Special Issue "Simulation and Analysis of Hydroclimate"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: 29 February 2024 | Viewed by 714

Special Issue Editor

Dr. Yuna Mao
E-Mail Website
Guest Editor
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
Interests: hydrological simulation and analysis; land–atmosphere interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The simulation and analysis of global hydroclimate are crucial steps in enhancing our understanding of water availability, droughts, floods, and various hydrological phenomena that significantly impact ecosystems, agriculture, water resources, and human societies worldwide. Hydroclimate simulation entails the utilization of sophisticated mathematical models to represent the intricate interactions among the atmosphere, land surface, and oceans, which collectively drive the complex water cycle on a global scale. Some well-known hydroclimate models employed in this research include the Weather Research and Forecasting (WRF) model, the Community Earth System Model (CESM), and the Variable Infiltration Capacity (VIC) model. The continuous development and improvement of these hydroclimate models are of the utmost importance in gaining deeper insights into global hydroclimate changes and making more accurate predictions about future shifts. Conducting in-depth analyses based on observational data and the outputs from global hydroclimate models are essential steps in exploring the underlying mechanisms behind hydroclimate changes. Such comprehensive analyses help researchers and decision-makers comprehend the drivers of extreme weather events, such as hurricanes, cyclones, and heatwaves, allowing for more effective mitigation and adaptation strategies. Overall, the combined efforts of hydroclimate simulation and analysis serve as a powerful toolset in tackling the pressing challenges posed by global hydroclimate changes. By gaining a comprehensive understanding of these phenomena, we can better prepare for and respond to water-related hazards, safeguard ecosystems, optimize water resource management, and foster resilience in human communities facing the impacts of a changing hydroclimate.

Dr. Yuna Mao
Guest Editor

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  • spatio-temporal analysis
  • long-term changes
  • model simulation
  • attribution analysis
  • future prediction

Published Papers (1 paper)

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16 pages, 4676 KiB  
Significant Reduction in Precipitation Seasonality and the Association with Extreme Precipitation in the Hai River Basin of China from 1960 to 2018
Atmosphere 2023, 14(10), 1552; https://doi.org/10.3390/atmos14101552 - 11 Oct 2023
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The Hai River Basin (HRB) serves as a vital center for the population, economy and politics in northern China. Natural hazards, particularly floods, pose significant risks to the region, often attributed to extreme precipitation events. Changes in precipitation seasonalitycc play a pivotal role [...] Read more.
The Hai River Basin (HRB) serves as a vital center for the population, economy and politics in northern China. Natural hazards, particularly floods, pose significant risks to the region, often attributed to extreme precipitation events. Changes in precipitation seasonalitycc play a pivotal role in influencing precipitation extreme events. Therefore, this study presents a comprehensive analysis of precipitation seasonality and its impact on precipitation extremes in HRB. By implementing a novel relative entropy method, we calculated the precipitation seasonality indicators using daily precipitation observations from 1960 to 2018 in HRB. We found a significant decreasing trend in precipitation seasonality (−0.03 decade−1, p = 0.04), accompanied by an earlier onset date (4.0 days decade−1, p = 0.01) and longer duration (4.3 days decade−1, p = 0.03) of the wet season. Notably, these trends are notably concentrated in the Beijing-Tianjin administrative regions. Additionally, a lower precipitation seasonality value indicated a more evenly distributed precipitation throughout the year, resulting in reduced occurrences of precipitation extremes. Consistently, we observed two precipitation extremes, extreme wet day precipitation R99T and maximum 1-day precipitation RX1Day, which exhibited significant decreasing trends at the rate of −0.5 mm decade−1 (p = 0.02) and −1.4 mm decade−1 (p = 0.05), respectively. Furthermore, we detected significant positive correlations of 0.31 (p = 0.02) and 0.35 (p = 0.01) between precipitation seasonality and precipitation extremes (R95T and R99T), suggesting that a more evenly distributed precipitation across seasons corresponds to fewer precipitation extremes over the past sixty years. Metropolitan areas, in particular, experienced a noteworthy reduction in precipitation seasonality and a decreased frequency of precipitation extreme events. The findings of this study shed new light on the intricate relationship between precipitation seasonality and extreme events, further helping policy making develop effective risk regulations for agriculture, floods, and urban waterlogging, ensuring sustainable development within the HRB. Full article
(This article belongs to the Special Issue Simulation and Analysis of Hydroclimate)
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