James, I was mainly responding to the idea of finding
spatial patterns related to forcing discrepancies over the past 20 years.
In addition, the alerts may be of value to a variety of researchers who study both temporal and
spatial patterns related to tree cover loss areas.
Not exact matches
The
spatial patterns of forest harvesting intensity were well explained by forest - resource
related variables (i.e., the share of plantation species, growing stock, forest cover), site conditions (i.e., topography, accessibility), and country - specific characteristics, whereas socioeconomic variables were less important.
It is striking to what extent they resemble the
spatial pattern seen in the AR4 ensemble free - running version rather than the initiallised forecast, though there are also some correlations there too (for instance, west of the Antarctic peninsula,
related to the ozone - hole and GHG
related increase in the Southern Annular Mode).
This appears to be
related to a poor representation of the
spatial relationships between rainfall variability and zonal wind
patterns across southeast Australia in the latest Coupled Model Intercomparison Project ensemble, particularly in the areas where weather systems embedded in the mid-latitude westerlies are the main source of cool - season rainfall.
Spatial patterns of loss and gain showed contrasting latitudinal
patterns, with a westward range shift of species around the species - rich equatorial transition zone in central Africa, and an eastward shift in southern Africa; shifts which appear to be
related mainly to the latitudinal aridity gradients across these ecological transition zones
As Mike noted, we should stay focused on the suite of (very interesting and) important scientific questions raised by this post — especially those
related to the idea of
spatial / temporal
patterns of climate data in relation to concepts and models of their likely physical causes.