Pub Date : 2024-01-23DOI: 10.1142/s2630534823500055
LI Xu, M. J. C. Crabbe
Under the influence of the Arctic amplification, sea ice variability in North Pacific is becoming a key indicator of global climate changes. Due to the widespread and complex impacts of North Pacific sea ice variations, the understanding of its dynamic changes, especially its spatial and temporal evolution patterns, has great significance. In this study, we used the rotated empirical orthogonal decomposition to divide the whole North Pacific into six feature zones on the evolution sea ice concentration under the recent global warming and highlighted the complexity and diversity of sea ice variations in the offshore waters.
{"title":"LEADING MODES AND FEATURE ZONES OF SEA ICE CONCENTRATION IN NORTH PACIFIC DURING SPRING SEASONS OF 2000–2020","authors":"LI Xu, M. J. C. Crabbe","doi":"10.1142/s2630534823500055","DOIUrl":"https://doi.org/10.1142/s2630534823500055","url":null,"abstract":"Under the influence of the Arctic amplification, sea ice variability in North Pacific is becoming a key indicator of global climate changes. Due to the widespread and complex impacts of North Pacific sea ice variations, the understanding of its dynamic changes, especially its spatial and temporal evolution patterns, has great significance. In this study, we used the rotated empirical orthogonal decomposition to divide the whole North Pacific into six feature zones on the evolution sea ice concentration under the recent global warming and highlighted the complexity and diversity of sea ice variations in the offshore waters.","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"56 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139604395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-18DOI: 10.1142/s2630534823300026
Salah Sahabi-Abed, Ahmed NOUR-EL-ISLAM SELMANE
We assess in this paper the spatiotemporal projections of extreme temperature indices over Algeria derived from the adjusted multi-model ensemble mean (MME) data derived from 11 daily historical simulations of CMIP6-GCMs models that participated in the IPCC Sixth Assessment Report (AR6). The projected spatial patterns of 12 extreme temperature indices defined by the Expert Team on Climate Change Detection and Indices are assessed for two future time periods: the mid-future 2041–2070 and the far future 2071–2100, relative to the baseline period 1985–2014 and under three Shared Socio-economic Pathways (SSP) scenarios: low emission SSP1-2.6; medium emission SSP2-4.5 and high emission scenario (SSP5-8.5). The selected climate indices reflect the intensity (TXx, TNx, TXn, TNn and DTR), frequency (TX90p and TN10p) and duration (WSDI, SU, CSDI, TR and FD) of the extreme thermal events. The MME Projections show a global heightened warming over Algeria. Future Climate features depict a continuous increase in the occurrence of hot days by the end of the century reaching 60% for SSP5-8.5 and an amplification of the intensity of the extreme temperature of about 6∘C for SSP5-8.5 and an extension of the heat wave duration period of about 80 days in the north and 100 days in the south of the country compared to the historical period. However, the study shows a projected simultaneous decline in the cold spell duration of 7 days and in the frost days reaching 25 days. A stabilization of the upsurge trend is remarkably observed for most indices under SSP1-2.6 starting from the 2050s. The future changes depicted in this study should help to assess the distribution of the impacts across different regions of Algeria in order to enhance resilience, establish the appropriate adaptation responses and improve disaster preparedness.
{"title":"SPATIOTEMPORAL PROJECTIONS OF EXTREME TEMPERATURE INDICES OVER ALGERIA USING CMIP6-GLOBAL CLIMATE MODELS","authors":"Salah Sahabi-Abed, Ahmed NOUR-EL-ISLAM SELMANE","doi":"10.1142/s2630534823300026","DOIUrl":"https://doi.org/10.1142/s2630534823300026","url":null,"abstract":"We assess in this paper the spatiotemporal projections of extreme temperature indices over Algeria derived from the adjusted multi-model ensemble mean (MME) data derived from 11 daily historical simulations of CMIP6-GCMs models that participated in the IPCC Sixth Assessment Report (AR6). The projected spatial patterns of 12 extreme temperature indices defined by the Expert Team on Climate Change Detection and Indices are assessed for two future time periods: the mid-future 2041–2070 and the far future 2071–2100, relative to the baseline period 1985–2014 and under three Shared Socio-economic Pathways (SSP) scenarios: low emission SSP1-2.6; medium emission SSP2-4.5 and high emission scenario (SSP5-8.5). The selected climate indices reflect the intensity (TXx, TNx, TXn, TNn and DTR), frequency (TX90p and TN10p) and duration (WSDI, SU, CSDI, TR and FD) of the extreme thermal events. The MME Projections show a global heightened warming over Algeria. Future Climate features depict a continuous increase in the occurrence of hot days by the end of the century reaching 60% for SSP5-8.5 and an amplification of the intensity of the extreme temperature of about 6∘C for SSP5-8.5 and an extension of the heat wave duration period of about 80 days in the north and 100 days in the south of the country compared to the historical period. However, the study shows a projected simultaneous decline in the cold spell duration of 7 days and in the frost days reaching 25 days. A stabilization of the upsurge trend is remarkably observed for most indices under SSP1-2.6 starting from the 2050s. The future changes depicted in this study should help to assess the distribution of the impacts across different regions of Algeria in order to enhance resilience, establish the appropriate adaptation responses and improve disaster preparedness.","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"110 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139614737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-12DOI: 10.1142/s2630534823300014
Fekadu Tadege Kobe
Climate change poses a global challenge with profound impacts on diverse aspects of the environment and human society. Understanding these impacts is crucial for formulating effective mitigation strategies. As one of the most critical threats to sustainable development, climate change is anticipated to affect the environment, human health, food security, economic activities, natural resources and physical infrastructure. This review focuses on climate change, its consequences and mitigation efforts in Ethiopia. Ethiopia has encountered both climate variability and change, evident in an average annual temperature increase of about 1.3∘C since 1960, with a corresponding rise of 0.28∘C per decade. Spatial and temporal variations in precipitation have also intensified, highlighting the country’s exposure to climate fluctuations. To address these challenges, the Ethiopian government has implemented various policies, strategies and programs aimed at enhancing adaptive capacity and minimizing the impacts of climate variability and change. The Climate-Resilient Green Economy (CRGE) of Ethiopia centers on four pillars: agriculture, forestry, renewable energy and advanced technologies. These pillars form the foundation for Ethiopia’s pursuit of a sustainable green economy. In conclusion, this review delves into the examination of climate change, its repercussions and the ongoing efforts to mitigate its effects in Ethiopia.
{"title":"UNDERSTANDING CLIMATE CHANGE IN ETHIOPIA: IMPACTS AND SOLUTIONS","authors":"Fekadu Tadege Kobe","doi":"10.1142/s2630534823300014","DOIUrl":"https://doi.org/10.1142/s2630534823300014","url":null,"abstract":"Climate change poses a global challenge with profound impacts on diverse aspects of the environment and human society. Understanding these impacts is crucial for formulating effective mitigation strategies. As one of the most critical threats to sustainable development, climate change is anticipated to affect the environment, human health, food security, economic activities, natural resources and physical infrastructure. This review focuses on climate change, its consequences and mitigation efforts in Ethiopia. Ethiopia has encountered both climate variability and change, evident in an average annual temperature increase of about 1.3∘C since 1960, with a corresponding rise of 0.28∘C per decade. Spatial and temporal variations in precipitation have also intensified, highlighting the country’s exposure to climate fluctuations. To address these challenges, the Ethiopian government has implemented various policies, strategies and programs aimed at enhancing adaptive capacity and minimizing the impacts of climate variability and change. The Climate-Resilient Green Economy (CRGE) of Ethiopia centers on four pillars: agriculture, forestry, renewable energy and advanced technologies. These pillars form the foundation for Ethiopia’s pursuit of a sustainable green economy. In conclusion, this review delves into the examination of climate change, its repercussions and the ongoing efforts to mitigate its effects in Ethiopia.","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":" 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139624270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-18DOI: 10.1142/s2630534823720014
A. Oberheitmann, Ruan Xiaodong
{"title":"Green Retirement homes in China - Background and case study","authors":"A. Oberheitmann, Ruan Xiaodong","doi":"10.1142/s2630534823720014","DOIUrl":"https://doi.org/10.1142/s2630534823720014","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131372773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-18DOI: 10.1142/s2630534823500031
Yue Han, Jiaxin (Cathy) Yang, Lipon Chandra Das
{"title":"Evaluation of SDSM Models for Climate Predictions in Bangladesh","authors":"Yue Han, Jiaxin (Cathy) Yang, Lipon Chandra Das","doi":"10.1142/s2630534823500031","DOIUrl":"https://doi.org/10.1142/s2630534823500031","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122255115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-16DOI: 10.1142/s263053482350002x
Li Xu, M. James, C. Crabbe
{"title":"Dominant Spatio-temporal Modes of Arctic Sea Ice during 2000-2020","authors":"Li Xu, M. James, C. Crabbe","doi":"10.1142/s263053482350002x","DOIUrl":"https://doi.org/10.1142/s263053482350002x","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123206989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-12DOI: 10.1142/s2630534823500018
P. Panja
{"title":"Can global warming change predator-prey dynamics: A modelling study","authors":"P. Panja","doi":"10.1142/s2630534823500018","DOIUrl":"https://doi.org/10.1142/s2630534823500018","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131365546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-16DOI: 10.1142/s2630534822500036
J. Shukla, S. Sundar, Ashish Kumar Mishra, R. Naresh
{"title":"Dynamical modeling and analysis of methane emission abatement","authors":"J. Shukla, S. Sundar, Ashish Kumar Mishra, R. Naresh","doi":"10.1142/s2630534822500036","DOIUrl":"https://doi.org/10.1142/s2630534822500036","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131022786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-16DOI: 10.1142/s2630534822500024
Fekadu Tadege Kobe, Anxing Liu
One of the most serious challenges in the world is climate change. This study examines variations in seasonal and yearly fluctuations in extreme temperatures and precipitation in Ethiopia from 1987 to 2020 using 36 meteorological stations located in various climatic zones. The outcomes of the study demonstrated increased trends in the average annual maximum and minimum temperatures, with values of 0.094∘C and 0.052∘C, respectively. Despite falling trends in the summer, most stations experienced higher winter temperatures than summer. Furthermore, the analysis revealed a trend toward an increase in the number of rain stations over the summer season, while a trend toward a decrease in the amount of precipitation for a number of stations in the winter season; otherwise, large changes expected in the dega (cold), woina dega (cool), and kola (warm) climatic zones during the summer season did not occur. Precipitation activity has been near normal in most dega (cold), woina dega (cool), and kola (warm) climatic zones over the preceding 33 years. However, precipitation in the berha (hot) climatic zone was lower than average, with fluctuating levels noted throughout the year. The average annual precipitation has been decreasing at a rate of 0.146[Formula: see text]mm per year over the past 33 years, indicating that only the winter season has shown a downward (decreasing) trend, while the other three seasons, such as summer, spring, and autumn, have shown growing trends. Furthermore, Ethiopia’s average annual rainfall continues to be on a downward trend (decreasing).
{"title":"ANALYSIS OF SEASONAL AND ANNUAL VARIATIONS OF EXTREME TEMPERATURES AND PRECIPITATION IN ETHIOPIA","authors":"Fekadu Tadege Kobe, Anxing Liu","doi":"10.1142/s2630534822500024","DOIUrl":"https://doi.org/10.1142/s2630534822500024","url":null,"abstract":"One of the most serious challenges in the world is climate change. This study examines variations in seasonal and yearly fluctuations in extreme temperatures and precipitation in Ethiopia from 1987 to 2020 using 36 meteorological stations located in various climatic zones. The outcomes of the study demonstrated increased trends in the average annual maximum and minimum temperatures, with values of 0.094∘C and 0.052∘C, respectively. Despite falling trends in the summer, most stations experienced higher winter temperatures than summer. Furthermore, the analysis revealed a trend toward an increase in the number of rain stations over the summer season, while a trend toward a decrease in the amount of precipitation for a number of stations in the winter season; otherwise, large changes expected in the dega (cold), woina dega (cool), and kola (warm) climatic zones during the summer season did not occur. Precipitation activity has been near normal in most dega (cold), woina dega (cool), and kola (warm) climatic zones over the preceding 33 years. However, precipitation in the berha (hot) climatic zone was lower than average, with fluctuating levels noted throughout the year. The average annual precipitation has been decreasing at a rate of 0.146[Formula: see text]mm per year over the past 33 years, indicating that only the winter season has shown a downward (decreasing) trend, while the other three seasons, such as summer, spring, and autumn, have shown growing trends. Furthermore, Ethiopia’s average annual rainfall continues to be on a downward trend (decreasing).","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122096837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-23DOI: 10.1142/s2630534822720019
M. Crabbe
{"title":"Deep Sea Mining for Renewable Technologies; a Case Study for using Big Data","authors":"M. Crabbe","doi":"10.1142/s2630534822720019","DOIUrl":"https://doi.org/10.1142/s2630534822720019","url":null,"abstract":"","PeriodicalId":262307,"journal":{"name":"International Journal of Big Data Mining for Global Warming","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128968973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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