The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
Figure 7-a shows surface soil moisture (black), with the yearly
mean reproduced for all years (orange), for a location near
Sainshand, southeast Mongolia. The difference between the
surface moisture and the mean is shown in figure 7-b. Rainfall-,
snow and temperature information has been available from
ground stations (7-c). Figure 8-d depicts the total precipitation
in mm (black line) and the number of rainy days per year (pink
line). It can be noted that after the data gab from 2001-2005 (7-
a, 7-b) the surface moisture signal is much lower than during
the measuring period before. The decrease is not sensor related.
This behaviour could be observed from numerous locations in
eastern Mongolia (which also all show a decrease in the number
of rainy days and precipitation in mm), such as the stations in
Bajndelger and Barum-Urt, while other areas in other countries
show a completely different behaviour.
vWWVWVWAW
-UÄ М.л M як JJL JiL-JLi, álu «*&$...; Ш »J, м.
ÂTJt
°i
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1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 7: Surface soil moisture development for a station near
Sainshand, Inner Mongolia, a) surface moisture (black) and
long term mean (orange), b) difference between the two, c)
ground station information d) precipitation and number of rainy
days.
4. CONCLUSION
Usually, the derivation of trends, analyzed under the scope of
climate change phenomena or related studies is performed on
time series of 20+ years. One could thus argue that the TU
Wien soil moisture time series is not yet long enough to derive
meaningful trends. However, previous studies, anomaly
analyses and the finding of this study indicate that the soil
moisture time series processed by TU Wien has a large
potential for long term trend analyses. It is the only time series
of its kind existing since 1992. Results presented within
grassland- and savannah-dominated areas clearly indicate
regions, which have become drier or wetter over time. These
findings could be verified through available in-situ data for a
few selected sites. Currently the ERS-Scatterometer based time
series is being extended and reprocessed with first data derived
from the METOP Advanced Scatterometer (Ascat). Therefore,
the extension and continuity of the time series based on two
sensors is guaranteed. Even though spatial coverage is not
always global, and temporal gaps do exist, the time series
allows for the observation of short term trends, and the
detection of the onset of probable long term trends. Furthermore,
the time series clearly reflects all global deviating events such
as strong droughts, floods, or El Niño events. We propose to
investigate the TU Wien dataset further, focussing on medium-
to long-term trend analyses and frequency analyses of
anomalous events.
ACKNOWLEDGEMENTS
The authors thank Klaus Scipal (ECMWF) for many valuable
ideas and comments.
Figure 8 shows a similar plot for a location in Northeast
Australia near Palmerville. According to this figure there is a
slight increase in surface moisture especially since 1998 (8-b:
curve is starting to slightly move upwards compared to the
zero-line) However, this is only a shorter phenomenon, which
can not be further observed after 2001 (no data).
SELECTED BIBLIOGRAPHY
Ceballos, A., Martinez-Femandez, J., Santos, F., and Alonso, P.,
2002. Soil Water Behaviour of sandy soils under semi-arid
conditions in the Duero Basin (Spain), J. Arid Env., 51, pp.
501-519.
Figure 8: Surface soil moisture development for a station near
Palmerville, Australia, a) surface moisture (black) and long
term mean (orange), b) difference between the two, c) ground
station information d) precipitation and number of rainy days
(from Australian quality controlled rainfall data, available daily
since the 1890’s from the Australian Bureau of Meteorology)
De Ridder, K., 2000, Quantitative estimate of skin soil moisture
with the Special Sensor Microwave/Imager, Bound-Lay. M, 96,
pp. 421-432.
Engman, E.T. and Chauhan, N., 1995. Status of microwave
soil moisture measurements with remote sensing.
Remute Sensing of Environment, 51, pp. 189-198.
Hollinger, S.E., and Isard S. A., 1994. A Soil Moisture
Climatology of Illinois, Journal of Climate, 7, pp. 822-833.
Jackson, T.J., Le Vine, D.M., Hsu, A.Y., Oldak, A., Starks, P.J.,
Swift, C.T., Isham, J., and Haken, M., 1999. Soil moisture
mapping at regional scales using microwave radiometry: The
southern Great Plains Hydrology Experiment. IEEE
Transactions on Geosciences and Remote Sensing, 37, pp.
2136-2151.
Jackson, T.J., 1993. Measuring surface soil moisture using
passive microwave remote sensing. Hydrologic Processes, 7, pp.
139-152
Knabe, S., 2004. Erfassung der räumlichen und zeitlichen
Veränderung von Bodenfeuchtemustem in semiariden Gebieten