A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002–2019)

Abstract
Long term surface soil moisture (SSM) data with stable and consistent quality are critical for global environment and climate change monitoring. L band radiometers onboard the recently launched Soil Moisture Active Passive (SMAP) Mission can provide the state-of-the-art accuracy SSM, while Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and AMSR2 series provide long term observational records of multi-frequency radiometers (C, X, and K bands). This study transfers the merits of SMAP to AMSR-E/2, and develops a global daily SSM dataset (named as NNsm) with stable and consistent quality at a 36 km resolution (2002–2019). The NNsm can reproduce the SMAP SSM accurately, with a global Root Mean Square Error (RMSE) of 0.029 m3/m3. NNsm also compares well with in situ SSM observations, and outperforms AMSR-E/2 standard SSM products from JAXA and LPRM. This global observation-driven dataset spans nearly two decades at present, and is extendable through the ongoing AMSR2 and upcoming AMSR3 missions for long-term studies of climate extremes, trends, and decadal variability.
Funding Information
  • Ministry of Science and Technology of the People's Republic of China (2019QZKK0206, 2017YFA0603703, 2019QZKK0206, 2019QZKK0206, 2019QZKK0206, 2019QZKK0206)
  • China Postdoctoral Science Foundation (2019M660609)
  • Ministry of Science and Technology of the People's Republic of China
  • Ministry of Science and Technology of the People's Republic of China
  • Ministry of Science and Technology of the People's Republic of China
  • Chinese Academy of Sciences (XDA20100103)
  • Ministry of Science and Technology of the People's Republic of China
  • Ministry of Science and Technology of the People's Republic of China