Processing of GRACE-FO satellite-to-satellite tracking data using the GRACE-SIGMA software

2020 ◽  
Author(s):  
Igor Koch ◽  
Mathias Duwe ◽  
Jakob Flury ◽  
Akbar Shabanloui
Keyword(s):  
Laser Ranging ◽  
Satellite Measurements ◽  
Satellite Mission ◽  
The Earth ◽  
Gravity Fields ◽  
Data Products ◽  
Level 1 ◽  
Orbit Types ◽  
Gravity Recovery

<p>The dual-satellite mission GRACE Follow-On (GRACE-FO) was launched in May 2018 as the successor of the Gravity Recovery And Climate Experiment (GRACE). In May 2019 first level 1 data products were made available to the community and are now published regularly. These products, among others, include orbits, accelerometer measurements, star camera data and micron and sub-micron precise inter-satellite range measurements. The data products are used by different groups to compute estimates of monthly gravity fields of the Earth. The in-house developed GRACE-SIGMA software is used at the Institut of Geodesy/Leibniz University Hannover for the estimation of monthly gravity fields. Several parts of the software’s processing chain, such as background modeling, were updated recently and different parametrization scenarios were tested. First solutions were estimated based on laser ranging interferometer measurements. Moreover, different orbit types, such as reduced-dynamic and kinematic, were tested. In this contribution, we present the influence of these updates and tests on the quality of the gravity fields. The obtained solutions are assessed in terms of error degree standard deviations and post-fit residuals of the inter-satellite measurements.</p>

scholarly journals Evaluation of Water Storage Change of Inland Cryosphere in Northwestern China

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Min Xu ◽  
Shichang Kang ◽  
Jiazhen Li
Keyword(s):  
Water Storage ◽  
Northwestern China ◽  
Satellite Mission ◽  
Pronounced Increase ◽  
The North ◽  
Gravity Fields ◽  
Grace Satellite ◽  
Gravity Recovery ◽  
Storage Change ◽  
Assimilation Model

The Gravity Recovery and Climate Experiment (GRACE) satellite mission provides measurements of Earth’s static and time-variable gravity fields with monthly resolution. In this study, changes of water storage in northwestern China were determined by GRACE monthly gravity field data obtained from 2003 to 2010. Comparisons of water storage change (WSC) simulated by a four-dimensional assimilation model (Noah) and observed by GRACE revealed similar patterns of change and a correlation coefficient of 0.71(P<0.05). Trend analysis indicated significant changes in the spatiotemporal variation of WSC in northwestern China during the 8-year study period, which were stronger in the east than in the west and more pronounced in the south than in the north. The most pronounced increase in water storage occurred in Gansu and Qinghai provinces, but, overall, water storage increased by 0.61 mm/a over northwestern China during the study period. Clear seasonal variations of WSC and precipitation were found, because glacial meltwater and precipitation are the main sources of water in the hydrosphere; meanwhile, the distributions of glaciers and permafrost also affect the spatial distribution of WSC.

GRACE and GRACE-FO Level-1 V04 Data Processing Status

2020 ◽  
Author(s):  
Christopher Mccullough ◽  
Tamara Bandikova ◽  
William Bertiger ◽  
Carmen Boening ◽  
Sung Byun ◽  
...  
Keyword(s):  
Data Processing ◽  
Attitude Determination ◽  
Precise Orbit Determination ◽  
Mass Change ◽  
Sensor Data ◽  
The Earth ◽  
Analysis Center ◽  
Level 1 ◽  
Gravity Recovery

&lt;p&gt;The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), launched in May 2018, provides invaluable information about mass change in the Earth system, continuing the legacy of GRACE. Fundamental requirements for successful mass change recovery are precise orbit determination and inter-satellite ranging, determination of the relative clock alignment of the ultra-stable oscillators (USOs), precise attitude determination, and accelerometry. NASA/Caltech Jet Propulsion Laboratory is the official Level-1 data processing and analysis center, and is currently processing software version 04. Here we present analysis of the aforementioned GRACE-FO sensor data, as well a preview of an upcoming GRACE reprocessing, and a discussion of measurement performance.&lt;/p&gt;

scholarly journals Multiple-data-based monthly geopotential model set LDCmgm90

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Wei Chen ◽  
Jiesi Luo ◽  
Jim Ray ◽  
Nan Yu ◽  
Jian Cheng Li
Keyword(s):  
Gravity Data ◽  
Gravity Models ◽  
Geopotential Model ◽  
Satellite Mission ◽  
Stripe Pattern ◽  
Angular Momenta ◽  
Multiple Data ◽  
Model Set ◽  
Gravity Recovery

Abstract While the GRACE (Gravity Recovery and Climate Experiment) satellite mission is of great significance in understanding various branches of Earth sciences, the quality of GRACE monthly products can be unsatisfactory due to strong longitudinal stripe-pattern errors and other flaws. Based on corrected GRACE Mascon (mass concentration) gridded mass transport time series and updated LDCgam (Least Difference Combination global angular momenta) data, we present a new set of monthly gravity models called LDCmgm90, in the form of Stokes coefficients with order and degree both up to 90. The LDCgam inputs are developed by assimilating degree-2 Stokes coefficients from various versions of GRACE (including Mascon products) and SLR (Satellite Laser Ranging) monthly gravity data into combinations of outputs from various global atmospheric, oceanic, and hydrological circulation models, under the constraints of accurately measured Earth orientation parameters in the Least Difference Combination (LDC) scheme. Taking advantages of the relative strengths of the various input solutions, the LDCmgm90 is free of stripes and some other flaws of classical GRACE products.

scholarly journals Quality of Orbit Predictions for Satellites Tracked by SLR Stations

2021 ◽  
Vol 13 (7) ◽  
pp. 1377
Author(s):  
Joanna Najder ◽  
Krzysztof Sośnica
Keyword(s):  
Extreme Case ◽  
Laser Ranging ◽  
Artificial Satellites ◽  
Satellite Orbits ◽  
Satellite Systems ◽  
Quality Degradation ◽  
The Earth ◽  
The Mean ◽  
Over Time

This study aims to evaluate and analyze the orbit predictions of selected satellites: geodetic, Global Navigational Satellite Systems (GNSS), and scientific low-orbiting, which are tracked by laser stations. The possibility of conducting satellite laser ranging (SLR) to artificial satellites depends on the access to high-quality predictions of satellite orbits. The predictions provide information to laser stations where to aim the telescope in search of a satellite to get the returns from the retroreflectors installed onboard. If the orbit predictions are very imprecise, SLR stations must spend more time to correct the telescope pointing, and thus the number of collected observations is small or, in an extreme case, there are none of them at all. Currently, there are about 120 satellites equipped with laser retroreflectors orbiting the Earth. Therefore, the necessity to determine the quality of predictions provided by various analysis centers is important in the context of the increasing number of satellites tracked by SLR stations. We compare the orbit predictions to final GNSS orbits, precise orbits of geodetic satellites based on SLR measurements determined in postprocessing, and kinematic orbits of low-orbiting satellites based on GPS data. We assess the quality degradation of the orbit predictions over time depending on the type of orbit and the satellite being analyzed. We estimate the time of usefulness of prediction files, and indicate those centers which publish most accurate predictions of the satellites’ trajectories. The best-quality predictions for geodetic satellites and Galileo reach the mean error of 0.5–1 m for the whole 5-day prediction file (for all three components), while the worst ones can reach values of up to several thousand meters during the first day of the prediction.

scholarly journals Retrieval of tropospheric NO<sub>2</sub> columns from SCIAMACHY combining measurements from limb and nadir geometries

2012 ◽  
Vol 5 (4) ◽  
pp. 5043-5105 ◽  
Author(s):  
A. Hilboll ◽  
A. Richter ◽  
A. Rozanov ◽  
Ø. Hodnebrog ◽  
A. Heckel ◽  
...  
Keyword(s):  
Systematic Bias ◽  
Satellite Measurements ◽  
Matching Algorithm ◽  
The Earth ◽  
Novel Approach ◽  
Tropospheric No2 ◽  
Invaluable Tool ◽  
Global Coverage ◽  
Sector Method

Abstract. Satellite measurements of atmospheric trace gases have proved to be an invaluable tool for monitoring the Earth system. When these measurements are to be used for assessing tropospheric emissions and pollution, as for example in the case of nadir measurements of nitrogen dioxide (NO2), it is necessary to separate the stratospheric from the tropospheric signal. The SCIAMACHY instrument offers the unique opportunity to combine its measurements in limb and nadir viewing geometries into a tropospheric data product, using the limb measurements of the stratospheric NO2 abundances to correct the nadir measurements' total columns. In this manuscript, we present a novel approach to limb/nadir matching, calculating one stratospheric NO2 value from limb measurements for every single nadir measurement, abandoning global coverage for the sake of spatial accuracy. As a comparison, modelled stratospheric NO2 columns from the Oslo CTM2 are evaluated as stratospheric correction, and both datasets are confronted with the originally used reference sector method. Our study shows that stratospheric NO2 columns from SCIAMACHY limb measurements very well reflect stratospheric conditions. The zonal variability of stratospheric NO2 is captured by our matching algorithm, and the quality of the resulting tropospheric NO2 columns improves considerably. Modelled stratospheric NO2 columns from the Oslo CTM2 agree remarkably well with the measurements. Both datasets need to be matched to the level of the nadir measurements, however, because a time and latitude dependent bias between both stratospheric datasets and the measured nadir columns can be observed over clean regions. After accounting for this systematic bias between SCIAMACHY nadir observations and the stratospheric columns, both new stratospheric correction methods provide a significant improvement to the retrieval of tropospheric NO2 columns from the SCIAMACHY instrument.

scholarly journals Improvements to the retrieval of tropospheric NO<sub>2</sub> from satellite – stratospheric correction using SCIAMACHY limb/nadir matching and comparison to Oslo CTM2 simulations

2013 ◽  
Vol 6 (3) ◽  
pp. 565-584 ◽  
Author(s):  
A. Hilboll ◽  
A. Richter ◽  
A. Rozanov ◽  
Ø. Hodnebrog ◽  
A. Heckel ◽  
...  
Keyword(s):  
Earth System ◽  
Spatial Accuracy ◽  
Satellite Measurements ◽  
Matching Algorithm ◽  
The Earth ◽  
Novel Approach ◽  
Tropospheric No2 ◽  
Invaluable Tool ◽  
Global Coverage

Abstract. Satellite measurements of atmospheric trace gases have proved to be an invaluable tool for monitoring the Earth system. When these measurements are to be used for assessing tropospheric emissions and pollution, as for example in the case of nadir measurements of nitrogen dioxide (NO2), it is necessary to separate the stratospheric from the tropospheric signal. The SCIAMACHY instrument offers the unique opportunity to combine its measurements in limb- and nadir-viewing geometries into a tropospheric data product, using the limb measurements of the stratospheric NO2 abundances to correct the nadir measurements' total columns. In this manuscript, we present a novel approach to limb/nadir matching, calculating one stratospheric NO2 value from limb measurements for every single nadir measurement, abandoning global coverage for the sake of spatial accuracy. For comparison, modelled stratospheric NO2 columns from the Oslo CTM2 are also evaluated for stratospheric correction. Our study shows that stratospheric NO2 columns from SCIAMACHY limb measurements very well reflect stratospheric conditions. The zonal variability of the stratospheric NO2 field is captured by our matching algorithm, and the quality of the resulting tropospheric NO2 columns improves considerably. Both stratospheric datasets need to be adjusted to the level of the nadir measurements, because a time- and latitude-dependent bias to the measured nadir columns can be observed over clean regions. After this offset is removed, the two datasets agree remarkably well, and both stratospheric correction methods provide a significant improvement to the retrieval of tropospheric NO2 columns from the SCIAMACHY instrument.

Comparison between Laser Ranging Interferometer and K/Ka band Ranging instruments.

2020 ◽  
Author(s):  
Sebastien Allgeyer ◽  
Herbert McQueen ◽  
Paul Tregoning
Keyword(s):  
Spectral Analysis ◽  
Spectral Band ◽  
Harmonic Spectrum ◽  
Laser Ranging ◽  
Range Data ◽  
Satellite Mission ◽  
Ka Band ◽  
Gravity Signal ◽  
Improved Accuracy

&lt;div&gt; &lt;p&gt;&lt;span&gt;The GRACE Follow-On mission is the first twin-satellite mission&lt;/span&gt;&lt;span&gt; equipped with a laser ranging interferometer (LRI) to measure the inter-satellite distance between the pair of satellites. The LRI operates independently of the K/Ka-band interferometer (KBR&lt;/span&gt;&lt;span&gt;)&amp;#160;and uses&lt;/span&gt;&lt;span&gt;&amp;#160;wavelengths&lt;/span&gt;&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;span&gt;10&lt;/span&gt;&lt;sup&gt;&lt;span&gt;4&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;&amp;#160;times&lt;/span&gt;&lt;span&gt;&amp;#160;shorter than the K-band&lt;/span&gt;&lt;span&gt;&amp;#160;system.&amp;#160;&amp;#160;&lt;/span&gt;&lt;span&gt;Released at the end of July 2019, the LRI range data is&amp;#160;&lt;/span&gt;&lt;span&gt;therefore&amp;#160;&lt;/span&gt;&lt;span&gt;expected to be of higher accuracy than the KBR and offers the possibility of a better spatial resolution. We compare the LRI and KBR observations of the GRACE-FO mission, from launch to December 2019, to assess the quality of the new LRI system.&lt;/span&gt;&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;span&gt;Spectral analysis of the level1B data shows that the noise level of the LRI is 3&amp;#160;&lt;/span&gt;&lt;span&gt;orders&lt;/span&gt;&lt;span&gt;&amp;#160;of magnitude smaller than the KBR&lt;/span&gt;&lt;span&gt;&amp;#160;and that&amp;#160;&lt;/span&gt;&lt;span&gt;the gravity signal can be detected in the spectral band up to&amp;#160;&lt;/span&gt;&lt;span&gt;30mHz in the LRI data&amp;#160;&lt;/span&gt;&lt;span&gt;compared&lt;/span&gt;&lt;span&gt;&amp;#160;to&amp;#160;&lt;/span&gt;&lt;span&gt;20mHz&lt;/span&gt;&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;span&gt;i&lt;/span&gt;&lt;span&gt;n&lt;/span&gt;&lt;span&gt;&amp;#160;the&amp;#160;&lt;/span&gt;&lt;span&gt;KBR&lt;/span&gt;&lt;span&gt;&amp;#160;data&lt;/span&gt;&lt;span&gt;.&lt;/span&gt;&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;span&gt;&amp;#160;We compare&lt;/span&gt;&lt;span&gt;&amp;#160;gravity&amp;#160;&lt;/span&gt;&lt;span&gt;fields&lt;/span&gt;&lt;span&gt;&amp;#160;estimated using LRI&amp;#160;&lt;/span&gt;&lt;span&gt;and KBR and show which parts of the spherical harmonic spectrum are affected by the improved accuracy of the LRI observations.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;

scholarly journals A 1% Measurement of the Gravitomagnetic Field of the Earth with Laser-Tracked Satellites

Universe ◽  
2020 ◽  
Vol 6 (9) ◽  
pp. 139
Author(s):  
David Lucchesi ◽  
Massimo Visco ◽  
Roberto Peron ◽  
Massimo Bassan ◽  
Giuseppe Pucacco ◽  
...  
Keyword(s):  
Systematic Errors ◽  
Laser Ranging ◽  
Careful Evaluation ◽  
Frame Dragging ◽  
Gravitational Perturbations ◽  
The Earth ◽  
Spacetime Curvature ◽  
Gravitomagnetic Field ◽  
Theory Of Gravitation ◽  
Gravity Recovery

A new measurement of the gravitomagnetic field of the Earth is presented. The measurement has been obtained through the careful evaluation of the Lense-Thirring (LT) precession on the combined orbits of three passive geodetic satellites, LAGEOS, LAGEOS II, and LARES, tracked by the Satellite Laser Ranging (SLR) technique. This general relativity precession, also known as frame-dragging, is a manifestation of spacetime curvature generated by mass-currents, a peculiarity of Einstein’s theory of gravitation. The measurement stands out, compared to previous measurements in the same context, for its precision (≃7.4×10−3, at a 95% confidence level) and accuracy (≃16×10−3), i.e., for a reliable and robust evaluation of the systematic sources of error due to both gravitational and non-gravitational perturbations. To achieve this measurement, we have largely exploited the results of the GRACE (Gravity Recovery And Climate Experiment) mission in order to significantly improve the description of the Earth’s gravitational field, also modeling its dependence on time. In this way, we strongly reduced the systematic errors due to the uncertainty in the knowledge of the Earth even zonal harmonics and, at the same time, avoided a possible bias of the final result and, consequently, of the precision of the measurement, linked to a non-reliable handling of the unmodeled and mismodeled periodic effects.

V04 Level-1 data processing status for GRACE and GRACE Follow-On

2020 ◽  
Author(s):  
Tamara Bandikova ◽  
Hui Ying Wen ◽  
Meegyeong Paik ◽  
William Bertiger ◽  
Mark Miller ◽  
...  
Keyword(s):  
Data Processing ◽  
Gravity Field ◽  
Attitude Determination ◽  
Precise Orbit Determination ◽  
Sensor Data ◽  
Satellite Mission ◽  
Gravity Field Recovery ◽  
Grace Data ◽  
Level 1 ◽  
Gravity Recovery

&lt;p&gt;On May 22, 2020, the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), will celebrate two years of successful in-orbit operation. The primary goal of this satellite mission is to provide information about time variations of the Earth&amp;#8217;s gravity field. This is possible due to precise orbit determination and inter-satellite ranging by determining the relative clock alignment of the USOs, precise attitude determination and accelerometry. High quality satellite observations are one of the fundamental requirements for successful gravity field recovery. NASA/Caltech Jet Propulsion Laboratory is the official Level-1 data processing and analysis center. The GRACE-FO Level-1 data are currently being processed with software version V04. This software will be used also for final reprocessing of the GRACE (2002-2017) Level-1 data. Here we present the analysis of two years of GRACE-FO sensor data as well as a preview of the reprocessed GRACE data, and discuss the measurement performance.&lt;/p&gt;

scholarly journals Evaluation of Total Ozone Column from Multiple Satellite Measurements in the Antarctic Using the Brewer Spectrophotometer

2021 ◽  
Vol 13 (8) ◽  
pp. 1594
Author(s):  
Songkang Kim ◽  
Sang-Jong Park ◽  
Hana Lee ◽  
Dha Hyun Ahn ◽  
Yeonjin Jung ◽  
...  
Keyword(s):  
Satellite Data ◽  
Total Ozone ◽  
Spatiotemporal Pattern ◽  
Satellite Measurements ◽  
Austral Spring ◽  
Total Ozone Column ◽  
Brewer Spectrophotometer ◽  
The Antarctic ◽  
Ozone Column

The ground-based ozone observation instrument, Brewer spectrophotometer (Brewer), was used to evaluate the quality of the total ozone column (TOC) produced by multiple polar-orbit satellite measurements at three stations in Antarctica (King Sejong, Jang Bogo, and Zhongshan stations). While all satellite TOCs showed high correlations with Brewer TOCs (R = ~0.8 to 0.9), there are some TOC differences among satellite data in austral spring, which is mainly attributed to the bias of Atmospheric Infrared Sounder (AIRS) TOC. The quality of satellite TOCs is consistent between Level 2 and 3 data, implying that “which satellite TOC is used” can induce larger uncertainty than “which spatial resolution is used” for the investigation of the Antarctic TOC pattern. Additionally, the quality of satellite TOC is regionally different (e.g., OMI TOC is a little higher at the King Sejong station, but lower at the Zhongshan station than the Brewer TOC). Thus, it seems necessary to consider the difference of multiple satellite data for better assessing the spatiotemporal pattern of Antarctic TOC.

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