WAMME-2: Land-Use Land-Cover Change (LULCC) Experiment
(summary)
The recent IGBP-iLEAPS and GEWEX-GLASS sponsored Land-Use and Climate
Identification of robust impacts (LUCID) experiment (Pitman et al., 2009; DeNoblet et
al., 2012) show considerably discrepancy among the models in terms of their response
to LULCC. In WAMME-2, we intend to provide basic understanding of impacts of
LULC change on the regional water cycle of the WAM/Sahel and to evaluate the
sensitivity of the seasonal and decadal variability of the West African climate to LULC
change. Our strategy is to apply observational data-based anomaly forcing, i.e.,
"idealized but realistic" forcing, in GCM and regional climate model (RCM) simulations.
Our change is roughly based on recent 50 year period using a combined crop and
pasture fraction changes from Hurt et al. (2011). We impose a simple LULC change
which represents a maximum feasible LULCC scenario and take the following steps to
achieve our goal:
1. Making consistent LULC changes in vegetation maps among models.
2. Proposing the modifications to each land class based on historical land use
change information, and possibly a set of surface parameters after careful
coordination with each of the different groups.
3. Maintain a consistent and monotonic meridional gradient of the LULCC in terms
of the surface vegetation distribution.
Within the WAMME-2 group, some participant models use similar land cover
classifications and the same LSM (such as SSiB and NOAH). It is hoped that this
should reduce some of the uncertainty and inter-model scatter that was found in the
LUCID experiment.
To determine the LULCC area, the combined crop and pasture area change
differences from 1950 to 2000 over West Africa (Fig..1) were derived from the LULCC
dataset produced by Hurtt et al., (2011). Distinguishing between pasture and crops is
difficult, since in reality farmers in much of this region graze their animals on cropland
after the harvest (P. Hiernaux, pers. com.). Using these differences as a guideline, we
define a mask (Fig. 2.) where changes in West Africa are the largest. We then impose
a simple set of land class change rules within this area. Note that compared to the
LULCC shown in Fig.2, we extend the mask to 20 N to ensure, as much as possible, a
consistent treatment regardless of spatial resolution of the different models.
In order to implement LULCC, we apply the basic idea that we degrade trees to
low vegetation or grasses, while we degrade low vegetation to bare soil. The basic
effect of land degradation is obtained through a reduction in surface roughness and
LAI, and an increase albedo. An example is shown for a dominant-class approach for
the COLA GCM in Fig. 3: we have changed classes 6 to 9 (broadleaf trees with ground
cover to broadleaf shrubs with bare soil), 7 to 11 (ground cover to bare soil) and 9 to
11 (broadleaf shrubs and bare soil to bare soil) over the masked zone.
Fig. 1 Combined crop and pasture area differences for selected recent periods over West Africa (Hurtt et
al., 2011). Negative areas correspond to land being abandoned (returning to a more natural reference
state).
Fig. 2 The masked
zone (purple) ranges
from the West coast to
35 E and 10 to 20 N,
and from -10 to 0 E and
the southern coast.
This is used as the
guideline for imposing
LULCC for WAMME-2.
a)
b)
Fig. 3 The default land class data for the COLA GCM are shown in panel a. In panel b, we have
changed classes 6 to 9 (broadleaf trees with ground cover to broadleaf shrubs with bare soil), 7 to 11
(ground cover to baresoil) and 9 to 11 (broadleaf shrubs and bare soil to bare soil) over the masked
zone.
An example for a tile-based LSM (CLM) is shown in Fig. 4. The left panel shows
the default CLM PFT fractions, while on the right panel, the modified PFT fractions
are shown. In order to be consistent with the LULCC imposed for the "dominant class
models", we have proposed changing the forest (PFTs 5 and 7) to grass (PFT 15),
and shrub (PFT 11) to baresoil (PFT 1) within the masked zone. Note however, that
we limit the grass PFT increases to a maximum of 30% to be roughly consistent with
the maximum land cover changes from Hurtt's data in this region (see Fig. 1).
a)
Control
b)
c)
Modified-Control Grass
d)
Modified
Modified – Control Bare soil
Fig. 4 Land class modification for a tile-based approach: example for CLM. In the masked zone, we
have transformed shrub to bare soil, and trees to shrub. Increases of any PFT are limited to 30%. In
the lower panels, the increases in Grass and Bare soil PFTs are shown (note the change in color
scale).
References
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