Articles | Volume 9, issue 2
Earth Syst. Sci. Data, 9, 833–848, 2017
https://doi.org/10.5194/essd-9-833-2017
Earth Syst. Sci. Data, 9, 833–848, 2017
https://doi.org/10.5194/essd-9-833-2017
Review article
17 Nov 2017
Review article | 17 Nov 2017

Instrument data simulations for GRACE Follow-on: observation and noise models

Neda Darbeheshti et al.

Related subject area

Data, Algorithms, and Models
Improved maps of surface water bodies, large dams, reservoirs, and lakes in China
Xinxin Wang, Xiangming Xiao, Yuanwei Qin, Jinwei Dong, Jihua Wu, and Bo Li
Earth Syst. Sci. Data, 14, 3757–3771, https://doi.org/10.5194/essd-14-3757-2022,https://doi.org/10.5194/essd-14-3757-2022, 2022
Short summary
The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation
Jie Chen, Qi Yao, Ziyue Chen, Manchun Li, Zhaozhan Hao, Cheng Liu, Wei Zheng, Miaoqing Xu, Xiao Chen, Jing Yang, Qiancheng Lv, and Bingbo Gao
Earth Syst. Sci. Data, 14, 3489–3508, https://doi.org/10.5194/essd-14-3489-2022,https://doi.org/10.5194/essd-14-3489-2022, 2022
Short summary
A high-resolution inland surface water body dataset for the tundra and boreal forests of North America
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022,https://doi.org/10.5194/essd-14-3349-2022, 2022
Short summary
A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan
Amy McNally, Jossy Jacob, Kristi Arsenault, Kimberly Slinski, Daniel P. Sarmiento, Andrew Hoell, Shahriar Pervez, James Rowland, Mike Budde, Sujay Kumar, Christa Peters-Lidard, and James P. Verdin
Earth Syst. Sci. Data, 14, 3115–3135, https://doi.org/10.5194/essd-14-3115-2022,https://doi.org/10.5194/essd-14-3115-2022, 2022
Short summary
HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand
Thomas R. Etherington, George L. W. Perry, and Janet M. Wilmshurst
Earth Syst. Sci. Data, 14, 2817–2832, https://doi.org/10.5194/essd-14-2817-2022,https://doi.org/10.5194/essd-14-2817-2022, 2022
Short summary

Cited articles

Bandikova, T., Flury, J., and Ko, U.: Characteristics and accuracies of the GRACE inter-satellite pointing, Adv. Space Res., 50, 123–135, 2012.
Case, K., Kruizinga, G., and Wu, S.: GRACE level 1B data product user handbook, JPL Publication D-22027, 2002.
Flechtner, F., Neumayer, K.-H., Dahle, C., Dobslaw, H., Fagiolini, E., Raimondo, J.-C., and Güntner, A.: What Can be Expected from the GRACE-FO Laser Ranging Interferometer for Earth Science Applications?, Surv. Geophys., 37, 453–470, https://doi.org/10.1007/s10712-015-9338-y, 2016.
Franklin, J. N.: Numerical simulation of stationary and non-stationary gaussian random processes, SIAM Review, 7, 68–80, 1965.
Gath, P.: Integration und Test der GRACE Follow-On Satelliten, Tech. Rep. 420305, Deutscher Luft- und Raumfahrtkongress, 2016.
Download
Short summary
The Gravity Recovery and Climate Experiment (GRACE) mission has yielded data on the Earth's gravity field to monitor temporal changes for more than 15 years. GRACE Follow-on will be the first satellite mission to use inter-satellite laser interferometry in space to measure the distance variations between two satellites caused by the Earth's global gravitational field. This paper describes the scientific basis and technical approaches used to simulate the GRACE Follow-on instrument data.