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4. Altimetry for the future: Building on 25 years of progress

Author

Abdalla, Saleh, Abdeh Kolahchi, Abdolnabi, Ablain, Michaël, Adusumilli, Susheel, Aich Bhowmick, Suchandra, Alou-Font, Eva, Amarouche, Laiba, Andersen, Ole Baltazar, Antich, Helena, Aouf, Lotfi, Arbic, Brian, Armitage, Thomas, Arnault, Sabine, Artana, Camila, Aulicino, Giuseppe, Ayoub, Nadia, Badulin, Sergei, Baker, Steven, Banks, Chris, Bao, Lifeng, Barbetta, Silvia, Barceló-Llull, Bàrbara, Barlier, François, Basu, Sujit, Bauer-Gottwein, Peter, Becker, Matthias, Beckley, Brian, Bellefond, Nicole, Belonenko, Tatyana, Benkiran, Mounir, Benkouider, Touati, Bennartz, Ralf, Benveniste, Jérôme, Bercher, Nicolas, Berge-Nguyen, Muriel, Bettencourt, Joao, Blarel, Fabien, Blazquez, Alejandro, Blumstein, Denis, Bonnefond, Pascal, Borde, Franck, Bouffard, Jérôme, Boy, François, Boy, Jean-Paul, Brachet, Cédric, Brasseur, Pierre, Braun, Alexander, Brocca, Luca, Brockley, David, Brodeau, Laurent, Brown, Shannon, Bruinsma, Sean, Bulczak, Anna, Buzzard, Sammie, Cahill, Madeleine, Calmant, Stéphane, Calzas, Michel, Camici, Stefania, Cancet, Mathilde, Capdeville, Hugues, Carabajal, Claudia Cristina, Carrere, Loren, Cazenave, Anny, Chassignet, Eric P., Chauhan, Prakash, Cherchali, Selma, Chereskin, Teresa, Cheymol, Cecile, Ciani, Daniele, Cipollini, Paolo, Cirillo, Francesca, Cosme, Emmanuel, Coss, Steve, Cotroneo, Yuri, Cotton, David, Couhert, Alexandre, Coutin-Faye, Sophie, Crétaux, Jean-François, Cyr, Frederic, d’Ovidio, Francesco, Darrozes, José, David, Cedric, Dayoub, Nadim, De Staerke, Danielle, Deng, Xiaoli, Desai, Shailen, Desjonqueres, Jean-Damien, Dettmering, Denise, Di Bella, Alessandro, Díaz-Barroso, Lara, Dibarboure, Gerald, Dieng, Habib Boubacar, Dinardo, Salvatore, Dobslaw, Henryk, Dodet, Guillaume, Doglioli, Andrea, Domeneghetti, Alessio, Donahue, David, Dong, Shenfu, Donlon, Craig, Dorandeu, Joël, Drezen, Christine, Drinkwater, Mark, Du Penhoat, Yves, Dushaw, Brian, Egido, Alejandro, Erofeeva, Svetlana, Escudier, Philippe, Esselborn, Saskia, Exertier, Pierre, Fablet, Ronan, Falco, Cédric, Farrell, Sinead Louise, Faugere, Yannice, Femenias, Pierre, Fenoglio, Luciana, Fernandes, Joana, Fernández, Juan Gabriel, Ferrage, Pascale, Ferrari, Ramiro, Fichen, Lionel, Filippucci, Paolo, Flampouris, Stylianos, Fleury, Sara, Fornari, Marco, Forsberg, Rene, Frappart, Frédéric, Frery, Marie-laure, Garcia, Pablo, Garcia-Mondejar, Albert, Gaudelli, Julia, Gaultier, Lucile, Getirana, Augusto, Gibert, Ferran, Gil, Artur, Gilbert, Lin, Gille, Sarah, Giulicchi, Luisella, Gómez-Enri, Jesús, Gómez-Navarro, Laura, Gommenginger, Christine, Gourdeau, Lionel, Griffin, David, Groh, Andreas, Guerin, Alexandre, Guerrero, Raul, Guinle, Thierry, Gupta, Praveen, Gutknecht, Benjamin D., Hamon, Mathieu, Han, Guoqi, Hauser, Danièle, Helm, Veit, Hendricks, Stefan, Hernandez, Fabrice, Hogg, Anna, Horwath, Martin, Idžanović, Martina, Janssen, Peter, Jeansou, Eric, Jia, Yongjun, Jia, Yuanyuan, Jiang, Liguang, Johannessen, Johnny A., Kamachi, Masafumi, Karimova, Svetlana, Kelly, Kathryn, Kim, Sung Yong, King, Robert, Kittel, Cecile M.M., Klein, Patrice, Klos, Anna, Knudsen, Per, Koenig, Rolf, Kostianoy, Andrey, Kouraev, Alexei, Kumar, Raj, Labroue, Sylvie, Lago, Loreley Selene, Lambin, Juliette, Lasson, Léa, Laurain, Olivier, Laxenaire, Rémi, Lázaro, Clara, Le Gac, Sophie, Le Sommer, Julien, Le Traon, Pierre-Yves, Lebedev, Sergey, Léger, Fabien, Legresy, Benoı̂t, Lemoine, Frank, Lenain, Luc, Leuliette, Eric, Levy, Marina, Lillibridge, John, Liu, Jianqiang, Llovel, William, Lyard, Florent, Macintosh, Claire, Makhoul Varona, Eduard, Manfredi, Cécile, Marin, Frédéric, Mason, Evan, Massari, Christian, Mavrocordatos, Constantin, Maximenko, Nikolai, McMillan, Malcolm, Medina, Thierry, Melet, Angelique, Meloni, Marco, Mertikas, Stelios, Metref, Sammy, Meyssignac, Benoit, Minster, Jean-François, Moreau, Thomas, Moreira, Daniel, Morel, Yves, Morrow, Rosemary, Moyard, John, Mulet, Sandrine, Naeije, Marc, Nerem, Robert Steven, Ngodock, Hans, Nielsen, Karina, Nilsen, Jan Even Øie, Niño, Fernando, Nogueira Loddo, Carolina, Noûs, Camille, Obligis, Estelle, Otosaka, Inès, Otten, Michiel, Oztunali Ozbahceci, Berguzar, P. Raj, Roshin, Paiva, Rodrigo, Paniagua, Guillermina, Paolo, Fernando, Paris, Adrien, Pascual, Ananda, Passaro, Marcello, Paul, Stephan, Pavelsky, Tamlin, Pearson, Christopher, Penduff, Thierry, Peng, Fukai, Perosanz, Felix, Picot, Nicolas, Piras, Fanny, Poggiali, Valerio, Poirier, Étienne, Ponce de León, Sonia, Prants, Sergey, Prigent, Catherine, Provost, Christine, Pujol, M-Isabelle, Qiu, Bo, Quilfen, Yves, Rami, Ali, Raney, R. Keith, Raynal, Matthias, Remy, Elisabeth, Rémy, Frédérique, Restano, Marco, Richardson, Annie, Richardson, Donald, Ricker, Robert, Ricko, Martina, Rinne, Eero, Rose, Stine Kildegaard, Rosmorduc, Vinca, Rudenko, Sergei, Ruiz, Simón, Ryan, Barbara J., Salaün, Corinne, Sanchez-Roman, Antonio, Sandberg Sørensen, Louise, Sandwell, David, Saraceno, Martin, Scagliola, Michele, Schaeffer, Philippe, Scharffenberg, Martin G., Scharroo, Remko, Schiller, Andreas, Schneider, Raphael, Schwatke, Christian, Scozzari, Andrea, Ser-giacomi, Enrico, Seyler, Frederique, Shah, Rashmi, Sharma, Rashmi, Shaw, Andrew, Shepherd, Andrew, Shriver, Jay, Shum, C.K., Simons, Wim, Simonsen, Sebatian B., Slater, Thomas, Smith, Walter, Soares, Saulo, Sokolovskiy, Mikhail, Soudarin, Laurent, Spatar, Ciprian, Speich, Sabrina, Srinivasan, Margaret, Srokosz, Meric, Stanev, Emil, Staneva, Joanna, Steunou, Nathalie, Stroeve, Julienne, Su, Bob, Sulistioadi, Yohanes Budi, Swain, Debadatta, Sylvestre-baron, Annick, Taburet, Nicolas, Tailleux, Rémi, Takayama, Katsumi, Tapley, Byron, Tarpanelli, Angelica, Tavernier, Gilles, Testut, Laurent, Thakur, Praveen K., Thibaut, Pierre, Thompson, LuAnne, Tintoré, Joaquín, Tison, Céline, Tourain, Cédric, Tournadre, Jean, Townsend, Bill, Tran, Ngan, Trilles, Sébastien, Tsamados, Michel, Tseng, Kuo-Hsin, Ubelmann, Clément, Uebbing, Bernd, Vergara, Oscar, Verron, Jacques, Vieira, Telmo, Vignudelli, Stefano, Vinogradova Shiffer, Nadya, Visser, Pieter, Vivier, Frederic, Volkov, Denis, von Schuckmann, Karina, Vuglinskii, Valerii, Vuilleumier, Pierrik, Walter, Blake, Wang, Jida, Wang, Chao, Watson, Christopher, Wilkin, John, Willis, Josh, Wilson, Hilary, Woodworth, Philip, Yang, Kehan, Yao, Fangfang, Zaharia, Raymond, Zakharova, Elena, Zaron, Edward D., Zhang, Yongsheng, Zhao, Zhongxiang, Zinchenko, Vadim, and Zlotnicki, Victor

Published
2021
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10. DTRF2020: Strategy, Results and Data Set

Author

Seitz, Manuela, primary, Blossfeld, Mathis, additional, Glomsda, Matthias, additional, Angermann, Detlef, additional, Rudenko, Sergei, additional, Zeitlhoefler, Julian, additional, and Seitz, Florian, additional

Published
2023
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13. DTRF2020: first results

Author

Seitz, Manuela, Bloßfeld, Mathis, Glomsda, Matthias, Angermann, Detlef, Rudenko, Sergei, and Zeitlhoefler Julian

Abstract

The presentation gives an overview over the DTRF2020 combination and its challenges.

Published
2022
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17. On the accuracy of contemporary orbits of altimetry satellites in the radial direction

Author

Rudenko, Sergei, Dettmering, Denise, Bloßfeld, Mathis, Zeitlhöfler, Julian, and Alkahal, Riva

Abstract

Precise orbits of altimetry satellites are a basis for sea surface height estimation, since they provide the reference for the measured distance from a satellite altimeter to a water surface. Various factors affect accuracy of orbits of these satellites, such as type and quality of observations used, proper corrections of measurements, proper modelling of satellite shape, size, optical properties of its surfaces and its orientation in space, accurate modelling of forces acting on a satellite, accurate terrestrial and celestial reference frame realizations and transformation between them, proper modelling of displacements of tracking stations, a proper parameter adjustment algorithm, observation weighting and other factors. Significant progress has been reached in precise orbit determination of altimetry satellites in the latest decades by different orbit determination groups. In this presentation, we investigate the accuracy in the radial direction of contemporary orbits of such altimetry satellites as TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A and some others derived in the ITRF2014 realization by various institutions using various types of observations covering totally time span from 1992 until 2021. We investigate single-satellite altimetry crossover differences, radial errors of individual orbit solutions and orbit differences in the radial direction between various orbit solutions for each satellite.

Published
2022
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18. DTRF2020: the ITRS 2020 Realization of DGFI-TUM

Author

Seitz, Manuela, Bloßfeld, Mathis, Glomsda, Matthias, Angermann, Detlef, Rudenko, Sergei, and Zeitlhöfler, Julian

Abstract

As one of the three ITRS Combination Centres of the IERS, DGFI-TUM is in charge of computing an ITRS 2020 realization. Compared to the ITRS 2014 realization, the situation regarding the input data has changed significantly as not only the observation periods have increased but also new general and technique-specific models are applied in the analysis. Many model changes have an impact on the realized intrinsic scale of the individual techniques in particular and GNSS now provides an independent scale for the first time. This changes the situation for scale realization and validation significantly. With regard to the combination strategy, post-seismic deformation and all three components of non-tidal loading are considered for the first time in DTRF2020. We will present the strategy and results of the DTRF2020 computation. Results from the analysis of the DORIS data and aspects relevant to DORIS applications will be highlighted.

Published
2022
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38. An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative

Author

Legeais, Jean-François, primary, Ablain, Michaël, additional, Zawadzki, Lionel, additional, Zuo, Hao, additional, Johannessen, Johnny A., additional, Scharffenberg, Martin G., additional, Fenoglio-Marc, Luciana, additional, Fernandes, M. Joana, additional, Andersen, Ole Baltazar, additional, Rudenko, Sergei, additional, Cipollini, Paolo, additional, Quartly, Graham D., additional, Passaro, Marcello, additional, Cazenave, Anny, additional, and Benveniste, Jérôme, additional

Published
2018
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39. An Accurate and Homogeneous Altimeter Sea Level Record from the ESA Climate Change Initiative

Author

Legeais, Jean-Francois, primary, Ablain, Michaël, additional, Zawadzki, Lionel, additional, Zuo, Hao, additional, Johannessen, Johnny A., additional, Scharffenberg, Martin G., additional, Fenoglio-Marc, Luciana, additional, Fernandes, M. Joana, additional, Andersen, Ole Baltazar, additional, Rudenko, Sergei, additional, Cipollini, Paolo, additional, Quartly, Graham D., additional, Passaro, Marcello, additional, Cazenave, Anny, additional, and Benveniste, Jérôme, additional

Published
2017
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40. REAPER: Reprocessing 12 Years of ERS-1 and ERS-2 Altimeters and Microwave Radiometer Data

Author

Brockley, David J., primary, Baker, Steven, additional, Femenias, Pierre, additional, Martinez, Bernat, additional, Massmann, Franz-Heinrich, additional, Otten, Michiel, additional, Paul, Frederic, additional, Picard, Bruno, additional, Prandi, Pierre, additional, Roca, Monica, additional, Rudenko, Sergei, additional, Scharroo, Remko, additional, and Visser, Pieter, additional

Published
2017
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41. A new phase in the production of quality-controlled sea level data

Author

Quartly, Graham D., primary, Legeais, Jean-François, additional, Ablain, Michaël, additional, Zawadzki, Lionel, additional, Fernandes, M. Joana, additional, Rudenko, Sergei, additional, Carrère, Loren, additional, García, Pablo Nilo, additional, Cipollini, Paolo, additional, Andersen, Ole B., additional, Poisson, Jean-Christophe, additional, Mbajon Njiche, Sabrina, additional, Cazenave, Anny, additional, and Benveniste, Jérôme, additional

Published
2017
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45. Impact of terrestrial reference frame realizations on altimetry satellites orbit quality, global and regional sea level trends: case ITRF2014 versus ITRF2008.

Author

Rudenko, Sergei, Esselborn, Saskia, Schöne, Tilo, and Dettmering, Denise

Subjects
*ALTIMETRY, *SEA level, *STANDARD deviations
Abstract

A terrestrial reference frame (TRF) is a basis for precise orbit determination of Earth orbiting satellites, since it defines positions and velocities of stations tracking data of which is used to derive satellite positions. In this paper, we investigate the impact of the International Terrestrial Reference Frame realization ITRF2014, as compared to its predecessor ITRF2008, on the quality of orbits, namely, on root-mean-square (RMS) fits of observations and orbital arc overlaps of three altimetry satellites (TOPEX/Poseidon, Jason-1 and Jason-2) at the time interval from August 1992 till April 2015 and on altimetry products computed using these orbits, such as single-satellite altimeter crossover differences, radial and geographically correlated mean sea surface height (SSH) errors, regional and global mean sea level trends. The satellite orbits are computed using Satellite Laser Ranging (SLR) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations of a global network of stations. We have found that using ITRF2014 generally improves orbit quality, as compared to using ITRF2008. Thus, the mean values of the RMS fits of SLR observations decreased (improved) by 2.4 and 8.8% for Jason-1 and Jason-2, respectively, but are almost not impacted for TOPEX/Poseidon, when using ITRF2014 instead of ITRF2008. The internal orbit consistency in the radial direction (as derived from arc overlaps) is reduced (improved) by 6.6%, 2.3%, and 5.9% for TOPEX/Poseidon, Jason-1, and Jason-2, respectively. Single satellite altimetry crossover analysis indicates reduction (improvement) of the absolute mean crossover differences by 0.2mm (8.1%) for TOPEX/Poseidon, 0.4mm (17.7%) for Jason-1 and 0.6mm (30.9%) for Jason-2 with ITRF2014 instead of ITRF2008. The major improvement of the mean values of the RMS of crossover differences (0.13mm (0.3%)) has been found for Jason-2. Multi-mission crossover analysis shows slight improvements in the standard deviations of radial errors: 0.1%, 0.2% and 1.6% for TOPEX/Poseidon, Jason-1 and Jason-2, respectively. The standard deviations of geographically correlated mean SSH errors improved by 1.1% for Jason-1 and 5.4% for Jason-2 and degraded by 1.3% for TOPEX/Poseidon. The change from ITRF2008 to ITRF2014 orbits has only minor effects on the estimation of regional and global sea level trends over the 22 years time series from 1993 to 2015. However, on interannual time scales (3-8 years) large scale coherent trend patterns are observed that seem to be connected to drifts between the origins of the tracking stations networks. This leads to uncertainties of interannual global mean sea level of up to 0.06mmyr-1 for TOPEX/Poseidon, 0.05mmyr-1 for Jason-1, and up to 0.12mmyr-1 for Jason-2. The respective changes of regional sea level trend on these time scales reach maximum values of 0.4mmyr-1 for TOPEX/Poseidon, of 0.5mmyr-1 for Jason-1 and of 1.0mmyr-1 for Jason-2. [ABSTRACT FROM AUTHOR]

Published
2018
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46. An Accurate and Homogeneous Altimeter Sea Level Record from the ESA Climate Change Initiative.

Author

Legeais, Jean-Francois, Ablain, Michaël, Zawadzki, Lionel, Zuo, Hao, Johannessen, Johnny A., Scharffenberg, Martin G., Fenoglio-Marc, Luciana, Fernandes, M. Joana, Andersen, Ole Baltazar, Rudenko, Sergei, Cipollini, Paolo, Quartly, Graham D., Passaro, Marcello, Cazenave, Anny, and Benveniste, Jérôme

Subjects
SEA level & the environment, ALTIMETERS
Abstract

Sea Level is a very sensitive index of climate change since it integrates the impacts of ocean warming and ice mass loss from glaciers and the ice sheets. Sea Level has been listed as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). During the past 25 years, the sea level ECV has been measured from space by different altimetry missions that have provided global and regional observations of sea level variations. As part of the Climate Change Initiative (CCI) program of the European Space Agency (ESA) (established in 2010), the Sea Level project (SL_cci) aimed at providing an accurate and homogeneous long-term satellite-based sea level record. At the end of the first phase of the project (2010-2013), an initial version (v1.1) of the sea level ECV has been made available to users (Ablain et al., 2015). During the second phase (2014-2017), improved altimeter standards have been selected to produce new sea level products (called SL_cci v2.0) based on 9 altimeter missions for the period 1993-2015 (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). Corresponding orbit solutions, geophysical corrections and altimeter standards used in this v2.0 dataset are described in details in Quartly et al. (2017). The present paper focuses on the description of the SL_cci v2.0 ECV and associated uncertainty and discusses how it has been validated. Various approaches have been used for the quality assessment such as internal validation, comparisons with sea level records from other groups and with in-situ measurements, sea level budget closure analyses and comparisons with model outputs. Compared to the previous version of the sea level ECV, we show that use of improved geophysical corrections, careful bias reduction between missions and inclusion of new altimeter missions lead to improved sea level products with reduced uncertainties at different spatial and temporal scales. However, there is still room for improvement since the uncertainties remain larger than the GCOS requirements. Perspectives for subsequent evolutions are also discussed. [ABSTRACT FROM AUTHOR]

Published
2017
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47. Orbit related sea level errors for TOPEX altimetry at seasonal to decadal time scales.

Author

Esselborn, Saskia, Rudenko, Sergei, and Schöne, Tilo

Subjects
SEA level, CLIMATE change, ALTIMETRY
Abstract

Interannual to decadal sea level trends are indicators of climate variability and change. A major source of global and regional sea level data is satellite radar altimetry, which relies on precise knowledge of the satellite's orbit. Here, we assess the error budget of the radial orbit component for the TOPEX/Poseidon mission for the period 1993 to 2004 from a set of different orbit solutions. Upper bound errors for seasonal, interannual (5 years), and decadal periods are estimated on global and regional scales based on radial orbit differences from three state-of-the-art orbit solutions provided by different research teams (GFZ, GSFC, and GRGS). The global mean sea level error related to the orbit is of the order of 7 mm (more than 10 % of the sea level variability) with negligible contributions on the annual and decadal time scale. In contrast, the orbit related error of the interannual trend is 0.1 mm/year (18 % of the corresponding sea level variability) and might hamper the estimation of an acceleration of the global mean sea level rise. For regional scales, the gridded orbit related error is up to 11 mm and for about half the ocean the orbit error accounts for at least 10 % of the observed sea level variability. The seasonal orbit error amounts to 10 % of the observed seasonal sea level signal in the Southern Ocean. At interannual and decadal time scales, the orbit related trend uncertainties reach regionally more than 1 mm/year. The interannual trend errors account for 10 % of the observed sea level signal in the Tropical Atlantic and the south-eastern Pacific. For decadal scales, the orbit related trend errors are prominent in a couple of regions including: South Atlantic, western North Atlantic, central Pacific, South Australian Basin, and Mediterranean Sea. Based on a set of test orbits calculated at GFZ, the sources of the observed orbit related errors are further investigated. Main contributors on all time scales are uncertainties in Earth's time variable gravity field models and on annual to interannual time scales discrepancies of the tracking station sub-networks, i.e., SLR and DORIS. [ABSTRACT FROM AUTHOR]

Published
2017
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49. Scale Factors of the Thermospheric Density: A Comparison of Satellite Laser Ranging and Accelerometer Solutions

Author

Lea Zeitler, Armin Corbin, Kristin Vielberg, Sergei Rudenko, Anno Löcher, Mathis Bloßfeld, Michael Schmidt, Jürgen Kusche, Corbin, Armin, 2 Institute of Geodesy and Geoinformation University of Bonn Bonn Germany, Vielberg, Kristin, Rudenko, Sergei, 1 Deutsches Geodätisches Forschungsinstitut Technische Universität München Munich Germany, Löcher, Anno, Bloßfeld, Mathis, Schmidt, Michael, and Kusche, Jürgen

Subjects
Geophysics, ddc:551.5, Space and Planetary Science, ddc:526.1, ddc
Abstract

A major problem in the precise orbit determination (POD) of satellites at altitudes below 1,000 km is the modeling of the aerodynamic drag which mainly depends on the thermospheric density and causes the largest non‐gravitational acceleration. Typically, empirical thermosphere models are used to calculate density values at satellite positions but current thermosphere models cannot provide the required accuracy. Thus, unaccounted variations in the thermospheric density may lead to significantly incorrect satellite positions. For the first time, we bring together thermospheric density corrections for the NRLMSISE‐00 model in terms of scale factors with a temporal resolution of 12 hr derived from satellite laser ranging (SLR) and accelerometer measurements. Whereas, the latter are in situ information given along the satellite orbit, SLR results have to be interpreted as mean values along the orbit within the underlying time interval. From their comparison, we notice a rather similar behavior with correlations of up to 80% and more depending on altitude. During high solar activity, scale factors vary around 30% at low solar activity and up to 70% at high solar activity from the value one. In addition, we found the scaled thermospheric density decreasing stronger as the modeled density of NRLMSISE‐00. To check the reliability of the SLR‐derived scale factors, we compare the POD result of two different software packages, namely DOGS‐OC from DGFI‐TUM and GROOPS from IGG Bonn. Furthermore, a validation of our estimated scale factors with respect to an external data set proofs the high quality of the obtained results., Plain Language Summary: Variations in the density of the thermosphere must be taken into account when modeling and predicting the motion of satellites in the near‐Earth environment. Typically, thermospheric densities at the position of satellites are provided by models, but their accuracy is limited. Due to the sensitivity of satellites orbiting the Earth in the altitude range of the thermosphere, they can be used to derive information about the thermospheric density. In this study, we compare for the first time thermospheric density corrections in terms of scale factors for the NRLMSISE‐00 model with a temporal resolution of 12 hr derived from two geodetic measurement techniques, namely satellite laser ranging (SLR) and accelerometry. Our results demonstrate that both measurement techniques can be used to derive comparable scale factors of the thermospheric density, which vary around the desired value one. This indicates to which extent the NRLMSISE‐00 model differs from the observed thermospheric density. On average, during high solar activity, the model underestimates the thermospheric density and can be scaled up using the estimated scale factors. We additionally discuss our estimated scale factors with respect to an external data set. Furthermore, we validate the approach of deriving scale factors from SLR measurements by using two independent software packages., Key Points: For the first time, we compare scale factors of the thermospheric density derived from satellite laser ranging (SLR) and accelerometer measurements. The estimated scale factors vary by up to 30% at low solar activity and up to 70% at high solar activity from the desired value 1. Correlations of 0.7–0.8 are obtained between the estimated scale factors from SLR and accelerometer measurements depending on the height., German Research Foundation (DFG), Technical University of Munich (TUM)

Published
2021

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