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Behzadi F, Javadi S, Yousefi H, Hashemy Shahdany SM, Moridi A, Neshat A, Golmohammadi G, Maghsoudi R. Projections of meteorological drought severity-duration variations based on CMIP6. Sci Rep 2024; 14:5027. [PMID: 38424157 DOI: 10.1038/s41598-024-55340-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 02/22/2024] [Indexed: 03/02/2024] Open
Abstract
This research utilized the outputs from three models of the Coupled Model Intercomparison Project Phase 6 (CMIP6), specifically CanESM5, GFDL-ESM4, and IPSL-CM6A-LR. These models were used under the SSP1-2.6 and SSP5-8.5 scenarios, along with the SPI and SPEI, to assess the impacts of climate change on drought in Iran. The results indicated that the average annual precipitation will increase under some scenarios and decrease under others in the near future (2022-2050). In the distant future (2051-2100), the average annual precipitation will increase in all states by 8-115 mm. The average minimum and maximum temperature will increase by up to 4.85 ℃ and 4.9 ℃, respectively in all states except for G2S1. The results suggest that severe droughts are anticipated across Iran, with Cluster 5 expected to experience the longest and most severe drought, lasting 6 years with a severity index of 85 according to the SPI index. Climate change is projected to amplify drought severity, particularly in central and eastern Iran. The SPEI analysis confirms that drought conditions will worsen in the future, with southeastern Iran projected to face the most severe drought lasting 20 years. Climate change is expected to extend drought durations and increase severity, posing significant challenges to water management in Iran.
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Affiliation(s)
- Farhad Behzadi
- Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Tehran, Iran
| | - Saman Javadi
- Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Tehran, Iran.
| | - Hossein Yousefi
- Department of Water and Environmental Engineering, Faculty of Civil, Shahid Beheshti University, Tehran, Iran
| | - S Mehdy Hashemy Shahdany
- Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Tehran, Iran
| | - Ali Moridi
- Department of Water and Environmental Engineering, Faculty of Civil, Shahid Beheshti University, Tehran, Iran
| | - Aminreza Neshat
- Department of GIS/RS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.
| | - Golmar Golmohammadi
- Department of Soil, Water and Ecosystem Sciences, Ranch Cattle REC, University of Florida, Gainesville, USA
| | - Rahimeh Maghsoudi
- Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Tehran, Iran
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Sun P, Zou Y, Yao R, Ma Z, Bian Y, Ge C, Lv Y. Compound and successive events of extreme precipitation and extreme runoff under heatwaves based on CMIP6 models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 878:162980. [PMID: 36963693 DOI: 10.1016/j.scitotenv.2023.162980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/22/2023] [Accepted: 03/17/2023] [Indexed: 05/13/2023]
Abstract
Global warming accelerates the rate of interregional hydrological cycles, thus leading to a significant increase in the frequency and intensity of global extreme events. An extreme event that causes other extreme events within a short period of time is a successive event. Compound and successive extreme events are more harmful than single extreme events. Therefore, this study revealed the evolution characteristics of compound heatwave and extreme precipitation/runoff events (CHP/CHR), successive heatwave and extreme precipitation/runoff events (SHP/SHR). The population exposure of the four compound events was assessed in the future. The results are as follows: (1) the frequencies of CHP, CHR, SHP, and SHR have all shown a significant upward trend since the Industrial Revolution, especially at low and high latitudes. Under the future SSP585 scenario, CHP and CHR had the largest change rates from 2065 to 2099 at 2.01 events/decade and 1.86 events/decade, respectively. (2) The proportion of severe and extreme events increased significantly in various regions from 1970 to 2014. SHP and SHR have the largest proportion of severe/extreme events in 2015-2039/2065-2099. (3) The CHP and CHR changes in the historical period mainly occurred at high latitudes, while SHP and SHR had the largest change rates in low latitudes. The temperature was dominant compound and successive events in the future. The intensity of the compound event was much larger than that of its corresponding successive event under the high-emission scenario. (4) Climate effect had the most obvious impact on the change of population exposure. Compared with the SSP126 scenario, the population exposure change of the compound event increased by 3.1 times and 3.2 times under the SSP585 scenario during 2065-2099 and 2015-2039, respectively.
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Affiliation(s)
- Peng Sun
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
| | - Yifan Zou
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
| | - Rui Yao
- School of Geography, Nanjing Normal University, Nanjing 210023, China.
| | - Zice Ma
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
| | - Yaojin Bian
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
| | - Chenhao Ge
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
| | - Yinfeng Lv
- School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China.
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Das J, Das S, Umamahesh NV. Population exposure to drought severities under shared socioeconomic pathways scenarios in India. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161566. [PMID: 36642272 DOI: 10.1016/j.scitotenv.2023.161566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/22/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
As a widespread natural hazard, droughts impact several aspects of human society adversely. Thus, the present study aims to answer the following research questions; (i) What are the expected variabilities in different drought conditions over India in the future? (ii) How the population exposure to drought varies under different climate change and population scenarios? (iii) How is the total exposure attributed to the individual exposure (climate, population, and interaction) in future climate change scenarios? In this sense, the study is performed under four Shared Socioeconomic Pathways scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) using thirteen Global Climate Models from Coupled Model Intercomparison Project Phase 6 and Standardized Precipitation Evapotranspiration Index as a drought indicator. The future period is divided into two parts i.e., 2023-2061 (T1) and 2062-2100 (T2), and compared with the historical period during 1967-2005. The results show that the severe (56 % to 72 % of the area) and extreme (99 % of the area) droughts are likely to increase under all the scenarios for 3-month scale conditions, respectively. The drought intensity is projected to increase under 3-and 12-month scale drought conditions. The population exposure to the extreme drought severity is anticipated to increase for both the drought conditions and the highest exposure is noticed under the SSP3-7.0 scenario. The significant contribution from climate or interaction effects is observed in the case of 3- and 9-month scale extreme drought conditions. The present study necessitates a call for effective measures to alleviate the risk, especially in the high-risk areas of India.
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Affiliation(s)
- Jew Das
- National Institute of Technology Warangal, India.
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Nguyen TTH, Li MH, Vu TM, Chen PY. Multiple drought indices and their teleconnections with ENSO in various spatiotemporal scales over the Mekong River Basin. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158589. [PMID: 36087676 DOI: 10.1016/j.scitotenv.2022.158589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/03/2022] [Accepted: 09/03/2022] [Indexed: 06/15/2023]
Abstract
Drought may lead to severe and diverse impacts on agriculture, economy, and society across different regions and periods, posing predictive and adaptive challenges. In recent years, severe droughts have affected >60 million people in the Mekong River Basin (MRB). Additionally, El Niño Southern Oscillation (ENSO) episodes had distinct influences on the occurrence and intensity of drought variability in the regions. Understanding the spatiotemporal characteristics of droughts across the MRB is critical to improving management and mitigation actions. This study aims to investigate spatiotemporal drought characteristics in the MRB and their teleconnection with the ENSO. Three multiple drought indices, including the Standardized Precipitation Index (SPI) for meteorological drought, Standardized Soil Water Index (SSWI) for agricultural drought, and Standardized Runoff Index (SRI) for hydrological drought were calculated to quantify drought events, drought frequency, and drought severity. The overall patterns showed more events and larger intensity were identified by the SPI than those by the SRI or the SSWI, while the higher frequency was observed by the SRI. The Middle Mekong basins seem to experience more drought events, while higher levels of frequency and intensity of droughts were observed in the Upper Mekong Basin. The correlation analysis between ENSO index and precipitation suggested that the strongest ENSO events in Dec-Jan-Feb may result in developments of meteorological drought in Mar-Apr-May, and further led to hydrological and agricultural drought in Apr-May-Jun. Such ENSO effects had significant influences on drought variabilities in southern MRB and were insignificant in the north. The multiple drought indices show skills in identifying spatial and temporal drought characteristics from meteorological, agricultural, and hydrological perspectives, and potential for drought outlook further considering their ENSO teleconnections. The results can be applied to the development of drought monitoring methods and adaptive strategies to mitigate drought impacts through scientific and quantitative assessments.
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Affiliation(s)
- Thi-Thu-Ha Nguyen
- Graduate Institute of Hydrological and Oceanic Sciences, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan City 32001, Taiwan.
| | - Ming-Hsu Li
- Graduate Institute of Hydrological and Oceanic Sciences, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan City 32001, Taiwan.
| | - Tue Minh Vu
- Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29631, USA.
| | - Pei-Yuan Chen
- Graduate Institute of Hydrological and Oceanic Sciences, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan City 32001, Taiwan.
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Xie C, Tian E, Jim CY, Liu D, Hu Z. Effects of climate-change scenarios on the distribution patterns of Castanea henryi. Ecol Evol 2022; 12:e9597. [PMID: 36514555 PMCID: PMC9731913 DOI: 10.1002/ece3.9597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/09/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
Castanea henryi, with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate-change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate-change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi, assisted by a proposed three-domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor-made strategies.
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Affiliation(s)
- Chunping Xie
- College of ScienceQiongtai Normal UniversityHaikouChina
| | - Erlin Tian
- College of ScienceQiongtai Normal UniversityHaikouChina
| | - Chi Yung Jim
- Department of Social SciencesEducation University of Hong KongTai PoHong KongChina
| | - Dawei Liu
- Nanjing Forest Police CollegeNanjingChina
| | - Zhaokai Hu
- Guangdong Ocean UniversityZhanjiangChina
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Impact of Climate and Land-Use Change on Groundwater Resources, Study of Faisalabad District, Pakistan. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071097] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Groundwater depletion has become a major concern all over the world. Recently, the rapid population growth and need for water and food have placed a massive strain on land and water resources. In this study, groundwater depletion resulting from land-use and climate change was investigated in the Faisalabad district, Pakistan, from 2000 to 2015. A Pearson correlation analysis between climatic parameters and land-use indices with groundwater was conducted to explore the major influencing factors. Interpolation maps of groundwater were generated using the inverse distance weighting interpolation (IDW) method. The Normalized Difference Built-up Index (NDBI) of five-year intervals demonstrated a strong increasing trend, whereas the Normalized Difference Vegetation Index (NDVI) presented a declining trend. The results also indicated a significant declining trend in groundwater levels in the region, with the annual average groundwater level decreasing at a rate of approximately 0.11 m/year. Climatic parameters (i.e., precipitation and temperature) further reveal an insignificant increasing trend estimated using the Mann–Kendall test and Sens’s slope. Overall, spatial analysis results showed a statistically significant positive trend in the groundwater level of the Faisalabad district, where the NDBI ratio is high and the NDVI is low, owing to the extensive extraction of groundwater for domestic and industrial use. These findings may be useful for a better understanding of groundwater depletion in densely populated areas and could also aid in devising safety procedures for sustainable groundwater management.
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Cropland Exposed to Drought Is Overestimated without Considering the CO2 Effect in the Arid Climatic Region of China. LAND 2022. [DOI: 10.3390/land11060881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Drought seriously restricts people’s lives and social–economic development. An accurate understanding of the evolution of drought characteristics and future changes in cultivated land exposure can reduce the risk of drought. There is evidence that increased CO2 concentrations alter the physiological properties of vegetation and, thus, affect drought evolution. In this study, both changes and differences in drought (i.e., characteristics and cropland exposure) with and without the CO2 effect over the arid region of China are investigated, using seven CMIP6 outputs and land-use under seven shared-socioeconomic-pathway (SSP)-based scenarios. The results show that: (1) drier conditions will be more severe in 2015–2100 under SSP5-8.5, especially if the CO2 effect is neglected. Moreover, the CO2 effect will increase with increasing emission concentrations; (2) drought intensity will be greater than in the baseline period (1995–2014, approximately −1.45) but weaker than that without the CO2 effect under all scenarios; (3) drought frequency will decrease, and will generally decline faster if the CO2 effect is not considered; (4) drought duration will increase and the difference between the presence and absence of the CO2 effect will always be smallest under SSP1-1.9 and largest under SSP5-8.5; (5) drought acreage will also increase, and neglecting the CO2 effect is always higher than that considering CO2. The difference between the two algorithms will increase with time; and (6) cropland exposure to drought will increase, and can even reach 669,000 km2 and 524,000 km2 considering and ignoring the CO2 effect, respectively. Our findings suggest that ignoring CO2 in drought evaluations will result in significant overestimations of drought projections.
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Present-day and future projection of East Asian summer monsoon in Coupled Model Intercomparison Project 6 simulations. PLoS One 2022; 17:e0269267. [PMID: 35658064 PMCID: PMC9165809 DOI: 10.1371/journal.pone.0269267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/17/2022] [Indexed: 11/19/2022] Open
Abstract
The East Asian summer monsoon (EASM) is an influential monsoon system that provides two-thirds of the annual precipitation in the Asian region. Therefore, considerable attention has been paid to the changes in future climate. Thus far, studies on EASM characteristics have not been conducted considering specific global warming level (GWL) using Coupled Model Inter-comparison Project 6 (CMIP6) simulations. We analyze the EASM characteristics in present-day (PD) and the changes in EASM corresponding to the projections at 1.5, 2.0, and 3.0°C GWLs. The newly released 30 CMIP6 models effectively captured the migration of the monsoon in PD with a pattern correlation coefficient of 0.91, which is an improvement over that reported in previous studies. As a result of the separate analysis of the P1 (first primary peak; 33–41 pentad) and P2 (from P1 to the withdrawal; 42–50 pentad) periods, a higher frequency of weak to moderate precipitation in P2 and a smaller amount of moderate to extreme precipitation in P1 are mainly occurred. The CMIP6 models project increasing precipitation of approximately 5.7%°C−1, 4.0%°C−1, and 3.9%°C−1 for the three GWLs, respectively, with longer durations (earlier onset and delayed termination). Under the three GWLs, the projected precipitation frequency decreases below 6 mm d−1 (76th percentile) and significant increases above 29 mm d−1 (97th percentile). These changes in precipitation frequency are associated with an increasing distribution of precipitation amount above 97th percentile. Additionally, these tendencies in P1 and P2 are similar to that of the total period, while the maximum changes occur in 3.0°C GWL. In particular, future changes in EASM accelerate with continuous warming and are mainly affected by enhanced extreme precipitation (above 97th percentile). Our findings are expected to provide information for the implementation of sustainable water management programs as a part of national climate policy.
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Mondal SK, Wang Y, Zhai J, Su B, Jiang S, Huang J, Jing C, Lin Q, Zhou J, Gao M, Jiang T. Projected urban exposure to extreme precipitation over South Asia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 822:153664. [PMID: 35124033 DOI: 10.1016/j.scitotenv.2022.153664] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 01/21/2022] [Accepted: 01/30/2022] [Indexed: 06/14/2023]
Abstract
Urbanization is one of the pivotal aspects of socioeconomic advancement which is critically vulnerable to climatic extremes. Extreme precipitation and urbanization are largely interlinked. Estimating the extreme precipitation-induced urban area exposure is the fundamental aspect of urban risk assessment for precipitation-related floods. In this study, future urban area exposure to extreme precipitation and associated influential factors are investigated over South Asia under 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C global warming thresholds. In this regard, we used newly released 20 up-to-date climate models outputs, and five Integrated Assessment Models (IAMs) based urban land-use products under four combined scenarios of the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from the sixth phase of Coupled Model Intercomparison Project (CMIP6). Extreme precipitation is characterized by adopting 20-, 50-, and 100-year return periods of annual maximum daily precipitation. Results reveal a massive urban area expansion over South Asia which is the utmost by 186.4% under SSP3-7.0 than the reference period (1995-2014). The variations in projected urban areas mainly occur in Indo-Gangetic Plain (IGP) region among scenarios. In relative terms, extreme precipitation frequency and associated urban area exposure are prospective to increase with continued global warming. The exposed urban area varies 4.5- to 7.4-fold higher under different warming thresholds than the reference period. The leading increase is estimated (7.4-fold) under 4.0 °C. Notably, for global warming targets set out by the Paris Agreement (1.5 °C, and 2.0 °C), exposed urban area is intended to be 10.2% higher under 2.0 °C than 1.5 °C. Spatially, the exposed urban area will be dominant in the southeast region relative to the reference period. Importantly, the interaction effect (simultaneous change in climate-urban land) is the principal contributor to the changes in urban area exposure to extreme precipitation over South Asia. However, this study's findings strongly support the accomplishment of the Paris Agreement target and provide a scientific basis for formulating urban land-use policy interventions.
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Affiliation(s)
- Sanjit Kumar Mondal
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yanjun Wang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianqing Zhai
- National Climate Center, China Meteorological Administrations, Beijing 100081, China
| | - Buda Su
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Shan Jiang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jinlong Huang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Cheng Jing
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Qigen Lin
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jian Zhou
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Miaoni Gao
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Tong Jiang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China.
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Why the Effect of CO2 on Potential Evapotranspiration Estimation Should Be Considered in Future Climate. WATER 2022. [DOI: 10.3390/w14060986] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Potential evapotranspiration (PET) is an important factor that needs to be considered in regional water management and allocation; thus, the reasonable estimation of PET is an important topic in hydrometeorology and other related fields. There is evidence that increased CO2 concentration alters the physiological properties of vegetation and thus affects PET. In this study, changes in PET with and without the CO2 effect over China is investigated using seven CMIP6-GCMs outputs under seven shared socioeconomic pathways (SSPs) based scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5), as well as the contribution rate of CO2 on PET in different climatic regions. Changes in estimated PET based on modified Penman–Monteith (PM) method that considers the CO2 effect is compared with the traditional PM method to examine how PET quantity varies (differences) between these two approaches. The results show that the PET values estimated by the two methods explored opposite trends in 1961–2014 over entire China; it decreases with consideration of CO2 but increases without consideration of CO2. In the future, overall PET is projected to increase under all scenarios during 2015–2100 for China and its three sub-regions. PET generally tends to grow slower when CO2 is taken into account (modified PM approach), than when it is not (traditional PM method). In terms of differences in the estimated PET by the two methods, the difference between the two adopted methods increased in China and its sub-regions for the 1961–2014 period. In the future, the difference in estimated PET is anticipated to continuously increase under SSP3-7.0 and SSP5-8.5. Spatially, a much greater extent of difference is found in the arid region. Across the arid region, the PET difference is projected to be the highest at 138% in the mid-term (2041–2060) with respect to the 1995–2014 period, whereas it tends to increase slower in the long-term period (2081–2100). Importantly, CO2 is found to be the most dominant factor (−154.2% contribution) to have a great effect on PET changes across the arid region. Our findings suggest that ignorance of CO2 concentration in PET estimation will result in significant overestimation of PET in the arid region. However, consideration of CO2 in PET estimation will be beneficial for formulating strategies on future water resource management and sustainable development at the local scale.
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China’s Socioeconomic and CO2 Status Concerning Future Land-Use Change under the Shared Socioeconomic Pathways. SUSTAINABILITY 2022. [DOI: 10.3390/su14053065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
China has experienced a huge socioeconomic advancement over the past few decades, resulting in great change in land use and land cover. To date, negligible attention has been given to examining the socioeconomic changes in the context of land-use change, especially from a futuristic standpoint. However, motivated by China’s latest carbon neutrality target, this study analyzes the prospective changes in socioeconomic status, and carbon dioxide emission in the context of future land-use change, focusing on three future periods: 2026–2030 (carbon dioxide peak phase), 2056–2060 (carbon-neutral phase), and 2080–2099 (long-term period). In this regard, recently published land-use products under seven Shared Socioeconomic Pathways-based scenarios (SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP2-4.5, SSP4-6.0, SSP3-7.0, and SSP5-8.5) as part of the CMIP6, as well as the projected GDP and population under five socioeconomic scenarios are used. To estimate socioeconomic change over prominent land-use types (urban), we combined five socioeconomic scenarios with seven corresponding SSPs-based land-use change scenarios (SSP1 with SSP1-1.9 and SSP1-2.6; SSP2 with SSP2-4.5; SSP3 with SSP3-7.0; SSP4 with SSP4-3.4 and SSP4-6.0; and SSP5 with SSP5-8.5 scenarios). Our results reveal that rapid urban land expansion in the future is the most dominant aspect in China. In the carbon neutrality phase (2056–2060), urban land is expected to expand ~80% more than that of the reference period (1995–2014). In the spatial aspect, the expansion of urban land is mainly prominent in the eastern and central parts of China. For socioeconomic changes, the most prominent increase in the urban population is estimated at 630.8% under SSP5-8.5 for the 2056–2060 period compared to the reference period. Regarding GDP for the urban area, industrial GDP will be higher than service GDP in the carbon emission peak phase (2026–2030), but it is projected to be overtaken by service GDP for the carbon-neutral target (2056–2060) and long-term periods (2080–2099). Further, the CO2 emission in China was found to increase with intensified urban land for the historical period (1995–2019). In the future, the largest increase in CO2 emission from the urban area is anticipated under SSP5-8.5 in the carbon-neutral target (2056–2060) phase, while CO2 emission will largely decline after (2056–2060) under SSP1-1.9, SSP1-2.6, and SSP4-3.4. Importantly, population change is expected to be the most predominant factor in future urban land expansion in China. These findings highlight the importance of well-governed urban-land development as a key measure to achieve China’s carbon neutrality goal.
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The Characteristics and Evaluation of Future Droughts across China through the CMIP6 Multi-Model Ensemble. REMOTE SENSING 2022. [DOI: 10.3390/rs14051097] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China’s droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control.
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Ayugi B, Shilenje ZW, Babaousmail H, Lim Kam Sian KTC, Mumo R, Dike VN, Iyakaremye V, Chehbouni A, Ongoma V. Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models. NATURAL HAZARDS (DORDRECHT, NETHERLANDS) 2022; 113:1151-1176. [PMID: 35431453 PMCID: PMC8993679 DOI: 10.1007/s11069-022-05341-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 03/25/2022] [Indexed: 05/06/2023]
Abstract
UNLABELLED The ongoing global warming has caused unprecedented changes in the climate system, leading to an increase in the intensity and frequency of weather and climate extremes. This study uses the sixth phase of Coupled Model Intercomparison Project (CMIP6) data to investigate projected changes in drought events over East Africa (EA) under four Shared Socioeconomic Pathway (SSP) emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-4.0, and SSP5-8.5). The CMIP6 data are bias-corrected using a quantile mapping method, with the Climatic Research Unit's precipitation dataset as reference. Drought is quantified using the standardized precipitation index and different measures of drought are estimated: drought duration, drought frequency, drought severity, and drought intensity. Evaluating the accuracy and reliability of historical data before and after bias correction demonstrates the importance of the approach. The overall distribution after bias correction depicts a close agreement with observation. Moreover, the multi-model ensemble mean demonstrate superiority over individual Global Circulation Models. Projected future changes show enhancement in precipitation over most parts of EA in the far future under different SSP scenarios. However, the arid and semi-arid regions are expected to receive less amount of precipitation, whereas the highlands and lake regions are expected to receive a larger amount of precipitation increase. Furthermore, the dry areas of EA are likely to experience more frequent drought events with longer duration, stronger intensity, and severity in the far future. Overall, this study identifies possible drought hotspots over EA, enabling early preparation for such events. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s11069-022-05341-8.
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Affiliation(s)
- Brian Ayugi
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044 China
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), University of Information Science and Technology, NanjingNanjing, 210044 China
| | - Zablon Weku Shilenje
- Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, 18000 Praha 8, Prague, Czech Republic
- Kenya Meteorological Department, P.O. Box 30259-00100, Nairobi, Kenya
| | - Hassen Babaousmail
- Binjiang College of Nanjing University of Information Science and Technology, Wuxi, 214105 China
| | - Kenny T. C. Lim Kam Sian
- Binjiang College of Nanjing University of Information Science and Technology, Wuxi, 214105 China
| | - Richard Mumo
- Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Plot 10071, Private Bag 16, Palapye, Botswana
| | - Victor Nnamdi Dike
- International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
- Energy, Climate, and Environment Science Group, Imo State Polytechnic Umuagwo, Ohaji, PMB, Owerri, 1472 Imo State Nigeria
| | - Vedaste Iyakaremye
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), University of Information Science and Technology, NanjingNanjing, 210044 China
- Rwanda Meteorology Agency, Nyarugenge KN 96 St, Kigali, Rwanda
| | - Abdelghani Chehbouni
- International Water Research Institute, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, 43150 Ben Guerir, Morocco
| | - Victor Ongoma
- International Water Research Institute, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, 43150 Ben Guerir, Morocco
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Iyakaremye V, Zeng G, Yang X, Zhang G, Ullah I, Gahigi A, Vuguziga F, Asfaw TG, Ayugi B. Increased high-temperature extremes and associated population exposure in Africa by the mid-21st century. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 790:148162. [PMID: 34102437 DOI: 10.1016/j.scitotenv.2021.148162] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/11/2021] [Accepted: 05/27/2021] [Indexed: 05/22/2023]
Abstract
Previous studies warned that heat extremes are likely to intensify and frequently occur in the future due to climate change. Apart from changing climate, the population's size and distribution contribute to the total changes in the population exposed to heat extremes. The present study uses the ensemble mean of global climate models from the Coupled Model Inter-comparison Project Phase six (CMIP6) and population projection to assess the future changes in high-temperature extremes and exposure to the population by the middle of this century (2041-2060) in Africa compared to the recent climate taken from 1991 to 2010. Two Shared Socioeconomic Pathways (SSPs), namely SSP2-4.5 and SSP5-8.5, are used. Changes in population exposure and its contributors are quantified at continental and for various sub-regions. The intensity of high-temperature extremes is anticipated to escalate between 0.25 to 1.8 °C and 0.6 to 4 °C under SSP2-4.5 and SSP5-8.5, respectively, with Sahara and West Southern Africa projected to warm faster than the rest of the regions. On average, warm days' frequency is also expected to upsurge under SSP2-4.5 (26-59%) and SSP5-8.5 (30-69%) relative to the recent climate. By the mid-21st century, continental population exposure is expected to upsurge by ~25% (28%) of the reference period under SSP2-4.5|SSP2 (SSP5-8.5|SSP5). The highest increase in exposure is expected in most parts of West Africa (WAF), followed by East Africa. The projected changes in continental exposure (~353.6 million person-days under SSP2-4.5|SSP2 and ~401.4 million person-days under SSP5-8.5|SSP5) are mainly due to the interaction effect. However, the climate's influence is more than the population, especially for WAF, South-East Africa and East Southern Africa. The study findings are vital for climate change adaptation.
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Affiliation(s)
- Vedaste Iyakaremye
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China; Rwanda Meteorology Agency, Nyarugenge KN 96 St, Kigali, Rwanda; African Institute for Mathematical Sciences Next Einstein Initiative (AIMS-NEI), KG590 St, Kigali, Rwanda
| | - Gang Zeng
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China.
| | - Xiaoye Yang
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China
| | - Guwei Zhang
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China
| | - Irfan Ullah
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China
| | - Aimable Gahigi
- Rwanda Meteorology Agency, Nyarugenge KN 96 St, Kigali, Rwanda
| | - Floribert Vuguziga
- Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China; Rwanda Meteorology Agency, Nyarugenge KN 96 St, Kigali, Rwanda
| | - Temesgen Gebremariam Asfaw
- Institute of Geophysics Space Science and Astronomy, Addis Ababa University, 1176 Addis Ababa, Ethiopia; Institute for Climate and Application Research (ICAR)/CICFEM/KLME/ILCEC, Nanjing University of Information Science and Technology, Nanjing, China
| | - Brian Ayugi
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; Organization of African Academic Doctors (OAAD), Off Kamiti Road, P.O. Box 25305-00100, Nairobi, Kenya
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Mondal SK, Tao H, Huang J, Wang Y, Su B, Zhai J, Jing C, Wen S, Jiang S, Chen Z, Jiang T. Projected changes in temperature, precipitation and potential evapotranspiration across Indus River Basin at 1.5-3.0 °C warming levels using CMIP6-GCMs. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 789:147867. [PMID: 34052498 DOI: 10.1016/j.scitotenv.2021.147867] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/14/2021] [Accepted: 05/14/2021] [Indexed: 06/12/2023]
Abstract
The projections of mean temperature, precipitation (P), and potential evapotranspiration (PET) reflect the probabilities of long-term changes of hydrologic processes and induced extreme events. In this paper, we investigated the future changes in some pivotal climatic variables (mean temperature, precipitation, and potential evapotranspiration) under 1.5 °C, 2.0 °C, and 3.0 °C specific warming levels (SWLs) across the Indus River Basin of South Asia. The seven global climate models output under seven different emission scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from the latest Sixth phase of Coupled Model Intercomparison Project (CMIP6) are used for this purpose. The Penman-Monteith approach is applied to estimate PET, and the water balance equation is for reflecting water surplus/deficit. Results indicate that except for precipitation, the greater increases in temperature and PET are inclined to happen with continued global warming. The highest increase in temperature is accounted for 14.6% (2.4 °C), and the enhanced PET is estimated at 5.2% higher than the reference period (1995-2014) under 3.0 °C SWL. While the precipitation is projected to increase by the highest 4.8% for 2.0 °C warming level. The differences in regional climate for an additional 0.5 °C (2.0-1.5 °C) and 1.0 °C (3.0-2.0 °C) of warming, the temperature is projected to increase by 0.4 °C and 0.9 °C in the entire IRB respectively. The highest increase in mean temperature (5.1%) and PET (2.4%) in the IRB are predicted to intensify for an additional 1.0 °C than that of 0.5 °C of warming, but precipitation is intended to decrease by 0.4%. Spatially, the increase in temperature, precipitation, and PET are dominated towards high elevation in the upper basin (north) under all the SWLs. The increased variability in climatological parameters across IRB depicts an evident occurrence of both wet events (upper basin) as well as dry events (lower basin) with the increase in global average temperature rise. However, these findings provide an insightful basis for water resource management as well as initiating mitigation and adaptation measures in the IRB related to water surplus (floods) and water deficit (droughts).
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Affiliation(s)
- Sanjit Kumar Mondal
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hui Tao
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Jinlong Huang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yanjun Wang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Buda Su
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Jianqing Zhai
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China; National Climate Center, China Meteorological Administrations, Beijing 100081, China
| | - Cheng Jing
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Shanshan Wen
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Shan Jiang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Ziyan Chen
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Tong Jiang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China.
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Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review. SUSTAINABILITY 2021. [DOI: 10.3390/su13169244] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.
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Mediterranean-Scale Drought: Regional Datasets for Exceptional Meteorological Drought Events during 1975–2019. ATMOSPHERE 2021. [DOI: 10.3390/atmos12080941] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Drought is one of the most complex climate-related phenomena and is expected to progressively affect our lives by causing very serious environmental and socioeconomic damage by the end of the 21st century. In this study, we have extracted a dataset of exceptional meteorological drought events between 1975 and 2019 at the country and subregional scales. Each drought event was described by its start and end date, intensity, severity, duration, areal extent, peak month and peak area. To define such drought events and their characteristics, separate analyses based on three drought indices were performed at 12-month timescale: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). A multivariate combined drought index (DXI) was developed by merging the previous three indices for more understanding of droughts’ features at the country and subregional levels. Principal component analysis (PCA) was used to identify five different drought subregions based on DXI-12 values for 312 Mediterranean stations and a new special score was defined to classify the multi-subregional exceptional drought events across the Mediterranean Basin (MED). The results indicated that extensive drought events occurred more frequently since the late 1990s, showing several drought hotspots in the last decades in the southeastern Mediterranean and northwest Africa. In addition, the results showed that the most severe events were more detected when more than single drought index was used. The highest percentage area under drought was also observed through combining the variations of three drought indices. Furthermore, the drought area in both dry and humid areas in the MED has also experienced a remarkable increase since the late 1990s. Based on a comparison of the drought events during the two periods—1975–1996 and 1997–2019—we find that the current dry conditions in the MED are more severe, intense, and frequent than the earlier period; moreover, the strongest dry conditions occurred in last two decades. The SPEI-12 and RDI-12 have a higher capacity in providing a more comprehensive description of the dry conditions because of the inclusion of temperature or atmospheric evaporative demand in their scheme. A complex range of atmospheric circulation patterns, particularly the Western Mediterranean Oscillation (WeMO) and East Atlantic/West Russia (EATL/WRUS), appear to play an important role in severe, intense and region-wide droughts, including the two most severe droughts, 1999–2001 and 2007–2012, with lesser influence of the NAO, ULMO and SCAND.
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