Overview of the Nephele Perturbed Parameter Ensemble for Aerosol‐Cloud Interactions in E3SMv3
Abstract Aerosol‐cloud interactions (aci) are the leading source of uncertainty in inferring climate sensitivity from the historical record. Earth system models (ESMs) struggle to represent aci because the processes responsible for these phenomena occur at much finer time and space scales than can be resolved by any ESM.
J. M. Nugent +29 more
wiley +1 more source
Empirical Mode Decomposition-Based Deep Learning Model Development for Medical Imaging: Feasibility Study for Gastrointestinal Endoscopic Image Classification. [PDF]
Deb M +18 more
europepmc +1 more source
Abstract The integration of satellite‐based observations into hydrological models offers transformation potential for improving discharge predictions globally, especially in regions lacking in situ measurements. This study presents CTRIP‐HyDAS, a global‐scale hydrological data assimilation framework that merges SWOT‐derived discharge observations with ...
Kaushlendra Verma +3 more
wiley +1 more source
Research on Bearing Fault Diagnosis Based on VMD-RCMWPE Feature Extraction and WOA-SVM-Optimized Multidataset Fusion. [PDF]
Wang S, Wang C, Lian Y, Luo B.
europepmc +1 more source
Abstract Hydropower is considered essential in meeting the increasing demand in low carbon energy in the context of climate change. Greenhouse gas emissions (GHG) by hydroelectric reservoirs have nevertheless become a major concern to the energy sector.
Maud Demarty +4 more
wiley +1 more source
Methodology for the Early Detection of Damage Using CEEMDAN-Hilbert Spectral Analysis of Ultrasonic Wave Attenuation. [PDF]
Shakir AM, Cascante G, Ameen TH.
europepmc +1 more source
RESIdual STability (RESIST) Calibration for Improved Hydrological Model Time Generalizability
Abstract Hydrological models are calibrated on specific periods based on how well simulations match streamflow observations by selecting the parameter vector(s) that provide the highest accuracy. This accuracy can decrease significantly during extrapolation to periods not seen during calibration, especially when they are characterized by different ...
Paul C. Astagneau +4 more
wiley +1 more source
Forecasting cashew production in India using a hybrid machine learning framework with STL decomposition, ensemble methods, and global trade network analysis. [PDF]
C S, A P.
europepmc +1 more source
Non‐Linear Reduced Order Modelling of Transonic Potential Flows for Fast Aerodynamic Analysis
ABSTRACT This work presents a physics‐based reduced order modelling (ROM) framework for the efficient simulation of steady transonic potential flows around aerodynamic configurations. The approach leverages proper orthogonal decomposition and a least‐squares Petrov‐Galerkin (LSPG) projection to construct intrusive ROMs for the full potential equation ...
M. Zuñiga +3 more
wiley +1 more source
PhysEmbedFormer: a physics-guided interpretable architecture for days-ahead forecasting of PV power. [PDF]
Yu Y, Loskot P, Gao Y.
europepmc +1 more source

