On agricultural drought monitoring in Australia using Himawari-8 geostationary thermal infrared observations

• Published in: International journal of applied earth observation and geoinformation 2020-09, Vol.91, p.102153, Article 102153
• Main Authors: Hu, Tian, van Dijk, Albert I.J.M., Renzullo, Luigi J., Xu, Zhihong, He, Jie, Tian, Siyuan, Zhou, Jun, Li, Hua
• Format: Article
• Language: English
• Subjects: Agricultural drought; Australia; case studies; drought; energy; evapotranspiration; evolution; food security; Himawari-8; lead; meteorology; soil water; spatial data; surface temperature; Thermal infrared; time series analysis; TRI; vegetation; water stress; wheat
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2020.102153

•Temperature Rise Index performs the best among the LST-based drought indices in comparison.•Temperature Rise Indices obtained from LST retrievals and brightness temperatures have similar performances.•Temperature Rise Index has the strongest peak correlation with wheat yield. Monitoring agricultural drought effectively and timely is important to support drought management and food security. Effective drought monitoring requires a suite of drought indices to capture the evolution process of drought. Thermal infrared signals respond rapidly to vegetation water stress, thus being regarded useful for drought monitoring at the early stage. Several temperature-based drought indices have been developed considering the role of land surface temperature (LST) in surface energy and water balance. Here, we compared the recently proposed Temperature Rise Index (TRI) with several agricultural drought indices that also use thermal infrared observations, including Temperature Condition Index (TCI), Vegetation Health Index (VHI) and satellite-derived evapotranspiration ratio anomaly (ΔfRET) for a better understanding of these thermal infrared drought indices. To do so, we developed a new method for calculating TRI directly from the top-of-atmosphere brightness temperatures in the two split-window channels (centered around ∼11 and 12 μm) rather than from LST. TRI calculated using the Himawari-8 brightness temperatures (TRI_BT) and LST retrievals (TRI_LST), along with the other LST-based indices, were calculated for the growing season (July–October) of 2015−2019 over the Australian wheatbelt. An evaluation was conducted by spatiotemporally comparing the indices with the drought indices used by the Australian Bureau of Meteorology in the official drought reports: the Precipitation Condition Index (PCI) and the Soil Moisture Condition Index (SMCI). All the LST-based drought indices captured the wet conditions in 2016 and dry conditions in 2019 clearly. Ranking of Pearson correlations of the LST-based indices with regards to PCI and SMCI produced very similar results. TRI_BT and TRI_LST showed the best agreement with PCI and SMCI (r > 0.4). TCI and VHI presented lower consistency with PCI and SMCI compared with TRI_BT and TRI_LST. ΔfRET had weaker correlations than the other LST-based indices in this case study, possibly because of outliers affecting the scaling procedure. The capability of drought early warning for TRI was demonstrated by comparing with the monthly time serie