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

Sci Data. 2021 May 27;8(1):143. doi: 10.1038/s41597-021-00925-8.

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.

Publication types

  • Dataset
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Climate Change*
  • Soil*
  • Water*

Substances

  • Soil
  • Water