Special Issue "Hydro-Climatic Trends, Variability, and Regime Shifts"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: 23 June 2022 | Viewed by 2510

Special Issue Editors

Dr. Chia-Jeng Chen
E-Mail Website
Guest Editor
Department of Civil Engineering, National Chung Hsing University, Taichung City 402, Taiwan
Interests: hydro-climatic modeling and forecasting; regional catastrophe modeling and risk assessments; integrated and interdisciplinary climate risk assessments; GIS and remote sensing applications; sustainability and environmental management
Special Issues, Collections and Topics in MDPI journals
Dr. Shaowu Bao
E-Mail Website
Guest Editor
Department of Coastal and Marine Systems Science, Coastal Carolina University Conway, Conway, SC 29528, USA
Interests: meteorology; hydrology; flooding

Special Issue Information

Dear Colleagues,

Unraveling trends and variability in hydro-climatic parameters (e.g., precipitation and temperature) are a fundamental research problem of great importance to environmental resource management, especially under the urgent circumstance of climate change. In addition to trends and variability, hydro-climatic systems are subject to regime shifts, manifested by an abrupt change from one system state to another. The regime shift could be irreversible or reversible, and occurs depending upon other state variables or physical processes. This Special Issue of Atmosphere invites diverse contributions related to better understanding such nonstationary hydro-climatic phenomena at varied spatiotemporal scales. Studies of this kind should be rooted in diagnostics of observed data with high-quality and long-term records. Using modeling approaches (statistical and/or numerical) to study the underlying mechanisms of the observed phenomena is encouraged. Other topics of interest include (1) linking the regional phenomena to large-scale, remote climate oscillations (e.g., ENSO); (2) developing new detection techniques for trends, variability, and regime shifts; (3) examining the recent extreme events or reviewing the historical “black swan” events that break hydro-climatic stationarity; (4) assessing the implication/impact of the nonstationary phenomena on weather and climate services (e.g., weather and climate forecasting) and environmental resource management; (5) discussing the relationship between the nonstationary phenomena and anthropogenic activities; and (6) projections of future changes in any of the aforementioned topics.

Dr. Chia-Jeng Chen
Dr. Shaowu Bao
Guest Editors

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Keywords

  • hydro-climate
  • hydro-meteorology
  • trends and variability
  • climate regime shifts
  • extreme events
  • teleconnections
  • climate change

Published Papers (4 papers)

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Research

Article
Climatic Trends of Variable Temperate Environment: A Complete Time Series Analysis during 1980–2020
Atmosphere 2022, 13(5), 749; https://doi.org/10.3390/atmos13050749 - 06 May 2022
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Abstract
The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley’s prestigious ecosystems and socio-economic components. The Himalayas’s local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region’s [...] Read more.
The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley’s prestigious ecosystems and socio-economic components. The Himalayas’s local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region’s hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen’s slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region’s food security and ecological sustainability. Full article
(This article belongs to the Special Issue Hydro-Climatic Trends, Variability, and Regime Shifts)
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Article
Climate Variation within the Range of Longleaf Pine Forests during the Past Century
Atmosphere 2022, 13(3), 465; https://doi.org/10.3390/atmos13030465 - 13 Mar 2022
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Abstract
Longleaf pine (Pinus palustris Mill.) forests are an important ecosystem in the southeastern United States, with high economic and ecological value. It is necessary to study the climate variation within its range in order to understand the effects of climate change on [...] Read more.
Longleaf pine (Pinus palustris Mill.) forests are an important ecosystem in the southeastern United States, with high economic and ecological value. It is necessary to study the climate variation within its range in order to understand the effects of climate change on longleaf pine forests. In this study, past climate data at three sites within the longleaf pine range were used to detect climate variation. The results indicated no dramatic change in solar radiation at the three sites. There were high variations in annual air temperature at the three sites. The trend of annual air temperature change depended on the time scale and start/end time. The annual air temperature generally increased from the 1960s at three sites. However, from 1901 to 2020, the trend of increasing annual air temperature was not consistent. The annual precipitation and the standardized precipitation-evapotranspiration index were relatively stable, with variation at the three sites. The regimes of annual and monthly air temperature and precipitation were not shifted based on the analysis of multiscale entropy. The climate niche of longleaf pine forests based on long-term climate data was broader than previously found. These results may be helpful to understand the interactions of the atmosphere and growth of longleaf pine forest and develop relevant management strategies. Full article
(This article belongs to the Special Issue Hydro-Climatic Trends, Variability, and Regime Shifts)
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Article
Meaningful Trend in Climate Time Series: A Discussion Based On Linear and Smoothing Techniques for Drought Analysis in Taiwan
Atmosphere 2022, 13(3), 444; https://doi.org/10.3390/atmos13030444 - 09 Mar 2022
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Abstract
Finding significant trends in hydroclimate time series has been deemed an essential task in numerous studies. Despite the existence of various trend detection methods, statistical significance is mostly examined for linear trends and related to the meaningfulness of the found trends. We wish [...] Read more.
Finding significant trends in hydroclimate time series has been deemed an essential task in numerous studies. Despite the existence of various trend detection methods, statistical significance is mostly examined for linear trends and related to the meaningfulness of the found trends. We wish to draw attention to a more general definition of meaningful trends by cross-referencing not only linear but also smoothing techniques. We apply linear regression (LR) and two smoothing techniques based on regularized minimal-energy tensor-product B-splines (RMTB) to the trend detection of standardized precipitation index (SPI) series over Taiwan. LR and both RMTB-based methods identify an overall upward (wetting) trend in the SPI series across the time scales in Taiwan from 1960 to 2019. However, if dividing the entire time series into the earlier (1960–1989) and later (1990–2019) sub-series, we find that some downward (drying) trends at varied time scales migrate from southcentral–southwestern to eastern regions. Among these significant trends, we have more confidence in the recent drying trend over eastern Taiwan since all the methods show trend patterns in highest similarity. We also argue that LR should be used with great caution, unless linearity in data series and independence and normality in residuals can be assured. Full article
(This article belongs to the Special Issue Hydro-Climatic Trends, Variability, and Regime Shifts)
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Article
The Spatio-Temporal Influence of Atmospheric Circulations on Monthly Precipitation in Great Britain
Atmosphere 2022, 13(3), 429; https://doi.org/10.3390/atmos13030429 - 07 Mar 2022
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Abstract
It has long been understood that the North Atlantic Oscillation (NAO) is a key driver of regional climate in Great Britain and across Europe. However, studies have also noted that there is spatio-temporal variability in NAO-rainfall signatures which arguably limits its practical inclusion [...] Read more.
It has long been understood that the North Atlantic Oscillation (NAO) is a key driver of regional climate in Great Britain and across Europe. However, studies have also noted that there is spatio-temporal variability in NAO-rainfall signatures which arguably limits its practical inclusion in water management. In this study we quantify, at high spatio-temporal resolution, the influence of a broader set of atmospheric circulations on monthly precipitation. Using Standardised Precipitation Indices for the Integrated Hydrological Unit (IHU) Groups of Great Britain we apply univariate and multivariate regression models to understand the potential of five atmospheric circulation indices to explain precipitation variability. As far as we are aware this represents the first high spatial and temporal resolution analysis quantifying the influence of a broad set of atmospheric circulations, both individually and in combination. We highlight the influence of each circulation and establish that the NAO only partially explains precipitation variability, especially in the southern regions and during the summer months, where circulations, such as the East Atlantic Pattern, also have an important influence. In summary, we suggest that there is significant explanatory value in looking beyond the NAO when seeking to understand hydroclimatological variability in Great Britain, and there is potential for future work to explore how this understanding can translate into the practical application of atmospheric circulation indices in water management. Full article
(This article belongs to the Special Issue Hydro-Climatic Trends, Variability, and Regime Shifts)
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