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biome4.f
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c---------------------------------------------------------------------------
c The BIOME4-system: biome4.f 4.2b2 02.11.99
c
c Copyright (c) 1999 by Jed O. Kaplan
c
c See COPYING file for copying and redistribution conditions.
c
c This program is free software; you can redistribute it and/or modify
c it under the terms of the GNU General Public License as published by
c the Free Software Foundation; version 2 of the License.
c
c This program is distributed in the hope that it will be useful,
c but WITHOUT ANY WARRANTY; without even the implied warranty of
c MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
c GNU General Public License for more details.
c
c Contact info: [email protected]
c---------------------------------------------------------------------------
c
c B I O M E 4 . F
c
c---------------------------------------------------------------------------
c This is BIOME4, based on BIOME3 (Haxeltine and Prentice 1996).
c
c All arguments to and from this subroutine are passed through two arrays:
c
c "vars_in" and "output"
c
c You can customize the contents of these arrays to suit your own needs
c based on the assignments in the beginning of the program and the
c output assignments in the subroutine "competition2". I suggest each
c user write his own driver software.
c
c The basic input variables required by this model are:
c Monthly mean- temperature, precipitation, %cloudiness (or sunshine)
c Absolute minimum temperature
c Water holding capacity (mm) in the top 30cm of the soil
c Water holding capacity (mm) in the rest of the soil
c Conductivity index of water through the soil column (see the soil
c and hydrology subroutines for more information).
c
c Caveat: compared to the original BIOME3 there is a lot of added
c functionality in this model, and in some cases complexity. The code
c may neither compile nor run on certain systems (it works well now
c compiled with g77 and running on an Intel Linux machine).
c
c Please direct your questions to me at [email protected]
c
c By Jed O. Kaplan 1994-1999.
c
c For further reference see:
c
c Haxeltine and Prentice, I.C. 1996. BIOME3: An equilibrium
c terrestrial biosphere model based on ecophysiological
c constraints, resource availibility and competition among
c plant functional types, Global Biogeochemical Cycles, 10(4) 693-709.
c
c Please remove this header and change the name of your new model
c if you make ANY alterations to the code!
c
c Author: Jed O. Kaplan
c Date: 22 October 1999
c Version: v4.2b2
c Revised: 02.11.99 by JOK
c Added back in d13C/DeltaE functionality
c Revised: 18.11.99 by JOK
c Changed competition subroutine (line 708-709),
c so that npp=npp(dom), not npp=npp(wdom).
c Revised: 15.12.99 by JOK
c Added functionality to tune soil parameters when the model
c is running in diagnostic mode. (line 240-251)
c Modified hydrology subroutine to handle low moisture retention
c soils (line 2356-2364) with else statements setting w to 0 when
c k=0 (this should be true)
c Revised: 17.12.99 by JOK
c Changed this header information to reflect what the soils data
c actually is.
c Examined hydrology subroutine to establish sensitivity to soil
c physical properties.
c Corrected line 2348 percolation function should always be to the
c power 4 (**4) and not scaled to k().
c
c------------------------------------------------------------------------
subroutine biome4(vars_in,output)
implicit none
integer numofpfts
parameter(numofpfts=13)
logical diagmode
integer optdata(0:numofpfts,500)
integer biome,pft
integer pfts(numofpfts),iopt
integer i
real lon,lat,co2,p,tdif,temp(12),prec(12),clou(12),soil(5)
real dtemp(365),dprec(365),dclou(365),dprecin(365)
real dpet(365),dphen(365,2),dmelt(365),realout(0:numofpfts,200)
real optnpp(0:numofpfts),optlai(0:numofpfts)
real pftpar(25,25),k(12),dayl(12),sun(12),wetness(0:numofpfts)
real gdd5,tcm,twm,tprec,gdd0,rad0,tmin,tminin
real tsoil(12),ddayl(365),maxdepth
real radanom(12),alttmin
real vars_in(50)
real output(500)
character*1 yorn
real sumagnpp,delag,wtagnpp
c----------------------------
character*40 biomename(28)
data biomename /
> 'Tropical evergreen forest',
> 'Tropical semi-deciduous forest',
> 'Tropical deciduous forest/woodland',
> 'Temperate deciduous forest',
> 'Temperate conifer forest',
> 'Warm mixed forest',
> 'Cool mixed forest',
> 'Cool conifer forest',
> 'Cold mixed forest',
> 'Evegreen taiga/montane forest',
> 'Deciduous taiga/montane forest',
> 'Tropical savanna',
> 'Tropical xerophytic shrubland',
> 'Temperate xerophytic shrubland',
> 'Temperate sclerophyll woodland',
> 'Temperate broadleaved savanna',
> 'Open conifer woodland',
> 'Boreal parkland',
> 'Tropical grassland',
> 'Temperate grassland',
> 'Desert',
> 'Steppe tundra',
> 'Shrub tundra',
> 'Dwarf shrub tundra',
> 'Prostrate shrub tundra',
> 'Cushion-forbs, lichen and moss',
> 'Barren',
> 'Land ice' /
c----------------------------
c assign the variables that arrived in the array vars_in
lon=vars_in(49)
lat=vars_in(1) !vars_in(49)-(vars_in(1)/vars_in(50))
co2=vars_in(2)
p=vars_in(3)
tminin=vars_in(4)
do i=1,12
temp(i)=vars_in(4+i)
prec(i)=vars_in(16+i)
clou(i)=vars_in(28+i)
end do
do i=1,4
soil(i)=vars_in(40+i)
end do
iopt=nint(vars_in(46))
if (iopt.eq.1.) then
diagmode=.true.
else
diagmode=.false.
end if
c----------------------------
c set a dummy rad anomaly (not used in this version)
do i=1,12
radanom(i)=1.0
end do
c-------------------------------------------------------------------------
c Reset the output matrix
do pft=0,numofpfts
do i=1,500
optdata(pft,i)=0
end do
end do
c-------------------------------------------------------------------------
c Initialize soil texture specific parameters
k(1)=soil(1)
k(2)=soil(2)
k(5)=soil(3)
k(6)=soil(4)
c-------------------------------------------------------------------------
c Linearly interpolate mid-month values to quasi-daily values:
call daily(temp,dtemp)
call daily(clou,dclou)
call daily(prec,dprecin)
c--------------------------------------------------------------------------
c Initialize parameters derived from climate data:
call climdata(tcm,twm,gdd5,gdd0,tprec,temp,prec,dtemp,alttmin)
call soiltemp(temp,soil,tsoil)
c--------------------------------------------------------------------------
c Calculate mid-month values for pet,sun & dayl from temp,cloud & lat:
call ppeett
> (lat,dtemp,dclou,dpet,temp,sun,dayl,rad0,ddayl,radanom)
c-------------------------------------------------------------------------
c Run snow model:
call snow(dtemp,dprec,dmelt,dprecin,maxdepth)
c-------------------------------------------------------------------------
c Initialize the evergreen phenology
do i=1,365
dphen(i,1)=1.0
dphen(i,2)=1.0
end do
c Initialize pft specific parameters
call pftdata(pftpar)
c--------------------------------------------------------------------------
c Rulebase of absolute constraints to select potentially presents pfts:
call constraints
> (tcm,twm,tminin,gdd5,rad0,pfts,tmin,maxdepth,gdd0)
c The tropical evergreen pft is not used in this version
c of the model. This is because the tropical deciduous tree
c will be evergreen if it is not subject to water stress.
c Otherwise the two pft's are parameterized in the same way,
c so not using the pft saves computation time.
pfts(1)=0
c--------------------------------------------------------------------------
if (diagmode) then
write(*,'(A,F8.2,A,F8.2)')'Longitude:',lon,' Latitude:',lat
write(*,'(A,F6.1,A,F6.1,A)')
> 'Tcm and Tmin are:',tcm,' and',tmin,' degrees C respectively.'
write(*,'(A,F8.1,A,F8.1,A)')
> 'GDD5 is:',gdd5,' and total annual precip is:',tprec,' mm.'
write(*,'(A,F8.1,A)')
> 'Maximum snowdepth is:',maxdepth*10.,' mm.'
write(*,'(A,2F7.2,3F7.1)')
> 'The current soil parameters are:',soil
write(*,'(A,$)')
> 'Enter new soil parameters? '
read(*,*)yorn
if (yorn.eq.'y') then
write(*,'(A,$)')'Percolation index ~(0-7): '
read(*,*)soil(1)
soil(2)=soil(1)
write(*,'(A,$)')'Top layer whc ~(0-999): '
read(*,*)soil(3)
write(*,'(A,$)')'Bottom layer whc ~(0-999): '
read(*,*)soil(4)
c Reinitialize soil texture specific parameters
k(1)=soil(1)
k(2)=soil(2)
k(5)=soil(3)
k(6)=soil(4)
end if
write(*,*)'The following PFTs will be computed:'
end if
c--------------------------------------------------------------------------
c Calculate optimal LAI & NPP for the selected pfts:
do pft=1,numofpfts
optlai(pft)=0.0
optnpp(pft)=0.0
if (pfts(pft).ne.0) then
if (pftpar(pft,1).ge.2) then
c Initialize the generic summergreen phenology
call phenology(dphen,dtemp,temp,tcm,tdif,tmin,pft,ddayl,pftpar)
end if
call findnpp(pfts,pft,optlai(pft),optnpp(pft),
> tprec,dtemp,sun,temp,dprec,dmelt,dpet,dayl,k,pftpar,optdata,
> dphen,co2,p,tsoil,realout,numofpfts)
end if
end do
c------------------------------------------------------------------------------
c Select dominant plant type/s on the basis of modelled optimal NPP & LAI:
call competition2
> (optnpp,optlai,wetness,tmin,tprec,pfts,optdata,output,diagmode,
> biome,numofpfts,gdd0,gdd5,tcm,pftpar,soil)
c------------------------------------------------------------------------------
c Final output biome is given by the integer biome:
output(1)=biome
output(48)=lon
output(49)=lat
do pft=1,numofpfts
output(300+pft)=nint(optnpp(pft))
output(300+numofpfts+pft)=nint(optlai(pft)*100.0)
c-----------------------
if (pfts(pft).ne.0) then
if (diagmode) then
c type some diagnostic output here
write(*,10)pft,optlai(pft),optnpp(pft),wetness(pft),
> ((optdata(pft,i)/10.),i=37,48)
10 format(I3,F5.2,F7.1,F6.1,12F6.1)
end if
end if
c-----------------------
end do
if (diagmode) then
write(*,'(A,I3,A,A)')'Biome',biome,' ',biomename(biome)
sumagnpp=0.0
delag=0.0
do i=1,6
if (optdata(8,36+i).gt.0) then
sumagnpp=sumagnpp+(real(optdata(8,36+i))/10.)
end if
end do
do i=1,6
if (optdata(8,36+i).gt.0) then
wtagnpp=real(optdata(8,36+i))/(sumagnpp*10.)
delag=delag+real((optdata(8,79+i))*wtagnpp/100.)
end if
end do
write(*,'(A,F6.2,A)')
> 'The deltaA of C3 grass is',delag,' per mil.'
write(*,*)'press return to continue'
read(*,*)
end if
return
end
c*******************************************************************************
subroutine competition2
>(optnpp,optlai,wetness,tmin,tprec,pfts,optdata,output,diagmode,
> biome,numofpfts,gdd0,gdd5,tcm,pftpar,soil)
implicit none
integer numofpfts
real optnpp(0:numofpfts),optlai(0:numofpfts),maxnpp,maxlai
real maxdiffnpp,woodylai,grasslai,driest(0:14) !numofpfts
real tmin,tcm,pftpar(25,25),soil(5),mwet,wettest(0:14)
real temperatenpp,tprec,wetness(0:numofpfts),lai,npp
real woodnpp,grassnpp,subnpp,gdd0,gdd5,ratio,lairatio,nppdif
real wetlayer(0:numofpfts,2),wetratio(0:numofpfts)
real npprat,treepct,grasspct
real output(500)
c real woodypercent,grasspercent
integer pft,pftmaxlai,pftmaxnpp,optpft,subpft
integer pfts(numofpfts),optdata(0:numofpfts,500)
integer dom,wdom,grasspft,m,pos,month,wetpft,firedays
integer biome,greendays,drymonth(0:14),subfiredays !numofpfts
logical grass(14),present(14),flop !numofpfts
logical diagmode
do pft=1,numofpfts
if (pft.ge.8) then
grass(pft)=.true.
else
grass(pft)=.false.
end if
grass(10)=.false.
if (optnpp(pft).gt.0.0) then
present(pft)=.true.
else
present(pft)=.false.
end if
end do
present(12)=.true.
c----Initialize all of the variables that index an array---
optpft=0
subpft=0
grasspft=0
pftmaxnpp=0
pftmaxlai=0
dom=0
wdom=0
wetpft=0
maxnpp=0.0
maxlai=0.0
temperatenpp=0.0
maxdiffnpp=0.0
grassnpp=0.0
c------------------------------------------------------------------------
c---- choose the dominant woody PFT on the basis of NPP:
c------------------------------------------------------------------------------
c-----Find the PFTs with the highest npp and lai-------------------------
do pft=1,12
if (grass(pft)) then !grass PFT's
if (optnpp(pft).gt.grassnpp) then
grassnpp=optnpp(pft)
grasspft=pft
end if
else
if (optnpp(pft).gt.maxnpp) then !woody PFT's
maxnpp=optnpp(pft)
pftmaxnpp=pft
end if
if (optlai(pft).gt.maxlai) then
maxlai=optlai(pft)
pftmaxlai=pft
else if (optlai(pft).eq.maxlai) then
maxlai=optlai(pftmaxnpp)
pftmaxlai=pftmaxnpp
end if
end if
end do
c-----Find average annual soil moisture value for all PFTs:----------
do pft=1,numofpfts
wetness(pft)=0.
wetlayer(pft,1)=0.0
wetlayer(pft,2)=0.0
drymonth(pft)=0
wettest(pft)=-1.0
driest(pft)=101.0
do m=1,12
c mwet=optdata(pft,m+12)
mwet=optdata(pft,m+412)
wetness(pft)=wetness(pft)+mwet/12.
wetlayer(pft,1)=wetlayer(pft,1)+optdata(pft,m+412)/12. !top
wetlayer(pft,2)=wetlayer(pft,2)+optdata(pft,m+424)/12. !bottom
if (mwet.gt.wettest(pft)) wettest(pft)=mwet
if (mwet.lt.driest(pft)) then
drymonth(pft)=m
driest(pft)=mwet
end if
end do
end do
c----------------------------------------
optpft=pftmaxnpp
wdom=optpft
c find the subdominant woody pft (2nd in NPP)
subnpp=0.0
subpft=0
do pft=1,7
if (pft.ne.wdom) then
if (optnpp(pft).gt.subnpp) then
subnpp=optnpp(pft)
subpft=pft
end if
end if
end do
c-----------------------------------------------------------
flop=.false.
1 continue
woodylai= optlai(wdom)
woodnpp = optnpp(wdom)
grasslai= optlai(grasspft)
if (wdom.ne.0) then
firedays=optdata(wdom,199)
subfiredays=optdata(subpft,199)
greendays=optdata(wdom,200)
else
firedays=0
subfiredays=0
greendays=0
end if
nppdif=optnpp(wdom)-optnpp(grasspft)
ratio=0.0
c------------------------------------------------------------
if ((wdom.eq.3.or.wdom.eq.5).and.tmin.gt.0.0) then
if (gdd5.gt.5000.0) then
wdom=2
goto 1
end if
end if
c------------------------------------------------------------
c Under certain conditions grass will be the dominant or co-dominant PFT:
if (wdom.eq.1) then
if (optnpp(wdom).lt.2000.0) then
wdom=2
subpft=1
goto 1
end if
end if
if (wdom.eq.2) then
if (woodylai.lt.2.0) then
optpft=grasspft
else if (grasspft.eq.9.and.woodylai.lt.3.6) then
optpft=14
else if
> (greendays.lt.270.and.tcm.gt.21.0.and.tprec.lt.1700.0)
> then
optpft=14
else
optpft=wdom
end if
end if
if (wdom.eq.3) then
if (optnpp(wdom).lt.140.0) then
optpft=grasspft
else if (woodylai.lt.1.0) then
optpft=grasspft
else if (woodylai.lt.2.0) then
optpft=14
else
optpft=wdom
end if
end if
if (wdom.eq.4) then
if (woodylai.lt.2.0) then
optpft=grasspft
else if (firedays.gt.210.and.nppdif.lt.0.0) then
if (.not.flop.and.subpft.ne.0) then
wdom=subpft
subpft=4
flop=.true.
goto 1
else
optpft=grasspft
end if
else if (woodylai.lt.3.0.or.firedays.gt.180) then
if (nppdif.lt.0.0) then
optpft=14
else if (.not.flop.and.subpft.ne.0) then
wdom=subpft
subpft=4
flop=.true.
goto 1
end if
else
optpft=wdom
end if
end if
if (wdom.eq.5) then
if (present(3)) then
wdom=3
subpft=5
goto 1
c else if (nppdif.lt.0.0) then
c if (.not.flop.and.subpft.ne.0) then
c wdom=subpft
c subpft=5
c flop=.true.
c goto 1
c end if
else if (optnpp(wdom).lt.140.0) then
optpft=grasspft
else if (woodylai.lt.1.2) then
optpft=14
else
optpft=wdom
end if
end if
c add npp limits on other PFT's (tropical mountain story)
if (wdom.eq.6) then
if (optnpp(wdom).lt.140.0) then
optpft=grasspft
else if (firedays.gt.90) then
if (.not.flop.and.subpft.ne.0) then
wdom=subpft
subpft=6
flop=.true.
goto 1
end if
else
optpft=wdom
end if
end if
if (wdom.eq.7) then
if (optnpp(wdom).lt.120.0) then
optpft=grasspft
c else if (optnpp(wdom).lt.120.0) then
c optpft=14
else if (wetness(wdom).lt.30.0.and.nppdif.lt.0.0) then
optpft=grasspft
else
optpft=wdom
end if
end if
if (wdom.eq.0) then
if (grasspft.ne.0) then
optpft=grasspft
else if (optnpp(13).ne.0.0) then
optpft=13
else
optpft=0
end if
end if
if (optpft.eq.0.and.present(10)) optpft=10
if (optpft.eq.10) then
if (grasspft.ne.9.and.(optnpp(grasspft).gt.optnpp(10))) then
optpft=grasspft
else
optpft=10
end if
end if
if (optpft.eq.grasspft) then
if (optlai(grasspft).lt.1.8.and.present(10)) then
optpft=10
else
optpft=grasspft
end if
end if
if (optpft.eq.11) then
if (wetness(optpft).le.25.0.and.(present(12))) then
optpft=12
end if
end if
c----------------------------------------------------------------------
c----------------------------------------------------------------------
c output some diagnostic results
if (diagmode) then
do pft=1,numofpfts
if (pfts(pft).ne.0) then
write(*,4)
> pft,drymonth(pft),driest(pft),wetness(pft),optdata(pft,199),
> optdata(pft,200)
4 format(2I5,2F6.2,2I5)
end if
end do
write(*,*)' wpft woodynpp woodylai gpft grassnpp subpft phi'
write(*,5)wdom,woodnpp,woodylai,grasspft,grassnpp,subpft,
> optdata(8,52)/100.
5 format(I5,F10.2,F10.2,I5,F10.2,I5,F8.2,F8.2)
end if
c------------------------------------------------------
c put some variables into format for output
dom=optpft
c------------------------------------------------------
if (optpft.eq.14) then
npprat=woodnpp/grassnpp
treepct=((8./5.)*npprat)-.54
if (treepct.lt.0.0) treepct=0.0
if (treepct.gt.1.0) treepct=1.0
grasspct=1.-treepct
dom=wdom
lai=(woodylai+(2.*grasslai))/3.0
npp=(woodnpp+(2.*grassnpp))/3.0
c NEP
do pos=137,148
optdata(dom,pos)=
> (optdata(wdom,pos)+(2.*(optdata(grasspft,pos))))/3.0
end do
c DeltaA
do pos=80,91
optdata(dom,pos)=
> (optdata(wdom,pos)+(2.*(optdata(grasspft,pos))))/3.0
end do
c NPP
do pos=37,48
optdata(dom,pos)=
> (optdata(wdom,pos)+(2.*(optdata(grasspft,pos))))/3.0
end do
c Rh
do pos=113,124
optdata(dom,pos)=
> (optdata(wdom,pos)+(2.*(optdata(grasspft,pos))))/3.0
end do
c DeltaE
optdata(dom,50)=
> treepct*optdata(wdom,50)+grasspct*optdata(grasspft,50)
c > (optdata(wdom,50)+(2.*(optdata(grasspft,50))))/3.0
c %C4 NPP
optdata(dom,98)=
> (optdata(wdom,98)+(2.*(optdata(grasspft,98))))/3.0
end if
c------------------------------------------------------
if (optlai(dom).eq.0.0) optpft=0
npp=optnpp(dom)
lai=optlai(dom)
c npp=optnpp(wdom)
c lai=optlai(wdom)
grasslai=optlai(grasspft)
c npp=optnpp(grasspft)
c lai=optlai(grasspft)
c lai=woodylai
c lai=grasslai
call newassignbiome
>(optpft,wdom,grasspft,subpft,npp,woodnpp,grassnpp,subnpp,
> greendays,biome,gdd0,gdd5,tcm,present,woodylai,grasslai,tmin)
c-----------------------------------------------------------------------
c The values of all output variables, except the actual biome type
c [output(1)] are assigned here:
output(2)=nint(lai*100.)
output(3)=nint(npp)
output(4)=nint(optlai(wdom)*100.)
output(5)=nint(optnpp(wdom))
output(6)=nint(optlai(grasspft)*100.)
output(7)=nint(optnpp(grasspft))
c Annual APAR / annual PAR expressed as a percentage:
output(8) = optdata(dom,8)
c Respiration costs (for dom plant type, wood or grass):
output(9) = optdata(dom,9)
c Soil moisture for dominant pft:
output(10)= nint(wetness(dom)*10.)
c Soil moisture for dominant pft:
c output(10)= nint(wetness(wdom)*10.)
c Predicted runoff (for dom plant type, wood or grass):
output(11)= optdata(wdom,6)
c Number of the dominant (woody) pft:
output(12)=optpft
c output(12)=wdom
c Total annual precipitation (hopefully<9999mm):
output(13)=nint(tprec)
if(output(13).gt.9999) output(13)=9999
c Total annual PAR MJ.m-2.yr-1
output(14)=optdata(dom,7)
output(15)=nint(100*lairatio)
output(16)=nint(nppdif)
if (lai.lt.2.0) then !FVC
output(17)=nint(lai/2.0*100.)
else
output(17)=100
end if
if (dom.eq.0) then
output(18)=0.0
else
output(18)=nint(pftpar(dom,6)*100.) !root percent
end if
c Store monthly fpar values in positions 25-36:
do 12 month=1,12
output(24+month)=optdata(dom,24+month)
12 continue
c Annual mean delta 13C stored in position 50-51
output(50)=real(optdata(dom,50))/10. !total deltaA
output(51)=optdata(dom,51) !average deltaA for mixed ecosystems
output(52)=optdata(8,52) !phi value
c------------------------------------
c changed to NPP for temporary output
output(60)=optnpp(1) !optimized NPP
output(61)=optnpp(2) !for all PFTs
output(62)=optnpp(3)
output(63)=optnpp(4)
output(64)=optnpp(5)
output(65)=optnpp(6)
output(66)=optnpp(7)
output(67)=optnpp(8)
output(68)=optnpp(9)
output(69)=optnpp(10)
output(70)=optnpp(11)
c------------------------------------
c output(60)=optdata(1,50) !mean C3 photosynthesis discrimination
c output(61)=optdata(2,50) !for all PFTs
c output(62)=optdata(3,50)
c output(63)=optdata(4,50)
c output(64)=optdata(5,50)
c output(65)=optdata(6,50)
c output(66)=optdata(7,50)
c output(67)=optdata(8,50)
c output(68)=optdata(9,50)
c
c output(69)=optdata(8,51) !mean C4 photosynthesis discrimination
c output(70)=optdata(9,51) !for grasses
c------------------------------------
do pos=80,91
output(pos)=optdata(dom,pos) !monthly discrimination for one pft
end do
do pos=37,48
output(pos)=optdata(dom,pos) !monthly npp, one pft
end do
do pos=101,112
output(pos)=optdata(dom,pos) !monthly delta e, dominant PFT
end do
do pos=113,124
output(pos)=optdata(dom,pos) !monthly het resp, dom pft
end do
do pos=125,136
output(pos)=optdata(dom,pos) !monthly isoresp (product)
end do
do pos=137,148
output(pos)=optdata(dom,pos) !monthly net C flux (npp-resp)
end do
do pos=160,172
output(pos)=optdata(dom,pos) !monthly mean gc
end do
do pos=173,184
output(pos)=optdata(dom,pos) !monthly LAI
end do
do pos=185,196
output(pos)=optdata(dom,pos) !monthly runoff
end do
output(149)=optdata(dom,149) !annual NEP
output(150)=optdata(dom,150) !annual mean A/g
output(97)=optdata(dom,97) !Mean annual hetresp scalar
output(98)=optdata(dom,98) !pct of NPP that is C4
output(99)=optdata(dom,99) !annual het resp
output(199)=optdata(wdom,199) !firedays
output(200)=optdata(dom,200) !greendays
do pos=201,241
output(pos)=optdata(dom,pos) !ten-day lai*100
end do
c Monthly soil moisture, mean, top, and bottom layers *100
open(37,file='hydro.dat',status='unknown')
do pos=389,400
output(pos)=optdata(dom,pos-376) !mean
end do
do pos=413,424
output(pos)=optdata(dom,pos) !top
end do
do pos=425,436
output(pos)=optdata(dom,pos) !bottom
end do
do month=1,12
write(37,*)month,output(412+month),output(424+month),dom
end do
output(425)=nint(wetlayer(dom,1))
output(426)=nint(wetlayer(dom,2))
output(427)=nint(wetratio(dom)*100.)
output(450)=optdata(dom,450) !meanKlit
output(451)=optdata(dom,451) !meanKsoil
output(452)=tcm !coldest monrh temp
output(453)=gdd0 !gdd0
output(454)=gdd5 !gdd5
c---------------------------------------------------------------------
return
end
c*******************************************************************************
subroutine newassignbiome
>(optpft,woodpft,grasspft,subpft,optnpp,woodnpp,grassnpp,subnpp,
> greendays,biome,gdd0,gdd5,tcm,present,woodylai,grasslai,tmin)
c this is a new subroutine for assigning biomes in BIOME3.5
c according to a new scheme of biomes.
c Jed Kaplan 3/1998
implicit none
integer biome,greendays
integer optpft,woodpft,grasspft,subpft
real optnpp,woodnpp,grassnpp,subnpp,nppdif,gdd0,gdd5,tcm
real woodylai,grasslai,tmin
logical present(14)
c list of the 28 biomes assigned, including land ice
c-------------------------------------------------------
c 1 Tropical evergreen forest
c 2 Tropical semi-deciduous forest
c 3 Tropical deciduous forest/woodland
c 4 Temperate deciduous forest
c 5 Temperate conifer forest
c 6 Warm mixed forest
c 7 Cool mixed forest
c 8 Cool conifer forest
c 9 Cold mixed forest
c 10 Evegreen taiga/montane forest
c 11 Deciduous taiga/montane forest
c 12 Tropical savanna
c 13 Tropical xerophytic shrubland
c 14 Temperate xerophytic shrubland
c 15 Temperate sclerophyll woodland
c 16 Temperate broadleaved savanna
c 17 Open conifer woodland
c 18 Boreal parkland
c 19 Tropical grassland