Geography Reference
In-Depth Information
its rough resolution is inappropriate to reveal the land surface-atmosphere inter-
actions for regional simulation cases. Importantly, it is worth pointing out that the
entire Amazon forests have been entirely converted into less vegetated lands in
terms of pasture, savanna, and cropland in the GCMs performances. Though this
unrealistic assumption could help to understand the importance of tropical
deforestation to regional and global climate changes as a whole, it is unable to help
reveal the regional anthropogenic climate changes mechanism. In contrast,
although the regional climate models (RCMs) with higher resolution are better at
revealing the mesoscale effects of land surface changes on regional climate vari-
ability, the potential climate uncertainties induced by future land surface modifi-
cation and vegetation alteration are still far from known.
Thus, the scientific objective of this case study is to estimate the potential
impacts of future tropical deforestation on regional climate changes in Brazilian
Amazon during 2090-2100 with WRF model performance. For this purpose, a
relative rational underlying land surface with high resolution should be projected
firstly. Given the observations and investigations showed that remarkable progress
in curbing tropical forests recession has been made in recent years, the prevailing
unreasonable land surface scenarios in which the entire forests are replaced with
lower coverage vegetation would not be used in this part. We analyze the char-
acteristics of forest land conversion between 2005 and 2100, and then the land
surface map in particular years could be identified. Thereafter, the control and
simulation experiments are designed for WRF modeling.
7.3.1 Data and Methodology
7.3.1.1 Data
The data used in this part include land surface data and lateral climate forcing
data. The respectable land cover product, generated by the GCAM model under
the state-of-the-art scenario (RCPs), is used to analyze the land cover conversions,
such as the changing trend and the fraction, which is critical to project the future
land surface properties (Hurtt et al.
2011
). These data harmonized the historical
land uses and the future land surface scenarios for studying the anthropogenic
impacts and the annually fractional landscape patterns and land surface transitions
for the period 1500-2100 at 0.58 9 0.5 8 resolutions. For the purpose of this
study, the forest land conversions during the period from 2005 to 2100 will be
identified.
There are three steps to predict and generate the future land surface maps.
Firstly, the fraction of transitioned cells that converted from the primary forest
and the secondary forest into other land cover types, including cropland, pasture,
