A comprehensive analysis of climate data (1958-2018) is carried out at the national scale in India to assess spatiotemporal variation in aridity. The aridity is analyzed using UNEP (United Nations Environment Programme) Aridity Index (AI), which is the ratio between Precipitation (P) and Potential Evapotranspiration (PET). Freely available Terra-Climate database, P and PET variables, offered an unprecedented opportunity for monitoring variations in AI and aridity index anomalies (AIA) at interseasonal and inter-decadal basis. The study also assesses longer term patterns of P and AI anomalies with vegetation anomalies. The results indicate that significant clustered areas with maximum dryness are located at west-central part of India, the state of Maharashtra. Overall, there is a gradual increase in the extent of arid zone during 60-year period and spatially maximum extent of percentage change in aridity area is observed. The change patterns of AI in India are largely driven by the changing patterns of precipitation. The maximum impact of decline in precipitation on AIA was observed during Kharif season frequently, for every 4-5 years during 1972-1992. The pattern repeated in the last few recent years (2013- 2018), the decline in precipitation resulted increased aridity. The study also reveals that the availability and usage of irrigation sources have increased from 2014 to 2018. Thus, despite of less precipitation positive vegetation has been resulted in this period. The findings are important to understand the impacts of climate change on land use pattern, and land and water resource management.
{"title":"Long Term Spatio-temporal Variations of Seasonal and Decadal Aridity in India","authors":"Pavan Kumar B, B. Pinjarla, P. Joshi, P. Roy","doi":"10.30564/jasr.v4i3.3475","DOIUrl":"https://doi.org/10.30564/jasr.v4i3.3475","url":null,"abstract":"A comprehensive analysis of climate data (1958-2018) is carried out at the national scale in India to assess spatiotemporal variation in aridity. The aridity is analyzed using UNEP (United Nations Environment Programme) Aridity Index (AI), which is the ratio between Precipitation (P) and Potential Evapotranspiration (PET). Freely available Terra-Climate database, P and PET variables, offered an unprecedented opportunity for monitoring variations in AI and aridity index anomalies (AIA) at interseasonal and inter-decadal basis. The study also assesses longer term patterns of P and AI anomalies with vegetation anomalies. The results indicate that significant clustered areas with maximum dryness are located at west-central part of India, the state of Maharashtra. Overall, there is a gradual increase in the extent of arid zone during 60-year period and spatially maximum extent of percentage change in aridity area is observed. The change patterns of AI in India are largely driven by the changing patterns of precipitation. The maximum impact of decline in precipitation on AIA was observed during Kharif season frequently, for every 4-5 years during 1972-1992. The pattern repeated in the last few recent years (2013- 2018), the decline in precipitation resulted increased aridity. The study also reveals that the availability and usage of irrigation sources have increased from 2014 to 2018. Thus, despite of less precipitation positive vegetation has been resulted in this period. The findings are important to understand the impacts of climate change on land use pattern, and land and water resource management.","PeriodicalId":193824,"journal":{"name":"Journal of Atmospheric Science Research","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130008254","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}
Himalayan glaciers‒ the store house of fresh water outside the polar region contributes ~45% of the total river flow by glacial melt in the Indus, Ganga and Brahmaputra watersheds which supports the livelihood of ~500 million people . The sustainability of these rivers is being questioned because of the growing evidences of accelerated glacier retreat in the recent decades, which is expected to have cascading effects on the mountainous areas and their surrounding lowlands. The rapid melting of Himalayan glaciers reveals their sensitivity to ongoing changes in climate dynamics, and if the current trend continues, rivers that rely heavily on snow/ice melt are expected to suffer hydrological disruptions to the point where some of the most populous areas may ‘run out of water’ during the dry season. Therefore, efforts are being made to study the glacier mass balance trends in order to understand the patterns and causes of recent recessional trend. Despite their importance, the absence of long-term mass-balance and remote sensing data restricts our knowledge of the Himalayan glaciers’ sensitivity/ response to climate change. Furthermore, such studies may be insufficient unless are compared to long-term glacier fluctuations (millennial and multi-millennial time scales), which aid in better understanding the natural trends of and human impacts on climate change, as well as assessing the causes and possible future of contemporary shrinking glaciers. This will also improve our understanding of past glacier behaviour in the context of primary causes of glacier change, which is critical for water resource management and understanding climate variability in high alpine areas where alternative proxy climate archives are typically scarce. Therefore, it is pertinent to pool our scientific resources and energy (i) towards understanding the Himalayan glaciers’ feeders (precipitation sources) and how they changed over time (geological and historical), as well as the causes of glaciers recession, one of which has been identified as (ii) black soot (carbon) in aerosol pollution.
{"title":"An Exigency for Ice Core Studies to Determine Spatio-temporal Variability in Moisture Sources and Impact of Black Carbon – Mineral Aerosols on the Himalayan Glaciers","authors":"Sheikh Nawaz Ali, Anil D. Shukla","doi":"10.30564/jasr.v4i3.3556","DOIUrl":"https://doi.org/10.30564/jasr.v4i3.3556","url":null,"abstract":"Himalayan glaciers‒ the store house of fresh water outside the polar region contributes ~45% of the total river flow by glacial melt in the Indus, Ganga and Brahmaputra watersheds which supports the livelihood of ~500 million people . The sustainability of these rivers is being questioned because of the growing evidences of accelerated glacier retreat in the recent decades, which is expected to have cascading effects on the mountainous areas and their surrounding lowlands. The rapid melting of Himalayan glaciers reveals their sensitivity to ongoing changes in climate dynamics, and if the current trend continues, rivers that rely heavily on snow/ice melt are expected to suffer hydrological disruptions to the point where some of the most populous areas may ‘run out of water’ during the dry season. Therefore, efforts are being made to study the glacier mass balance trends in order to understand the patterns and causes of recent recessional trend. Despite their importance, the absence of long-term mass-balance and remote sensing data restricts our knowledge of the Himalayan glaciers’ sensitivity/ response to climate change. Furthermore, such studies may be insufficient unless are compared to long-term glacier fluctuations (millennial and multi-millennial time scales), which aid in better understanding the natural trends of and human impacts on climate change, as well as assessing the causes and possible future of contemporary shrinking glaciers. This will also improve our understanding of past glacier behaviour in the context of primary causes of glacier change, which is critical for water resource management and understanding climate variability in high alpine areas where alternative proxy climate archives are typically scarce. Therefore, it is pertinent to pool our scientific resources and energy (i) towards understanding the Himalayan glaciers’ feeders (precipitation sources) and how they changed over time (geological and historical), as well as the causes of glaciers recession, one of which has been identified as (ii) black soot (carbon) in aerosol pollution.","PeriodicalId":193824,"journal":{"name":"Journal of Atmospheric Science Research","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124672499","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}
Atmospheric aerosol concentrations have been found to change constantly due to the influence of source, winds and human activities over short time periods. This has proved to be a constraint to the study of varied aerosol concentrations in urban atmosphere alongside changing relative humidity and how it affects visibility and aerosol particle size distribution. In this research simulation was carried out using Optical Properties of Aerosols and Clouds (OPAC 4.0) average concentration setup for relative humidity (RH) 0-99% at visible wavelength 0.4-0.8 μm to vary the concentrations of three aerosol components: WASO (Water-soluble), INSO (Insoluble) and SOOT. The Angstrom exponents (α), the curvatures (α2) and atmospheric turbidities (β) were obtained from the regression analysis of Kaufman’s first and second order polynomial equations for visibility. The research determined the mean exponent of the aerosol size growth curve (µ) from the effective hygroscopic growth (geff) and the humidification factors (γ) from visibility enhancement f (RH, λ). The mean exponent of aerosol size distributions (υ) was determined from µ and γ. The results showed that with varied WASO, INSO and SOOT concentrations respectively at different RH, aerosol particle size distributions showed bimodal characteristics with dominance of fine mode particles. Hazy atmospheric conditions prevailed with increasing turbidity.
{"title":"Effect of Varying Aerosol Concentrations and Relative Humidity on Visibility and Particle Size Distribution in Urban Atmosphere","authors":"U. Abdulkarim, B. Tijjani","doi":"10.30564/jasr.v4i3.3430","DOIUrl":"https://doi.org/10.30564/jasr.v4i3.3430","url":null,"abstract":"Atmospheric aerosol concentrations have been found to change constantly due to the influence of source, winds and human activities over short time periods. This has proved to be a constraint to the study of varied aerosol concentrations in urban atmosphere alongside changing relative humidity and how it affects visibility and aerosol particle size distribution. In this research simulation was carried out using Optical Properties of Aerosols and Clouds (OPAC 4.0) average concentration setup for relative humidity (RH) 0-99% at visible wavelength 0.4-0.8 μm to vary the concentrations of three aerosol components: WASO (Water-soluble), INSO (Insoluble) and SOOT. The Angstrom exponents (α), the curvatures (α2) and atmospheric turbidities (β) were obtained from the regression analysis of Kaufman’s first and second order polynomial equations for visibility. The research determined the mean exponent of the aerosol size growth curve (µ) from the effective hygroscopic growth (geff) and the humidification factors (γ) from visibility enhancement f (RH, λ). The mean exponent of aerosol size distributions (υ) was determined from µ and γ. The results showed that with varied WASO, INSO and SOOT concentrations respectively at different RH, aerosol particle size distributions showed bimodal characteristics with dominance of fine mode particles. Hazy atmospheric conditions prevailed with increasing turbidity.","PeriodicalId":193824,"journal":{"name":"Journal of Atmospheric Science Research","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114958198","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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