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

Deadline for manuscript submissions: closed (30 August 2024) | Viewed by 8618

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Special Issue Editors

Dr. Yang Yu

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Guest Editor

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: climate change; eco-hydrological modeling; evapotranspiration; drought; land degradation
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Dr. Lei Wang

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Guest Editor

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: abiotic stress tolerance; seed ecology; phytohormone signaling; seed heteromorphism; halophytles
Special Issues, Collections and Topics in MDPI journals

Dr. Cun Chang

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Guest Editor

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: LUCC; ecological remote sensing monitoring; sustainable development

Special Issue Information

Dear Colleagues,

The impacts of climate change have been widely recognized around the world, especially in arid environments. The ecosystems of arid/semi-arid areas are often vulnerable due to the extreme climatic situation and water shortage.

Arid lands are characterized by scarce water resources, a delicate ecological balance, and vulnerability to climate change impacts. This Special Issue aims to explore the various aspects of climate change and its implications for regional sustainability in arid lands worldwide. We welcome contributions that investigate the interactions between the atmosphere and the land surface, focusing on topics such as water availability, energy cycles, land cover change, and adaptation strategies.

Potential research areas for this Special Issue include, but are not limited to, the following:

Regional climate modeling and projections for arid areas;
Impacts of climate variability and change on water resources in arid regions;
Land–atmosphere interactions and feedback mechanisms in arid ecosystems;
Sustainable land management techniques and their role in climate resilience;
Climate change adaptation and mitigation strategies for arid regions;
Socio-economic implications and policy interventions for sustainable development in arid lands.

We invite researchers and experts in the field to submit their original research articles, reviews, or conceptual papers to contribute to this Special Issue. Manuscripts should adhere to the journal’s guidelines and will undergo a rigorous peer-review process.

This Special Issue aims to bring together the latest research and advancements in the understanding of the complex dynamics of arid regions, particularly in the context of climate change and environmental sustainability. It is our hope that the research presented in this Special Issue will inform policy decisions and contribute to the development of sustainable practices in these vulnerable regions.

Dr. Yang Yu
Dr. Lei Wang
Dr. Cun Chang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

climate change
regional sustainability
arid lands
saline agriculture
seed ecology
LUCC
remote sensing
sustainable management

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Published Papers (9 papers)

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Research

24 pages, 4625 KiB

Open AccessArticle

Extreme Temperature Index in China from a Statistical Perspective: Change Characteristics and Trend Analysis from 1961 to 2021

by Xulei Wang, Lifeng Wu and Huiying Liu

Atmosphere 2024, 15(11), 1398; https://doi.org/10.3390/atmos15111398 - 20 Nov 2024

Viewed by 151

Abstract

Against the backdrop of intensified global climate change, the frequency and intensity of extreme weather events in mainland China continue to rise due to its unique topography and complex climate types. In-depth research on the trends and impacts of climate extremes can help develop effective adaptation and mitigation strategies to protect the environment and enhance social resilience. In this research, temperature data from 2029 meteorological stations for the period 1961–2021 were used to study 15 extreme temperature indices and 3 extreme composite temperature indices. Linear propensity estimation and the Mann–Kendall test were applied to analyze the spatial and temporal variations in extreme temperatures in China, and Pearson’s correlation analysis was used to reveal the relationship between these indices and atmospheric circulation. The results show that in the past 60 years, the extreme temperature index in China has shown a trend of decreasing low-temperature events and increasing high-temperature events; in particular, the increase in warm nights is significantly higher than that of warm days. In terms of spatial distribution, daily maximum temperature less than the 10th percentile (TX10P) and daily minimum temperature greater than the 90th percentile (TN90P) increased significantly in the warm temperate sub-humid (WTSH) region, north subtropical humid (NSH) region, and marginal tropical humid (MTH) region, whereas frost days (FD0) and diurnal temperature range (DTR) decreased significantly. In the extreme composite temperature index, extreme temperature range (ETR) showed a downward trend, while compound heatwave (CHW) and compound heatwave and relative humidity (CHW-RH20) increased, with the latter mainly concentrated in the WTSH and NSH regions. Correlation analysis with climate oscillation shows that Arctic Oscillation (AO), Atlantic Multiannual Oscillation (AMO), and El Niño–Southern Oscillation (ENSO) are positively correlated with extremely high temperatures, whereas North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) are negatively correlated. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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14 pages, 3463 KiB

Open AccessArticle

Effects of Stumping and Meteorological Factors on Sap Flow Characteristics of Haloxylon ammodendron in Ulan Buh Desert, Northwestern China

by Yingbin Ma, Yaru Huang, Jingbo Zhang, Xuting Hao, Zhiming Xin, Jian Cui, Xue Dong, Haoyi Wang, Chunxia Han, Jinlei Zhu and Qi Lu

Atmosphere 2024, 15(11), 1286; https://doi.org/10.3390/atmos15111286 - 27 Oct 2024

Viewed by 511

Abstract

The shrub/dwarf tree Haloxylon ammodendron is a prevalent woody plant used to combat desertification in the arid and semi-arid regions of northwestern China. Despite its drought resistance, artificial stands of this species experience significant degradation approximately ten years post-afforestation. Stumping, which involves cutting a portion of the above-ground part of shrubs/trees, is a common practice aimed at reducing water consumption and enhancing the growth of these stands. However, the impact of stumping on the sap flow of H. ammodendron remain inadequately understood, posing challenges to the sustainable management of these artificial stands. In this study, we monitored the sap flow of H. ammodendron subjected to various stumping treatments in the Ulan Buh Desert using the PS-TDP8 tree sap flow monitoring system. Concurrently, we measured several meteorological factors with an automatic weather station. We examined the changes in sap flow velocity following stumping and its response to meteorological factors to elucidate water use during growth. Our findings indicate that both the change in sap flow velocity and characteristics were closely associated with the degree of stumping. The initiation time of sap flow for H. ammodendron under different stumping treatments was earlier than that of the control group. The daily mean value and daily accumulation of sap flow followed the order: 50% stumping > control (no stumping) > 75% stumping > 100% stumping. Sap flow velocity and daily sap flow accumulation increased at 50% stumping but decreased at 75% and 100% stumping. Stumping altered the relationships between sap flow velocity and meteorological factors, with the correlation coefficient between these variables decreasing as the degree of stumping increased. The sap flow following stumping was primarily influenced by both the degree of stumping and meteorological factors. These results may contribute to a better understanding of water transport during the growth of H. ammodendron following stumping. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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20 pages, 4809 KiB

Open AccessArticle

Spatial and Temporal Patterns of Rainfall Erosivity in Southern Africa in Extreme Wet and Dry Years

by Jasper Knight and Mohamed A. M. Abd Elbasit

Atmosphere 2024, 15(11), 1283; https://doi.org/10.3390/atmos15111283 - 26 Oct 2024

Viewed by 661

Abstract

Soil erosivity is a key indicator of the effectiveness of precipitation acting on the land’s surface and is mainly controlled by event-scale and seasonal weather and climatic factors but is also influenced by the nature of the land’s surface, including relief and vegetation cover. The aim of this study is to examine spatial and temporal variations in soil erosivity across southern Africa using rainfall data for the period 2000–2023 and a gridded raster spatial modelling approach. The two wettest and driest years in the record (±>1.5 standard deviation of rainfall values) were identified, which were 2000 and 2006, and 2003 and 2019, respectively. Monthly rainfall values in these extreme wet/dry years were then analyzed for four rainfall regions (arid, semiarid, subhumid, humid), identified according to their annual rainfall totals. These data were then used to calculate Precipitation Concentration Index (PCI) values as an expression of rainfall seasonality, and the modified Fournier index (MFI) was used to quantify rainfall erosivity. The results show that there are significant differences in erosivity between the different climate regions based on rainfall seasonality and also their distinctive environmental settings. In turn, these reflect the synoptic climatic conditions in these regions, their different precipitation sources, and rainfall totals. The results of this study show that calculated MFI values at the national scale, which is the approach taken in most previous studies, cannot effectively describe or account for erosivity values that characterize different climatic regions at the sub-national scale. Furthermore, the mismatch between PCI and MFI spatial patterns across the region highlights that, under semiarid, and highly seasonal rainfall regimes, episodic rainfall events interspersed with periods of dryness result in significant variability in erosivity values that are unaccounted for by rainfall totals or seasonality alone. In these environments, flash floods and wind erosion result in regional-scale soil erosion and land degradation, but these processes and outcomes are not clear when considering MFI values alone. Fully evaluating spatial and temporal patterns of erosivity in their climatic and environmental contexts, as developed in this study, has implications for sediment and carbon exports, as well as identifying the major regions in which land degradation is an environmental and agricultural issue. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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22 pages, 2427 KiB

Open AccessArticle

Assessing Spatio-Temporal Hydrological Impacts of Climate Change in the Siliana Watershed, Northwestern Tunisia

by Imen El Ghoul, Haykel Sellami, Slaheddine Khlifi and Marnik Vanclooster

Atmosphere 2024, 15(10), 1209; https://doi.org/10.3390/atmos15101209 - 10 Oct 2024

Viewed by 524

Abstract

Climate change is one of the most critical factors impacting hydrological dynamic systems. This study investigated how climate change influences the hydrological dynamics within the Siliana watershed in northwestern Tunisia, employing the Soil and Water Assessment Tool (SWAT) model. The analysis compared streamflow patterns for the future period (2046–2072) with a baseline period (1979–2005). Simulations were carried out using four combinations of regional and global climate models from EURO-CORDEX, based on two Representative Concentration Pathways (RCP4.5 and RCP8.5). The results indicate a projected annual precipitation decrease of 22% with RCP4.5 and 27% with RCP8.5, accompanied by a temperature rise of up to 7 °C under RCP8.5. Streamflow is anticipated to decrease by 44% under RCP4.5 and 69% under RCP8.5. Extreme events show intensified high flows of shorter durations and increased low flows. Analysis using the Standardized Precipitation Evapotranspiration Index (SPEI) revealed longer and more intense droughts. Under the RCP8.5 scenario, 24% of the watershed faces extreme drought, while 76% experiences severe drought conditions. These findings highlight notable changes in hydrological indicators, emphasizing the urgent need for adaptive strategies in water resource management within the Siliana Basin to mitigate the effects of climate change. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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39 pages, 6368 KiB

Open AccessFeature PaperArticle

Calibration for Improving the Medium-Range Soil Forecast over Central Tibet: Effects of Objective Metrics’ Diversity

by Yakai Guo, Changliang Shao, Guanjun Niu, Dongmei Xu, Yong Gao and Baojun Yuan

Atmosphere 2024, 15(9), 1107; https://doi.org/10.3390/atmos15091107 - 11 Sep 2024

Viewed by 464

Abstract

The high spatial complexities of soil temperature modeling over semiarid land have challenged the calibration–forecast framework, whose composited objective lacks comprehensive evaluation. Therefore, this study, based on the Noah land surface model and its full parameter table, utilizes two global searching algorithms and eight kinds of objectives with dimensional-varied metrics, combined with dense site soil moisture and temperature observations of central Tibet, to explore different metrics’ performances on the spatial heterogeneity and uncertainty of regional land surface parameters, calibration efficiency and effectiveness, and spatiotemporal complexities in surface forecasting. Results have shown that metrics’ diversity has shown greater influence on the calibration—predication framework than the global searching algorithm’s differences. The enhanced multi-objective metric (EMO) and the enhanced Kling–Gupta efficiency (EKGE) have their own advantages and disadvantages in simulations and parameters, respectively. In particular, the EMO composited with the four metrics of correlated coefficient, root mean square error, mean absolute error, and Nash–Sutcliffe efficiency has shown relatively balanced performance in surface soil temperature forecasting when compared to other metrics. In addition, the calibration–forecast framework that benefited from the EMO could greatly reduce the spatial complexities in surface soil modeling of semiarid land. In general, these findings could enhance the knowledge of metrics’ advantages in solving the complexities of the LSM’s parameters and simulations and promote the application of the calibration–forecast framework, thereby potentially improving regional surface forecasting over semiarid regions. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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26 pages, 29445 KiB

Open AccessArticle

Weather Research and Forecasting Model (WRF) Sensitivity to Choice of Parameterization Options over Ethiopia

by Andualem Shiferaw, Tsegaye Tadesse, Clinton Rowe and Robert Oglesby

Atmosphere 2024, 15(8), 974; https://doi.org/10.3390/atmos15080974 - 14 Aug 2024

Viewed by 1142

Abstract

Downscaling seasonal climate forecasts using regional climate models (RCMs) became an emerging area during the last decade owing to RCMs’ more comprehensive representation of the important physical processes at a finer resolution. However, it is crucial to test RCMs for the most appropriate model setup for a particular purpose over a given region through numerical experiments. Thus, this sensitivity study was aimed at identifying an optimum configuration in the Weather, Research, and Forecasting (WRF) model over Ethiopia. A total of 35 WRF simulations with different combinations of parameterization schemes for cumulus (CU), planetary boundary layer (PBL), cloud microphysics (MP), longwave (LW), and shortwave (SW) radiation were tested during the summer (June to August, JJA) season of 2002. The WRF simulations used a two-domain configuration with a 12 km nested domain covering Ethiopia. The initial and boundary forcing data for WRF were from the Climate Forecast System Reanalysis (CFSR). The simulations were compared with station and gridded observations to evaluate their ability to reproduce different aspects of JJA rainfall. An objective ranking method using an aggregate score of several statistics was used to select the best-performing model configuration. The JJA rainfall was found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All the simulations captured the spatial distribution of JJA rainfall with the pattern correlation coefficient (PCC) ranging from 0.89 to 0.94. However, all the simulations overestimated the JJA rainfall amount and the number of rainy days. Out of the 35 simulations, one that used the Grell CU, ACM2 PBL, LIN MP, RRTM LW, and Dudhia SW schemes performed the best in reproducing the amount and spatio-temporal distribution of JJA rainfall and was selected for downscaling the CFSv2 operational forecast. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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23 pages, 35497 KiB

Open AccessArticle

Projected Increase in Heatwaves under 1.5 and 2.0 °C Warming Levels Will Increase the Socio-Economic Exposure across China by the Late 21st Century

by Jinping Liu, Antao Wang, Tongchang Zhang, Pan Pan and Yanqun Ren

Atmosphere 2024, 15(8), 900; https://doi.org/10.3390/atmos15080900 - 28 Jul 2024

Viewed by 883

Abstract

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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32 pages, 5530 KiB

Open AccessArticle

Calibration for Improving the Medium-Range Soil Temperature Forecast of a Semiarid Region over Tibet: A Case Study

by Yakai Guo, Baojun Yuan, Aifang Su, Changliang Shao and Yong Gao

Atmosphere 2024, 15(5), 591; https://doi.org/10.3390/atmos15050591 - 13 May 2024

Cited by 2 | Viewed by 1049

Abstract

The high complexity of the parameter–simulation problem in land surface models over semiarid areas makes it difficult to reasonably estimate the surface simulation conditions that are important for both weather and climate in different regions. In this study, using the dense site datasets of a typical semiarid region over Tibet and the Noah land surface model with the constrained land parameters of multiple sites, an enhanced Kling–Gupta efficiency criterion comprising multiple objectives, including variable and layer dimensions, was obtained, which was then applied to calibration schemes based on two global search algorithms (particle swarm optimization and shuffled complex evaluation) to investigate the site-scale spatial complexities in soil temperature simulations. The calibrations were then compared and further validated. The results show that the Noah land surface model obtained reasonable simulations of soil moisture against the observations with fine consistency, but the negative fit and huge spatial errors compared with the observations indicated its weak ability to simulate the soil temperature over regional semiarid land. Both calibration schemes significantly improved the soil moisture and temperature simulations, but particle swarm optimization generally converged to a better objective than shuffled complex evaluation, although with more parameter uncertainties and less heterogeneity. Moreover, simulations initialized with the optimal parameter tables for the calibrations obtained similarly sustainable improvements for soil moisture and temperature, as well as good consistency with the existing soil reanalysis. In particular, the soil temperature simulation errors for particle swarm optimization were unbiased, while those for the other method were found to be biased around −3 K. Overall, particle swarm optimization was preferable when conducting soil temperature simulations, and it may help mitigate the efforts in surface forecast improvement over semiarid regions. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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21 pages, 3952 KiB

Open AccessArticle

Water Resources Evaluation in Arid Areas Based on Agricultural Water Footprint—A Case Study on the Edge of the Taklimakan Desert

by Lingyun Zhang, Yang Yu, Ireneusz Malik, Malgorzata Wistuba, Lingxiao Sun, Meiling Yang, Qian Wang and Ruide Yu

Atmosphere 2023, 14(1), 67; https://doi.org/10.3390/atmos14010067 - 29 Dec 2022

Cited by 6 | Viewed by 2028

Abstract

Water scarcity is an important factor limiting agricultural development in arid areas. Clarifying and evaluating the current situation of water resources in arid regions is helpful for decision-makers in the rational use of water resources. This study takes a typical arid region located at the edge of Taklamakan Desert-Hotan region as the study area. The water footprint (WF) of the Hotan region was calculated based on 20 years of data information from 2000–2019. An evaluation system was established using four aspects of the WF: structural indicators, efficiency indicators, ecological safety indicators, and sustainability indicators. The results show that the WF of the study area is mainly dominated by blue water consumption, with a proportion of 65.74%. The WF of crop production is larger than that of livestock production. The produced WF of grain crops is the highest of all products with a share of 44.21%. The increase in the local agricultural WF reached 53.18% from 2000 to 2019, but it was still lower than the amount of water available for agriculture. The evaluation results indicated that the region’s WF import dependency is lower than the global level, with an annual average self-sufficiency rate of 91.13% and an increase of 878.95% in the WF economic efficiency index. The agricultural WF produced in Hotan is exported in the form of trade, but the quantitative contribution is small and does little to relieve water stress in other regions. The agricultural water consumption was still within the range of local water resources that could be carried but only 6 years of sustainable water use, and the future development was not optimistic. With the ratio of produced WF to available water resources maintained at about 58%, the local available water resources should be above 43.21 × 10⁸ m³ to initially ensure the sustainable use of water resources. There were 12 drought years in the study period, which are prone to droughts and high disaster levels. The drought-water scarcity systems behaved in three phases: 2000–2011 (uncoordinated level), 2012–2015 (transitional phase), and 2016–2019 (coordinated level). Water scarcity threatened by drought reduced. The occurrence of meteorological droughts was more related to natural factors while the changes in WF were mainly driven by socio-economic elements such as human activities. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands)

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