Big Data in Earth system science and progress towards a digital twin
The concept of a digital twin of Earth envisages the convergence of Big Earth Data with
physics-based models in an interactive computational framework that enables monitoring …
physics-based models in an interactive computational framework that enables monitoring …
Artificial Intelligence for Prediction of Climate Extremes: State of the art, challenges and future perspectives
Scientific and technological advances in numerical modelling have improved the quality of
climate predictions over recent decades, but predictive skill remains limited in many aspects …
climate predictions over recent decades, but predictive skill remains limited in many aspects …
Emulating aerosol optics with randomly generated neural networks
Atmospheric aerosols have a substantial impact on climate and remain one of the largest
sources of uncertainty in climate prediction. Accurate representation of their direct radiative …
sources of uncertainty in climate prediction. Accurate representation of their direct radiative …
Reconstruction of all-weather land surface temperature based on a combined physical and data-driven model
X Zhang, P Gou, F Zhang, Y Huang, Z Wang… - … Science and Pollution …, 2023 - Springer
At present, the remote sensing (RS) thermal infrared (TIR) images that are commonly used
to obtain land surface temperature (LST) are contaminated by clouds and thus cannot obtain …
to obtain land surface temperature (LST) are contaminated by clouds and thus cannot obtain …
Improving Solar Radiation Nowcasts by Blending Data-Driven, Satellite-Images-Based and All-Sky-Imagers-Based Models Using Machine Learning Techniques
Accurate solar radiation nowcasting models are critical for the integration of the increasing
solar energy in power systems. This work explored the benefits obtained by the blending of …
solar energy in power systems. This work explored the benefits obtained by the blending of …
Investigating the inter-relationships among multiple atmospheric variables and their responses to precipitation
In this study, a comprehensive investigation into the inter-relationships among twelve
atmospheric variables and their responses to precipitation was conducted. These variables …
atmospheric variables and their responses to precipitation was conducted. These variables …
Quantifying the impact of vertical resolution on the representation of marine boundary layer physics for global-scale models
MA Smalley, MD Lebsock… - Monthly Weather …, 2023 - journals.ametsoc.org
While GCM horizontal resolution has received the majority of scale improvements in recent
years, ample evidence suggests that a model's vertical resolution exerts a strong control on …
years, ample evidence suggests that a model's vertical resolution exerts a strong control on …
MagNet—A Data‐Science Competition to Predict Disturbance Storm‐Time Index (Dst) From Solar Wind Data
Enhanced interaction between solar‐wind and Earth's magnetosphere can cause space
weather and geomagnetic storms that have the potential to damage critical technologies …
weather and geomagnetic storms that have the potential to damage critical technologies …
Forecasting precipitation based on teleconnections using machine learning approaches across different precipitation regimes
Precipitation forecasts are of high significance for different disciplines. In this study,
precipitation was forecasted using a wide range of teleconnection signals across different …
precipitation was forecasted using a wide range of teleconnection signals across different …
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， 韩伟孝， 王维真… - 地球科学进展, 2023 - adearth.ac.cn
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 …