Published July 9, 2020 | Version v2
Dataset Open

Long-Term Global Satellite Soil Moisture from Maximized Temporal Correlations (1998-2015)

Creators

  • 1. Nanjing University of Information Science and Technology
  • 2. University of New South Wales
  • 3. National Climate Center, China Meteorological Administration

Description

A long-term merged satellite soil moisture product spanning 1998 to 2015. An existing combination approach that maximizes temporal correlations is used to combine six passive microwave satellite soil moisture products within the period. These include the Special Sensor Microwave Imagers (SSM/I), the Tropical Rainfall Measuring Mission (TRMM/TMI), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) sensor on the National Aeronautics and Space Administration’s (NASA) Aqua satellite, the WindSAT radiometer, onboard the Coriolis satellite and the soil moisture retrievals from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission on Water (GCOM-W). The sixth is the microwave radiometer imager (MWRI) onboard China’s Fengyun-3B (FY3B) satellite, which is being used for the first time in a merging scheme. 

For more details on the quality of the data and the methodology used, please refer to the references listed:

Hagan, D.F.T.; Wang, G.; Kim, S.; Parinussa, R.M.; Liu, Y.; Ullah, W.; Bhatti, A.S.; Ma, X.; Jiang, T.; Su, B. Maximizing Temporal Correlations in Long-Term Global Satellite Soil Moisture Data-Merging. Remote Sens. 2020, 12, 2164.

Kim, S.; Parinussa, R.M.; Liu, Y.Y.; Johnson, F.M.; Sharma, A. A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation. Geophys. Res. Lett. 2015, 42, 6662–6670.

Notes

This research was funded by the National Key Research and Development Program of China, Grant Number 2017YFA0603701; the National Natural Science Foundation of China Grant Numbers, 41875094 and 41850410492; and the Sino-German Cooperation Group Project (GZ1447).

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Additional details

Related works

Is documented by
Journal article: 10.3390/rs12132164 (DOI)

References

  • Hagan, D.F.T.; Wang, G.; Kim, S.; Parinussa, R.M.; Liu, Y.; Ullah, W.; Bhatti, A.S.; Ma, X.; Jiang, T.; Su, B. Maximizing Temporal Correlations in Long-Term Global Satellite Soil Moisture Data-Merging. Remote Sens. 2020, 12, 2164.
  • Kim, S.; Parinussa, R.M.; Liu, Y.Y.; Johnson, F.M.; Sharma, A. A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation. Geophys. Res. Lett. 2015, 42, 6662–6670.