Not exact matches
«Climate
change will lead to
spatial shifts in the suitability of malaria transmission, with the total area in Africa becoming unsuitable for malaria matching or even exceeding the total area
where malaria will become more suitable,» he said.
Paraphrasing the text in the post, aerosols that are input into the atmosphere, due to their
spatial heterogeneity, also cause regions of heating or cooling that the atmosphere can respond to by
changing its circulation — and that might have further climate effects in places far away from
where the aerosols are input.
Highlighting the
spatial depth, Fish often
changes the importance of the foreground and background which results with unexpected
spatial effects like in the painting Dog Days (1993)
where the figure of the dog seems smaller than the watermelon pieces on the table in the foreground.
See e.g. this review paper (Schmidt et al, 2004),
where the response of a climate model to estimated past
changes in natural forcing due to solar irradiance variations and explosive volcanic eruptions, is shown to match the
spatial pattern of reconstructed temperature
changes during the «Little Ice Age» (which includes enhanced cooling in certain regions such as Europe).
A slowly evolving
change in the circulation may thus lead to seemingly abrupt
changes in precipitation in regions
where the existing
spatial gradients in rainfall are largest.
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.
Since it takes several hundred years for the deep ocean water to cycle up to the top,
where it can be warmed up and lose CO2, it makes sense to suppose that if a warming event is initiated by something else (like
changes in the amount and
spatial distribution of incoming solar radiation,) the concomitant rise in atmospheric CO2 (which would enhance the initial warming) might lag behind by several hundred years.
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).