Land data assimilation: Harmonizing theory and data in land surface process studies
Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …
An agenda for land data assimilation priorities: Realizing the promise of terrestrial water, energy, and vegetation observations from space
The task of quantifying spatial and temporal variations in terrestrial water, energy, and
vegetation conditions is challenging due to the significant complexity and heterogeneity of …
vegetation conditions is challenging due to the significant complexity and heterogeneity of …
Challenges in understanding the variability of the cryosphere in the Himalaya and its impact on regional water resources
The Himalaya plays a vital role in regulating the freshwater availability for nearly a billion
people living in the Indus, Ganga, and Brahmaputra River basins. Due to climate change …
people living in the Indus, Ganga, and Brahmaputra River basins. Due to climate change …
Passive microwave remote sensing of snow depth: Techniques, challenges and future directions
S Tanniru, R Ramsankaran - Remote Sensing, 2023 - mdpi.com
Monitoring snowpack depth is essential in many applications at regional and global scales.
Space-borne passive microwave (PMW) remote sensing observations have been widely …
Space-borne passive microwave (PMW) remote sensing observations have been widely …
Improving snow estimates through assimilation of MODIS fractional snow cover data using machine learning algorithms and the common land model
In this study, an innovative MODIS fractional snow cover (SCF) data assimilation (DA)
prototype framework that invokes machine learning (ML) techniques and Common land …
prototype framework that invokes machine learning (ML) techniques and Common land …
Hydrological perspectives on integrated, coordinated, open, networked (ICON) science
BS Acharya, B Ahmmed, Y Chen… - Earth and Space …, 2022 - Wiley Online Library
Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic
processes to ensure safe, sufficient, and equal water distribution. These hydrologic data …
processes to ensure safe, sufficient, and equal water distribution. These hydrologic data …
Retrieval of snow depth on arctic sea ice from the FY3B/MWRI
L Li, H Chen, L Guan - Remote Sensing, 2021 - mdpi.com
Given their high albedo and low thermal conductivity, snow and sea ice are considered key
reasons for amplified warming in the Arctic. Snow-covered sea ice is a more effective …
reasons for amplified warming in the Arctic. Snow-covered sea ice is a more effective …
Grand challenges of hydrologic modeling for food-energy-water nexus security in high mountain Asia
Climate-influenced changes in hydrology affect water-food-energy security that may impact
up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in …
up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in …
More severe drought detected by the assimilation of brightness temperature and terrestrial water storage anomalies in Texas during 2010–2013
Texas experienced an extreme drought on record in 2011. Model simulations or satellite
observations have been used to assess and analyze the drought. In this study, a method …
observations have been used to assess and analyze the drought. In this study, a method …
深度学习融合遥感大数据的陆地水文数据同化: 进展与关键科学问题.
黄春林， 侯金亮， 李维德， 顾娟， 张莹… - Advances in Earth …, 2023 - search.ebscohost.com
以深度学习为核心的数据驱动方法逐步应用于地球科学领域, 但这类方法在模型的可解释性和
物理一致性等方面还存在挑战. 在遥感大数据背景下, 如何结合深度学习和数据同化方法 …
物理一致性等方面还存在挑战. 在遥感大数据背景下, 如何结合深度学习和数据同化方法 …