Japan Geoscience Union Meeting 2023

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-HW Hydrology & Water Environment

[A-HW19] Hydrology & Water Environment

Wed. May 24, 2023 1:45 PM - 3:15 PM 105 (International Conference Hall, Makuhari Messe)

convener:Koichi Sakakibara(Department of Environmental Sciences, Faculty of Science, Shinshu University), Sho Iwagami(Forestry and Forest Products Research Institute, Forest Research and Management Organization, National Research and Development Agency), Takeshi Hayashi(Faculty of Education and Human Studies, Akita University), Keisuke Fukushi(Institute of Nature & Environmental Technology, Kanazawa University), Chairperson:Shunji Kotsuki(Center for Environmental Remote Sensing, Chiba University), Koichi Sakakibara(Department of Environmental Sciences, Faculty of Science, Shinshu University), Sho Iwagami(Forestry and Forest Products Research Institute, Forest Research and Management Organization, National Research and Development Agency), Takeshi Hayashi(Faculty of Education and Human Studies, Akita University), Keisuke Fukushi(Institute of Nature & Environmental Technology, Kanazawa University)

2:15 PM - 2:30 PM

[AHW19-13] Dry gets drier and wet gets wetter (DDWW) paradigm is subject to the choice of datasets

*Abhishek Abhishek1,2, Jinghua Xiong3, Shenglian Guo3, Jie Chen3, Jiabo Yin3 (1.Indian Institute of Science, India, 2.Tokyo Institute of Technology, Japan, 3.Wuhan University, China)

Keywords:Climate change, DDWW paradigm, Multimodal assessments

In the premise of intensifying hydrological cycle, the DDWW (Dry gets drier, and wet gets wetter) paradigm has been used to quantify the impact of climate change on various hydrometeorological variables (e.g., precipitation, evaporation) or a combination thereof. However, no one has attempted to examine the validity of this much-debated paradigm from the terrestrial water storage (TWS) change perspective. Considering the essential role of TWS in the wetting and drying of the land system, here (Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022), we built upon a large ensemble of TWS datasets, including different satellite-based products, global hydrological models, and land surface models to evaluate the DDWW hypothesis during the historical period (1985–2014) with a 0.05 significance level. We find that 11.01%–40.84% (range by various datasets) of global land confirms the DDWW paradigm, while 10.21% –35.43% of the area shows the opposite pattern. We demonstrate that different choices of data sources can reasonably influence the test results up to a four-fold difference. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWS change under climate change and highlight the need for careful inferences from the DDWW paradigm.