GSWP-2 Multi-Model Analysis
The multi-model analysis (MMA) from
GSWP-2 is the first global land-surface analysis of its kind, including
state variables, fluxes, and other land surface properties. This is in
many respects a land-surface analog to the atmospheric reanalyses in
that it represents a best estimate of conditions over an extended
period of the recent past. Using the results of multiple land surface models provides
a model-independent result that is superior the results of any
individual model, and typically as good as or better than the best
model at each point and time. Of particular value, this
multi-model analysis includes uncertainty estimates for all of the
fields, based on the inter-model spread.
The MMA covers the period from January 1986 through December 1995, at a spatial resolution of 1° by 1° on a regular latitude-longitude grid, including all land surface points north of 60°S according to the land-sea mask of ISLSCP Initiative II.
Not all of the 13 models necessarily contribute to the calculation of any particular variable. See the data inclusion chart for a list of which models contributed to which variables.
There are three categories of model output data provided in the GSWP-2 MMA:
Documentation of the common input data sets is also provided here:
- Monthly mean fields -
These include all of the relevant standard land surface model output
fields from GSWP-2 as listed by ALMA (120 time steps) as both means
among all models, and the inter-model standard deviations.
- Climatological monthly fields - These are the 10-year mean values of the standard ALMA fields for each month (12 time steps).
- Daily state variables - These are daily mean values for soil moisture and temperature at 6 levels.
- Model input data sets -
These are global 1° grids of land surface parameters and meteorological
forcing data used to specify initial conditions and boundary conditions (forcing)
for the participating land surface models.
- Documentation of the forcing data is available as COLA Technical Report #159.
Images of the monthly and
climatological MMA fields are also provided for browsing (click on the
variable name for a table of images):
Caveats about the data
In addition to the disclaimer regarding this
analysis, there are some specific issues with regard to the fields that users should be aware of:
Additional caveats are discussed in the text of the accompanying technical report.
has some bogus points, particularly over the deserts of Arabia and
North Africa, that are due to the lack of variability in time of deep
soil moisture affecting the normalization proceedure (these quantities
should average to zero over the 10-year period, but do not at these
- SurfStor and EWater each have only one model (SiBUC) contributing non-zero values, and are probably not representative of a multi-model extimate.
- WaterTableD refers to
the depth to the saturated zone in LSSs with TOPModel or similar
groundwater interactions, and is not analogous to actual water table
depths, especially outside of very humid regions.
- Many of the snow-related variables (e.g., SWE, SnowDepth)
show an unusually large range of values over permanent ice points
(e.g., parts of Greenland) which are largely the result of the behavior
of a single model.
- High precipitation amounts are found in some high-latitude
coastal areas (e.g., Norway, southeastern Alaska) particularly for
snow. This is a result of a combination of factors that led to an
overzealous wind correction for gauge undercatch in these regions.