To timely share the data of global soil moisture monitoring data, “A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2022)” released by the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn), has been recently updated to August 31, 2022. Based on AMSR-E/AMSR2 TB, a completely domestic independent algorithm is adopted to retrieve global surface soil moisture (SSM) on a daily scale, with accuracy equivalent to SMAP SSM products. Also, the product  features long-term and high temporal-spatial consistency, able to provide global SSM data spanning nearly two decades (July 27, 2002-August 31, 2022).  

Soil moisture is a key variable in water and energy exchange between land and atmosphere. Accurate soil moisture information plays an important role in agricultural drought monitoring, flood forecasting and early warning, and crop yield prediction. Against the backdrop of global warming, extreme weather and climate events are increasing. South China underwent several regional rainstorms in May and June, and then experienced a wide range of high-temperature heat waves from July to August. This dataset was able to timely monitor the impact of heat waves and drought events on soil moisture this summer (as indicated in the figure below). In addition, the data products of SMAP satellites were missing in June-July 2019 and early August 2022, while this dataset could provide a good supplement to the missing data products of SMAP. This global observation-driven dataset spans nearly two decades at present, and is extendable through the ongoing AMSR2 and upcoming AMSR3 missions for the use of researchers and policy decision-makers concerned, and for long-term studies of climate extremes, trends, and decadal variability.

Fig. Global SSM monthly average value anomalies in May-August, 2022

The dataset was released in early 2021 in the form of a data paper in Scientific Data (IF=8.501) by A/Prof. Lu Hui of the Department of Earth System Science, Tsinghua University (corresponding author) and Yao Panpan, assistant researcher of the Aerospace Information Research Institute, Chinese Academy of Sciences (first author) in collaboration of researchers of the Masachussetts Institute of Technology.  The paper has drawn close attention and been downloaded many times (browsed for over 10,000 times and downloaded for over 1,000 times). This research is supported by the Second Qinghai-Tibet Plateau Scientific Research as a special national project, and by the "Global Ocean-Land-Atmosphere-Ice Water Cycle Coupling Model R & D and Attribution of Extreme Hydrological Events", a project in the National Key Research and Development Program.

Article information: Yao, P.P., Lu, H., Shi, J.C., Zhao, T.J., Yang K., Cosh, M.H., Gianotti, D.J.S., & Entekhabi, D. (2021). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). Scientific Data, 8, 143 (2021).

Data information: Yao Panpan and Lu Hui. (2020). (2020). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2022), National Tibetan Plateau Data Center, DOI: 10.11888/Soil.tpdc.270960. CSTR: 18406.11.Soil.tpdc.270960.

Data link: https://data.tpdc.ac.cn/zh-hans/data/c26201fc-526c-465d-bae7-5f02fa49d738

Written by Yao Panpan and Lu Hui