The 29th CDPW, Madison, Wisconsin, Oct. 18-22, 2004

The 29th CDPW, Madison, Wisconsin, Oct. 18-22, 2004

The 29th CDPW, Madison, Wisconsin, Oct. 18-22, 2004

Global Land Surface Memory and Its Impacts
Yun Fan, Huug van den Dool & Peitao Peng
CPC/NCEP/NOAA
http://www.cpc.ncep.noaa.gov/soilmst/index.htm

1

Motivation &
Background

4

Temporal & spatial evolution

5

Land Surface Memory & its impacts

The lower boundary condition of the atmosphere, such as SST, soil moisture
and snow cover often have a longer memory than weather itself. Land surface
processes play an important role in weather and climate prediction. In order to
improve our understanding of land surface-atmosphere interaction on different
time scales, we need to improve our understanding of the land surface
hydrological & energy cycles. Also to further improve weather forecast &
climate prediction, we need more accurate land initial conditions.

2

Auto correlations of the global
land surface soil
moisture,which show that cold
seasons and dry areas often
have longer memory than those
in warm seasons and wet areas.

Model & Data
The soil moisture budget (Huang et al 1996) over an area A:

dW (t )
P(t ) E (t ) R(t ) G (t )
dt
Where W(t) is soil water content
R(t) net streamflow divergence

P(t) precipitation

The maximum & minimum land surface soil
moisture and the months of these extremes
take place.

Difference of March & September soil
moisture climatology, which shows two
kinds of climates and annual range of
land surface soil water variability.

Local correlations of the land
surface soil moisture and the
land surface air temperature
in next month show local
impacts of the soil moisture
on the land surface air
temperature.

E(t) evapotranspiration

G(t) net groundwater loss

Forcing Data:
-CPC Monthly Global Precipitation Over Land
-Monthly Global Reanalysis/CDAS 2m Temperature
Data Coverage:

3

S outheast China

56+ years (1948-present)

Bengal

CPC soil moisture monitor & prediction activities
Drought & flood monitoring
Empirical forecast tools (Constructed Analog)
GFS forecast & climate prediction

The annual cycle (right) & anomalies (left) of the observed (black) and simulated (green)
top 1 meter column soil moisture in north, central & south Illinois from 1984 to 2004.

Recent CPC global soil moisture status

Non-local correlations of the land surface soil moisture (southeast China or Bengal)
and the global land surface precipitation and air temperature show the non-local
impacts of the land surface soil moisture.

6
Seasonal variation of the land surface water recharge or discharge. Monsoon is the
dominant feature.

Simulated extreme hydrological events

EOFs & PCs of the
global lower boundary
(normalized SST and
soil moisture) for
March 1950-2003. Both
the El-Nino Southern
Oscillation and long
term trend modes are
clearly seen in the
leading EOFs & PCs of
combined SST and soil
moisture..

Summary & Future Work
An accurate and homogeneous global lower boundary condition is very important
for weather and climate predictions.
The preliminary results show that the CPC global (near real time) soil moisture
dataset can reasonably reproduce the annual cycle & interannual variability of the
observed soil moisture, when compared to Illinois observations and GRACE
satellite data. The simulated land surface hydrologic cycle and extreme events
also look realistic.
Future Work
Need more detailed data validation & analysis. Add a simple cold season physics in near future.
Model comparisons (e.g. With RR, Noah LSM and VIC LSM etc. ).
Demonstrate more detailed non-local impacts of soil moisture & prediction experiments etc.

Reference:
Fan, Y., H. van den Dool, 2004: Climate Prediction Center global monthly soil moisture data set at 0.5 degree resolution
for 1948 to present. J.Geophys.Res. 109, D10102, doi:10.1029/2003JD004345
H. van den Dool, J. Huang, and Y. Fan, 2003: Performance and analysis of the constructed analogue method applied to
U.S. soil moisture over 1981-2001. J. Geophys. Res., 108(D16), 8617, doi:10.1029/2002JD003114
Huang, J., H. van den Dool, and K. G. Georgakakos, 1996: Analysis of model-calculated soil moisture over the US (19311993) and applications to long range temperature forecasts. J.Climate, 9, 1350-1362.
Also see the poster by Huug van den Dool et al for the latest GRACE data comparisons.

Acknowledgment: This project was supported by the GCIP Grant (GC00-095) and GAPP
Grant (GC04-039).

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