CEOP/GLDAS integration to evaluate land surface model performance
The Coordinated Enhanced Observing Period (CEOP) is an
international effort intended “to understand and model the influence of
continental hydroclimate processes on the predictability of global atmospheric
circulation and changes in water resources, with a particular focus on the heat
source and sink regions that drive and modify the climate system and anomalies”
(Koike 2004). This is an ambitious goal, and it requires the effective
integration of field observation, satellite data, and modeling systems. GLDAS
is a valuable tool for CEOP because it assimilates the information from a
number of models and observation systems to provide optimal estimates of land
surface states and fluxes. These products are used to support regional climate
analysis, model initialization, and globally-consistent intercomparisons
between CEOP field sites. At the same time, the detailed field data collected
during CEOP can be used to evaluate the land surface models (LSMs) included in
GLDAS and to inform future model development.
Sample application
One of the strengths of CEOP/GLDAS integration is the
ability to evaluate the performance and sensitivity of land surface models at
diverse sites around the globe. Kato et al. (2007) applied GLDAS to assess LSM
performance at four CEOP sites. Simulations with Noah LSM, Mosaic LSM, and
Common Land Model were compared with CEOP observations for a temperate
grassland (Lindenberg, Germany), a semi-arid cropland (Tongyu, China), a temperate cropland (Bondville, Illinois), and a wet temperate forest (Tumbarumba, Australia) (Figure 1). Each LSM was then used in a set of numerical experiments, designed to assess
model sensitivity to various sources of simulation uncertainty, including input
data on elevation, soils, land cover, precipitation, and radiation (Table 1).
Results indicated that the simulation of evapotranspiration was most sensitive
to precipitation, land cover, and radiation (in that order), sensible heat flux
was most sensitive to radiation, precipitation and land cover, and soil
moisture was most sensitive to precipitation, soil, and land cover. In
general, radiation was a more important source of sensitivity in energy-limited
regimes while precipitation was of primary importance in water-limited regimes.
Nonetheless, the selection of LSM was generally the most important factor
governing output, indicating the need for continued model development.

Figure 1: Monthly accumulated
evapotranspiration (mm/month) from October 2002 to September 2003. Lines
represent the CEOP reference site observations (blue) and control run output
from the three LSMs: Noah (orange), CLM (pink), and Mosaic (turquoise). [From
Kato et al. (2007)]

Table 1: Sensitivity by model,
represented by the normalized RMS of the difference between output from the
experimental simulation and the control, for evapotranspiration, sensible heat
flux, and top layer soil moisture. Differences were normalized by dividing by
the seasonal mean of the control, thus the numbers are unitless. The type of
sensitivity is indicated by the column heading. Results were averaged over the
entire period, 1 October 2002 to 30 September 2003. Results for the
precipitation and radiation experiments were also averaged over the two
alternative forcings tested for each. Table cells are colorized to guide the
reader's eyes, with the highest sensitivity for a given row (site and season)
shown in red, followed by orange, yellow, green, and blue in order of
decreasing sensitivity. [From Kato et al. (2007)]
References
Kato, H., M. Rodell, F. Beyrich, H. Cleugh, E. van Gorsel,
and H. Liu, 2007: Sensitivity of land surface simulations to model physics,
land characteristics, and forcings, at four CEOP sites. Journal of the
Meteorological Society of Japan, 85A, 187-204.
Koike, T., 2004: The Coordinated Enhanced Observing Period—An
initial step for integrated global water cycle observation. WMO Bull., 53
(2), 115–121.
Relevant links
General information: CEOP,
GLDAS
GLDAS at GES DISC: ftp://agdisc.gsfc.nasa.gov/data/s4pa/GLDAS_SUBP/