Not exact matches
The detailed models produced using the MT imaging data of the southwestern U.S. more accurately portrayed surface
structures at a
scale of less than 100 kilometers, Liu said, which is important because features like volcanoes and faults are localized phenomena that are harder to
predict using larger -
scale models.
By merging this concept of the early universe with specific mathematical models of the effects of dark energy, scientists were able to
predict a characteristic
scale — a typical distance between concentrations of galaxies — that should be evident in the
structure of the universe.
As we get better models, the realism and
structure of those wiggles will likely become more realistic — but in the end they define the limits to what we will be able to
predict at regional / decadal
scales.
However, most of the current Earth system models that
predict climate change and C cycle feedbacks lack both a mechanistic formulation for height -
structured competition for light and an explicit
scaling from individual plants to the globe.
Finally, I have proposed a theory based on non-linear dynamics which
predicts a highly
structured series of cycles in the Universe, and explains the distance periodicities of
structures at all
scales in the Universe from the Hubble
scale to particles.
But Franklin said that in contrast to track forecasts,
predicting storm intensity requires knowing lots of small -
scale details that computer models have trouble capturing, from the dynamics of a storm's
structure to the characteristics of air masses being pulled into a storm's circulation.
Using the statistical
structure of temporal correlations in fluctuations for generated and forecast power time series, we quantify two types of forecast error: a timescale error (eτ) that quantifies deviations between the high frequency components of the forecast and generated time series, and a
scaling error (eζ) that quantifies the degree to which the models fail to
predict temporal correlations in the fluctuations for generated power.
The findings indicate a theoretically
predicted factor
structure, high internal consistency, and document the convergent and discriminant validity of the MDI
scales.
Furthermore, the three - dimensional
structure of ODD was confirmed by confirmatory factor analysis and the CPRS - R emotional lability
scale significantly
predicted the ODD irritable dimension.