Zobrazeno 1 - 10
of 130
pro vyhledávání: '"Chang-qing Ke"'
Publikováno v:
Advances in Climate Change Research, Vol 15, Iss 5, Pp 815-829 (2024)
The dynamics of glaciers serve as one of the most important indicators of climate change. Whilst current research has primarily concentrated on long-term interannual glacier mass balance and its response to climate change, glaciers may respond more r
Externí odkaz:
https://doaj.org/article/51790c1eb0904232a6862fc8caa3277f
Publikováno v:
Earth's Future, Vol 12, Iss 8, Pp n/a-n/a (2024)
Abstract Wetlands formed by natural sediment deposition account for a large proportion of new coastal lands, and these new wetlands usually have active ecosystems and obvious ecological effects. However, previous studies largely overlooked this sedim
Externí odkaz:
https://doaj.org/article/7ef233295a3b42fe8c05c1230d2689ae
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 4, Pp 1772-1796 (2024)
This study examines two downscaling techniques, convolutional neural networks (CNNs) and feedforward neural networks for predicting precipitation and temperature, alongside statistical downscaling as a benchmark model. The daily climate predictors we
Externí odkaz:
https://doaj.org/article/56bd63f7aa27486998d5ee30d09f006c
Publikováno v:
Aqua, Vol 73, Iss 3, Pp 520-537 (2024)
The management of wastewater treatment plant (WWTP) and the assessment of uncertainty in its design are crucial from an environmental engineering perspective. One of the key mechanisms in WWTP operation is activated sludge, which is related to the bi
Externí odkaz:
https://doaj.org/article/967175521c5347bca5f54d1b9e3a698a
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 14, Pp n/a-n/a (2024)
Abstract The state and fate of snow on sea ice are crucial in the mass and energy balance of sea ice. The function of atmospheric rivers (ARs) on snow depth over sea ice has not been measured thus far, limiting the understanding of the mechanism of s
Externí odkaz:
https://doaj.org/article/82b7b097876e4a458471beea7f496fce
Publikováno v:
Advances in Climate Change Research, Vol 14, Iss 3, Pp 372-386 (2023)
The southeastern Tibetan Plateau (SETP) is a region in High Mountain Asia with the most serious glacier mass loss. However, long-term and large regional-scale studies that estimate glacier mass balance in this area remain limited. In this study, we g
Externí odkaz:
https://doaj.org/article/29e9c34950564d43954220e898120c9a
Publikováno v:
Journal of Glaciology, Vol 69, Pp 500-512 (2023)
High Mountain Asia (HMA) glaciers are critical water reserves for montane regions, which are readily influenced by climate change. The glacier mass balance during 2000–2021 over HMA was estimated by comparing the elevations from ICESat-2 and the NA
Externí odkaz:
https://doaj.org/article/17c6af6bc7cf4c5fbb365cc37f023865
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4024-4038 (2023)
Remote sensing is an effective means for lake water level monitoring on the Tibetan Plateau (TP). The purpose of this study is to estimate water levels of lakes on the TP using the Global Ecosystem Dynamics Investigation (GEDI) and Cloud and Land Ele
Externí odkaz:
https://doaj.org/article/aab8bba13dc341bea46273e21f2280b2
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 2035-2049 (2023)
Accurate multitemporal glacier change investigations and analyses are lacking on the southeastern Tibetan Plateau (SETP). A combination of photogrammetry, optical remote sensing, and synthetic aperture radar datasets can accurately identify large-sca
Externí odkaz:
https://doaj.org/article/8bd56e9038e44dc287b5233a5443643d
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3465 (2022)
Research into glacial mass change in West Kunlun (WK) has been sufficient, but most of the existing studies were based on geodetic methods, which are not suitable for specific health state analyses of each glacier. In this paper, we utilize Advanced
Externí odkaz:
https://doaj.org/article/706b1499a40b4ff3b54aef2347367815