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Global soil moisture analysis at DWD. Introduction. Long term experiment. Evaporation from plants is described in a derived form of the penman combination formula: - PowerPoint PPT Presentation
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Hess, R. 2001: Assimilation of screen-level observations by variational soil moisture analysis. Meteorol. Atmos. Phys. 77, 145-154.Jacobs, C.M.M. and H.A.R. De Bruin, 1992: The Sensitivity of Regional Transpiration to Land-Surface Characteristics: Significance of Feedback. J. Clim. 5, 683-698.Mahfouf, J-F. 1991. Analysis of soil moisture from near-surface parameters: A feasibility study. J. Appl. Meteorol. 30: 1534-1547.
Conclusions and OutlookFig. 1 shows the corresponding change of 2m
temperature at 12:00 UTC compared to average latent
heat flux for the last hour before noon. The good
correlation is obvious and justifies the linear
approximations.
Latent heat flux from plants Evaporation processes are simulated in the soil model
part TERRA for bare soil and for plants separately with
the latter one clearly dominating in most regions of
Europe period during the vegetation period. Bare soil
evaporation however is an important process over arid to
semiarid regions.
Surface energy balance
Net short wave incoming solar radiation is balanced by
latent, sensible, and ground heat flux. Assuming small
variations in soil water the main modification is on the
partitioning between latent and sensible heat.
Using the definition of sensible heat, a constant flux
approximation between 2m and first model level and the
assumption that small variations in T2m are proportional to
variations in surface temperature Ts, we get a relation
between the variation in T2m and latent heat flux.
Evaporation from plants is described in a derived form
of the penman combination formula:
Epot is the potential evaporation, rla and ra are the
aerodynamic resistances for moisture transport from
the leaves to the canopy air and from canopy air to
the first atmospheric layer of the model respectively.
The stomatal resistance describes the transport
through the plants into the canopy air and contains the
dependence on root zone soil water content.
Calculating the sensitivity Lhfl/w, by using the
derivative /w of 5) and inserting this into 3) we get
an analytical expression for the sensitivity T2m/w:
The sensitivities calculated for evaporation from plants
and bare soil are implemented in a variational soil
moisture assimilation scheme (SMA) that is principally
based on the SMA for the COSMO system (Hess, 2001)
and adapted for the global GME model system. Figure 3
shows results for a long term experiment with SMA
compared to the reference run without SMA. A clear
reduction of the bias and standard deviation of 2m
temperature during the spring to summer period is
found. Good results are also achieved for 2m relative
humidity and a positive impact on the geopotential in the
boundary layer is found as well (not shown). However
soil moisture (Fig 3b) generally looses seasonal
variability due to a systematic compensating effect of
the positive summer temperature bias.
Small errors in the daily forecast of precipitation, evaporation and runoff accumulate to uncertainties of soil water content
and lead to systematic biases of temperature and humidity profiles in the boundary layer if no corrections are applied.
To prevent from such drifts a new soil moisture assimilation scheme has been developed that runs operationally in the
GME assimilation cycle since March 2011. As many other variational schemes implemented at different NWP centers
(e.g. Canadian Met Service, DWD, ECMWF, Meteo France) the scheme is based on minimisation of screen level forecast
errors by adjusting the soil water content, and implicitly correcting the partitioning of available energy into latent and
sensible heat.
The original method proposed by Mahfouf (1991) and described in Hess, 2001 requires at least two additional model
forecast runs to calculate the gradient of the cost function i.e. the sensitivity T2m/w with T2m as 2m temperature and w as
soil water content of the respective top and bottom soil layers. To overcome this computational costly approach in the
new scheme the sensitivity of screen level temperature on soil moisture changes is parameterized with derivatives of
analytical relations for transpiration from vegetation and bare soil evaporation as motivated by Jacobs and De Bruin
(1992). The comparison of both methods shows high correlation of the temperature sensitivity under conditions of
moderate to strong soil-atmosphere coupling that justifies the approximation.
Fig. 3: Verification of 2m temperature and soil water content in an experiment with SMA compared to the reference run without SMA.
Parameterisation of sensitivity T2m/w
Global soil moisture analysis at DWD
Introduction
GShflLhflRnet
ShflLhfl
m
a
pT
r
cLhfl 2
Lhfl (W/m2)
T2m
(K)
Lai
slaa
apotsnowipl
f
rrr
rEfffLhfl
)1)(1(
tlppwpfcap
pwproothumtemradssss fww
wwFFFrrrr
)()( 1
max,1
min,1
max,1
1)
2)
3)
4)
5)
6)root
rootk
pwproot
s
s
s
LAIfap
a
k
m
z
dz
ww
r
r
r
frr
Lhfl
c
r
w
T ,
max,
2 )1(1
)(1
Figure 1: Variation of T2m with soil moisture change correlates well with variation of latent heat flux
Sensitivity T2m/w
This formula was compared with sensitivities
calculated from finite differences of real model runs as
described for equation 3). Figure 2a) shows general
good correlation when all grid points are taken into
account. This can even be improved when only grid
points with latent heat flux over a given threshold are
considered (2b).
Figure 2: Parameterised sensitivity T2m/w compared to sensitivity calculated from explicit model forecast runs with modified initial soil moisture content for a radiation day over Europe. See text for details.
Long term experiment
This relation is validated with the COSMO model for a
day with radiation conditions over central Europe
by running 81 model forecasts with initial soil moisture in
the range between plant wilting point and field capacity.
Soil wetness index SWI=(w-wpwp)/(wfcap-wpwp) for top (0-10
cm) and bottom layer (10-100 cm). was changed between
0 and 1 in steps of 0.125.
No further need for additional model runs !
• A parameterisation of the sensitivity T2m/w has been
developed to overcome the computational costs of
additional forecast runs in the variational SMA for GME.• The method has proven capability to improve near
surface parameters and is operational since March 2011.• Degradation of soil water content due to systematic biases
requires modification of physical parameterisation.
a) b)
References
01 Mar 01 Apr 01 May 01 Jun 01 Jul 01 Aug 01 Mar 01 Apr 01 May 01 Jun 01 Jul 01 Aug
W_S
O (
mm
)
Year 2009 Year 2009
a) b)
dT2m(12:00)/dwb(0:00) (model)
dT
2m
(12
:00
)/d
wb
(0:0
0)
(pa
ram
.)
dT2m/dwb (model)
dT
2m
/dw
b (
pa
ram
.) Lhfl<200W/m2