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Figure 19.6 Comparison of phenological indicators from fi eld observations in Siberia
at 3 sites over 5 years with the remotely sensed indicators 'Start', 'Peak' and 'End' of
growing season. Remotely sensed indicators are highlighted with a diagonal fi ll
pattern. Shown is the mean Julian day of the events averaged over the years and sites.
Bars show plus/minus one standard deviation. Reprinted from Balzter, H., Gerard, F.,
Weedon, G., Grey, W., Combal, B., Bartholomé, E., Bartalev, S. and Los, S. (2007c)
Coupling of vegetation growing season anomalies with hemispheric and regional scale
climate patterns in Central and East Siberia. Journal of Climate , 20(15), 3713-29,
doi: 10.1175/JCLI4226. (C) Copyright 2008 American Meteorological Society (AMS).
ity because of a dimming and cooling effect from volcanic aerosols (Slayback et al.,
2003). This drop was greater at high latitudes and particularly pronounced in the
boreal biome, where Slayback et al. (2003) found NDVI trends between 1982 and
1999 to be almost zero, despite the evidence for a Northern Hemisphere greening
trend observed by Bogaert et al. (2002) using averaged NDVI values over the
growing season. Differences in remote sensing data processing and statistical methods
make direct comparisons between studies very diffi cult. Nevertheless, the increasing
length of available time series of remote sensing data offers tremendous new oppor-
tunities to detect changes in the biosphere.
Atmospheric gases
So far, this chapter has covered various remote sensing methods to characterise
terrestrial carbon pools and fl uxes, including forest biomass, land cover and fi re.
However, ultimately atmospheric greenhouse gas concentrations contribute to the
observed increase in global average temperatures (known as global warming).
Recently, a range of novel approaches has been developed to estimate atmospheric
greenhouse gas concentrations in the air column between the satellite sensor and
the ground. In 2002, the European Space Agency launched the ENVISAT satellite,
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