Zobrazeno 1 - 10
of 5 757
pro vyhledávání: '"Sea-ice thickness"'
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Landfast sea ice (LFSI) is sensitive to local climate change, making it an important component of the cryosphere system. In this study, the LFSI around the pan-Arctic domain was simulated from 1979 to 2021 using a well-validated snow and ice thermody
Externí odkaz:
https://doaj.org/article/2dc0c36de98d4ec1a97c3baae5a3f430
Autor:
Hoyeon Shi, Rasmus Tonboe, Sang‐Moo Lee, Gorm Dybkjær, Byung‐Ju Sohn, Suman Singha, Fabrizio Baordo
Publikováno v:
Earth and Space Science, Vol 11, Iss 10, Pp n/a-n/a (2024)
Abstract CryoSat‐2 has been successful in observing sea ice thickness from space by providing ice freeboard information. The initial estimate of the ice freeboard, called radar freeboard, is obtained by analyzing the observed waveform using a retra
Externí odkaz:
https://doaj.org/article/b7551ada5e2440f88eb741ede35164f8
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Sea ice thickness (SIT) is a critical and sensitive parameter in the climate system, with its dynamic changes profoundly influencing global climate models, navigational routes, and the potential for Arctic resource development. Given the widespread a
Externí odkaz:
https://doaj.org/article/2fc13521ff324ccba377e60eb738f5fb
Publikováno v:
Haiyang Kaifa yu guanli, Vol 41, Iss 6, Pp 35-46 (2024)
This study examines the future spatial distributions and long-term trends of the sea ice concentration (SIC) and the sea ice thickness (SIT) in the Arctic, along with the potential impacts of the Temperature at Surface (TAS), using the outputs of six
Externí odkaz:
https://doaj.org/article/1e24fa49c2c941b993ea98d5783aafe8
Autor:
Yunjian Xie, Qingyun Yan
Publikováno v:
Satellite Navigation, Vol 5, Iss 1, Pp 1-13 (2024)
Abstract Sea ice, a significant component in polar regions, plays a crucial role in climate change through its varying conditions. In Global Navigation Satellite System-Reflectometry (GNSS-R) studies, the observed surface reflectivity Γ serves as a
Externí odkaz:
https://doaj.org/article/3d755496c814420d802fbdd8b3d6fb92
Autor:
Haotian Zhang, Chuanfeng Zhao, Yan Xia, Annan Chen, Yikun Yang, Jie Yang, Xin Zhao, Yulei Chi, Hongtao Xu, Shouyi Zhong
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 16, Pp n/a-n/a (2024)
Abstract Over the past 30 years, the Arctic Dipole Anomaly (DA) has repeatedly led to record lows in summer sea ice extent, with cloud radiative effects (CRE) playing a crucial regulatory role. Here, we reveal the CRE variations between positive and
Externí odkaz:
https://doaj.org/article/c498c08a439f47359b6d35a358c10870
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10752-10758 (2024)
This study proposes a machine learning based methodology for estimating Arctic thin sea ice thickness (up to 1 m) from brightness temperature measurements of SMOS. The approach involves employing the so-called Burke model for sea ice emission modelin
Externí odkaz:
https://doaj.org/article/fadfe9bdb9854d28b51196e34624737d
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 8710-8723 (2024)
The accuracy and reliability of the latest version of multisource satellite derived Arctic sea ice thickness (SIT) in thinner ice regions are currently uncertain. This study integrated a comprehensive comparison and assessment of Arctic SIT derived f
Externí odkaz:
https://doaj.org/article/1e214122e1674edcb9cf3cdc03c63ee8
Publikováno v:
Remote Sensing, Vol 16, Iss 23, p 4565 (2024)
Sea ice thickness is an important component of the Arctic environment, bearing crucial significance in investigations pertaining to global climate and environmental changes. This study employs data from the HaiYang-2B satellite altimeter (HY-2B ALT)
Externí odkaz:
https://doaj.org/article/6cbb99ab7d9040ad86e9c0d18f70af24
Publikováno v:
Remote Sensing, Vol 16, Iss 20, p 3764 (2024)
Revolutionary advances in artificial intelligence (AI) in the past decade have brought transformative innovation across science and engineering disciplines. In the field of Arctic science, we have witnessed an increasing trend in the adoption of AI,
Externí odkaz:
https://doaj.org/article/e5c98fc56c684b7aafcc63e32742c1fe