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The Himalayan cryosphere:A critical assessment and evaluation of glacial melt fraction in the Bhagirathi basin
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作者 Abul Amir Khan Naresh Chandra Pant +3 位作者 Anindaya Sarkar S.K.Tandon Meloth Thamban Mahalinganathan K 《Geoscience Frontiers》 SCIE CAS CSCD 2017年第1期107-115,共9页
The cryosphere constitutes an important subset of the hydrosphere. The Himalayan cryosphere is a significant contributor to the hydrological budget of a large river system such as the Ganges. Basic data on the cryosph... The cryosphere constitutes an important subset of the hydrosphere. The Himalayan cryosphere is a significant contributor to the hydrological budget of a large river system such as the Ganges. Basic data on the cryosphere in the Himalaya is inadequate and also has large uncertainties. The data on glacial melt component in the Himalayan rivers of India also shows high variability. The Gangotri glacier which constitutes nearly a fifth of the glacierized area of the Bhagirathi basin represents one of the fastest receding, large valley glaciers in the region which has been surveyed and monitored for over sixty years. The availability of measurement over a long period and relatively small glacier-fed basin for the Bha- girathi river provides suitable constraints for the measurement of the glacial melt fraction in a Himalayan river. Pre- and post-monsoon samples reveal a decreasing trend of depletion of 0180 in the river water from glacier snout (Gaumukh) to the confluence of the Bhagiratbi river with the Alaknanda river near Devprayag. Calculations of existing glacial melt fraction (-30% at Rishikesh) are not consistent with the reported glacial thinning rates. It is contended that the choice of unsuitable end-members in the three component mixing model causes the overestimation of glacial melt component in the river discharge. Careful selection of end members provides results (-11% at Devprayag) that are consistent with the expected thinning rates. 展开更多
关键词 CryosphereGlacial melt fractionBhagirathi riverOxygen isotope
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Research agenda for the Russian Far East and utilization of multiplatform comprehensive environmental observations 被引量:1
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作者 Tuukka Petäjä Kirill S.Ganzei +11 位作者 Hanna K.Lappalainen Ksenia Tabakova Risto Makkonen Jouni Räisänen Sergey Chalov Markku Kulmala Sergej Zilitinkevich Petr Ya Baklanov Renat B.Shakirov Natalia V.Mishina Evgeny G.Egidarev Igor I.Kondrat’ev 《International Journal of Digital Earth》 SCIE 2021年第3期311-337,共27页
The Russian Far East is a region between China and the Russian Arctic with a diverse climatological,geophysical,oceanic,and economical characteristic.The southern region is located in the Far East monsoon sector,while... The Russian Far East is a region between China and the Russian Arctic with a diverse climatological,geophysical,oceanic,and economical characteristic.The southern region is located in the Far East monsoon sector,while the northern parts are affected by the Arctic Ocean and cold air masses penetrating far to the south.Growing economic activities and traffic connected to the China Belt and Road Initiative together with climate change are placing an increased pressure upon the Russian Far East environment.There is an urgent need to improve the capacity to measure the atmospheric and environmental pollution and analyze their sources and to quantify the relative roles of local and transported pollution emissions in the region.In the paper,we characterize the current environmental and socio-economical landscape of the Russian Far East and summarize the future climate scenarios and identify the key regional research questions.We discuss the research infrastructure concept,which is needed to answer the identified research questions.The integrated observations,filling in the critical observational gap at the Northern Eurasian context,are required to provide state-of-the-art observations and enable follow-up procedures that support local,regional,and global decision making in the environmental context. 展开更多
关键词 Russian Far East greenhouse gases aerosol particles insitu observations Earth observation data
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Atmospheric and ecosystem big data providing key contributions in reaching United Nations’Sustainable Development Goals 被引量:1
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作者 Markku Kulmala Anna Lintunen +5 位作者 Ilona Ylivinkka Janne Mukkala Rosa Rantanen Joni Kujansuu Tuukka Petäjä Hanna K.Lappalainen 《Big Earth Data》 EI 2021年第3期277-305,共29页
Big open data comprising comprehensive,long-term atmospheric and ecosystem in-situ observations will give us tools to meet global grand challenges and to contribute towards sustainable develop-ment.United Nations’Sus... Big open data comprising comprehensive,long-term atmospheric and ecosystem in-situ observations will give us tools to meet global grand challenges and to contribute towards sustainable develop-ment.United Nations’Sustainable Development Goals(UN SDGs)provide framework for the process.We present synthesis on how Station for Measuring Earth Surface-Atmosphere Relations(SMEAR)observation network can contribute to UN SDGs.We describe SMEAR II flagship station in Hyytiälä,Finland.With more than 1200 variables measured in an integrated manner,we can under-stand interactions and feedbacks between biosphere and atmo-sphere.This contributes towards understanding impacts of climate change to natural ecosystems and feedbacks from ecosys-tems to climate.The benefits of SMEAR concept are highlighted through outreach project in Eastern Lapland utilizing SMEAR I observations from Värriöresearch station.In contrast to boreal environment,SMEAR concept was also deployed in Beijing.We underline the benefits of comprehensive observations to gain novel insights into complex interactions between densely popu-lated urban environment and atmosphere.Such observations enable work towards solving air quality problems and improve the quality of life inside megacities.The network of comprehensive stations with various measurements will enable science-based deci-sion making and support sustainable development by providing long-term view on spatio-temporal trends on atmospheric compo-sition and ecosystem parameters. 展开更多
关键词 Grand challenges in-situ observations big open data SMEAR concept SDGs
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