Evaluating a tiled land-surface model with multi-site energy flux observations

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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


• 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

21.04.23 2Department of Physics / Annika Nordbo / Evaluating a tiled land-surface model with multi-site energy flux observations


2. Methods



• 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


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


• 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



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


2.4. Surface energy balance

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Rn

G

H LE

Turbulent fluxes (eddy-covariance)

Mixed layerThermocline depth



3. Results



3.1 Water temperature

Thermocline deepens

towards fall

Isothermal under ice

ice melting 8 days late

Measured Modeled

Inverse stratification

3.2 Energy fluxesNet radiation, average diurnal courses per month

Lake: modeled Rn larger

Forest: modeled Rn smaller


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


Model ice-out 8 days late

Ice/snow

Measurements include only

heat storage in ground

Sensible heat flux , average diurnal courses per month

Urban: largest

Lake: tiny, different phase

heat to the water -> ice-out

Forest: modeled smaller in spring

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


Forest: modeled larger

in spring


• 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


• 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



Annika Nordbo

Department of physics

P.O.Box 48

FI – 00014 University of Helsinki

[email protected]

+358 50 415 4830

www.tinyurl.com/HelsinkiMicromet

Danke!


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


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Evaluating a tiled land-surface model with multi-site energy flux observations