evaluating a tiled land-surface model with multi-site energy flux observations
DESCRIPTION
Evaluating a tiled land-surface model with multi-site energy flux observations. A. Nordbo 1 , A. Manrique-Sunen 2 , G. Balsamo 2 , I. Mammarella 1 , and A. Beljaars 2. 1 University of Helsinki, Finland 2 European Centre for Medium-Range Weather Forecasts. - PowerPoint PPT PresentationTRANSCRIPT
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Evaluating a tiled land-surface model with multi-site energy flux observations
A. Nordbo1, A. Manrique-Sunen2, G. Balsamo2, I. Mammarella1, and A. Beljaars2
21.04.23 1
1 University of Helsinki, Finland2 European Centre for Medium-Range Weather Forecasts
Acknowledgements: Leena Järvi, Pasi Kolari, Samuli Launiainen, Jussi Huotari, Anne Ojala, Timo Vesala
Department of Physics / Annika Nordbo / Evaluating a tiled land-surface model with multi-site energy flux observations
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• Resolution of NWPs not sufficient for resolving smaller scale surface heterogeneities
→ represented by coupling tiles (different surfaces) with one atmospheric column
• research on the pros and cons of this type of coupling is scarce
• current loading of the ECMWF surface scheme is 1.7% of computational power
• AIM: To run ECMWF surface scheme offline with ERA-Interim forcing and compare results with measurements from 3 distinct sites
→ is tiling worthwhile?
1. Background
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2. Methods
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• Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land HTESSEL (cycle 37R1 )
• currently 6 tiles over land; lakes considered only if fraction >50%
• estimates surface water and energy fluxes, soil temperature and water content
• LAKEHTESSEL (Dutra et al. 2010) includes lake model Flake (Mironov 2008)
• no urban scheme
• year 2006 (each run iterated 3 times)
2.1 Models
Balsamo et al. 2011
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2.2. Measurement sites
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SMEAR II, Hyytiälä
Lake Valkea-Kotinen
SMEAR III, Helsinki
Eddy-covariance technique for flux measurements
‒ 49-year-old Scots pine stand
‒ extinction coefficient 3.0 m-1
‒ depth 4 m, area 0.041 km2
Järv
i et a
l. 20
09N
ordb
o et
al.
2011
Laun
iain
en e
t al.
2010
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• Forcing: ERA-Interim reanalysis
•T255, 80 km grid
•10m height
• Forest: geographical information:
•Integrated Forecast System
•T1279, 16km grid
•75% tall vegetation, 8% bare ground, 17% lakes (not considered)
• Lake: run with 100% lake fraction
• Urban: no runs
2.3 Forcing & run details
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Comparison of forcing data from ERAI and observations10-day running means
31m
1.5m16.8m
1kPa
Lake higherForest lower
ERAI20 Wm-2 higher
lakelower in springhigher in fall
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2.4. Surface energy balance
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Rn
G
H LE
Turbulent fluxes (eddy-covariance)
Mixed layerThermocline depth
Department of Physics / Annika Nordbo / Evaluating a tiled land-surface model with multi-site energy flux observations
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3. Results
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3.1 Water temperature
Thermocline deepens
towards fall
Isothermal under ice
ice melting 8 days late
Measured Modeled
Inverse stratification
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3.2 Energy fluxesNet radiation, average diurnal courses per month
Lake: modeled Rn larger
Forest: modeled Rn smaller
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Heat storage change , average diurnal courses per month
21.04.23 12Matemaattis-luonnontieteellinen tiedekunta / Henkilön nimi / Esityksen nimi
Lake: modeled amplitude larger
Forest: fluxes tiny
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21.04.23 13Matemaattis-luonnontieteellinen tiedekunta / Henkilön nimi / Esityksen nimi
Model ice-out 8 days late
Ice/snow
Measurements include only
heat storage in ground
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Sensible heat flux , average diurnal courses per month
Urban: largest
Lake: tiny, different phase
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heat to the water -> ice-out
Forest: modeled smaller in spring
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Latent heat flux , average diurnal courses per month
Forest: more evaporation in spring and less
in summer
Lake: huge evaporation in model all the time -> huge
vapor pressure deficit
Lake: nocturnal evaporation 50 Wm-2
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21.04.23 17Matemaattis-luonnontieteellinen tiedekunta / Henkilön nimi / Esityksen nimi
Forest: modeled larger
in spring
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• FLake gives an isothermal temperature profile under ice though water really inversely stratified → reason for late ice melting?
• Does tiling work with very different surfaces (lake-vegetation)?
4. Summary and discussion
Fluxes Forest Lake Urban
Rn ERAI SWdown larger, LWdown smaller (less clouds), different albedos important
G A lot smaller than at lake Large seasonal heat storage change, time of ice-out important!
-
LE Transpiration, modeled energy partitioning different in spring
Night-time evaporation important, large ERAI water vapor deficit induces too much evaporation
Impervious surfaces
H Same order of magnitude and in phase with LE
Tiny and out of phase with LE Anthropogenic heat flux
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• run for lake using closer ERAI forcing• runs with higher level forcing (30m & 60m)
→ how does tiling work now?• runs using real measurements
→ how much of the error is attributed to ERAI forcing?
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5. Future
Department of Physics / Annika Nordbo / Evaluating a tiled land-surface model with multi-site energy flux observations
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21.04.23 20Matemaattis-luonnontieteellinen tiedekunta / Henkilön nimi / Esityksen nimi
Annika Nordbo
Department of physics
P.O.Box 48
FI – 00014 University of Helsinki
+358 50 415 4830
www.tinyurl.com/HelsinkiMicromet
Danke!
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Balsamo G., S. Boussetta, E. Dutra, A. Beljaars, P. Viterbo, B. Van den Hurk (2011) Evolution of land-surface processes in the IFS. ECMWF Newsletter No. 127.
Dutra E., Stepanenko V.M., Balsamo G., Viterbo P., Miranda P.M.A., Mironov D., Schär S. (2010) An offline study of the impact of lakes on the performance of the ECMWF surface scheme. Bor. Env. Res. 15: 100-112.
Järvi, L., Hannuniemi, H., Hussein, T., Junninen, H., Aalto, P.P., Hillamo, R., Mäkelä, T., Keronen, P., Siivola, E., Vesala, T. and Kulmala, M. (2009). The urban measurement station SMEAR III: Continuous monitoring of air pollution and surface-atmosphere interactions in Helsinki, Finland. Boreal Environ. Res., 14, 86-109.
Launiainen (2010) Seasonal and inter-annual variability of energy exchange above a boreal Scots pine forest. Biogeosciences, 7, 1–20.
Mironov D. (2008) Parameterization of Lakes in Numerical Weather Prediction, Description of Lake Model. Technical Report No. 11. Deutsche Wetterdienst.
Nordbo A., S. Launiainen, I. Mammarella, M. Leppäranta, J. Huotari, A. Ojala, T. Vesala (2011) Long-term energy flux measurements and energy balance over a small boreal lake using eddy covariance technique. J. Geophys. res. 116:1-17. doi:10.1029/2010JD014542
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References
Lake Valkea-Kotinen also in the Lake intercomparison project (LakeMIP)www.unige.ch/climate/lakemip/index.html
Department of Physics / Annika Nordbo / Evaluating a tiled land-surface model with multi-site energy flux observations