Required sampling density of ground-based soil moisture and brightness temperature observations for calibration and validation of L-band satellite observations based on a virtual reality

Lv, Shaoning; Schalge, Bernd; Saavedra Garfias, Pablo; Simmer, Clemens

doi:https://doi.org/10.5194/hess-24-1957-2020

Articles | Volume 24, issue 4

https://doi.org/10.5194/hess-24-1957-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-1957-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 4

Research article

|

17 Apr 2020

Research article |

| 17 Apr 2020

Required sampling density of ground-based soil moisture and brightness temperature observations for calibration and validation of L-band satellite observations based on a virtual reality

Shaoning Lv, Bernd Schalge, Pablo Saavedra Garfias, and Clemens Simmer

Data sets

Virtual catchment simulation based on the Neckar region version 1 B. Schalge, G. Baroni, B. Haese, D. Erdal, G. Geppert, P. Saavedra, V. Haefliger, H. Vereecken, S. Attinger, H. Kunstmann, O. A. Cirpka, F. Ament, S. Kollet, I. Neuweiler, H.-J. Hendricks Franssen, and C. Simmer https://doi.org/10.26050/WDCC/Neckar_VCS_v1

Short summary

Passive remote sensing of soil moisture has good potential to improve weather forecasting via data assimilation in theory. We use the virtual reality data set (VR01) to infer the impact of sampling density on soil moisture ground cal/val activity. It shows how the sampling error is growing with an increasing sampling distance for a SMOS–SMAP scale footprint in about 40 km, 9 km, and 3 km. The conclusion will help in understanding the passive remote sensing soil moisture products.