 |
| Titel |
Detecting causation mechanisms of soil moisture patterns in Germany |
| VerfasserIn |
Luis Samaniego, Rohini Kumar, Matthias Zink, Kirsten Warrach-Sagi, Volker Wulfmeyer |
| Konferenz |
EGU General Assembly 2013
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250078053
|
|
|
|
|
|
| Zusammenfassung |
| Detecting trends, feedbacks, and causation mechanisms in hydrometeorologic variables such
as soil moisture is a challenging task because of the nonlinear dynamics of the
atmosphere-land-vegetation system, the assimilation of noisy observations, and the structural
and parametric uncertainty of land surface models (LSM). Quite often, wrong conclusions
can be drawn because uncorrelated variables may be assumed to have no causal relationship
with presupposed predictors.
The main goal of this study is to test whether a significant “Granger causality” (Granger
1969) exist between monthly soil moisture fields over Germany and large-scale circulation
patterns, characterized by anomalies of sea level pressure over the Northern Hemisphere or
geopotential height and atmospheric humidity over Europe. The advantage of this
testing framework stems from the fact that it is based on predictability instead of
correlation to identify causation, as it is the case with standard correlation-based
approaches.
Two contrasting modeling paradigms, the land surface NOAH model and the
process-based hydrologic model mHM (Samaniego et al. 2012) are employed to
estimate daily soil moisture over Germany during the period from 1989 to 2009.
WRF/NOAH was forced with ERA-Interim data at the boundary of the EURO-CORDEX
Region
(www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11°. To ease
comparison, mHM was also forced with daily precipitation and temperature fields generated
by WRF during the same period at 4Ã4Â km resolution. Main physiographic characteristics in
NOAH such as land cover and soil texture are represented with a 1Ã1Â km MODIS data set
and a single horizon, coarse resolution FAO soil map with 16 soil texture classes,
respectively. The multiscale parameter regionalization technique (MPR, Samaniego et al.
2010) embedded in mHM allows to estimate effective model parameters based
on detailed input data (100Ã100Â m) obtained from Corine land cover and soil
texture fields for various horizons comprising 72 classes. mHM global parameters,
in contrast with those of NOAH, were obtained by closing the water balance in
major German river basins. For the "Granger causality" test, variables such as sea
level pressure or geopotential height at 500 hPa (dss.ucar.edu/datasets/ds010.0/,
data-portal.ecmwf.int/data/d/interim_daily) are used as predictor fields including the lagged
values of these variables.
Results indicate that the subgrid variability of the land surface properties and the
parametrization schemes have greater influence on soil moisture simulations. Mann-Kendall
tests performed with mHM data indicated the existence of a negative trend (p-value 5%) in
soil moisture during summer months which is the consequence of observed downward trend
in precipitation and upward trend in temperature. On the contrary, soil moisture simulations
in winter months did not exhibited significant trends. The Granger-causation mechanisms of
these trends are under investigation. |
|
|
|
|
|
|