Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a sig...Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.展开更多
In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in...In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in such a network is the localization of underwater nodes.Localization is required for tracking objects and detecting the target.It is also considered tagging of data where sensed contents are not found of any use without localization.This is useless for application until the position of sensed content is confirmed.This article’s major goal is to review and analyze underwater node localization to solve the localization issues in UWSN.The present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes underwater.Also,a detailed subdivision of these localization schemes is given.Further,these localization schemes are compared from different perspectives.The detailed analysis of these schemes in terms of certain performance metrics has been discussed in this paper.At the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.展开更多
Land surface temperature(LST)is a crucial parameter for understanding the Earth's surface energy balance,which provides insights into climate dynamics and local environmental conditions.Thus,the present study aims...Land surface temperature(LST)is a crucial parameter for understanding the Earth's surface energy balance,which provides insights into climate dynamics and local environmental conditions.Thus,the present study aims to evaluate the spatial and elevation-wise trends in the daytime,nighttime,and mean LST across the Indus River Basin(IRB)using MODIS 8-day product for the period between 2002 and 2022.The elevation,cloud cover,and land cover type data are used for explaining the emerging LST trends.The Theil slope estimator and MannKendall significance test were used for estimating the seasonal and annual LST trends.The findings show warming in mean daytime(0.020-0.024℃/yr)(except winter and post-monsoon),nighttime(0.013-0.049℃/yr),and mean(0.001-0.042℃/yr)LST in all the seasons(highest in monsoon).The annual mean nighttime LST(0.025℃/yr)is rising significantly faster than the mean daytime LST(0.0016℃/yr),showing the presence of a“nighttime warming effect”,which possibly increases human discomfort,particularly during the warm pre-monsoon and humid monsoon season.Elevation-dependent warming(EDW)is predominant in mean daytime LST in two elevation zones,namely(i)0-3 km and(ii)above 4 km,in all seasons,except in post-monsoon.In contrast,EDW in mean nighttime LST is observed up to 3 km and above 6 km in the basin in all the seasons,excluding post-monsoon.The warming trend in LST may be attributed to rising atmospheric moisture,cloud cover,declining snow cover,and changes in land cover to non-vegetated land.However,further investigations will involve exploring the underlying factors contributing to the observed anomalies in nighttime LST,considering variables such as regional energy balance and atmospheric stability.This research contributes to an understanding of the thermal dynamics in the mountain basin,aiding in climate studies,land management,and the development of effective adaptation strategies in the IRB.展开更多
基金the Banaras Hindu University,Varanasi,Uttar Pradesh(India),for providing a seed grant(Letter No.R/Dev/D/IoE/Equipment/Seed Grant-II/2022-23/52078)under the Institute of Eminence(IoE)Jyotsna Singh(Ref.No.210510120701),Subhash Singh(Ref.No.220510022095),and Purushottam Tiwari(Ref.No.210510406257)are grateful to the University Grants Commission(UGC)of the Ministry of Education,Government of India(New Delhi)for providing financial support to the present study+2 种基金the Copernicus Climate Change Service(C3S)team at the European Centre for Medium-Range Weather Forecasts(ECMWF)for providing ERA5 reanalysis data in the public domainreceived a seed grant from the Banaras Hindu University,Varanasi,Uttar Pradesh(India)(Letter No.R/Dev/D/IoE/Equipment/Seed Grant-II/2022-23/52078)under the Institute of Eminence(IoE)Jyotsna Singh(Ref.No.210510120701),Subhash Singh(Ref.No.220510022095),and Purushottam Tiwari(Ref.No.210510406257)received a fellowship from the University Grants Commission(UGC)of the Ministry of Education,Government of India(New Delhi)。
文摘Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.
文摘In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in such a network is the localization of underwater nodes.Localization is required for tracking objects and detecting the target.It is also considered tagging of data where sensed contents are not found of any use without localization.This is useless for application until the position of sensed content is confirmed.This article’s major goal is to review and analyze underwater node localization to solve the localization issues in UWSN.The present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes underwater.Also,a detailed subdivision of these localization schemes is given.Further,these localization schemes are compared from different perspectives.The detailed analysis of these schemes in terms of certain performance metrics has been discussed in this paper.At the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.
基金the Banaras Hindu University,Varanasi,Uttar Pradesh(India),for providing a seed grant(Letter No.R/Dev/D/IoE/Equipment/SeedGrantII/2022-23/52078)under the Institute of Eminence(IoE)。
文摘Land surface temperature(LST)is a crucial parameter for understanding the Earth's surface energy balance,which provides insights into climate dynamics and local environmental conditions.Thus,the present study aims to evaluate the spatial and elevation-wise trends in the daytime,nighttime,and mean LST across the Indus River Basin(IRB)using MODIS 8-day product for the period between 2002 and 2022.The elevation,cloud cover,and land cover type data are used for explaining the emerging LST trends.The Theil slope estimator and MannKendall significance test were used for estimating the seasonal and annual LST trends.The findings show warming in mean daytime(0.020-0.024℃/yr)(except winter and post-monsoon),nighttime(0.013-0.049℃/yr),and mean(0.001-0.042℃/yr)LST in all the seasons(highest in monsoon).The annual mean nighttime LST(0.025℃/yr)is rising significantly faster than the mean daytime LST(0.0016℃/yr),showing the presence of a“nighttime warming effect”,which possibly increases human discomfort,particularly during the warm pre-monsoon and humid monsoon season.Elevation-dependent warming(EDW)is predominant in mean daytime LST in two elevation zones,namely(i)0-3 km and(ii)above 4 km,in all seasons,except in post-monsoon.In contrast,EDW in mean nighttime LST is observed up to 3 km and above 6 km in the basin in all the seasons,excluding post-monsoon.The warming trend in LST may be attributed to rising atmospheric moisture,cloud cover,declining snow cover,and changes in land cover to non-vegetated land.However,further investigations will involve exploring the underlying factors contributing to the observed anomalies in nighttime LST,considering variables such as regional energy balance and atmospheric stability.This research contributes to an understanding of the thermal dynamics in the mountain basin,aiding in climate studies,land management,and the development of effective adaptation strategies in the IRB.
