We found significant changes in the spatial distributions of temperature predictability in the present and future climate compared to the preindustrial climate, although
the spatial average changes for North America were rather small -LRB-
Not exact matches
Since 1900, the
change in
spatial coverage does not seem to have affected land records significantly.2 Before then, however, even careful analysis may lead to long - term
averages that are either too warm or too cold by up to 0.1 C. 1 Records may be affected by
changes in the way observations are made.
The processing of these observations is straightforward, but large gaps in
spatial coverage compromise the reliability of global
averages, and
changes in instrumentation can give rise to spurious trends.
While El Nino may not necessarily
change the global
average NPP / GPP ratio of close to 0.5, it could affect the
spatial distribution of that ratio.
Two kind of variabilities are involved, the
spatial variability between the
changes in
average temperature from the past to the later period and the variability around the mean at every location.
Current computer models can faithfully simulate many of the important aspects of the global climate system, such as
changes in global
average temperature over many decades; the march of the seasons on large
spatial scales; and how the climate responds to large - scale forcing, like a large volcanic eruption.
The widespread trend of increasing heavy downpours is expected to continue, with precipitation becoming less frequent but more intense.13, 14,15,16 The patterns of the projected
changes of precipitation do not contain the
spatial details that characterize observed precipitation, especially in mountainous terrain, because the projections are
averages from multiple models and because the effective resolution of global climate models is roughly 100 - 200 miles.
In order to estimate globally
averaged temperature
changes with a high degree of accuracy, it is necessary to have a broad
spatial distribution of observations that are made with high precision.break
A measurement comparing these systems demonstrates an unprecedented atomic clock instability of 1.6 × 10 ^ -18 after only 7 hours of
averaging... Clock measurement at the 10 ^ -18 level can be used to resolve
spatial and temporal fluctuations equivalent to 1 cm of elevation in Earth's gravitational field (25 — 28), potentially impacting geodesy, hydrology, geology, and climate
change studies.
The point is that getting the
average surface temperature requires a lot more sampling, and requires accounting for local
spatial changes (topo, vegetative, etc.) that getting the surface temperature anomaly does not.
No climate model can predict climate
changes at a local level where the effects are felt - predictions are only made for
averages collated at a continental
spatial scale and over periods of decades.
greenhouse forcing: a global
average change in LW radiative forcing (With some
spatial variation that can be understood from physics).
These range from simple
averaging of regional data and scaling of the resulting series so that its mean and standard deviation match those of the observed record over some period of overlap (Jones et al., 1998; Crowley and Lowery, 2000), to complex climate field reconstruction, where large - scale modes of
spatial climate variability are linked to patterns of variability in the proxy network via a multivariate transfer function that explicitly provides estimates of the spatio - temporal
changes in past temperatures, and from which large - scale
average temperature
changes are derived by
averaging the climate estimates across the required region (Mann et al., 1998; Rutherford et al., 2003, 2005).