Geosci. Model De ., 8, 2035–2065, 2015
www.geosci-model-de .ne /8/2035/2015/
doi:10.5194/gmd-8-2035-2015
© Au ho (s) 2015. CC A ibu ion 3.0 License.
A e ically disc e ised canopy desc ip ion o ORCHIDEE
(SVN 2290) and he modi ica ions o he ene gy, wa e and ca bon
luxes
K. Naud s1,14, J. Ryde 1, M. J. McG a h1, J. O o1,10, Y. Chen1, A. Valade1, V. Bellasen2, G. Be honga ay3,
G. Bönisch4, M. Campioli3, J. Gha as1, T. De G oo e3,11, V. Ha e d5, J. Ka ge4, N. MacBean1, F. Maignan1,
P. Me ilä6, J. Penuelas7,12, P. Peylin1, B. Pin y8, H. P e zsch9, E. D. Schulze4, D. Solyga1,13, N. Vuicha d1, Y. Yan3, and
S. Luyssae 1
1LSCE, IPSL, CEA-CNRS-UVSQ, 91191 Gi -su -Y e e, F ance
2INRA, 21079 Dijon, F ance
3Uni e si y o An we p, 2610 Wil ijk, Belgium
4MPI-Biogeochemis y, Jena, Ge many
5CSIRO-Ocean and A mosphe e Flagship, 2600 Canbe a, Aus alia
6METLA, Oulu, Finland
7CSIC, Global Ecology Uni CREAF-CSIC-UAB, Ce danyola del Valles, Spain
8Eu opean Commission, Join Resea ch Cen e, Isp a, I aly
9TUM, Munich, Ge many
10Helmhol z-Zen um Gees hach , Clima e Se ice Cen e 2.0, Hambu g, Ge many
11VITO, 2400 Mol, Belgium
12CREAF, Ce danyola del Vallès, Spain
13CGG, 91341 Massy, F ance
14MPI-Me eo ology, Hambu g, Ge many
Co espondence o: K. Naud s ([email p o ec ed])
Recei ed: 29 Oc obe 2014 – Published in Geosci. Model De . Discuss.: 05 Decembe 2014
Re ised: 04 May 2015 – Accep ed: 22 May 2015 – Published: 13 July 2015
Abs ac . Since 70% o global o es s a e managed and
o es s impac he global ca bon cycle and he ene gy ex-
change wi h he o e lying a mosphe e, o es managemen
has he po en ial o mi iga e clima e change. Ye , none o
he land-su ace models used in Ea h sys em models, and
he e o e none o oday’s p edic ions o u u e clima e, ac-
coun s o he in e ac ions be ween clima e and o es man-
agemen . We add essed his gap in modelling capabili y by
de eloping and pa ame ising a e sion o he ORCHIDEE
land-su ace model o simula e he biogeochemical and bio-
physical e ec s o o es managemen . The mos signi ican
changes be ween he new b anch called ORCHIDEE-CAN
(SVN 2290) and he unk e sion o ORCHIDEE (SVN
2243) a e he allome ic-based alloca ion o ca bon o lea ,
oo , wood, ui and ese e pools; he ansmi ance, ab-
so bance and e lec ance o adia ion wi hin he canopy; and
he e ical disc e isa ion o he ene gy budge calcula ions.
In addi ion, concep ual changes we e in oduced owa ds a
be e p ocess ep esen a ion o he in e ac ion o adia ion
wi h snow, he hyd aulic a chi ec u e o plan s, he ep esen-
a ion o o es managemen and a nume ical solu ion o he
pho osyn hesis o malism o Fa quha , on Caemme e and
Be y. Fo consis ency easons, hese changes we e ex en-
si ely linked h oughou he code. Pa ame isa ion was e-
isi ed a e in oducing 12 new pa ame e se s ha ep esen
speci ic ee species o gene a a he han a g oup o o en
dis an ly ela ed o e en un ela ed species, as is he case in
widely used plan unc ional ypes. Pe o mance o he new
model was compa ed agains he unk and alida ed agains
independen spa ially explici da a o basal a ea, ee heigh ,
canopy s uc u e, g oss p ima y p oduc ion (GPP), albedo
and e apo anspi a ion o e Eu ope. Fo all es ed a iables,
Published by Cope nicus Publica ions on behal o he Eu opean Geosciences Union.
2036 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
ORCHIDEE-CAN ou pe o med he unk ega ding i s abil-
i y o ep oduce la ge-scale spa ial pa e ns as well as hei
in e -annual a iabili y o e Eu ope. Depending on he da a
s eam, ORCHIDEE-CAN had a 67 o 92% chance o e-
p oduce he spa ial and empo al a iabili y o he alida ion
da a.
1 In oduc ion
Fo es s play a pa icula ly impo an ole in he global ca -
bon cycle. Fo es s s o e almos 50% o he e es ial o -
ganic ca bon and 90% o ege a ion biomass (Dixon e al.,
1994; Pan e al., 2011). Globally, 70% o he o es is man-
aged and he impo ance o managemen is s ill inc easing
bo h in ela i e and absolu e e ms. In densely popula ed e-
gions, such as Eu ope, almos all o es is in ensi ely man-
aged by humans. Recen ly, o es managemen has become a
op p io i y on he agenda o poli ical nego ia ions o mi iga e
clima e change (Kyo o P o ocol, h p://un ccc.in / esou ce/
docs/con kp/kpeng.pd ). Because o es plan a ions may e-
mo e CO2 om he a mosphe e, i used o ene gy p oduc-
ion, ha es ed imbe is a subs i u e o ossil uel. Fo es
managemen hus has g ea po en ial o mi iga ing clima e
change, which was ecognised in he Uni ed Na ions F ame-
wo kCon en ionon Clima eChangeand he Kyo oP o ocol.
Fo es s no only in luence he global ca bon cycle, bu hey
also d ama ically a ec he wa e apou and ene gy luxes
exchanged wi h he o e lying a mosphe e. I has been shown,
o example, ha he e apo anspi a ion o young plan a ions
can be so g ea ha he s eam low o neighbou ing c eeks
is educed by 50% (Jackson e al., 2005). Modelling s udies
on he impac o o es plan a ions in egions ha a e snow-
co e ed in win e sugges ha because o hei e lec ance
( he so-called albedo), o es could inc ease egional empe -
a u e by up o ou deg ees (Be s, 2000; Bala e al., 2007;
Da in e al., 2007; Zhao and Jackson, 2014). Managemen -
ela ed changes in he albedo, ene gy balance and wa e cycle
o o es s (Ami o e al., 2006a, b) a e o he same magni-
ude as he di e ences be ween o es s, g asslands and c op-
lands (Luyssae e al., 2014). Mo eo e , changes in he wa-
e apou and he ene gy exchange may o se he cooling
e ec ob ained by managing o es s as s onge sinks o a -
mosphe ic CO2(Pielke e al., 2002). Despi e he key implica-
ions o o es managemen on he ca bon–ene gy–wa e ex-
change, he e ha e been no in eg a ed s udies on he e ec s
o o es managemen on he Ea h’s clima e.
Ea h sys em models a e he mos ad anced ools o p e-
dic ing u u e clima e (Bonan, 2008). These models ep e-
sen he in e ac ions be ween he a mosphe e and he su -
ace benea h, wi h he su ace o malised as a combina ion
o open oceans, sea ice and land. Fo land, i e classes a e
dis inguished: glacie , lake, we land, u ban and ege a ed.
Vege a ion is ypically ep esen ed by di e en plan unc-
ional ypes. ORCHIDEE is he land-su ace componen o
he IPSL (Ins i u Pie e Simon Laplace) Ea h sys em model.
Hence, by design, he ORCHIDEE model can be un cou-
pled o he LMDz global ci cula ion model. In his coupled
se -up, he a mosphe ic condi ions a ec he land su ace and
he land su ace, in u n, a ec s he a mosphe ic condi ions.
Coupled land–a mosphe e models hus o e he possibili y
o quan i y bo h he clima ic e ec s o changes in he land
su ace and he e ec s o clima e change on he land su -
ace. The mos ad anced land-su ace models used, o in-
s ance, in Ea h sys em models o p edic clima e changes
(see he ecen CMIP5 exe cise), accoun o changes in eg-
e a ion co e bu conside o es s o be ma u e and ageless,
e.g. JSBACH (Reick e al., 2013), CLM (S öckli e al., 2008),
MOSES (Cox e al., 1999), ORCHIDEE (K inne e al.,
2005) and LPJ-DVGM (Bonan e al., 2003). A p esen , none
o he p edic ions o u u e clima e hus accoun s o he
essen ial in e ac ions be ween o es managemen and cli-
ma e. This gap in modelling capabili y p o ides he mo i a-
ion o u he de elopmen o he ORCHIDEE land-su ace
model o ealis ically simula e bo h he biophysical and bio-
geochemical e ec s o o es managemen on he clima e.
The ORCHIDEE-CAN (sho o ORCHIDEE-CANOPY)
b anch o he land-su ace model was speci ically de eloped
o quan i y he clima ic e ec s o o es managemen .
The aim o his s udy is o desc ibe he model de el-
opmen s and pa ame isa ion wi hin ORCHIDEE-CAN and
o e alua e i s pe o mance. ORCHIDEE-CAN is alida ed
agains s uc u al, biophysical and biogeochemical da a on
he Eu opean scale. To allow compa ison wi h he s anda d
e sion o ORCHIDEE, ORCHIDEE-CAN was un wi h
a single-laye ene gy budge . A mo e de ailed desc ip ion
and e alua ion o he new mul i-laye ene gy budge and
mul i-le el adia i e ans e scheme is gi en by Ryde e al.
(2014), Chen e al. (2015) and McG a h e al. (2015b). A
new o es managemen econs uc ion, which is needed o
d i e o es managemen in ORCHIDEE-CAN, is p esen ed
in McG a h e al. (2015a), and he in e ac ions be ween o es
managemen and he new albedoschemeha e beendiscussed
by O o e al. (2014).
2 Model o e iew
2.1 The s a ing poin : ORCHIDEE SVN 2243
The land-su ace model used o his s udy, ORCHIDEE, is
based on wo di e en modules (K inne e al., 2005, hei
Fig. 2). The i s module desc ibes he as p ocesses such as
he soil wa e budge and he exchanges o ene gy, wa e and
CO2 h ough pho osyn hesis be ween he a mosphe e and he
biosphe e (Ducoud é e al., 1993; de Rosnay and Polche ,
1998). The second module simula es he ca bon dynamics o
he e es ial biosphe e and essen ially ep esen s p ocesses
such as main enance and g ow h espi a ion, ca bon alloca-
ion, li e decomposi ion, soil ca bon dynamics and phenol-
Geosci. Model De ., 8, 2035–2065, 2015 www.geosci-model-de .ne /8/2035/2015/
K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2037
ogy (Vio y and de Noble -Ducoud é, 1997). The unk e -
sion o ORCHIDEE desc ibes global ege a ion by 13 me a-
classes (MTCs) wi h a speci ic pa ame e se (one o ba e
soil, eigh o o es s, wo o g asslands and wo o c op-
lands). Each MTC can be di ided in o a use -de ined numbe
o plan unc ional ypes (PFTs) which can be cha ac e ised
by a leas one pa ame e alue ha di e s om he pa am-
e e se ings o he MTC. Pa ame e s ha a e no gi en a
he PFT le el a e assigned he de aul alue o he MTC o
which he PFT belongs. By de aul , none o he pa ame e s
is speci ied a he PFT le el; hence, MTCs and PFTs a e he
same o he s anda d ORCHIDEE- unk e sion. A concise
desc ip ion o he main p ocesses in he ORCHIDEE- unk
e sion and a sho mo i a ion o change hese modules in
ORCHIDEE-CAN is gi en in Table 1.
Be o e unning simula ions, i is necessa y o b ing he
soil ca bon pools in o equilib ium due o hei slow ill a es,
an app oach known as model spin-up (Tho n on and Rosen-
bloom, 2005; Xia e al., 2012). Fo a long ime, spin-ups
ha e been pe o med by b u e o ce, i.e. unning he model
i e a i ely o e a su icien ly long pe iod which allows e en
he slowes ca bon pool o each equilib ium. This naï e ap-
p oach is eliable bu slow (in he case o ORCHIDEE i akes
3000 simula ion yea s) and hus comes wi h a la ge com-
pu a ional demand, o en exceeding he compu a ional cos
o he simula ion i sel . Al e na i e spin-up me hods calling
only pa s o he model, e.g. subsequen cycles o 10 yea s
o pho osyn hesis only ollowed by 100 yea cycles o soil
p ocesses only, ha e been used o ORCHIDEE o educe
he compu a ional cos in he pas . These app oaches, how-
e e , end o lead o ins abili ies in li e and ca bon pools.
In ecen yea s, semi-analy ical me hods ha e been p oposed
as a cos -e ec i e solu ion o he spin-up issue (Ma in e al.,
2007; La dy e al., 2011; Xia e al., 2012). A ma ix-sequence
me hod has been implemen ed in ORCHIDEE ollowing he
app oach used by he PaSim model (La dy e al., 2011). The
semi-analy ical spin-up implemen ed in ORCHIDEE elies
on algeb aic me hods o sol e a linea sys em o equa ions
desc ibing he se en ca bon pools sepa a ely o each PFT.
Con e gence o he me hod and hus equilib ium o he ca -
bon pools is assumed o be eached when he a ia ion o he
passi e ca bon pool (which is he slowes ) d ops below a p e-
de ined h eshold. The ne biome p oduc ion (NBP) is used
as a second diagnos ic c i e ion o con i m equilib ium o he
ca bon pools. In o de o op imise compu ing esou ces, he
semi-analy ical spin-up will s op be o e he end o he un
once he con e gence c i e ia a e me . ORCHIDEE’s imple-
men a ion o he semi-analy ical spin-up has been alida ed
on egional and global scales agains a naï e spin-up, and
has been ound o con e ge 12 o 20 imes as e . The la ges
gains we e ealised in he opics and he smalles gains in
bo eal clima e (no shown).
Plan wa e
supply
Hyd aulic
a chi ec u e
Canopy
s uc u e
1 day
Ca bon
alloca ion
Radia ion
scheme
30 min
30 min
30 min
30 min
30 min 1 day
Wa e
s ess
Phenology
Pho o-
syn hesis
Soil
hyd ology
30 min
Ene gy
budge
T anspi a ion
demand
T anspi a ion
Mo ali y
1 day
30 min
1 day
1 day
(1)
(2)
(7)
(3)
(4)
(5)
(6)
Figu e 1. Schema ic o e iew o he changes in ORCHIDEE-CAN.
Fo he unk he mos impo an p ocesses and connec ions a eindi-
ca ed in black, while he p ocesses and connec ions ha we e added
o changed in ORCHIDEE-CAN a e indica ed in ed. Numbe ed
a ows a e discussed in Sec . 2.2.
2.2 Modi ica ions be ween ORCHIDEE SVN 2243
and ORCHIDEE-CAN SVN 2290
One majo o e a ching change in he ORCHIDEE-CAN
b anch is he inc ease in in e nal consis ency wi hin he
model by adding connec ions be ween he di e en p ocesses
(Fig. 1, ed a ows). A mo e speci ic no el y is he in o-
duc ion o ci cum e ence classes wi hin o es PFTs, based
on he wo k o Bellassen e al. (2010). Fo he empe a e
and bo eal zone, ee heigh and c own diame e a e cal-
cula ed om allome ic ela ionships o ee diame e ha
we e pa ame ised based on he F ench, Spanish, Swedish
and Ge man o es in en o y da a and he obse a ional da a
om P e zsch (2009). The ci cum e ence classes hus al-
low calcula ion o he social posi ion o ees wi hin he
canopy, which jus i ies applying an in a- ee compe i ion
ule (Deleuze e al., 2004) o accoun o he ac ha ees
wi h a dominan posi ion in he canopy a e mo e likely o in-
e cep ligh han supp essed ees, and, he e o e, con ibu e
mo e o he s and le el pho osyn hesis and biomass g ow h.
To espec he compe i ion ule o Deleuze e al. (2004),
a new alloca ion scheme was de eloped based on he pipe
model heo y (Shinozaki e al., 1964) and i s implemen a ion
by Si ch e al. (2003). The scheme alloca es ca bon o di -
e en biomass pools (lea es, ine oo s, and sapwood) while
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2038 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
Table 1. Concise desc ip ion o he modules in he s anda d ORCHIDEE e sion wi h he mo i a ion o change he modules in ORCHIDEE-CAN.
Module Desc ip ion Mo i a ion o change
Albedo Fo each PFT he o al albedo o he g id squa e is compu ed as a weigh ed a e age o
he ege a ion albedo, he soil albedo, and he snow albedo. The scheme o e looks he e ec o ege a ion shading ba e soil o
spa se canopies and gi es he g ound in all PFTs he same e lec ance
p ope ies as ba e soil.
Soil hyd ology Ve icalwa e low in hesoilis basedon he Fokke –Planckequa ion ha esol eswa e
di usion in non-sa u a ed condi ions om he Richa ds equa ion (Richa ds, 1931). The
2m soil column consis s o 11 mois u e laye s wi h an exponen ially inc easing dep h
(D’O ge al e al., 2008).
No change
Soil empe a u e The soil empe a u e is compu ed acco ding o he Fou ie equa ion using a ini e di e -
ence implici scheme wi h se en nume ical nodes une enly dis ibu ed be ween 0 and
5.5m (Hou din, 1992).
No change
Ene gy budge The coupled ene gy balance scheme, and i s exchange wi h he a mosphe e, is based
on ha o Du esne and Gha as (2009). The su ace is desc ibed as a single laye ha
includes bo h he soil su ace and any ege a ion.
A big lea app oach does no accoun o wi hin canopy anspo o
ca bon, wa e and ene gy. Fu he , i is inconsis en wi h he cu en
mul i-laye pho osyn hesis app oach and he new mul i-laye albedo ap-
p oach.
Pho osyn hesis C3 and C4 pho osyn hesis is calcula ed ollowing Fa quha e al. (1980) and Colla z
e al. (1992), espec i ely. Pho osyn hesis assigns a i icial LAI le els o calcula e he
ca bon assimila ion o he canopy. These le els allow o a sa u a ion o pho osyn hesis
wi h LAI, bu ha e no physical meaning.
The scheme uses a simple Bee law ansmission o ligh o each le el,
which is inconsis en wi h he new albedo scheme.
Au o ophic espi a ion Au o ophic espi a ion dis inguishes main enance and g ow h espi a ion. Main enance
espi a ion occu s in li ing plan compa men s and is a unc ion o empe a u e,
biomass and, he p esc ibed ca bon/ni ogen a io o each issue (Ruimy e al., 1996). A
p esc ibed ac ion o 28% o he pho osyn ha es alloca ed o g ow h is used in g ow h
espi a ion (McC ee, 1974). The emaining assimila es a e dis ibu ed among he a i-
ous plan o gans using an alloca ion scheme based on esou ce limi a ions (see alloca-
ion).
No change
Ca bon alloca ion Ca bon is alloca ed o he plan ollowing esou ce limi a ions F iedlings ein e al.
(1999). Plan s alloca e ca bon o hei di e en issues in esponse o ex e nal limi a-
ions o wa e , ligh and ni ogen a ailabili y. When he a ios o hese limi a ions a e
ou o bounds, p esc ibed alloca ion ac o s a e used.
The esou ce limi a ion app oach equi es capping LAI a a p ede ined
alue. Due o his cap, he alloca ion ules a e mos o en no applied,
educing he scheme o p esc ibing alloca ion.
Phenology A he end o each day, he model checks whe he he condi ions o lea onse a e
sa is ied. The PFT-speci ic condi ions a e based on long- and sho - e m wa m h and/o
mois u e condi ions (Bo a e al., 2000).
No change
Mo ali y and u no e All biomass pools ha e a u no e ime. Li ing biomass is ans e ed o he li e pool;
li e is decomposed o ans e ed o he soil pool. This app oach is no capable o modelling s and dimensions.
Soil and li e ca bon
and he e o ophic espi-
a ion
Following (Pa on e al., 1988), p esc ibed ac ions o he di e en plan componen s
go o he me abolic and s uc u al li e pools ollowing senescence, u no e o mo al-
i y. The decay o me abolic and s uc u al li e is con olled by empe a u e and soil o
li e humidi y. Fo s uc u al li e , i s lignin con en also in luences he decay a e.
No change
Fo es managemen An explici dis ibu ion o indi idual ees (Bellassen e al., 2010) is he basis o a
p ocess-based simula ion o mo ali y. The abo eg ound s and-scale wood inc emen
is dis ibu ed on a yea ly ime s ep among indi idual ees acco ding o he ule o
(Deleuze e al., 2004): he basal a ea o each indi idual ee g ows p opo ionally o i s
ci cum e ence.
The concep o he o iginal implemen a ion we e e ained, howe e , he
implemen a ion was adjus ed o consis ency wi h he new alloca ion
scheme and o ha e a la ge di e si y o managemen s a egies.
Geosci. Model De ., 8, 2035–2065, 2015 www.geosci-model-de .ne /8/2035/2015/
K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2039
espec ing he di e ences in longe i y and hyd aulic conduc-
i i y be ween he pools. In addi ion o he biomass o he
di e en pools, lea a ea index (LAI), c own olume, c own
densi y, s em diame e , s em heigh and s and densi y a e cal-
cula ed and now depend on accumula ed g ow h. The new
scheme allows o he emo al o he pa ame e ha caps he
maximum LAI (Table 1).
The calcula ion o ee dimensions (e.g. sapwood a ea and
ee heigh ) ha espec he pipe heo y suppo s making use
o he hyd aulic a chi ec u e o plan s o calcula e he plan
wa e supply (Fig. 1, a ow 1), which is he amoun o wa-
e a plan can anspo om he soil o i s s oma a. The
ep esen a ion o he plan hyd aulic a chi ec u e is based on
he scheme o Hickle e al. (2006). The wa e supply is cal-
cula ed as he a io o he p essu e di e ence be ween soil
and lea es, and he o al hyd aulic esis ance o he oo s,
lea es and sapwood, whe e he sapwood esis ance is in-
c eased when ca i a ion occu s. Species-speci ic pa ame e
alues we e compiled om he li e a u e. As he scheme
makes use o he soil wa e po en ial, i equi es he use o he
11-laye hyd ology scheme o de Rosnay (2002) (Table 1).
When anspi a ion based on ene gy supply exceeds anspi-
a ion based on he wa e supply, he la e es ic s s oma al
conduc ance di ec ly, which is a physiologically mo e eal-
is ic ep esen a ion o d ough s ess han he educ ion o
he ca boxyla ion capaci y (Flexas e al., 2006) done in he
s anda d e sion o ORCHIDEE ( u he also e e ed o as
he “ unk” e sion). In line wi h his app oach, he d ough
s ess ac o used o igge phenology and senescence is now
calcula ed as he a io be ween he anspi a ion based on wa-
e supply and anspi a ion based on a mosphe ic demand
(Fig. 1, a ow 2).
The new alloca ion scheme also d as ically changed he
way o es s a e ep esen ed in he ORCHIDEE-CAN b anch.
Al hough he exac loca ion o he canopies in he s and is
no known, indi idual ee canopies a e now sphe ical ele-
men s wi h hei ho izon al loca ion ollowing a Poisson dis-
ibu ion ac oss he s and. Each PFT con ains a use -de ined
numbe o model ees, each one co esponding o a ci -
cum e ence class. Model ees a e eplica ed o gi e ealis ic
s and densi ies. Following ee g ow h, canopy dimensions
and s and densi y a e upda ed (Fig. 1, a ow 3). This o -
mula ion esul s in a dynamic canopy s uc u e ha is ex-
ploi ed in o he pa s o he model, i.e. p ecipi a ion in e -
cep ion, anspi a ion, ene gy budge calcula ions, a adia ion
scheme (Fig. 1, a ow 4) and abso bed ligh o pho osyn he-
sis (Fig. 1, a ow 5). In he unk e sion hese p ocesses a e
d i en by he big-lea canopy assump ion. The in oduc ion
o an explici canopy s uc u e is hough o be a key de elop-
men wi h espec o he objec i es o he ORCHIDEE-CAN
b anch, i.e. quan i ying he biogeochemical and biophysical
e ec s o o es managemen on a mosphe ic clima e.
The adia ion ans e scheme a he land su ace bene i s
om he in oduc ion o canopy s uc u e. The unk e sion
o ORCHIDEE p esc ibes he ege a ion albedo solely as a
unc ion o LAI. In he ORCHIDEE-CAN b anch each ee
canopy is assumed o be composed o uni o mly dis ibu ed
single sca e e s. Following he assump ion o a Poisson dis-
ibu ion o he ees on he land su ace, he model o Ha e d
e al. (2012) calcula es he ansmission p obabili y o ligh o
any gi en e ical poin in he o es . This ansmission p ob-
abili y is hen used o calcula e an e ec i e LAI, which is a
s a is ical desc ip ion o he e ical dis ibu ion o lea mass
ha accoun s o s and densi y and ho izon al ee dis ibu-
ion. The complexi y and compu a ional cos s a e la gely e-
duced by using he e ec i e LAI in combina ion wi h he 1-
D wo-s eam adia ion ans e model o Pin y e al. (2006)
a he han esol ing a ull 3-D canopy model. By using he
e ec i e LAI, he 1-D model ep oduces he adia i e luxes
o he 3-D model. The app oach o he wo-s eam adia-
ion ans e model was ex ended o a mul i-laye canopy
(McG a h e al., 2015b) o be consis en wi h he mul i-laye
ene gy budge and o be e accoun o non-linea i ies in
he pho osyn hesis model. The sca e ing pa ame e s and he
backg ound albedo (i.e. he albedo o he su ace below he
dominan ee canopy) o he wo-s eam adia ion ans e
model we e ex ac ed om he Join Resea ch Cen e Two-
s eam In e sion Package (JRC-TIP) emo e sensing p oduc
(Sec . 4.7). This app oach p oduces luxes o he ligh ab-
so bed, ansmi ed, and e lec ed by he canopy a e ically
disc e ised le els, which a e hen used o he ene gy bud-
ge (Fig. 1, a ow 6) and pho osyn hesis calcula ions (Fig. 1,
a ow 5).
The canopy adia i e ans e scheme o Pin y e al. (2006)
sepa a es he calcula ion o he luxes esul ing om down-
welling di ec and di use ligh , wi h di e en sca e ing pa-
ame e s a ailable o nea -in a ed (NIR) and isible (VIS)
ligh sou ces. The snow albedo scheme in he unk does
no dis inguish be ween hese wo sho -wa e bands. The e-
o e, hesnowscheme o heBiosphe e-A mosphe eT ans e
Scheme (BATS) o he Communi y Clima e Model (Dickin-
son e al., 1986) was inco po a ed in o he ORCHIDEE-CAN
b anch, since i dis inguishes be ween he NIR and VIS adi-
a ion. The adia ion scheme o Pin y e al. (2006) equi es
snow o be pu on he soil below he ee canopy ins ead o
on he canopy i sel . The calcula ion o he snow co e age o
a PFT he e o e had o be e ised acco ding o he scheme
o Yang e al. (1997), which allows o snow o comple ely
co e he g ound a dep hs g ea e han 0.2m. The pa ame e
alues o Yang e al. (1997) we e used in he ORCHIDEE-
CAN b anch.
TheORCHIDEE-CANb anchdi e s om anyo he land-
su ace model by he inclusion o a newly de eloped mul i-
laye ene gy budge . The e a e now subcanopy wind, em-
pe a u e, humidi y, long-wa e adia ion and ae odynamic e-
sis ance p o iles, in addi ion o a check o ene gy closu e
a all le els. The ene gy budge ep esen s an implemen a-
ion o some o he cha ac e is ics o de ailed single-si e, i -
e a i e canopy models (e.g. Baldocchi, 1988; Ogee e al.,
2003) wi hin a sys em ha is coupled implici ly o he a -
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2040 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
mosphe e. As an enhancemen o he unk e sion o OR-
CHIDEE (Table 1), he new app oach also gene a es a lea
empe a u e, using a ege a ion p o ile and a e ical sho -
wa e and long-wa e adia ion dis ibu ion scheme (Ryde
e al., 2014), which will be ully a ailable when pa ame i-
sa ion o he scheme has been comple ed ac oss es si es
co esponding o he species wi hin he model (Chen e al.,
2015). As wi h he unk e sion, he new ene gy budge is
calcula ed implici ly (Polche e al., 1998; Bes e al., 2004).
An implici solu ion is a linea solu ion in which he su ace
empe a u e and luxes a e calcula ed in e ms o he a mo-
sphe ic inpu a he same ime s ep, whe eas an explici so-
lu ion uses a mosphe ic inpu om he p e ious ime s ep o
calcula e he su ace empe a u e and luxes. Al hough i is
less s aigh o wa d o de i e, he implici solu ion is mo e
compu a ionally e icien and s able, which allows he model
o be un o e a ime s ep o 15min when coupled o he
LMDz a mosphe ic model – much longe han would be he
case o an explici model. Pa ame e s we e de i ed by op-
imising he model agains he obse a ions om sho - e m
ield campaigns. The new scheme may also be educed o he
exis ing single laye case, so as o p o ide a means o com-
pa ison and compa ibili y wi h he ORCHIDEE- unk e -
sion.
The combined use o he new ene gy budge and he hy-
d aulic a chi ec u e o plan s equi ed changes o he calcula-
ion o he s oma al conduc ance and pho osyn hesis (Fig. 1,
a ow 7). When wa e supply limi s anspi a ion, s oma al
conduc ance is educed and pho osyn hesis needs o be e-
calcula ed. Gi en ha pho osyn hesis is among he compu-
a ional bo lenecks o he model, he semi-analy ical p oce-
du e as a ailable in p e ious unk e sions ( 2031 and u -
he ) is eplaced by an adjus ed implemen a ion o he analy -
ical pho osyn hesis scheme o Yin and S uik (2009), which
is also implemen ed in he la es ORCHIDEE- unk e sion.
In addi ion o an analy ical solu ion o pho osyn hesis, he
scheme includes a modi ied A henius unc ion o he em-
pe a u e dependence ha accoun s o a dec ease in ca -
boxyla ion capaci y (kVcmax) and elec on anspo capaci y
(kJmax; see Table 2 o a iable explana ions) a high empe -
a u es and a empe a u e-dependen kJmax/Vcmax a io (Ka ge
and Kno , 2007). The empe a u e esponse o kVcmax and
kJmax was pa ame ised wi h alues om eanalysed da a in
he li e a u e (Ka ge and Kno , 2007), whe eas kVcmax and
kJmax a a e e ence empe a u e o 25◦C we e de i ed om
obse ed species-speci ic alues in he TRY da abase (Ka ge
e al., 2011). As he amoun o abso bed ligh a ies wi h
heigh (o canopy dep h), he abso bed ligh compu ed om
he albedo ou ines is now di ec ly used in he pho osyn hesis
scheme, esul ing in ull consis ency be ween he op o he
canopy albedo and abso p ion. This new app oach eplaces
he old scheme which used mul iple le els based on he lea
a ea index, no he physical heigh .
ORCHIDEE-CAN inco po a es a sys ema ic mass balance
closu e o ca bon cycling o ensu e ha ca bon is no ge ing
c ea ed o des oyed du ing he simula ion. Hence, budge
closu e is now consis en ly checked o wa e , ca bon and
ene gy h oughou he model.
The unk uses 13 PFTs o ep esen ege a ion globally:
one PFT o ba e soil, eigh o o es s, wo o g asslands,
and wo o c oplands. The ORCHIDEE-CAN b anch makes
use o he ex e nalisa ion o he PFT-dependen pa ame e s
by adding 12 pa ame e se s ha ep esen he main Eu o-
pean ee species. Species pa ame e s we e ex ac ed om a
wide ange o sou ces including o iginal obse a ions, la ge
da abases, p ima y esea ch and emo e sensing p oduc s
(Sec . 4). The use o age classes is in oduced h ough ex-
e nalisa ion o he PFT pa ame e s as well. Age classes a e
used du ing land co e change and o es managemen o
simula e he eg ow h o a o es . Following a land co e
change, biomass and soil ca bon pools (bu no soil wa e
columns) a e ei he me ged o spli o ep esen he a ious
ou comes o a land co e change. The numbe o age classes
is use de ined. Con a y o ypical age classes, he bound-
a ies a e de e mined by he ee diame e a he han he age
o he ees.
Finally, he o es managemen s a egies in he
ORCHIDEE-CAN b anch we e e ined om he o igi-
nal o es managemen (FM) b anch (Bellassen e al., 2010).
Sel - hinning was ac i a ed o all o es s ega dless o
human managemen , con a y o he o iginal FM b anch.
The new de aul managemen s a egy hus has no human
in e en ion bu includes sel - hinning, which eplaces he
ixed 40 yea u no e ime o woody biomass. Th ee
managemen s a egies wi h human in e en ion ha e been
implemen ed:(1) “highs ands”, inwhich humanin e en ion
is es ic ed o hinning ope a ions based on s and densi y
and diame e , wi h occasional clea -cu s. Abo eg ound
s ems a e ha es ed du ing ope a ions, while b anches
and belowg ound biomass a e le o li e ; (2) “coppices”
in ol e wo kinds o cu s. The i s coppice cu is based
on s em diame e and he abo eg ound woody biomass is
ha es ed, whe eas he belowg ound biomass is le li ing.
F om his belowg ound biomass, new shoo s sp ou , which
inc eases he numbe o abo eg ound s ems. In subsequen
cu s he numbe o shoo s is no inc eased, al hough all
abo eg ound wood biomass is s ill ha es ed; and (3) “sho
o a ion coppices”, whe e o a ion pe iods a e based on
age and a e gene ally e y sho (3–6 yea s). The di e en
managemen s a egies can occu wi h o wi hou li e
aking, which educes he li e pools and has a long- e m
e ec on soil ca bon (Gimmi e al., 2012). All managemen
ypes a e pa ame ised based on o es in en o y da a, yield
ables and guidelines o o es managemen . The inclusion
o o es managemen esul ed in wo addi ional ca bon
pools, b anches and coa se oo s (i.e. abo eg ound and
belowg ound woody biomass) and he e o e equi ed an
ex ension o he semi-analy ical spin-up me hod (Sec . 2.1).
The semi-analy ical spin-up is now un o nine C pools.
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K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2041
Table 2. Va iable desc ip ion. Va iables we e g ouped as ollows: F= lux, = ac ion, M=pool, m=modula o , d=s and dimension,
T= empe a u e, p=p essu e, R= esis ance, q=humidi y, g= unc ion.
Symbol in ex Uni Symbol in ORCHIDEE-CAN Desc ip ion
F m gCm−2s−1 esp_main Main enance espi a ion
F g gCm−2s−1 esp_g ow h G ow h espi a ion
FLW,i Wm2 _lw Long-wa e adia ion inciden a ege a ion le el i
FSW,i Wm2 _sw Sho -wa e adia ion inciden a ege a ion le el i
FT s ms−1T anspi _supply Amoun o wa e ha a ee can ge up om he soil o i s lea es o anspi a ion
Ta,i K emp_a mos_p es,
emp_a mos_nex A mosphe ic empe a u e a he “p esen ” and “nex ” ime s ep, espec i ely, a
le el i
TL,i K emp_lea _p es Lea empe a u e a le el i
qa,i kgkg−1q_a mos_p es, q_a mos_nex Speci ic humidi y a he “p esen ” and “nex ” ime s ep, espec i ely, a le el i
qL,i kgkg−1q_lea _p es Lea -speci ic humidi y a le el i
MlgCplan −1Cl Lea mass o an indi idual plan
MsgCplan −1Cs Sapwood mass o an indi idual plan
MhgCplan −1Ch Hea wood mass o an indi idual plan
M gCplan −1C Roo mass o an indi idual plan
Mlinc gCplan −1Cl_inc Inc emen in lea mass o an indi idual plan
Msinc gCplan −1Cs_inc Inc emen in sapwood mass o an indi idual plan
M inc gCplan −1C _inc Inc emen in oo mass o an indi idual plan
M o inc gC b_inc_ o To al biomass inc emen
Minc gCplan −1b_inc Inc emen in plan biomass o an indi idual plan
Mswc m3m−3swc Volume ic soil wa e con en
mw– ws ess_ ac Modula o o wa e s ess as expe ienced by he plan s
mψMPa psi_soil_ une Modula o o accoun o esis ance in he soil- oo in e ace
mNdea h – scale_ ac o No malisa ion ac o o mo ali y
mLAIco – lai_co ec ion_ ac o Adjus able pa ame e in he calcula ion o gap p obabili ies o g asses and c ops
dhm heigh Plan heigh
dlm−2– One-sided lea a ea o an indi idual plan
dsm−2– Sapwood a ea o an indi idual plan
dhinc m del a_heigh Heigh inc emen
ddbh m dia Plan diame e
dba m2plan −1ba Basal a ea
dbainc m2plan −1del a_ba Basal a ea inc emen
dci c m ci c S em ci cum e ence o an indi idual plan
dind ees n_ci c_class Numbe o ees in diame e class l
dcm2c own_shadow_h P ojec ed a ea o an opaque ee c own
dcsa m2csa_sap P ojec ed c own su ace a ea
dLAI m2
lea m−2
g ound – Lea a ea index
dLAIe – laie E ec i e lea a ea index
dLAIabo e – lai_sum Sum o he LAI o all le els abo e he cu en le el
dA,i m2– C oss-sec ional a ea o ege a ion le el i
dhl,i m del a_h Vege a ion heigh o le el i
dV,i m3– Volume o ege a ion le el i
d d – oo _dens Roo densi y
dλindm2– In e se o he indi idual plan densi y
pdel a MPa del a_P P essu e di e ence be ween lea es and soil
pψs MPa psi_soil oo Bulk soil wa e po en ial in he oo ing zone
pψsMPa psi_soil Soil wa e po en ial o each soil laye
R MPasm−3R_ oo Hyd aulic esis ance o oo s
Rsap MPasm−3R_sap Hyd aulic esis ance o sapwood
RlMPasm−3R_lea Hyd aulic esis ance o lea es
R emp MPasm−3– Hyd aulic esis ance o oo s, sapwood o lea es adjus ed o empe a u e
Ra,i sm−1big_ Ae odynamic esis ance o ege a ion a le el iin he canopy
Rs,i sm−1big_ _p ime Sum o he s oma al and lea bounda y laye esis ance e ms o la en hea
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2042 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
Table 2. Con inued.
Symbol in ex Uni Symbol in ORCHIDEE-CAN Desc ip ion
Pwc – Pwc_h Po osi y o a ee c own
ees
Pgap – PgapL Gap p obabili y o ees
gc
Pgap – PgapL Gap p obabili y o g asses and c ops
bs
Pgap – PgapL Gap p obabili y o ba e soil
ici
dea h – mo ali y Mo ali y ac ion pe ci cum e ence class
KF – KF Lea alloca ion ac o
LF – LF Roo alloca ion ac o
γ– gamma Slope o he in a-speci ic compe i ion
sm s Slope o linea ised ela ionship be ween heigh and basal a ea
l – lea _ e lec ance Re lec ance o a single lea
l – lea _ ansmi ance T ansmi ance o a single lea
Rbgd – bdg_ e lec ance Re lec ance o he g ound benea h he canopy
R
Coll, eg – Collim_alb_BB,
Iso op_alb_BB Re lec ed ac ion o ligh o he a mosphe e which has collided wi h canopy
elemen s, sepa a ed o di ec and di use sou ces, espec i ely
R
UnColl, bgd – Collim_alb_BC,
Iso op_alb_BC Re lec ed ac ion o ligh o he a mosphe e which has no collided wi h any
canopy elemen s, sepa a ed o di ec and di use sou ces, espec i ely
T
UnColl, eg – Collim_T an_Uncoll T ansmi ed ac ion o ligh o he g ound which has no collided wi h any
canopy elemen s
R
Coll, bgd,1 – – Re lec ed ac ion o ligh which has s uck he backg ound a single ime and
has collided wi h ege a ion
R
Coll, bgd,n– – Re lec ed ac ion o ligh which has s uck he backg ound mul iple imes and
has collided wi h ege a ion
zm z_a ay Heigh abo e he soil
θz adians sola _angle Sola zeni h angle
θµ adians – Cosine o he sola zeni h angle
gG– – Lea o ien a ion unc ion
gσ– sigmas Cu -o ci cum e ence o he in a-speci ic compe i ion, calcula ed as a unc ion
o knci c
3 Desc ip ion o he de elopmen s
3.1 Alloca ion
Following bud bu s , pho osyn hesis p oduces ca bon ha is
added o he labile ca bon pool. Labile ca bon is used o sus-
ain he main enance espi a ion lux (F m), which is he ca -
bon cos o keep exis ing issue ali e (Am ho , 1984). Main-
enance espi a ion o he whole plan is calcula ed by sum-
ming main enance espi a ion o he di e en plan compa -
men s, which is a unc ion o he ni ogen concen a ion o
he issue ollowing he Bee –Lambe law and sub ac ed
om he whole-plan labile pool (up o a maximum o 80%
o he labile pool).
The emaining labile ca bon pool is spli in o an ac i e and
a non-ac i e pool. The size o he ac i e pool is calcula ed
as a unc ion o plan phenology and empe a u e and was
o malised ollowing Ryan (1991), Si ch e al. (2003) and
Zaehle and F iend (2010). The emaining non-ac i e pool is
used o es o e he labile and ca bohyd a e ese e pools ac-
co ding o he ules p oposed in Zaehle and F iend (2010).
The labile pool is limi ed o 1% o he plan biomass o 10
imes he ac ual daily pho osyn hesis. Any excess ca bon is
ans e ed o he non- espi ing ca bohyd a e ese e pool.
The ca bohyd a e ese e pool is capped o e lec limi ed
s a ch accumula ion in plan s, bu ca bon can mo e eely
be ween he wo ese e pools. A e accoun ing o g ow h
espi a ion (F g), i.e. he cos o p oducing new issue ex-
cluding he ca bon equi ed o build he issue i sel (Am ho ,
1984), he o al alloca able C used o plan g ow h is ob-
ained (M o inc).
New biomass is alloca ed o lea es, oo s, sapwood, hea -
wood, and ui s. Alloca ion o lea es, oo s and wood e-
spec s he pipe model heo y (Shinozaki e al., 1964) and
hus assumes ha p oducing one uni o lea mass equi es
a p opo ional amoun o sapwood o anspo wa e om
he oo s o he lea es as well as a p opo ional ac ion o
oo s o ake up he wa e om he soil. The di e en biomass
pools ha e di e en u no e imes, and he e o e a he end
o he daily ime s ep, he ac ual biomass componen s may no
longe espec he allome ic ela ionships. Consequen ly, a
he s a o he ime s ep ca bon is i s alloca ed o es o e he
allome ic ela ionships be o e he emaining ca bon is allo-
ca ed in he manne desc ibed below.The scaling pa ame e
be ween lea and sapwood mass is de i ed om:
dl=kls ×mw×ds(1)
whe e dlis he one-sided lea a ea o an indi idual plan , ds
is he sapwood c oss-sec ion a ea o an indi idual plan , kls
a pa ame e linking lea a ea o sapwood c oss-sec ion a ea,
Geosci. Model De ., 8, 2035–2065, 2015 www.geosci-model-de .ne /8/2035/2015/
K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2043
and mwis he wa e s ess as de ined in Sec . 3.2. Al e na-
i ely, lea a ea can be w i en as a unc ion o lea mass (Ml)
and he speci ic lea a ea (ksla):
dl=Ml×ksla.(2)
Sapwood mass Mscan be calcula ed om he sapwood
c oss-sec ion a ea dsas ollows:
Ms=ds×dh×kρs,(3)
whe e dhis he ee heigh and kρsis he sapwood densi y.
Following subs i u ion o Eqs. (2) and (3) in o Eq. (1), lea
mass can be w i en as a unc ion o sapwood mass:
Ml=(Ms× KF)/dh,(4)
whe e,
KF =(kls ×mw)/ksla ×kρs,(5)
whe e kls is calcula ed as a unc ion o he gap ac ion as
suppo ed by si e-le el obse a ions (Simonin e al., 2006):
kls =klsmin + Pgap, ees ×(klsmax −klsmin). (6)
klsmin is he minimum obse ed lea a ea o sapwood a ea
a io, klsmax is he maximum obse ed lea a ea o sapwood
a ea a io and Pgap, ees is he ac ual gap ac ion. By using
he gap ac ion as a con ol o kls mo e ca bon will be allo-
ca ed o he lea es un il canopy closu e is eached.
Following Magnani e al. (2000), sapwood mass and oo
mass (M ) a e ela ed as ollows:
Ms=ksa ×dh×M ,(7)
whe e he pa ame e ksa is calcula ed acco ding o Magnani
e al. (2000) ( hei Eq. 17):
ksa =p(k con/kscon)×(kτs/kτ )×kρs,(8)
whe e k con is he hyd aulic conduc i i y o oo s, kscon is he
hyd aulic conduc i i y o sapwood, kτsis he longe i y o
sapwood and kτ is he oo longe i y. Following subs i u ion
o Eq. (4) in o Eq. (7) and some ea angemen , lea mass can
be w i en as a unc ion o oo mass:
Ml= LF ×M ,(9)
whe e,
LF =ksa × KF.(10)
Pa ame e alues used in Eqs. (1) o (9), i.e. klsmax,klsmin,
ksa ,ksla,kρs,k con,kscon,kτsand kτ , a e based on li e a u e
e iew (Tables S1, S2 and S3 in he Supplemen ). The allo-
me ic ela ionships be ween he plan componen s and he
hyd aulic a chi ec u e o he plan (Sec . 3.2) a e bo h based
on he pipe model heo y; hence, bo h he alloca ion and he
hyd aulic a chi ec u e module use he same pa ame e alues
o oo and sapwood conduc i i y.
In his e sion o ORCHIDEE, o es s a e modelled o
ha e knci c ci cum e ence classes wi h dind iden ical ees in
each one. Hence, he alloca able biomass (M o inc) needs o
be dis ibu ed ac oss ldiame e classes:
M o inc =X(l)[dind(l) ×Minc(l)],(11)
whe e Minc(l) is he biomass ha can be alloca ed o diame e
class l. Mass conse a ion hus equi es:
Minc(l) =Mlinc(l) +M inc(l) +Msinc(l),(12)
whe e Mlinc(l),M inc(l) and, Msinc(l) a e he inc ease in lea ,
oo and wood biomass o a ee in diame e class l, espec-
i ely. Equa ions (4) and (9) can be ew i en as
(Ml(l) +Mlinc(l))/(Ms(l) +Msinc(l))= KF/(dh(l)
+dhinc(l))(13)
(Ml(l) +Mlinc(l))=(M (l) +M inc(l))× LF (14)
An allome ic ela ionship is used o desc ibe he ela ion-
ship be ween ee heigh and basal a ea (P e zsch, 2009):
dh(l) =kα1×(4/π ×dba(l))(kβ1/2).(15)
The change in heigh is hen calcula ed as
dhinc(l) = [kα1×(4/π×(dba(l)+dbainc(l)))(kβ1/2)]−dh(l),(16)
whe e dba(l) and dbainc(l) a e he basal a ea and i s inc emen ,
espec i ely. kα1and kβ1a e allome ic cons an s ela ing ee
diame e and heigh . The dis ibu ion o C ac oss he ldi-
ame e classes depends on he basal a ea o he model ee
wi hin each diame e class. T ees wi h a la ge basal a ea a e
assigned mo e ca bon o wood alloca ion han ees wi h a
small basal a ea, acco ding o he me hod o Deleuze e al.
(2004).
dbainc(l) = γ×dci c(l) −km·gσ+
q(km×gσ+dci c(l))2−(4×gσ×dci c(l))/2,(17)
whe e kmis a pa ame e , γand gσa e calcula ed om pa-
ame e s and dci c(l) is he ci cum e ence o he model ee in
diame e class l.gσis a unc ion o he diame e dis ibu ion
o he s and a a gi en ime s ep.
Equa ions (10) o (16) need o be simul aneously sol ed.
An i e a i e scheme was a oided by linea ising Eq. (15),
which was ound o be an accep able nume ical app oxima-
ion as alloca ion is calcula ed a a daily ime s ep, and hence
he changes in heigh a e small and he ela ionship is locally
linea :
dhinc(l) =dbainc(l)/ s,(18)
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2050 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
agains a compila ion o 100+obse a ions o biomass
p oduc ion e iciency.
5. The lea o sapwood a ea a io was manually uned
(Sec . 4.9) o ma ch 100+si e-le el g oss p ima y p o-
duc ion (GPP) and LAI obse a ions eco ded o e Eu-
ope.
4.1 In oducing 12 new PFTs
Simila ly o he ORCHIDEE unk, he ORCHIDEE-CAN
b anch dis inguishes 13 me aclasses (MTC) o ege a ion.
Ou side Eu ope he o iginal MTC classi ica ion o OR-
CHIDEE was kep , while inside Eu ope 12 new pa ame e
se s ep esen ing he main Eu opean ee species we e added.
The de aul ege a ion dis ibu ion map in ORCHIDEE, i.e.
Olson e al. (1983), was eplaced by an up- o-da e global
MTC map which has been p oduced using he ESA CCI ECV
Land Co e map (h p://www.esa-landco e -cci.o g/) (Poul-
e e al., 2015). The mapping om land co e o MTC ba-
sically ollowed Poul e e al. (2011), al hough Table 5 ( he
“c oss-walking” able) has been upda ed ollowing discus-
sions wi h he LC-CCI eam a Uni e si e Ca holique de Lou-
ain. Fo he Eu opean domain, he global MTC dis ibu ion
was o e laid by a ee species dis ibu ion map (B us e al.,
2012).
This s udy ocusses on ee species wi h a co e age o
mo e han 2% in Eu ope, yielding se en species g oups
co e ing in o al 78.8% o he Eu opean o es a ea: Be-
ula sp., Fagus syl a ica,Pinus syl es is,Picea sp., Pinus
pinas e ,Que cus ilex and a g oup combining Que cus obu
and Que cus pe aea. Fo Pinus syl es is,Picea sp. and Be-
ula sp. An addi ional dis inc ion be ween bo eal and em-
pe a e o es was made o he species map and pa ame isa-
ion: ees loca ed in No way, Sweden and Finland we e con-
side ed bo eal, while ees g owing a lowe la i udes we e
ca ego ised as empe a e. Gi en he po en ial ole o ee
species o he Salicacea genus in sho o a ion coppice man-
agemen , a sepa a e PFT was pa ame ised o Populus sp.
Fu he mo e, o imp o e he pa ame isa ion o he MTC o
bo eal needlea ed deciduous o es , obse a ions om La ix
sp. we e included when possible.
Fo hese 12 o es species, 12 new PFTs we e c ea ed,
wi h each PFT belonging o a single MTC (Tables S2, S3 and
S4). Almos 79% o he Eu opean o es was pa ame ised a
he species le el. The emaining 21% was eclassi ied in o
ou esidual g oups, i.e. a empe a e and bo eal needlelea
e e g een and a empe a e and bo eal b oadlea ed esidual
g oup. Fo use ou side Eu ope, he o iginal MTC classi ica-
ion o ORCHIDEE was kep . The pa ame e s o he esid-
ual g oups and MTCs a e he mean o he pa ame e s o he
species-le el PFTs ha a e in he MTC, wi h he excep ion
o albedo pa ame e s ha could be ex ac ed om emo e-
sensing p oduc s. Finally, sepa a e PFTs we e in oduced o
bo eal g asses and c oplands, which allowed o a bo eal
pa ame isa ion o phenology, senescence and g ow h. This
app oach, which dis inguishes a o al o 28 PFTs, allows a
highe axonomic esolu ion o e Eu ope, be e de ines o -
es ypes compa ed o he mo e gene al MTC app oach and
acili a es he use o obse a ions o de i e pa ame e s.
4.2 Alloca ion
The alloca ion scheme elies on he lea o sapwood a ea
a io (Sec . 4.9) and he ela ionship be ween diame e and
heigh . Following a loga i hmic ans o ma ion o he mo e
han 150000 da a poin s om he na ional o es in en o y
da a o Spain, F ance, Ge many and Sweden, he wo pa am-
e e s (i.e. kα1and kβ1) desc ibing he ela ionship be ween
diame e and heigh (Eq. 15) we e i ed a he species le el
making use o a leas squa e eg ession. Pa ame e alues o
MTCs we e de i ed by g ouping he species in o MTCs and
i ing he pa ame e s. Da a sou ces and pa ame e es ima es
a e p esen ed in Tables S2 and S3.
4.3 Fo es managemen and mo ali y
Fo es managemen and ee mo ali y a e con olled by
(Sec . 3.7): (1) maximum ee diame e (no symbolic
no a ion; called la ges _ ee_diam in ORCHIDEE-CAN),
(2) minimum s and densi y (no symbolic no a ion; called
n ees_dia_p o i in ORCHIDEE-CAN), (3) en i onmen al
mo ali y (no symbolic no a ion; called esidence_ ime in
ORCHIDEE-CAN), (4) sel - hinning (kα2and kβ2) and,
(5) an h opogenic hinning (no symbolic no a ion; called
alpha_RDI_uppe , alpha_RDI_lowe , be a_RDI_uppe and
be a_RDI _lowe in ORCHIDEE-CAN) whe e he pa ame-
e s depend on he managemen s a egy.
Maximum ee diame e was ex ac ed om he F ench,
Swedish, Ge man and Spanish o es in en o ies as he ob-
se ed 50% quan ile o diame e a b eas heigh . The 50%
quan ile a he han he obse ed maximum was used o ac-
coun o he ac ha la ge-scale land-su ace models a e
expec ed o ep oduce la ge-scale pa e ns a he han local
ex emes. Minimum s and densi y was es ima ed as he ex-
pec ed s and densi y o he maximum ee diame e o a
s and unde sel - hinning. Al hough bo h c i e ia a e ela ed
o each o he h ough he obse ed sel - hinning ela ionship
(see below), he minimum numbe o ees is used o decide
when unmanaged o es s should be eplaced, whe eas bo h
he maximum diame e and he minimum numbe a e used
o managed si es as c i e ia o ini ia e a clea cu . Pa ame-
e s o an h opogenic hinning a e based on he na ional o -
es in en o y da a and checked agains he JRC da abase o
species-speci ic yield ables. Pa ame e alues a e p esen ed
in Table S5. Resou ce compe i ion be ween ees in he same
s and has been epo ed o esul in he so-called sel - hinning
ela ionship ha ela es he numbe o indi iduals wi hin a
s and o he s and biomass (Reineke, 1933; Ki a e al., 1953;
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K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2051
Yoda e al., 1963):
(Ms+Mh)×kρs=kα×(dind)−kβ,(39)
whe e kαand kβa e he cons an s o he sel - hinning ela-
ionship. Fu he mo e, s em olume can be w i en as a unc-
ion o ee diame e (ddbh), ee heigh and s em o m ac o
(kα0) o accoun o he ac ha he s em shape is no a pe -
ec cylinde :
(Ms+Mh)·kρs=kα0×(ddbh)2×dh.(40)
Following he allome ic ela ionship gi en in Eq. (15),
ee heigh can be w i en as a unc ion o ee diame e .
Hence, he sel - hinning ela ionship can be e-w i en o e-
la e s and diame e o s and densi y:
ddbh =kα2×(dind)−kβ2,(41)
whe e, kβ2 ela es o kβ1(as in Eq. 15) as ollows:
kβ2= −3/2×(2+kβ1)(42)
kα1and kβ1we e es ima ed by i ing Eq. (15) o obse ed
diame e and heigh o indi idual ees om NFI o Swe-
den, Ge many, F ance and Spain. kβ2was calcula ed om
Eq. (42) and kα2was es ima ed by i ing Eq. (41) o obse a-
ions o he quad a ic mean s and diame e and s and densi y
om NFI da a.
4.4 Hyd aulic a chi ec u e
Ini ial choices o pa ame e s o his scheme we e based on
he alues and pa ame e sou ces lis ed by Hickle e al.
(2006). All da a sou ces we e e isi ed and he sea ch was
ex ended o ob ain alues a he PFT a he han MTC le el.
Gi en ha plan hyd ology is a he well s udied, obse ed
pa ame e s we e a ailable o mos o he species. Da a
sou ces a e lis ed in Table S1, whe eas he pa ame e al-
ues a e shown in Table S3. Ou implemen a ion o hyd aulic
a chi ec u e equi ed he in oduc ion o a uning pa ame e
(mψ) o accoun o p ocesses ha a e cu en ly absen in
he scheme, e.g. plan wa e s o age and soil– oo esis ance.
A p ocess-based desc ip ion o hese p ocesses (i.e. Spe y
e al., 1998; S eppe e al., 2006) is being es ed and should
educe he e ec o he uning pa ame e and e en ually al-
low i s emo al om he model.
Fo he ime being, he modula o mψwas uned manu-
ally agains he species dis ibu ion map o ob ain a ma ch
be ween he simula ed and obse ed species dis ibu ions.
When he modula o is se o ze o, all PFTs expe ience ex-
cessi e wa e s ess esul ing in la ge-scale plan mo ali y.
The modula o was inc eased un il he p esc ibed ege a-
ion dis ibu ion which was based on emo e-sensing obse -
a ions (Sec . 4.1), su i ed whe e i was p esc ibed. To his
aim, he model was un o 50 yea s, o ced wi h 5.2 o
he CRU-NCEP clima ology o Eu ope (Clima ic Resea ch
Uni , Uni e si y o Eas Anglia). No e ha he alues o
he modula o depend on he clima e da a ha a e used o
o ce he model. Simila ly he modula o s may need o be e-
uned when ORCHIDEE-CAN is coupled o an a mosphe ic
model.
4.5 Canopy s uc u e
The ela ionship be ween diame e and p ojec ed c own su -
ace a ea ollows he model p oposed by P e zsch (2009):
dcsa =kap ×dkbp
dbh (43)
wi h pa ame e s es ima ed using he da a se p esen ed in
P e zsch and Diele (2012). This da a se con ains diame-
e and p ojec ed c own su ace a eas obse a ions o o e
37000 indi idual ees in Eu ope co e ing almos 30 species.
Following loga i hmic ans o ma ion o he obse a ions a
linea leas squa e eg ession was used o i species-speci ic
pa ame e alues. Pa ame e alues a e shown in Table S2.
Pa ame e alues o MTCs we e de i ed by g ouping he
species in o MTCs and i ing he pa ame e s. No obse a-
ions we e a ailable o he bo eal zone and empe a e e e -
g een deciduous species. Fo he bo eal species, a subse o
he empe a e obse a ions (Pinus syl es is,Picea abies and
Be ula pendula) was used, i.e. he ela ionship be ween dcsa
and ddbh was i ed o all a ailable da a o Pinus syl es is.
Nex , all obse a ions wi h a dcsa ha alls below he p e-
dic ed dcsa we e selec ed as conside ed o ep esen a bo-
eal subse . Gi en he impo ance o snow p essu e on c own
s uc u e, selec ing obse a ions wi h sub a e age dcsa is jus-
i iable as a i s app oxima ion. Subsequen ly, he pa ame-
e s we e i ed o his subse o da a. Fo Que cus ilex no
da a we e a ailable and pa ame e s we e uned such ha he
c own diame e was 0.85m less han he ee heigh .
4.6 Analy ical solu ion o pho osyn hesis
Th ee o iginally MTC-speci ic pho osyn he ic pa ame e s
(kVcmax,kJmax and ksla) we e de i ed a he species le el by
ob aining weigh ed si e means o each species om he TRY
global lea ai da abase (Ka ge e al., 2011) and addi ion-
ally om Medlyn e al. (2002). Only kVcmax and kJmax s an-
da dised o a common o mula ion and pa ame isa ion o he
pho osyn hesis model by (Fa quha e al., 1980) we e used.
Mos kVcmax and kJmax alues in he TRY da abase had al-
eady been s anda dised o a e e ence empe a u e o 25◦C
(Ka ge and Kno , 2007). Subsequen ly, a species-speci ic
kJmax,op /kVcmax,op a io was calcula ed om he eco ds
which included bo h kVcmax,op and kJmax,op measu emen s.
F om his a io, which was wi hin a ange o 1.91–2.47
o each species, kJmax,op was calcula ed o eco ds which
o iginally only included kVcmax. Only geo- e e enced ob-
se a ions wi hin Eu ope we e used and he dis inc ion be-
ween bo eal and empe a e o es was made simila o he
species map. Depending on he species his esul ed in 5
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2052 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
o 183 obse a ions o ksla and 11 o 173 obse a ions o
kVcmax,op and kJmax,op . F om hese obse a ions species-
speci ic means we e calcula ed, weigh ed o di e ences in
he numbe o obse a ions pe si e. The pa ame e alues
a e shown in Table S3.
4.7 Mul i-laye wo-way adia ion scheme o all
canopies
The adia ion ans e scheme makes use o pa ame e s de-
sc ibing lea and backg ound p ope ies, i.e. lea single sca -
e ing and p e e ed sca e ing di ec ion ( o bo h isible
(VIS) and nea -in a ed (NIR) wa eleng hs) and he so-
called backg ound albedo o he albedo o he su ace be-
low he dominan ee canopy (VIS and NIR). All pa ame e s
we e aken om he Join Resea chCen e Two-s eamIn e -
sionPackage(JRC-TIP) (Pin y e al., 2011a, b).This is a so -
wa e package (Pin y e al., 2007) which in e s a wo-s eam
model (Pin y e al., 2006) o bes i he MODIS b oadband
isible and nea -in a ed whi e sky su ace albedo om 2001
o 2010 a 1km esolu ion (Pin y e al., 2011a). The in e se
p ocedu e implemen ed in he JRC-TIP is shown o be o-
bus , eliable, and complian wi h la ge-scale p ocessing e-
qui emen s (Pin y e al., 2011a). Fu he mo e, his package
ensu es he physical consis ency be ween se s o obse a-
ions, he wo-s eam model pa ame e s, and adia ion luxes.
Only pa ame e alues o which he pos e io s anda d
de ia ion o he p obabili y densi y unc ions we e signi -
ican ly smalle han he p io s anda d de ia ion we e se-
lec ed om he JRC-TIP op imisa ion (Pin y e al., 2011a),
since his condi ion ensu es s a is ically signi ican alues.
Species- and MTC-speci ic alues we e de i ed om JRC-
TIP by pe o ming a mul iple eg ession. This me hods de-
e mines, in an objec i e way, how he ac ions o each MTC
o species explain he JRC-TIP pa ame e . The mul iple e-
g ession was pe o med sepa a ely o he six pa ame e s: he
single sca e ing o lea es ( o bo h VIS and NIR), he sca -
e ing di ec ion o lea es (VIS and NIR) and he backg ound
albedo (VIS and NIR). Each JRC-TIP pa ame e was used
as he dependen a iable and he independen a iables con-
sis ed o he ac ions o each MTC (Poul e e al., 2015) o
species (B us e al., 2012). These ac ions we e used o ind
a linea unc ion ha bes p edic ed each JRC-TIP pa ame-
e . The co esponding slope o a eg ession o each MTC
o species ac ion gi es he MTC o species dependen JRC-
TIP alue. The mul iple eg ession was pe o med wi hou an
in e cep . To a oid pollu ion by he seasonal cycle, he mul i-
ple eg ession was applied only o he pixels o he No he n
Hemisphe e. Only pixels ha we e less han 10% co e ed
by non- ege a i e ac ions whe e selec ed o he analysis
and only signi ican esul s ollowing an F es and posi i e
2 alues we e selec ed. The de i ed pa ame e alues a e
shown in Table S4.
4.8 Main enance espi a ion
Bo h he unk and ORCHIDEE-CAN b anch educe he
de ini ion o ne p ima y p oduc ion o biomass p oduc ion;
hence, ca bon leaching om he oo s, ola ile o ganic emis-
sions om he lea es, dissol ed and pa icula e ca bon losses
h ough wa e luxes and ca bon subsidies o myco yhzae
a e no accoun ed o in he model. These luxes a e (inco -
ec ly) accoun ed o in he modelled au o ophic espi a ion.
Modelled au o ophic espi a ion should he e o e be consid-
e ed an e ec i e a he han a ue alue. Fo his eason, he
basal a e o au o ophic espi a ion was op imised agains
126 si e obse a ions o he biomass p oduc ion e iciency
(kcmain ) calcula ed as he a io be ween annual biomass p o-
duc ion and annual pho osyn hesis (Vicca e al., 2012; Cam-
pioli e al., 2015), using a Bayesian op imisa ion scheme. The
scheme, o which mo e de ails a e gi en in San a en e al.
(2007), uses a s anda d a ia ional me hod based on he i e -
a i e minimisa ion o a cos unc ion ha measu es bo h he
model da a mis i and he pa ame e de ia ions om p io
knowledge (Ta an ola, 2005).
The simula ions ha we e used in he Bayesian op imi-
sa ion p esc ibed a 20m all ege a ion o empe a e ee
species, a 15m all ege a ion o bo eal ee species and a
10m all ege a ion o Medi e anean ee species as i s ini-
ial condi ion. This app oach educed he need o se e al
decades o simula ions o a single yea o g ow a ma u e
o es s. In o al, he simula ions we e un o 10 yea s and
co e ed he Eu opean domain. The i s yea was disca ded
and he a io be ween modelled GPP and NPP was a e aged
o e he emaining 9 yea s. P io o he op imisa ion, he ob-
se a ions we e a e aged o ag icul u al PFTs (0.57), and
deciduous (0.44) and e e g een (0.53) o es PFTs; he ob-
se ed unce ain y was 0.03. The pa ame e alues we e se
o ange be ween 0.0032 and 0.160. The op imisa ion con-
e ged wi hin 11 i e a ions and he op imised pa ame e al-
ues a e shown in Table S2.
I emains un es ed how well he simula ed e ec i e au-
o ophic espi a ion ep esen s he ( a ely) obse ed au-
o ophic espi a ion. No e ha in he cases o bo h he
unk and he ORCHIDEE-CAN b anch o ORCHIDEE, a
ma ch be ween e ec i e and obse ed au o ophic espi a-
ion should no be in e p e ed as e idence o desi ed model
beha iou because se e al componen s o ne p ima y p o-
duc ion a e no modelled ye .
A e he op imisa ion o he main enance espi a ion co-
e icien (kcmain ), he model simula es easonable biomass
p oduc ion e iciency o a uni o pho osyn hesis. Hence, he
inal s ep o he pa ame isa ion ocussed on op imising he
lea a ea, as his is one o he main d i e s o pho osyn hesis.
4.9 Sapwood o lea a ea a io
The ege a ion s uc u e simula ed by he ORCHIDEE-CAN
b anch is sensi i e o he alue o kls which desc ibes he a io
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K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2053
be ween he lea and sapwood a ea o an indi idual ee. The
a ailable obse a ions show a wide ange wi hin and ac oss
o es species. Dependencies o kls on ee heigh (McDow-
ell e al., 2002; No ick e al., 2009), ee diame e ollow-
ing s and hinning (Simonin e al., 2006) and CO2(Pa aki
e al., 2006) ha e been epo ed. Mos obse a ions, how-
e e , come om expe imen s whe e ime was subs i u ed by
space which hampe s easing apa he sou ces o a iabili y.
Gi en he a ia ion and unce ain y in he obse a ions and
he model sensi i i y o his pa ame e , we manually uned
i s alue wi hin he obse ed ange, o ma ch Eu opean-wide
obse a ions o lea a ea index as eco ded in he Da abase o
Global Fo es Ecosys em S uc u e and Func ion Luyssae
e al. (2007).
This da abase was used o calcula e a mean and maximum
obse ed lea a ea index a he species le el o he empe a e
and bo eal egion. Ini ially 20 yea long Eu opean-wide sim-
ula ions we e used o simula e lea a ea index o a species,
when he la ge-scale lea a ea index app oached he mean
a ge alue and did no exceed he maximum alue, he sim-
ula ions we e ex ended o each 100 yea s o checking he
empo al e olu ion o lea a ea index. We delibe a ely op i-
mised he sapwood o lea a ea a io (kls) by making use o
s and-le el da a o educe ci cula i y wi h he model alida-
ion (see below).
Limi ed es s o e a pe iod o 100 yea s in a Sco s pine o -
es a 51–52◦N, 13–14◦E (Fig. S1 in he Supplemen ) sug-
ges ed ha op imising kcmain and kls had he la ges e ec
on he maximum LAI, which dec eased by almos 17% a e
op imisa ion compa ed o a simula ion wi h p io pa ame-
e alues. Mean annual GPP, mean annual anspi a ion and
basal a ea dec eased by, espec i ely, 6, 6 and 7% compa ed
o a simula ion wi h p io pa ame e alues (Fig. S1).
5 Valida ion
ORCHIDEE-CAN is designed as he land-su ace model o
be coupled o he LMDz a mosphe ic model. As such, u-
u e applica ions o ORCHIDEE-CAN a e expec ed o be e-
gional o global in he spa ial domain and o span se e al
yea s in he empo al domain. Gi en i s an icipa ed uses, he
abili y o he model o ep oduce la ge-scale spa ial pa e ns
as well as hei in e -annual a iabili y is essen ial. The i s
applica ions o he model, bo h o line and coupled o he a -
mosphe e, will ocus on Eu ope. The alida ion, he e o e,
epo s pe o mance indices bo h o e Eu ope as o e eigh
sepa a e egions wi hin Eu ope (Bellp a e al., 2012). These
eigh egions, which pa ially o e lap, a e de ined a e Bell-
p a e al. (2012). Fu he mo e, he pe o mance indices a e
calcula ed o win e , sp ing, summe and au umn, and hus
allow one o e alua e he capaci y o he model o ep oduce
obse ed annual cycles.
In addi ion o he oo mean squa e e o , a land pe o -
mance index (LPI) based on he p inciples laid ou o he
Clima e Pe o mance Index (Mu phy e al., 2004, hei SI)
was also calcula ed. LPI no malises he oo o he squa ed
di e ences be ween he simula ions and obse a ions by he
obse ed spa ial and empo al a iance. The LPI was used
o es ima e he likelihood ha he simula ed a iable belongs
o he same popula ion as he obse ed a iable, de ined as
exp(−0.5LPI2). An LPI equal o 1 indica es ha he model
co ec ly ep oduces he mean obse ed alue and implies a
likelihood o 61% (Mu phy e al., 2004) ha he simula ions
and obse a ions come om he same popula ion. Simila ly,
an LPI o 2 educes his likelihood o 13%. An LPI o less
han 0.32 has a likelihood o mo e han 95% and he e o e
indica es a s a is ically signi ican esul .
While de eloping ORCHIDEE-CAN, he nume ical ap-
p oaches ha added unc ionali y o he code we e selec ed
on he basis o hei pe o mance a he si e le el (see below).
Ra he han unning he same si e-le el es s o ou imple-
men a ion, we pe o med a complemen a y la ge-scale ali-
da ion. The s eng h o ou app oach lies no in he de ails, as
is he case o si e-le el alida ion, bu in i s wid h by simul-
aneously es ing model pe o mance o s uc u al a iables
such as basal a ea (de Rigo e al., 2014), canopy s uc u e
(Pin y e al., 2011a) and canopy heigh (Sima d e al., 2011),
biogeochemical luxes such as GPP (Jung e al., 2008), bio-
physical luxes such as albedo (Schaa e al., 2002) and luxes
a he in e ace o biogeochemis y and biophysics such as
e apo anspi a ion (Jung e al., 2008). The selec ion o a i-
ables was limi ed by he a ailabili y o spa ially explici da a-
de i ed p oduc s o Eu ope.
Fo he alida ion, bo h he unk and ORCHIDEE-CAN
b anch we e un om 1850 o 1900 using CRU-NCEP cli-
ma e o cing om 1901 o 1950 a 0.5 deg ee esolu ion.
F om 1901 un il 2012, he co esponding CRU-NCEP o c-
ing da a o each yea we e used. Bo h e sions used he
11 laye soil hyd ology, he single-laye ene gy budge and
he same land co e map (Poul e e al., 2015). Gi en ha no
Eu opean-wide, spa ially explici and da a-de i ed p oduc s
we e ound o he alida ion o he ne ca bon lux, he e
was no need o a ca bon spin-up. Fo he ORCHIDEE-CAN
b anch, he obse ed ee heigh and basal a ea we e com-
pa ed agains he simula ion alues a he end o 2010 ( he
unk does no simula e hese a iables). Fo bo h he unk
and he ORCHIDEE-CAN b anch, he obse ed GPP, e ap-
o anspi a ion, e ec i e LAI and VIS and NIR albedos we e
compa ed agains mon hly means be ween 2001 and 2010.
5.1 Species e sus PFTs
In ORCHIDEE-CAN he PFT concep was e ined by
pa ame ising he main Eu opean ee species g oups
(Sec . 4.1). To e alua e he e ec o he species pa ame i-
sa ion, we pe o med a companion simula ion o he con ig-
u a ion desc ibed abo e, bu a he MTC le el. Model pe o -
mance was ba ely a ec ed by he use o he MTC pa ame e s,
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2054 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
compa ed o he simula ion wi h he species pa ame e s (see
Fig. S2 o RMSE sco es).
5.2 Alloca ion
In ORCHIDEE-CAN, unc ional ela ionships which a y by
species and ligh s ess a e used o alloca e ca bon among
he ine oo s, oliage and sapwood. The alloca ion scheme
la gely ollows Zaehle and F iend (2010), who in u n was
inspi ed by Si ch e al. (2003). App oaches simula ing allo-
ca ion based on unc ional ela ionships we e ound o ou -
compe e alloca ion schemes based on cons an ac ions o
esou ce limi a ion (De Kauwe e al., 2014). The abili y o
hese schemes o ep oduce oliage, ine oo and sapwood
epo ed in la ge obse a ional da a se s ( o example, Luys-
sae e al., 2007) demons a es ha hese schemes cap u e
he main obse ed ea u es (Zaehle and F iend, 2010). In
addi ion, alloca ion schemes making use o unc ional ela-
ionships we e also capable o simula ing he obse ed e -
ec o ele a ed CO2on wo ma u e o es ecosys ems (De
Kauwe e al., 2014). Despi e hese successes, he schemes
we e epo ed o be sensi i e o hei pa ame isa ion. Di -
e ences in pa ame e s we e epo ed o esul in subs an-
ial di e ences in he simula ed alloca ion. The pa ame e s
o he unc ional ela ionships used in ORCHIDEE-CAN
a e gi en in Table S2. The main concep ual di e ence be-
ween he alloca ion scheme by Zaehle and F iend (2010) and
ORCHIDEE-CAN is ha he la e was designed o simula e
one o mo e diame e classes.
Gi en ha pho osyn hesis is s ill calcula ed a he s and
le el (and hus no a he ee le el) he alloca ion ule o
Deleuze e al. (2004) was in eg a ed in he unc ional allo-
ca ion scheme o accoun o ligh and esou ce compe i ion
wi hin a s and. Whe e he unc ional ela ionships a e used
o simula e ca bon alloca ion wi hin an indi idual ee o a
gi en diame e , he ule o Deleuze e al. (2004) alloca es
ca bon ac oss he di e en diame e classes. The alloca ion
ule which models he adial inc emen o indi idual ees
in pu e e en-aged s ands was success ully es ed o No -
way sp uce and Douglas i s ands in F ance (Deleuze e al.,
2004). A simila app oach o modelling adial inc emen has
al eady been implemen ed in a e sion close o he unk o
ORCHIDEE (Bellassen e al., 2010) and was able o suc-
cess ully simula e s and cha ac e is ics such as heigh , basal
a ea and s and diame e (Bellassen e al., 2011). This p e i-
ous implemen a ion di e s om he cu en implemen a ion
in i s ime esolu ion (which is now daily ins ead o yea ly),
i s analy ical solu ion and he unde lying alloca ion scheme
(which is now based on unc ional ela ionships ins ead o
esou ce limi a ion).
The a o emen ioned s udies pe o med a de ailed alida-
ion o he wo app oaches dealing wi h ca bon alloca ion,
which we e combined in ORCHIDEE-CAN. Complemen-
a y o hese s udies, we pe o med a Eu opean-wide ali-
da ion o ou implemen a ion and pa ame isa ion o hese
well- es ed schemes agains a emo e-sensing-based map o
ee heigh (Sima d e al., 2011), upscaled eddy-co a iance
obse a ions o GPP (Jung e al., 2008) and a map o basal
a ea based on na ional o es in en o y da a (de Rigo e al.,
2014). The model’s abili y o ep oduce GPP is hough o
e lec i s capaci y o simula e he oliage biomass, a co ec
simula ion o heigh e lec s he model’s capaci y o simula e
abo eg ound woody biomass, and i s capaci y o ep oduce
obse ed basal a eas sugges s ha he in e ac ion o s and
densi y and indi idual ee diame e a e well cap u ed.
The new implemen a ion and pa ame isa ion o he
wi hin- ee and wi hin-s and alloca ion schemes we e ound
o ha e a 91, 68 and 72% chance ha he simula ions will
ep oduce he obse a ions o GPP, ee heigh and basal
a ea o Eu ope, espec i ely (Table 3). Gi en ha basal
a ea and heigh a e no a ailable om he unk e sion
o ORCHIDEE, we could no compa e he pe o mance o
model e sions in his espec . Wi h espec o GPP, he
ORCHIDEE-CAN b anch was ound o ou pe o m he unk
by 12% and hus inc eased he likelihood ha ORCHIDEE-
CAN is an unbiased simula o o he spa ial and empo al
a iabili y o GPP om 79 o 91%. Imp o ed pe o mance
o he ORCHIDEE-CAN b anch compa ed o he unk is
obse ed o all egions in summe whe e he RMSE o GPP
was hal ed om 2.5–5 o 1–2gCm−2day−1(Figs. 2, 3 and
4).Al hough pa o he high likelihood could be due o he
ac ha he obse ed GPP was upscaled making use o sim-
ila clima ologies being used as he o cings o he mod-
els, his ci cula i y could nei he ha e con ibu ed o he im-
p o ed pe o mance be ween he unk and he ORCHIDEE-
CAN b anch no o he dec ease in RMSE. The imp o e-
men s a e hough o be due o s uc u al changes o he
model such as alloca ion, hyd aulic a chi ec u e and canopy
s uc u e as well as o he use o mo e consis en pa ame i-
sa ion.
5.3 Plan wa e supply
Ou implemen a ion o plan hyd aulic a chi ec u e was
la gely based on he scheme o Hickle e al. (2006), which
was es ed globally and a si e le el. Global simula ion e-
sul s o ac ual e apo anspi a ion we e ound o ep oduce
a ailable da a (Baumga ne and Reichel, 1975; Henning,
1989). A he si e le el, he model ag eed well wi h he mag-
ni ude and seasonali y o eddy-co a iance measu emen s o
ac ual e apo anspi a ion o 15 Eu opean o es si es (EU-
ROFLUX), wi h a endency o sligh ly o e es ima e ac ual
e apo anspi a ion o 6 si es (Hickle e al., 2006).
The maximum amoun o wa e ha can be anspo ed
by a ee elies on he hyd aulic a chi ec u e o he ee and
he e o e on he capaci y o he model o simula e ee and
s and dimensions as well as on he model’s capaci y o sim-
ula e soil wa e con en . As an addi ional es , ou imple-
men a ion o he model was compa ed agains he upscaled
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K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2055
Figu e 2. Roo mean squa e e o o ORCHIDEE-CAN o g oss p ima y p oduc ion, e apo anspi a ion, isible and nea -in a- ed albedo,
e ec i e lea a ea index, basal a ea and heigh o di e en egions and pe iods (DJF: Decembe –Feb ua y, MAM: Ma ch–May, JJA: June–
Augus , SON: Sep embe –No embe ). The g ay-scale o he symbols indica es he numbe o pixels included in he calcula ion. The ansi ion
om g een o whi e indica es an RMSE o 100%.
eddy-co a iance measu emen s o GPP and ac ual e apo-
anspi a ion (Jung e al., 2008). The capaci y o join ly e-
p oduce GPP and ac ual e apo anspi a ion is an indica o
ha he model success ully ep oduces he coupling be ween
CO2and wa e exchange. Model alida ion showed 91 and
87% chance (compa ed o 79 and 45% o he unk) ha
ORCHIDEE-CAN ep oduces he upscaled GPP and ac ual
e apo anspi a ion da a (Table 3, Fig. 4). The RMSE o
ac ual e apo anspi a ion du ing summe d opped well be-
low 1mmday−1 o mos egions (Fig. 2), whe eas i ne e
d opped below 1mmday−1 o he unk (Fig. 3).
5.4 Canopy s uc u e
The canopy s uc u e model by Ha e d e al. (2012) was
p e iously alida ed agains g ound-based LIDAR da a o
se e al es si es wi h a ying densi y, s uc u al complexi y,
laye ing and clumping (Lo ell e al., 2012). Model-de i ed
canopy gap p obabili ies compa ed wi h obse a ions using
a one-sample es we e signi ican o 11 ou o 12 es si es.
We conside ed his esul o be a su icien p oo o use his
canopy s uc u e model in he ORCHIDEE-CAN b anch and
added o i s alida ion by compa ing he simula ed canopy
s uc u e model o e Eu ope agains a emo e-sensing-based
map o ee heigh (Sima d e al., 2011) and he JRC-TIP
e ec i e LAI p oduc (Pin y e al., 2011a). The e ec i e
LAI alue exp esses he capabili y o he canopy o in e -
cep di ec adia ion, and is hus associa ed wi h he p oba-
bili y dis ibu ion unc ion o he canopy gaps (Ha e d e al.,
2012). Thus he e ec i e LAI con ains in o ma ion abou he
o es s uc u e and lea dis ibu ion o he canopy. In he
ORCHIDEE-CAN b anch, canopy s uc u e is used o cal-
cula e he albedo, oughness leng h, abso bed ligh o pho-
osyn hesis and lea a ea ha is coupled o he a mosphe e
o e.g. anspi a ion and in e cep ion o p ecipi a ion.
The ORCHIDEE-CAN b anch is he i s b anch o OR-
CHIDEE ha makes use o an e ec i e LAI o calcula e
he in e ac ion be ween he canopy and he a mosphe e. The
LPI and RMSE o he b anch, he e o e, canno be compa ed
agains he unk. O e all, he combined implemen a ion o
he alloca ion scheme and he canopy s uc u e model shows
a 67% chance o ep oduce he sa elli e-based es ima es o
e ec i e LAI. Su p isingly, e ec i e LAI is be e simula ed
in sp ing and au umn when dynamics wi hin he canopy a e
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2056 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
Figu e 3. Roo mean squa e e o o ORCHIDEE unk o g oss p ima y p oduc ion, e apo anspi a ion and isible and nea -in a ed albedo
o di e en egions and pe iods (DJF: Decembe –Feb ua y; MAM: Ma ch–May; JJA: June–Augus ; SON: Sep embe –No embe ). The g ey
scale o he symbols indica es he numbe o pixels included in he calcula ion. The ansi ion om g een o whi e indica es an RMSE o
100%.
GPP (gC m-2 day-1)Basal a ea (m2 ha-1)
Figu e 4. Compa ison be ween obse a ions and simula ions o
ORCHIDEE-CAN o g oss p ima y p oduc ion and basal a ea o e
Eu ope. G oss p ima y p oduc ion ep esen s he mean o June–
Augus be ween 2001–2010 and basal a ea is he alue a he end o
2010.
subs an ial due o lea on-se and senescence. Fo he pe i-
ods when he e ec i e LAI is expec ed o be mos s able,
i.e. summe and win e , LPI app oached and equen ly ex-
ceeded 1 (da a no shown). Pa o his sho coming may be
due o he lack o sh ubs in he land co e classi ica ion. In
he model, sh ublands a e eplaced by o es and/o g ass-
lands, likely esul ing in di e ences be ween he obse ed
and simula ed canopy s uc u e. This lapse also appea s in
he RMSE o e ec i e LAI (RMSE highe han 0.8, Fig. 2)
5.5 Top o he canopy albedo
The adia ion ans e model (Pin y e al., 2006) has
been alida ed ex ensi ely agains ealis ic complex h ee-
dimensional canopy scena ios (Pin y e al., 2006) and as pa
o he RAdia ion ans e Model In e compa ison (RAMI)
p ojec . The 1-D canopy adia ion ans e model by Pin y
e al. (2006) was demons a ed o accu a ely simula e bo h
he ampli ude and he angula a ia ions o all adian luxes
wi h espec o he sola zeni h angle (Widlowski e al.,
2011). In addi ion, he adia ion ans e model and i s e -
ec i e alues ex ac ed om he JRC-TIP da a se we e suc-
cess ully applied o a single o es si e (Pin y e al., 2011c).
P e iously we epo ed on he capaci y o he adia ion
ans e model o simula e he e ec s o o es managemen
on albedo (O o e al., 2014). Fo he la e , o es p ope ies
we e p esc ibed and he adia ion ans e model was ali-
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K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2057
Table 3. Likelihood ha he simula ed a iable comes om he same popula ion as he da a. The ORCHIDEE- unk e sion does no include e ec i e LAI, basal a ea and heigh . No e
ha he likelihood o Eu ope canno be de i ed om he alues o he o he egions due o he o e lap be ween egions.
ORCHIDEE-CAN ORCHIDEE-TRUNK
GPP EVAPO ALB_NIR ALB_VIS EFFLAI BA HEIGHT GPP EVAPO ALBEDO EFFLAI BA HEIGHT
B i ish Isles 0.91 0.87 0.78 0.45 0.55 0.47 0.13 0.91 0.49 0.74 0.04 − − −
Ibe ian Peninsula 0.80 0.80 0.73 0.65 0.60 0.09 0.66 0.65 0.37 0.25 0.04 − − −
F ance 0.86 0.90 0.92 0.46 0.60 0.66 0.60 0.69 0.46 0.75 0.02 − − −
Mid−Eu ope 0.92 0.93 0.88 0.86 0.68 0.80 0.76 0.81 0.48 0.64 0.46 − − −
Scandina ia 0.92 0.83 0.47 0.91 0.59 0.62 0.24 0.81 0.31 0.55 0.65 − − −
Alps 0.92 0.86 0.46 0.83 0.68 0.80 0.47 0.77 0.52 0.25 0.52 − − −
Medi e anean 0.84 0.77 0.77 0.80 0.65 0.51 0.72 0.54 0.45 0.43 0.45 − − −
Eas e n Eu ope 0.93 0.94 0.70 0.93 0.73 0.71 0.76 0.84 0.52 0.51 0.75 − − −
Eu ope 0.91 0.87 0.71 0.92 0.67 0.72 0.68 0.79 0.45 0.61 0.69 – – –
da ed agains op-o - he-canopy albedo da a om i e ob-
se a ional si es. Di e ences in he spa ial scales be ween
he obse ed and simula ed albedo alues we e accoun ed
o by p esen ing he mean June albedo du ing 2001–2010
(O o e al., 2014). The simula ed summe ime canopy albedo
alls wi hin he ange o obse a ion. Howe e , he e occu s
a sligh o e es ima ion in he nea -in a ed wa eleng h band
compa ed o he single si e measu emen . O e ly high nea -
in a ed single sca e ing albedo alues o pine, as ob ained
om he JRC-TIP p oduc , a e he mos likely cause. The
obse ed de ia ion is no due o a sho coming in he model
i sel , bu e lec s he di icul ies he JRC-TIP has wi h op i-
mising pa ame e alues in he absence o ield obse a ions
in he speci ic case o spa se canopies (O o e al., 2014).
Fo he spa ial alida ion we use he whi e-sky albedo
(VIS and NIR) om Mode a e Resolu ion Imaging Spec o-
adiome e (MODIS, Schaa e al., 2002) a 0.5◦ esolu ion
(dis ibu ed in ne CDF o ma by he In eg a ed Clima e Da a
Cen e (ICDC, h p://icdc.zmaw.de) Uni e si y o Hambu g,
Hambu g, Ge many). O e la ge spa ial and empo al do-
mains he ORCHIDEE-CANb anch ep oduces he obse ed
VIS and NIR albedo and i s a iabili y; LPI o he albedo in
he isible ligh is especially sa is ying wi h a likelihood o
92% o he simula ions o come om he same popula ion
as he obse a ions (Table 3). This high o e all pe o mance
index, howe e , hides pe o mance issues o e Scandina ia
and he Alps du ing he snow season. The RMSE o VIS and
NIR albedo wi hou snow lies a ound 0.05, whe eas du ing
he snow season he RMSE inc eases o 0.20 (VIS) and 0.18
(NIR) o e hese egions (Fig. 2). When he ORCHIDEE-
CAN b anch is coupled o an a mosphe ic model, howe e ,
hese de ia ions will only ha e a mino e ec on he clima e,
owing o low incoming adia ion du ing mos o he snow
season, especially in Scandina ia.
P e ious alida ion o he adia ion ans e model showed
ha he la ges disc epancies we e occu ing in he nea -
in a ed domain wi h a snow-co e ed backg ound (Pin y
e al., 2006). Wi h he excep ion o he snow-co e ed season,
he new albedo scheme, which elies on he simula ed canopy
s uc u e, esul ed in a subs an ial imp o emen o 0.05–0.15
compa ed o he unk o he RMSE in bo h he VIS and NIR
ange in Scandina ia and he Alps (Figs. 2 and 3). The Eu o-
pean LPI-based likelihood ha ou model simula ions come
om he same popula ions as he MODIS albedo inc eased
by a ema kable 11 and 23% o , espec i ely, NIR and VIS
albedo ( om 61 and 69% o he unk o 72 and 92% o
he ORCHIDEE-CAN, Table 3).
Gi en ha he pa ame isa ion o he canopy adia ion
ans e model used in ORCHIDEE-CAN elies on MODIS,
he high likelihood may no come as a su p ise. Howe e , ou
implemen a ion o he adia ion ans e model also elies on
he simula ed abso bed ligh , simula ed GPP, simula ed al-
loca ion and simula ed canopy s uc u e (which depends on
mo ali y and o es managemen ). In he absence o all hese
p ocesses ou canopy adia ion ans e model is expec ed
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2058 K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE
o ep oduce he MODIS da a wi h a p obabili y o 100%.
Hence, he likelihood o 72 and 92% ( o NIR and VIS, e-
spec i ely) could also be in e p e ed as a e i ica ion o he
a o emen ioned calcula ions; all calcula ions ha de e mine
he canopy s uc u e educe he ep oducibili y o he da a by
only 8–28% (100 o 72 o 92%).
5.6 Ene gy luxes
The mul i-laye scheme is in he p ocess o a de ailed e al-
ua ion ac oss a ange o es condi ions (Ryde e al., 2014),
and u he alida ion ac oss a ange o si es is ongoing. The
schemeis able o p oduce wi hin-canopy empe a u e andhu-
midi y p o iles, and success ully simula es he in-canopy a-
dia ion dis ibu ion, as well as he sepa a ion o he canopy
om he soil su ace. Howe e , in o de o p ese e a mea-
su e o con inui y wi h p e ious e alua ions o he model,
he mul i-laye solu ion is he e se o single-laye ope a-
ion mode, which includes he e ec s o hyd aulic limi a-
ion (Sec . 3.2) and canopy s uc u e (Sec . 3.3) on he ene gy
budge .
The single-laye se -up o he mul i-laye solu ion makes
use o an imp o ed albedo es ima ion and is he e o e ex-
pec ed o be e simula e he ne adia ion ha needs o be e-
dis ibu ed in he canopy. This has been con i med a a single
si e wi h a spa se canopy (Ryde e al., 2014). Fu he mo e,
he imp o emen s in ac ual e apo anspi a ion in addi ion o
he low RMSE (Fig. 2) a e expec ed o be p opaga ed in he
pe o mance o he ene gy budge .
5.7 Fo es managemen s a egies
Model compa ison has p e iously demons a ed ha explic-
i ly ea ing hinning p ocesses is essen ial o ep oduce lo-
cal and la ge-scale biomass obse a ions (Wol e al., 2011).
This inding jus i ies he implemen a ion o gene ic ap-
p oaches o o es managemen despi e he di icul ies asso-
cia ed wi h de ining and quan i ying o es managemen and
i s in ensi y (Schall and Amme , 2013). Al hough he use
o so-called na u alness indices, in which he cu en s a e
o he o es in e e enced agains he po en ial s a e o he
o es , has been c i icised because o di icul ies in de ining
he po en ial s a e o he o es (Schall and Amme , 2013),
such app oaches we e demons a ed o co ec ly ank di e -
en managemen s a egies acco ding o hei in ensi y (Luys-
sae e al., 2011).
Na u alness indices making use o only diame e and s and
densi y o he so-called ela i e densi y index (RDI) ha e
been p e iously implemen ed a he s and le el (Fo in e al.,
2012) as well as in la ge-scale models (Bellassen e al.,
2010). This app oach was shown o success ully ep oduce
he biomass changes du ing he li e cycle o a o es (Bel-
lassen e al., 2011; Fo in e al., 2012). The implemen a ion
o a o es y model based on he ela i e densi y index was
epo ed o pe o m be e han simple s a is ical models o
0
5
10
15
20
25
Biomass (
103
gC m
−
2
)
(A)(A)(A)(A)
0
5
10
15
20
25
C.W.D. (
103
gC m
−
2
)
(B)(B)(B)(B)
1800 1850 1900 1950 2000
Yea
0
5
10
15
20
25
30
T ee heigh (m)
(C)(C)(C)(C)
1800 1850 1900 1950 2000
Yea
0
10
20
30
40
50
60
Cum. ha es (
103
gC m
−
2
)
(D)(D)(D)(D)
Figu e5. Impac o he di e en o es managemen s a egies on an
oak o es o unmanged (g een), high s and (o ange) and coppice
(blue) compa ed o a Popla sho o a ion coppicing ( ed) a 48◦N,
2◦E. The simula ion was un wi hou spin-up o be e isualise ca -
bon build-up in he coa se woody deb is (C.W.D.) pool. Simula ion
cycled o a single yea (1990) o clima e da a o minimise he in e -
annual a iabili y due o clima ic yea - o-yea a iabili y
s and-le el a iables such as s and densi y, basal a ea, s and-
ing olume and heigh (Bellassen e al., 2011). Al hough he
pe o mance o he model was epo ed as less sa is ying o
ee-le el a iables, he app oach is ne e heless conside ed
eliable o modelling he e ec s o o es managemen on
biomass s ocks o o es s ac oss a ange o scales om plo
o coun y (Bellassen e al., 2011).
In he absence o o es managemen , ORCHIDEE-CAN
simula es ha he s ands de elop in o all canopy (Fig. 5a),
wi h a high biomass (Fig. 5b), a subs an ial dead wood and
li e pool (Fig. 5c) and no ha es (Fig. 5d). High s and man-
agemen educes he heigh , s anding biomass and li e pools
(Fig. 5a–c) bu p oduces biomass o ha es (Fig. 5d). Un-
de coppicing, he educ ion in o es age is e lec ed in a
sho e canopy and lowe biomass and li e pools (Fig. 5a–
c) compa ed o high s and managemen . The ha es is mo e
e enly sp ead in ime bu alls below he ha es gene a ed
by high s and managemen (Fig. 5d). Gi en he sho e o-
a ions, canopy heigh , s anding biomass and li e pools a e
lowe o sho o a ion coppicing wi h popla and willow
compa ed o all o he managemen s a egies applied on oak
o es (Fig. 5a–c). Sho o a ion coppice was ha es ed e -
e y 3 yea s esul ing in a quasi-con inuous supply o woody
biomass (Fig. 5d).
The o es y model implemen ed in ORCHIDEE-CAN is
based on he RDI app oach by Bellassen e al. (2010). We
complemen ed ea lie alida ion o such an app oach o e
F ance (Bellassen e al., 2011) by a new Eu opean-wide al-
ida ion o basal a ea. On he Eu opean scale we e i ied he
simula ed basal a ea and heigh agains obse ed basal a ea
Geosci. Model De ., 8, 2035–2065, 2015 www.geosci-model-de .ne /8/2035/2015/
K. Naud s e al.: A e ically disc e ised canopy desc ip ion o ORCHIDEE 2059
Figu e 6. Roo mean squa e e o (RMSE) o ee diame e o di -
e en species (shown as di e en ma ke s) o di e en egions
o e F ance (shown as A o K). Open iangle, Pinus syl es is;
open ci cle, Pinus pinas e ; open squa e, Picea Sp.; illed diamond,
Que cus ilex/sube ; illed iangle, Be ula Sp.; illed ci cle, Fagus
syl a ica; illed squa e, Que cus obu /pe aea.
om na ional o es in en o ies (de Rigo e al., 2014) and
heigh om emo e sensing (Sima d e al., 2011). Wi h an
RMSE o 3–7 o heigh and 7–15 o BA, and a chance
o , espec i ely, 68 and 72% o ep oduce he da a on he
Eu opean scale (Table 3), ou model is capable o co ec ly
simula ing he mean heigh and basal a ea bu ails o cap-
u e much o he spa ial a iabili y (Fig. 4; empo al a iabil-
i y was no conside ed because he da a p oduc s we e only
a ailable o one ime pe iod).
Fu he mo e, we e alua ed basal a ea and ee diame e a
he species le el o 11 egions o e F ance, which ep e-
sen s a ine spa ial scale han a ge ed by he model de el-
opmen s and hei pa ame isa ion. The da a we e ex ac ed
om he F ench o es in en o y be ween 2005 and 2010 and
we used he same simula ions as o he Eu opean alida ion
in he p e ious pa ag aph. We selec ed pixels included in he
F ench in en o y da a and o bo h simula ions and obse -
a ions we calcula ed a mo ing a e age o he diame e and
basal a ea pe age class o hen calcula ed he RMSE (Fig. 6).
To accoun o in insic species di e ences in diame e and
basal a ea, we no malised he RMSE. The no malised RMSE
was lowe han 30% o he mean ee diame e o mean basal
a ea o each egion o Be ula sp., Pinus pinas e and Que -
cus ilex. Fo Fagus syl a ica,Pinus syl es is,Picea sp. and
Que cus obu /pe aea he no malised RMSE o diame e
and basal a ea exceeded 50% o one o ou egions o ee
diame e and basal a ea (no shown).
The inabili y o ully cap u e he obse ed spa ial a iabil-
i y in he simula ion could be due o he simula ion p o ocol
ha s a ed in 1850 wi h 2 o 3m all ees all o e Eu ope. A
longe simula ion accoun ing o he majo his o ical changes
in o es managemen such as he e o es a ion in he 1700s
ollowing an all ime low in he Eu opean o es co e , he
s a o high s and managemen a he expense o coppicing
in he ea ly 1800s, and he e o es a ion p og ams ollowing
Wo ld Wa II (Fa ell e al., 2000) is expec ed o imp o e
he spa ial a iabili y in ee heigh and basal a ea. Regional
de ia ions such as hose obse ed on he Ibe ian Peninsula
o o e he en i e Medi e anean ( hus including pa o he
Ibe ian Peninsula) may be due o he lack o sh ubs in he
landco e map and pa ame isa ion o he ORCHIDEE-CAN
b anch. The e o e he models simula es a highe s and den-
si y and highe basal a ea o egions whe e in eali y sh ubs
occu (Fig. 4).
The pa ame isa ion o he o es y module s ongly de-
pends on he na ional o es in en o ies om Spain, F ance,
Ge many and Sweden. The e o e e i ica ion agains he
same da a con ains li le in o ma ion abou he model qual-
i y. Ne e heless, no ime-dependen ela ionships we e used
in he ORCHIDEE-CAN b anch; hus he model’s capaci y
o ep oduce he ela ionship be ween basal a ea and s and
age, diame e and s and age o wood olume and s and age
could be conside ed a la gely independen es o he model
quali y. These es s we e pe o med o e eigh bioclima ic e-
gions o F ance and he ORCHIDEE-CAN b anch was ound
o la gely cap u e he ime dependencies o basal a ea, diam-
e e and wood olume (no shown).
6 Conclusions
ORCHIDEE-CAN (SVN 2290) di e s om he unk e -
sion o ORCHIDEE (SVN 2243) by he allome ic-based
alloca ion o ca bon o lea , oo , wood, ui and ese e
pools; he ansmi ance, abso bance and e lec ance o a-
dia ion wi hin he canopy; and he e ical disc e isa ion o
he ene gy budge calcula ions. Concep ual changes owa ds
a be e p ocess ep esen a ion we e made o he in e ac-
ion o adia ion wi h snow, he hyd aulic a chi ec u e o
plan s, he ep esen a ion o o es managemen and a nume -
ical solu ion o he pho osyn hesis o malism o Fa quha ,
on Caemme e and Be y. Fu he mo e, hese changes we e
ex ensi ely linked h oughou he code o imp o e he con-
sis ency o he model. By making use o obse a ion-based
pa ame e s, he physiological ealism o he model was im-
p o ed and signi ican epa ame isa ion was done by in o-
ducing 12 new pa ame e se s ha ep esen speci ic ee
species o gene a a he han a g oup o phylogene ically o -
en un ela ed species, as is he case in widely used plan unc-
ional ypes (PFTs). As PFTs ha e no meaning ou side he
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