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Atmosphere
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Simulation and Analysis of Hydroclimate
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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: closed (29 February 2024) | Viewed by 3892

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

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

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Published Papers (3 papers)

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Research

15 pages, 1632 KiB  
Article
Vegetation–Topographic Landscape and the Influence of Water and Sediment in the Shule River Basin
by Jianjun Zeng and Yanqiang Cui
Atmosphere 2024, 15(4), 459; https://doi.org/10.3390/atmos15040459 - 8 Apr 2024
Viewed by 856
Abstract
The study of the effect of vegetation cover on water and sediment content is of great significance for the in-depth understanding of ecological and environmental effects in river basins and the formulation of corresponding management measures. Based on the monitoring data of rainfall [...] Read more.
The study of the effect of vegetation cover on water and sediment content is of great significance for the in-depth understanding of ecological and environmental effects in river basins and the formulation of corresponding management measures. Based on the monitoring data of rainfall and runoff of Panjiazhuang and Dangchengwan Hydrologic Stations in Shule River Basin from 2000 to 2020 and the sediment discharge of Changmabao, methods such as geographic information technology (GIS), landscape pattern analysis, land use transfer matrix, correlation analysis, principal component analysis, and linear regression analysis were used to study water and sediment change, land use pattern, vegetation change characteristics, and local water and sediment change in Shule River Basin and construct vegetation–topographic landscape factors. The main research results are as follows: (1) Vegetation coverage in the Shule River Basin increased year by year from 2000 to 2020, with a cumulative increase of 0.064 in 20 years. Vegetation cover has a significant effect on water and sediment content, and the correlation is −0.966. (2) The cultivated land area of the Shule River Basin increased by 604 km2 from 2000 to 2020, and the conversion rate was 67%. From 2000 to 2020, the water area increased by 442 km2, and the conversion rate was 51%. The area of grassland and forest increased by 198 km2 and 12 km2, respectively, and the conversion rate was 68% and 33%, respectively. Forest had the highest transfer rate (0.67). The lowest conversion rate was 0.32 for grassland. (3) The variation coefficient of water and sediment content in Shule River Basin during 1971–2020 was 45.21%, and the highest variation coefficient during 2001–2010 was 49.15%. The lowest variation coefficient was 39.73% during 2011–2020. The annual sediment transport in the Shule River Basin fluctuates greatly and has a high degree of dispersion during 1971–2020. (4) The results of the landscape index in Shule River Basin during 2000–2020 had a small difference, with a difference of less than 0.5. According to the principal component analysis of landscape index and water and sediment content, the maximum patch index (LPI) had the strongest positive correlation with water and sediment content (0.958). The diversity index SHDI had the strongest negative correlation with water and sediment content (−0.995). Full article
(This article belongs to the Special Issue Simulation and Analysis of Hydroclimate)
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17 pages, 11872 KiB  
Article
Dynamic and Thermodynamic Contributions to Late 21st Century Projected Rainfall Change in the Congo Basin: Impact of a Regional Climate Model’s Formulation
by Alain T. Tamoffo, Alessandro Dosio, Torsten Weber and Derbetini A. Vondou
Atmosphere 2023, 14(12), 1808; https://doi.org/10.3390/atmos14121808 - 9 Dec 2023
Cited by 1 | Viewed by 1329
Abstract
Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses [...] Read more.
Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses late 21st-century (2071–2100) precipitation projections for the Congo Basin under representative concentration pathway (RCP) 8.5, using the Rossby Centre Regional Climate Model (RCM) RCA4. Specifically, we examine the impact of the RCM formulation (reduction of turbulent mixing) on future change in seasonal mean precipitation by comparing the results of the modified model version (RCA4-v4) with those of the standard version (RCA4-v1) used in CORDEX (Coordinated Regional Climate Downscaling Experiment). The two RCM versions are driven by two global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). The results show that seasonal precipitation is largely affected by modifications in the atmospheric column moisture convergence or divergence, and, in turn, associated with changes in the dynamic (ΔDY) and thermodynamic (ΔTH) components of the moisture-budget equation. Projected decreased precipitation in the dry seasons (December–January–February and June–July–August) is linked to increased moisture divergence driven by dynamic effects (changes in circulation), with most experiments showing ΔDY as the main contributor (>60%) to the total moisture budget. Overall, precipitation is projected to increase in the wet seasons (March–April–May and September–October–November), which can be attributed to both dynamic and thermodynamic effects, but with a larger thermodynamic contribution (changes in specific humidity, ΔTH > 45%), compared to the dynamic one (ΔDY > 40%). Through a comparison of the two model versions, we found that the formulation (reducing turbulent mixing) and boundary conditions (driving GCM) strongly influence precipitation projections. This result holds substantial value for ensuring the fitness of models for future projections intended for decision-makers. Full article
(This article belongs to the Special Issue Simulation and Analysis of Hydroclimate)
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16 pages, 4676 KiB  
Article
Significant Reduction in Precipitation Seasonality and the Association with Extreme Precipitation in the Hai River Basin of China from 1960 to 2018
by Xin Zhang and Yuna Mao
Atmosphere 2023, 14(10), 1552; https://doi.org/10.3390/atmos14101552 - 11 Oct 2023
Cited by 1 | Viewed by 1211
Abstract
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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