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: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

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: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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: Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

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.