| 1 | ! ================================================================================================================================= |
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| 2 | ! MODULE : lpj_gap |
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| 3 | ! |
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| 4 | ! CONTACT : orchidee-help _at_ listes.ipsl.fr |
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| 5 | ! |
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| 6 | ! LICENCE : IPSL (2006) |
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| 7 | ! This software is governed by the CeCILL licence see ORCHIDEE/ORCHIDEE_CeCILL.LIC |
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| 8 | ! |
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| 9 | !>\BRIEF Simulate mortality of individuals and update biomass, litter and |
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| 10 | !! stand density of the PFT |
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| 11 | !! |
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| 12 | !!\n DESCRIPTION : Simulate mortality of individuals and update biomass, litter and |
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| 13 | !! stand density of the PFT. This module differs from lpj_kill.f90 in that this |
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| 14 | !! module kills individuals within a PFT and lpj_kill.f90 removes a PFT from a |
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| 15 | !! gridbox |
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| 16 | !! |
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| 17 | !! RECENT CHANGE(S): None |
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| 18 | !! |
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| 19 | !! REFERENCE(S) : |
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| 20 | !! - Sitch, S., B. Smith, et al. (2003), Evaluation of ecosystem dynamics, |
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| 21 | !! plant geography and terrestrial carbon cycling in the LPJ dynamic |
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| 22 | !! global vegetation model, Global Change Biology, 9, 161-185.\n |
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| 23 | !! - Waring, R. H. (1983). "Estimating forest growth and efficiency in relation |
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| 24 | !! to canopy leaf area." Advances in Ecological Research 13: 327-354.\n |
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| 25 | !! |
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| 26 | !! SVN : |
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| 27 | !! $HeadURL: svn://forge.ipsl.jussieu.fr/orchidee/branches/ORCHIDEE_2_2/ORCHIDEE/src_stomate/lpj_gap.f90 $ |
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| 28 | !! $Date: 2017-06-28 16:04:50 +0200 (Wed, 28 Jun 2017) $ |
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| 29 | !! $Revision: 4470 $ |
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| 30 | !! \n |
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| 31 | !_ ================================================================================================================================ |
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| 32 | |
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| 33 | MODULE lpj_gap |
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| 34 | |
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| 35 | ! modules used: |
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| 36 | USE xios_orchidee |
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| 37 | USE stomate_data |
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| 38 | USE pft_parameters |
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| 39 | USE ioipsl_para |
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| 40 | USE constantes |
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| 41 | |
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| 42 | IMPLICIT NONE |
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| 43 | |
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| 44 | ! private & public routines |
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| 45 | |
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| 46 | PRIVATE |
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| 47 | PUBLIC gap,gap_clear |
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| 48 | |
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| 49 | ! Variable declaration |
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| 50 | |
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| 51 | LOGICAL, SAVE :: firstcall_gap = .TRUE. !! first call flag |
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| 52 | !$OMP THREADPRIVATE(firstcall_gap) |
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| 53 | REAL(r_std), PARAMETER :: frost_damage_limit = -3 + ZeroCelsius !! Spring frost-damage limitation (K) |
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| 54 | REAL(r_std), PARAMETER :: coldness_mort = 0.04 !! Daily mortality induced by extreme coldness in winter |
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| 55 | CONTAINS |
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| 56 | |
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| 57 | |
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| 58 | !! ================================================================================================================================ |
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| 59 | !! SUBROUTINE : gap_clear |
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| 60 | !! |
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| 61 | !>\BRIEF Set the firstcall_gap flag back to .TRUE. to prepare for the next simulation. |
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| 62 | !_ ================================================================================================================================ |
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| 63 | |
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| 64 | SUBROUTINE gap_clear |
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| 65 | firstcall_gap = .TRUE. |
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| 66 | END SUBROUTINE gap_clear |
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| 67 | |
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| 68 | |
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| 69 | !! ================================================================================================================================ |
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| 70 | !! SUBROUTINE : gap |
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| 71 | !! |
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| 72 | !>\BRIEF Simulate tree and grass mortality, transfer dead biomass to litter and update stand density |
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| 73 | !! |
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| 74 | !! DESCRIPTION : Calculate mortality of trees and grasses, transfer the dead biomass to litter pool, |
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| 75 | !! and update biomass pool and number of individuals. To get tree mortality, it's possible to choose either a |
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| 76 | !! constant mortality rate; or to calculate the tree mortality rate based on it's growth efficiency, which is |
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| 77 | !! defined as this year's net biomass increment per leaf area.\n |
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| 78 | !! |
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| 79 | !! When using growth efficiency mortality, first calculate the net biomass increment for the last year, then |
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| 80 | !! calculate the growth efficiency and finally calculate the growth efficiency mortality.\n |
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| 81 | !! |
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| 82 | !! Eqation to calculate growth efficiency: |
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| 83 | !! \latexonly |
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| 84 | !! \input{gap1.tex} |
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| 85 | !! \endlatexonly |
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| 86 | !! Where $greff$ is growth efficiency, $\Delta$ is net biomass increment, |
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| 87 | !! $C_{leaf} is last year's leaf biomass, and $SLA$ the specific leaf area. |
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| 88 | !! |
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| 89 | !! |
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| 90 | !! Eqation to calculate growth efficiency mortality: |
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| 91 | !! \latexonly |
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| 92 | !! \input{gap2.tex} |
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| 93 | !! \endlatexonly |
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| 94 | !! Where $mort_{greff}$ is the growth efficiency mortality, $greff$ is growth |
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| 95 | !! efficiency, $k_{mort1}$ is asymptotic maximum mortality rate. |
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| 96 | !! |
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| 97 | !! The name for variable ::availability is not well chosen. Actually the meaning of the variable is mortailty |
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| 98 | !! rate derived from growth efficiency related mortality. ?? Suggestion: change the name "availability" to |
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| 99 | !! "mortgref", which means "mortality caused by ".\n |
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| 100 | !! |
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| 101 | !! RECENT CHANGE(S): None |
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| 102 | !! |
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| 103 | !! MAIN OUTPUT VARIABLE(S): ::biomass; biomass, ::ind density of individuals, ::bm_to_litter biomass transfer |
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| 104 | !! to litter and ::mortality mortality (fraction of trees that is dying per time step) |
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| 105 | !! |
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| 106 | !! REFERENCE(S) : |
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| 107 | !! - Sitch, S., B. Smith, et al. (2003), Evaluation of ecosystem dynamics, |
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| 108 | !! plant geography and terrestrial carbon cycling in the LPJ dynamic |
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| 109 | !! global vegetation model, Global Change Biology, 9, 161-185. |
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| 110 | !! - Waring, R. H. (1983). "Estimating forest growth and efficiency in relation |
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| 111 | !! to canopy leaf area." Advances in Ecological Research 13: 327-354. |
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| 112 | !! |
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| 113 | !! FLOWCHART : None |
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| 114 | !!\n |
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| 115 | !_ ================================================================================================================================ |
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| 116 | |
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| 117 | SUBROUTINE gap (npts, dt, & |
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| 118 | npp_longterm, turnover_longterm, lm_lastyearmax, & |
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| 119 | PFTpresent, t2m_min_daily, Tmin_spring_time, & |
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| 120 | biomass, ind, bm_to_litter, mortality ) |
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| 121 | |
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| 122 | |
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| 123 | !! 0. Variable and parameter declaration |
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| 124 | |
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| 125 | !! 0.1 Input variables |
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| 126 | INTEGER(i_std), INTENT(in) :: npts !! Domain size (-) |
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| 127 | REAL(r_std), INTENT(in) :: dt !! Time step (days) |
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| 128 | REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: npp_longterm !! "Long term" (default 3-year) net primary |
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| 129 | !! productivity |
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| 130 | !! @tex $(gC m^{-2} year^{-1})$ @endtex |
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| 131 | REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(in) :: turnover_longterm !! "Long term" (default 3-year) turnover |
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| 132 | !! rate @tex $(gC m^{-2} year^{-1})$ @endtex |
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| 133 | REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: lm_lastyearmax !! Last year's maximum leaf mass, for each |
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| 134 | !! PFT @tex $(gC m^{-2})$ @endtex |
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| 135 | LOGICAL, DIMENSION(npts,nvm), INTENT(in) :: PFTpresent !! Is the pft present in the pixel |
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| 136 | REAL(r_std), DIMENSION(npts), INTENT(in) :: t2m_min_daily !! Daily minimum 2 meter temperatures (K) |
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| 137 | REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: Tmin_spring_time !! Number of days after begin_leaves (leaf onset) |
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| 138 | |
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| 139 | !! 0.2 Output variables |
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| 140 | |
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| 141 | REAL(r_std), DIMENSION(npts,nvm),INTENT(out) :: mortality !! Mortality (fraction of trees that is |
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| 142 | !! dying per time step) |
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| 143 | |
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| 144 | !! 0.3 Modified variables |
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| 145 | |
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| 146 | REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(inout) :: biomass !! Biomass @tex $(gC m^{-2}) $@endtex |
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| 147 | REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: ind !! Number of individuals |
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| 148 | !! @tex $(m^{-2})$ @endtex |
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| 149 | REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(inout) :: bm_to_litter !! Biomass transfer to litter |
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| 150 | !! @tex $(gC m^{-2})$ @endtex |
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| 151 | |
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| 152 | !! 0.4 Local variables |
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| 153 | |
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| 154 | REAL(r_std), DIMENSION(npts) :: delta_biomass !! Net biomass increase for the previous |
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| 155 | !! year @tex $(gC m^{-2} year^{-1})$ @endtex |
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| 156 | REAL(r_std), DIMENSION(npts) :: dmortality !! Dead biomass caused by mortality |
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| 157 | !! @tex $(gC m^{-2}) $@endtex |
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| 158 | REAL(r_std), DIMENSION(npts) :: vigour !! Growth efficiency, an indicator of tree |
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| 159 | !! vitality, used to calculate mortality |
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| 160 | REAL(r_std), DIMENSION(npts) :: availability !! Mortality rate derived by growth |
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| 161 | !! efficiency @tex $(year^{-1})$ @endtex |
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| 162 | INTEGER(i_std) :: i, j,k,m !! Indices |
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| 163 | |
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| 164 | !_ ================================================================================================================================ |
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| 165 | |
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| 166 | IF ( firstcall_gap ) THEN |
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| 167 | |
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| 168 | firstcall_gap = .FALSE. |
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| 169 | |
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| 170 | ENDIF |
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| 171 | |
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| 172 | IF (printlev>=3) WRITE(numout,*) 'Entering gap',lpj_gap_const_mort |
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| 173 | |
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| 174 | mortality(:,:) = zero |
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| 175 | |
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| 176 | ! loop over #PFT |
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| 177 | DO j = 2,nvm |
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| 178 | |
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| 179 | !! 1. Tree mortality |
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| 180 | |
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| 181 | IF ( is_tree(j) ) THEN |
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| 182 | |
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| 183 | !! 1.1 Use growth efficiency or constant mortality? |
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| 184 | IF ( .NOT. lpj_gap_const_mort ) THEN |
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| 185 | |
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| 186 | !! 1.1.1 Estimate net biomass increment |
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| 187 | ! To calculate growth efficiency mortality, first estimate net biomass increment by |
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| 188 | ! subtracting turnover from last year's NPP. |
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| 189 | WHERE ( PFTpresent(:,j) .AND. ( lm_lastyearmax(:,j) .GT. min_stomate ) ) |
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| 190 | |
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| 191 | !??! the following should be removed |
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| 192 | ! note that npp_longterm is now actually longterm growth efficiency (NPP/LAI) |
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| 193 | ! to be fair to deciduous trees |
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| 194 | ! calculate net biomass increment |
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| 195 | delta_biomass(:) = MAX( npp_longterm(:,j) - ( turnover_longterm(:,j,ileaf,icarbon) + & |
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| 196 | turnover_longterm(:,j,iroot,icarbon) + turnover_longterm(:,j,ifruit,icarbon) + & |
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| 197 | turnover_longterm(:,j,isapabove,icarbon) + turnover_longterm(:,j,isapbelow,icarbon) ) ,zero) |
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| 198 | |
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| 199 | !! 1.1.2 Calculate growth efficiency |
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| 200 | ! Calculate growth efficiency by dividing net biomass increment by last year's |
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| 201 | ! maximum LAI. (corresponding actually to the maximum LAI of the previous year) |
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| 202 | vigour(:) = delta_biomass(:) / (lm_lastyearmax(:,j)*sla(j)) |
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| 203 | |
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| 204 | ELSEWHERE |
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| 205 | |
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| 206 | vigour(:) = zero |
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| 207 | |
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| 208 | ENDWHERE |
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| 209 | |
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| 210 | !! 1.1.3 Calculate growth efficiency mortality rate |
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| 211 | WHERE ( PFTpresent(:,j) ) |
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| 212 | |
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| 213 | availability(:) = availability_fact(j) / ( un + ref_greff * vigour(:) ) |
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| 214 | ! Scale mortality by timesteps per year |
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| 215 | mortality(:,j) = MAX(min_avail,availability(:)) * dt/one_year |
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| 216 | |
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| 217 | ENDWHERE |
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| 218 | |
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| 219 | ELSE ! .NOT. lpj_gap_const_mort |
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| 220 | |
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| 221 | !! 1.2 Use constant mortality accounting for the residence time of each tree PFT |
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| 222 | WHERE ( PFTpresent(:,j) ) |
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| 223 | |
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| 224 | mortality(:,j) = dt/(residence_time(j)*one_year) |
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| 225 | |
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| 226 | ENDWHERE |
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| 227 | |
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| 228 | ENDIF ! .NOT. lpj_gap_const_mort |
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| 229 | |
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| 230 | !! 1.3 Mortality in DGVM |
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| 231 | ! If the long term NPP is zero, all trees are killed |
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| 232 | !??! This is this only applied in the DGVM maybe in order to make the DGVM respond faster and thus make the vegetation dynamics more dynamic? |
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| 233 | !??! the link here with lpj_kill.f90 is still not clear and so would leave to who especially working on this. |
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| 234 | IF ( ok_dgvm ) THEN |
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| 235 | |
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| 236 | WHERE ( PFTpresent(:,j) .AND. ( npp_longterm(:,j) .LE. min_stomate ) ) |
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| 237 | |
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| 238 | mortality(:,j) = un |
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| 239 | |
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| 240 | ENDWHERE |
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| 241 | |
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| 242 | ENDIF |
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| 243 | |
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| 244 | IF ( ok_dgvm .AND. (tmin_crit(j) .NE. undef) ) THEN |
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| 245 | ! frost-sensitive PFTs |
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| 246 | WHERE ( t2m_min_daily(:) .LT. tmin_crit(j) ) |
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| 247 | mortality(:,j) = MIN(un,(coldness_mort*(tmin_crit(j)-t2m_min_daily(:))+mortality(:,j) ) ) |
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| 248 | ENDWHERE |
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| 249 | ENDIF |
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| 250 | |
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| 251 | IF ( ok_dgvm .AND. leaf_tab(j)==1 .AND. pheno_type(j)==2) THEN |
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| 252 | ! Treat the spring frost for broadleaf and summergreen vegetations |
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| 253 | ! leaf_tab=broadleaf and pheno_typ=summergreen |
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| 254 | DO i=1,npts |
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| 255 | IF ( (Tmin_spring_time(i,j)>0) .AND. (Tmin_spring_time(i,j)<spring_days_max+1) ) THEN |
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| 256 | IF ( t2m_min_daily(i) .LT. frost_damage_limit ) THEN |
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| 257 | mortality(i,j) = MIN(un,(0.01*(frost_damage_limit-t2m_min_daily(i))* & |
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| 258 | Tmin_spring_time(i,j)/spring_days_max+mortality(i,j) ) ) |
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| 259 | END IF |
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| 260 | END IF |
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| 261 | END DO |
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| 262 | END IF |
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| 263 | |
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| 264 | |
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| 265 | !! 1.4 Update biomass and litter pools |
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| 266 | ! Update biomass and litter pool after dying and transfer recently died biomass to litter |
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| 267 | |
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| 268 | DO m = 1,nelements |
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| 269 | DO k = 1, nparts |
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| 270 | |
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| 271 | WHERE ( PFTpresent(:,j) ) |
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| 272 | |
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| 273 | dmortality(:) = mortality(:,j) * biomass(:,j,k,m) |
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| 274 | bm_to_litter(:,j,k,m) = bm_to_litter(:,j,k,m) + dmortality(:) |
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| 275 | biomass(:,j,k,m) = biomass(:,j,k,m) - dmortality(:) |
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| 276 | |
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| 277 | ENDWHERE |
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| 278 | |
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| 279 | ENDDO |
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| 280 | END DO |
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| 281 | |
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| 282 | !! 1.5 In case of dynamic vegetation, update tree individual density |
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| 283 | IF ( ok_dgvm ) THEN |
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| 284 | |
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| 285 | WHERE ( PFTpresent(:,j) ) |
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| 286 | |
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| 287 | ind(:,j) = ind(:,j) * ( un - mortality(:,j) ) |
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| 288 | |
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| 289 | ENDWHERE |
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| 290 | |
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| 291 | ENDIF |
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| 292 | ELSE |
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| 293 | |
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| 294 | !! 2. Grasses mortality |
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| 295 | |
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| 296 | ! For grasses, if last year's NPP is very small (less than 10 gCm^{-2}year{-1}) |
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| 297 | ! the grasses completely die |
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| 298 | IF ( .NOT.ok_dgvm .AND. .NOT.lpj_gap_const_mort) THEN |
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| 299 | |
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| 300 | WHERE ( PFTpresent(:,j) .AND. ( npp_longterm(:,j) .LE. npp_longterm_init ) ) |
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| 301 | |
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| 302 | mortality(:,j) = un |
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| 303 | |
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| 304 | ENDWHERE |
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| 305 | |
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| 306 | ! Update biomass and litter pools |
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| 307 | DO m = 1,nelements |
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| 308 | DO k = 1, nparts |
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| 309 | |
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| 310 | WHERE ( PFTpresent(:,j) ) |
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| 311 | |
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| 312 | dmortality(:) = mortality(:,j) * biomass(:,j,k,m) |
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| 313 | |
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| 314 | bm_to_litter(:,j,k,m) = bm_to_litter(:,j,k,m) + dmortality(:) |
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| 315 | |
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| 316 | biomass(:,j,k,m) = biomass(:,j,k,m) - dmortality(:) |
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| 317 | |
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| 318 | ENDWHERE |
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| 319 | |
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| 320 | ENDDO |
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| 321 | END DO |
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| 322 | |
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| 323 | ENDIF |
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| 324 | |
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| 325 | ENDIF !IF ( is_tree(j) ) |
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| 326 | |
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| 327 | ENDDO !loop over pfts |
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| 328 | |
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| 329 | !! 3. Write to history files |
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| 330 | |
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| 331 | ! output in fraction of trees that dies/day. |
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| 332 | mortality(:,:) = mortality(:,:) / dt |
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| 333 | |
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| 334 | CALL xios_orchidee_send_field("mortality",mortality) |
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| 335 | |
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| 336 | CALL histwrite_p (hist_id_stomate, 'MORTALITY', itime, & |
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| 337 | mortality, npts*nvm, horipft_index) |
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| 338 | |
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| 339 | IF (printlev>=4) WRITE(numout,*) 'Leaving gap' |
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| 340 | |
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| 341 | END SUBROUTINE gap |
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| 342 | |
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| 343 | END MODULE lpj_gap |
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