Decadal Change in Soil Moisture Over East Asia in Response to a Decade‐Long Warming Hiatus

Abstract

East Asia has experienced long-term warming and drying in the twentieth century.However, a phenomenon known as the "warming hiatus" changed the trend of enhanced soil drying over East Asia. In contrast to the previous long-term drying in the last century, time series of soil moisture showed a shift from a downtrend to uptrend around 2005, and prominent wetting was located in the northeast (semiarid and dry subhumid regions) and southeast of China (extreme humid regions). Our results illustrated that such abrupt change in soil moisture was closely related to the change of warming during hiatus. The warming hiatus played a more important role in decadal soil wetting over these semiarid and dry subhumid regions, compared to relatively limited influence of surface atmosphere temperature over humid regions. The weakened drying during the hiatus decade suggests that the response of wetting/drying to climate in drylands is closely related to decadal surface atmosphere temperature, which will deepen our understanding of the mechanism on the role of surface atmosphere temperature in the process of wetting/drying in drylands over different time scales.

Temporal and Spatial Variations of Soil Moisture Over Xinjiang Based on Multiple GLDAS Datasets

“…Because GLDAS datasets provide high spatiotemporal resolutions variables which makes it is an effective resource to study the water cycle based on these datasets, they have been widely used in many previous studies (Scanlon, et al, 2012;Mukheriee and Ramachandran, 2018;Kong et al, 2019;Chen and Yuan, 2020;Hoffmann et al, 2020;Niu, et al, 2020;Solander et al, 2020;Hu et al, 2021). To match the temporal (monthly) and spatial resolution (1.0 × 1.0) of the GRACE datasets, the GLDAS LSMs datasets examined in this study are those included in GLDAS V1 VIC and Mosaic with the period of 1979-present, and GLDAS V2.1 Noah V3.3 with the period of 2000-present.…”

“…Because GLDAS datasets provide hydrological variables in high spatial and temporal resolutions, they have been widely used in many previous studies in the field of hydrology (Kong et al, 2019;Chen and Yuan, 2020;Hoffmann et al, 2020;Niu, et al, 2020;Solander et al, 2020). The soil moisture from the GLDAS V1 (i.e.…”

Dominant role of Atlantic multidecadal oscillation in the tipping point of maximum and minimum temperatures over inner East Asia

“…The Aridity index (AI) represents the severity of drought, which is defined as the ratio of precipitation to potential evapotranspiration calculated in Huang et al (2020). According to the AI value, land can be classified into hyperarid (AI < 0.05), arid (0.05 ≤ AI < 0.2), semiarid (0.2 ≤ AI < 0.5), semi-humid (0.5 ≤ AI < 0.65), and humid (AI ≥ 0.65) regions (Kong et al, 2019). Figure 1 shows the multiyear dry-wet conditions based on the AI over East Asia from 1982 to 2014 and the geographical position of inner East Asia.…”