Global land moisture trends: drier in dry and wetter in wet over land

Abstract

The “dry gets drier, wet gets wetter” (DGDWGW) paradigm is widely accepted in global moisture change. However, Greve et al.1 have declared that this paradigm has been overestimated. This controversy leaves a large gap in the understanding of the evolution of water-related processes. Here, we examine the global moisture trends using satellite soil moisture for the past 35 years (1979–2013). Our results support those of Greve et al., although there are quantitative differences. Generally, approximately 30% of global land has experienced robust moisture trends (22.16% have become drier, and 7.14% have become wetter). Only 15.12% of the land areas have followed the DGDWGW paradigm, whereas 7.77% have experienced the opposite trend. A new finding is that there is a significant “drier in dry, wetter in wet” (DIDWIW) trend paradigm; 52.69% of the drying trend occurred in arid regions, and 48.34% of the wetter trend occurred in the humid regions. Overall, 51.63% of the trends followed the DIDWIW paradigm, and 26.93% followed the opposite trend. We also identified the DGDWGW and DIDWIW paradigms in low precipitation-induced arid regions in which the dry soil led to an increasing sensible heat flux and temperature and subsequently potential evapotranspiration.

Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees

“…Figure 7 shows the spatial distribution of monthly downscaled and GLDAS soil moisture from May to September in 2015. The spatial distributions of both soil moisture data by land cover are consistent with the literature [95,96]. Both soil moisture products show relatively high soil moisture levels in forest regions (i.e., southern China, Korea Peninsula, and Japan), while presenting dry soil in desert and built up regions (i.e., Shandong, Gobi Desert).…”

Consistency and Discrepancy of Global Surface Soil Moisture Changes From Multiple Model‐Based Data Sets Against Satellite Observations

“…Regional studies, such as those in China, India, and North America, indicated that ECV outperforms other soil moisture data sets (An et al, ; Chakravorty et al, ; Jia et al, ; Nicolai‐Shaw et al, ; Qiu et al, ; Zeng et al, ). In recent studies, ECV soil moisture has been widely accepted and used as reliable soil moisture observations for estimating long‐term changes of hydrological cycle in different regions (e.g., Chen et al, ; Feng, ; Feng & Zhang, ; Zohaib et al, ). Therefore, given the lack of a global‐scale high‐density network of in situ soil moisture measurements, as well as the large inconsistency of specifications of the existing in situ measurements (e.g., measurement methods, installation modes, and depths), this study employs ECV soil moisture as a reference to evaluate model‐based soil moisture data sets generated by different types of models (Dorigo et al, ).…”

Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia

“…Moreover, the influencing factors such as P and T skin have different effects on the trend of RZSM in each climate region. Specifically, in the tropical climate regions, the trend of RZSM is increasing along with increasing trends of P , T skin , and AET, substantiating the intensified hydrological cycle and the paradigm “warmer gets wetter” [ Taylor , ; Feng and Zhang , ]. Interestingly, in arid climate regions, RZSM trend decreases despite increasing P .…”

“…To obtain long‐term SM observations from the space, a first attempt to merge SM products from different active and passive microwave satellites was introduce by Liu et al [, ], under the European Space Agency (ESA) Program on Global Monitoring of essential climate variable (ECV). Many studies have utilized the ESA's Climate Change Initiative (CCI) SM for analyzing the SM trend [ Dorigo et al , ; Feng and Zhang , ; Qiu et al , ; Chen et al , ]. Recently, Feng [] utilized the ESA CCI SM to analyze the isolated effect of climate and vegetation change across different spatial scales.…”