at each resolution level independently, the pyramid algorithm is applied to connect the different levels and estimate the coefficients sequentially. In this presentation, numerical investigations are conducted to demonstrate the advantages of this newly developed MRR scheme in comparison to both the single-level approach and the MRR without using the pyramid algorithm.

Description: Up to 50% of the signal delays of L-band signals used in the Global Navigation Satellite System comes from the topside ionosphere and plasmasphere. In this study, we apply an Ensemble Kalman Filter (EnKF) approach to estimate the 4D electron density of the topside ionosphere and plasmasphere based on space-based STEC data. NeQuick model is used as background. The STEC measurements of eleven LEO satellites are used for the reconstructions. The majority of the approaches, working with EnKF, uses physics-based models for the propagation step. In our work, we investigate the question how the propagation step can be realized, in the case that a physical propagation model is not available or discarded due to computational burden. We explore different propagation models and compare them with the iterative reconstruction technique SMART+ for two periods of the year 2015 covering quiet to perturbed ionospheric conditions. We check the capability of the estimations to reproduce assimilated STEC as well as to reconstruct independent STEC measurements. The comparison with the assimilated STEC shows that during both periods all methods reduce the statistics (Median, SD, RMS) of the STEC residuals in comparison to the background model by up to 86%. In summary, the results indicate that the methods EnKF with exponential decay as propagation model (EnKFexp) and SMART+ perform best, reducing the independent STEC residuals by up to 64%, compared to the NeQuick model.

Description: The global and regional ionospheric maps are often used for a wide range of applications in geosciences, in particular to support precise positioning, but also for geophysical and atmospheric studies. There are currently many analysis centers and research groups providing operational and test VTEC maps. However, IGS ACs and other groups use different mathematical models and estimation techniques resulting different resolutions, accuracies and time delays of their products. Therefore, there is a need to compare and validate existing VTEC models. In this presentation, we present the overview talk about the work within the last 4 years of the IAG Joint Working Group (JWG 4.3.4) on validation of VTEC models for high-precision and high resolution applications. Among others, we evaluated (1) the accuracy and consistency of the IAAC GIMs during high and low solar activity periods of the 24th solar cycle, (2) the accuracy the two most popular ionospheric mapping functions - SLM and MSLM, (3) deterministic and stochastic approaches to VTEC modelling, (4) GIMs performance in single point and precise point positioning GNSS applications, (5) the accuracy and consistency of GNSS-derived VTEC maps and empirical models, (6) GIMs performance using external data (JASON) and GNSS, (7) the accuracy of new global ionosphere models.