Using Flux Observations to Improve Land-Atmosphere Modelling: A One-Dimensional Field Study Robert Pipunic, Jeffrey Walker & Andrew Western The University of Melbourne Cathy Trudinger & Ying Ping Wang CSIRO Marine and Atmospheric Research Supported by an Australian Postgraduate Award Scholarship and University of Melbourne – CSIRO Collaborative Research Support Scheme
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Using Flux Observations to Improve Land-Atmosphere Modelling: A One-Dimensional Field Study Robert Pipunic, Jeffrey Walker & Andrew Western The University.
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Using Flux Observations to Improve Land-Atmosphere Modelling:
A One-Dimensional Field Study
Robert Pipunic, Jeffrey Walker & Andrew Western
The University of Melbourne
Cathy Trudinger & Ying Ping Wang
CSIRO Marine and Atmospheric Research
Supported by an Australian Postgraduate Award Scholarship and
University of Melbourne – CSIRO Collaborative Research Support Scheme
Synthetic Twin Experiments
21.2 21.9 0.018 3.0
52.2 37.4 0.0303.7
22.0 20.42.0
74.1 47.8 0.046 3.1
21.4 21.7 0.020 2.9
54.1 38.4 0.032 3.3
25.5 21.43.4
21.8 21.3 0.0201.7
56.6 36.1 0.032 2.4
0.017
0.013
LE (W/m^2) H (W/m^2) Root θ (v/v) Root Tsoil(˚C)
Model Outputs
Sta
cked
RM
SE
fro
m a
ll as
sim
ilati
on
ru
ns
Tskin fortnightly
Tskin 2-daily
θ every 3 days
LE&H fortnightly
LE&H 2-daily
H fortnightly
H 2-daily
LE fortnightly
LE 2-daily
Assimilation Runs
Pipunic et al., 2007. Remote Sensing of Environment, In Press.
Kyeamba Creek Experimental Site
3D sonic anemometer & open path gas analyser for LE & H, 3m above ground: 10Hz measurements, 30min averages recorded
Barometric pressure sensor: 1 reading per hourAir temperature & relative humidity probe, 2m above ground: 30min averages recordedWind direction and speed: 30min averages recordedTipping rain gauge bucket: 30min totals recorded4-way radiometer, incoming & outgoing shortwave & longwave radiation: 30min averages recorded
Below the Ground
30cm
60cm
90cm
8cm
(Not to scale)
CS615 Soil Moisture Probes: Measuring every 30 mins
Soil heat flux plates: 30min averages recorded
5cm10cm2cm
20cm
50cm
100cm
Soil temperature probes: Measuring every 30 mins
CSIRO Biosphere Model (CBM) / CABLE
Long Wave Radiation
Short Wave Radiation
Precipitation
LEH
CO2
G Snow
(Not to scale)
L1L2
L5
L4
L3
L6
Wind
Canopy model (Wang & Leuning, 1998):
• LE, H and CO2 for a ‘sunlit’ and a ‘shaded’ leaf canopy;
• LE and H calculated from both vegetation and bare soil based on fraction of transmitted radiation through canopy.
Six computational soil layers using the soil and snow scheme by Kowalczyk et al. (1994):
• Uniform properties for all layers;• Individual volumetric moisture and
temperature - moisture governed by Richard’s equation.
Ensemble Member Generation
obsnew yyPerturbing meteorological variables:
Random number generated at each time step in series, zero mean
Random number generated once for each ensemble and applied to whole series, zero mean
Air Temperature Ensembles
05
1015202530354045
0 1 2 3Days
Tem
per
atu
re (
Deg
.C)
Ensemble MembersObserved Series
Turner et al., 2007. Remote Sensing of Environment, In Press.
Assimilation Over 1 Year Period (2005)• LE+H assimilated on MODIS timescale – twice a day where SW
radiation is >500Wm-2 (representing no cloud cover).
• Surface soil moisture on SMOS timescale – every 3 days.
Offline - Spun-upObserved Root Zone MoistureSurface Soil Moisture AssimilationLE+H Assimilation
0
10
20
30
40
50
0 60 120 180 240 300 360Days
Ro
ot
Zo
ne
Te
mp
era
ture
(D
eg
.C)
Summary of Results
0.29
113.187.6
0.12
140.2103.1
LE (W/m^2) H (W/m^2) Root ZoneSoil Moisture
(Vol/Vol)
Sta
cked
RM
SE
fro
mb
oth
ass
imil
atio
n r
un
s
Surface SoilMoisture
LE+H
Assimilation Runs
Conclusions
• LE and H assimilation results are better than SM results for estimating LE and H, but slightly worse for soil moisture
• The land surface model used exhibits soil moisture and temperature biases when using standard parameters and forcing; this is likely to be typical of most NWP land models
• Temperature and moisture biases need to be accounted for using a bias-aware assimilation approach