Rethinking climate change: Natural variability, solar forcing, model uncertainties, and policy implications

Current global climate models (GCMs) support with high confidence the view that rising greenhouse gases and other ...
JSTOR Daily

Estimation of Daily Evaporation from Shallow Groundwater Using Empirical Models with a Temperature Coefficient

This is a preview. Log in through your library . Abstract Shallow groundwater evaporation (𝛦𝑔) is a major component of the hydrological cycle, especially in semiarid and arid locations. Empirical ...
Nature

Empirical modeling

Empirical modeling involves the development of models that explain, predict, or simulate a particular aspect of the world, rather than purely theoretical or abstract principles. Empirical modeling ...
JSTOR Daily

Learning from a lot: Empirical Bayes for high-dimensional model-based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
PV Tech

From assumptions to accuracy: Why the PV industry needs physics-based solar data

The use of better-quality data can improve the business case for a number of solar projects. Image: Photon Group. The integrity of a PV project largely depends on the quality of the solar, ...
National Academies of Sciences%2c Engineering%2c and Medicine

Corrosion of Buried Steel at New and In-Service Infrastructure

Visit NAP.edu/10766 to get more information about this book, to buy it in print, or to download it as a free PDF. Corrosion is a process that, in theory, could be accurately predicted if sufficient ...
Semiconductor Engineering

DL Atomistic Semi-Empirical Pseudopotential Model For Nanomaterials (UC Berkeley, LBNL et al.)

A new technical paper titled “Deep-learning atomistic semi-empirical pseudopotential model for nanomaterials” was published by researchers at UC Berkeley, Lawrence Berkeley National Laboratory et al. ...