Not exact matches
Research on VAMs indicates that even subtle changes to explanatory variables in value - added
models change substantively the ratings of individual.Omitting
key variables can lead to
bias and including them can reduce that
bias.
These systems likely contribute to an observed regional trend of increasing extreme rainfall, and poor prediction of them likely contributes to a warm, dry
bias in climate
models downstream of the Sierras de Córdoba in a
key agricultural region.
This WP aims to improve the resolution of ocean
models, as well as the representation of physical and biogeochemical processes, in
key regions of the world's oceans (particularly tropical coastal regions, the Southern Ocean and high Northern latitudes) to reduce well known
biases in ESMs.
Apart from being important for comparison between
model simulations and observations, the
bias adjustment can calibrate the uncertainty, enhance prediction skill and become a
key concept for communication purposes.