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stomate_season.f90 @ 7541

Last change on this file since 7541 was 7541, checked in by fabienne.maignan, 2 years ago
Zhang publication on coupling factor
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1	! =================================================================================================================================
2	! MODULE : stomate_season
3	!
4	! CONTACT : orchidee-help _at_ listes.ipsl.fr
5	!
6	! LICENCE : IPSL (2006). This software is governed by the CeCILL licence see ORCHIDEE/ORCHIDEE_CeCILL.LIC
7	!
8	!>\BRIEF This module calculates long-term meteorological parameters from daily temperatures
9	!! and precipitations (essentially for phenology).
10	!!
11	!!\n DESCRIPTION: None
12	!!
13	!! RECENT CHANGE(S): None
14	!!
15	!! SVN :
16	!! $HeadURL: svn://forge.ipsl.jussieu.fr/orchidee/branches/ORCHIDEE_2_2/ORCHIDEE/src_stomate/stomate_season.f90 $
17	!! $Date: 2017-10-18 11:15:06 +0200 (Wed, 18 Oct 2017) $
18	!! $Revision: 4693 $
19	!! \n
20	!_ =================================================================================================================================
21
22	MODULE stomate_season
23
24	! modules used:
25	USE xios_orchidee
26	USE ioipsl_para
27	USE stomate_data
28	USE constantes
29	USE constantes_soil
30	USE pft_parameters
31	USE solar
32	USE grid
33	USE time, ONLY : one_year, julian_diff, LastTsYear
34
35	IMPLICIT NONE
36
37	! private & public routines
38
39	PRIVATE
40	PUBLIC season,season_clear
41
42	LOGICAL, SAVE :: firstcall_season = .TRUE. !! first call (true/false)
43	!$OMP THREADPRIVATE(firstcall_season)
44
45	CONTAINS
46
47	!! ================================================================================================================================
48	!! SUBROUTINE : season_clear
49	!!
50	!>\BRIEF Flag setting
51	!!
52	!! DESCRIPTION : This subroutine sets flags ::firstcall_season, to .TRUE., and therefore activates
53	!! section 1.1 of the ::season subroutine which writes messages to the output. \n
54	!! This subroutine is called at the end of the subroutine ::stomate_clear, in the
55	!! module ::stomate.
56	!!
57	!! RECENT CHANGE(S):None
58	!!
59	!! MAIN OUTPUT VARIABLE(S): ::firstcall_season
60	!!
61	!! REFERENCE(S) : None
62	!!
63	!! FLOWCHART : None
64	!! \n
65	!_ =================================================================================================================================
66
67	SUBROUTINE season_clear
68	firstcall_season=.TRUE.
69	END SUBROUTINE season_clear
70
71
72
73	!! ================================================================================================================================
74	!! SUBROUTINE : season
75	!!
76	!>\BRIEF This subroutine calculates many of the long-term biometeorological variables
77	!! needed in the phenology subroutines and in the calculation of long-term vegetation
78	!! dynamics in the LPJ DGVM.
79	!!
80	!! DESCRIPTION This subroutine is called by the module ::stomate before LPJ, and mainly deals
81	!! with the calculation of long-term meteorological variables, carbon fluxes and
82	!! vegetation-related variables that are used to calculate vegetation dynamics
83	!! in the stomate modules relating to the phenology and to the longer-term
84	!! changes in vegetation type and fractional cover in the LPJ DGVM modules. \n
85	!! In sections 2 to 5, longer-term meteorological variables are calculated. The
86	!! long-term moisture availabilities are used in the leaf onset and senescence
87	!! phenological models ::stomate_phenology and ::stomate_turnover that require
88	!! a moisture condition. The long term temperatures are also required for phenology
89	!! but in addition they are used in calculations of C flux and the presence and
90	!! establishment of vegetation patterns on a longer timescale in the LPJ DGVM modules.
91	!! Finally the monthly soil humidity/relative soil moisture is used in the C
92	!! allocation module ::stomate_alloc. \n
93	!! Sections 12 to 14 also calculate long-term variables of C fluxes, including NPP,
94	!! turnover and GPP. The first two are used to calculate long-term vegetation
95	!! dynamics and land cover change in the LPJ DVGM modules. The weekly GPP is used
96	!! to determine the dormancy onset and time-length, as described below. \n
97	!! The long-term variables described above are are used in certain vegetation
98	!! dynamics processes in order to maintain consistency with the basic hypotheses of the
99	!! parameterisations of LPJ, which operates on a one year time step (Krinner et al., 2005).
100	!! In order to reduce the computer memory requirements, short-term variables (e.g. daily
101	!! temperatures) are not stored for averaging over a longer period. Instead
102	!! the long-term variables (e.g. monthly temperature) are calculated at each time step
103	!! using a linear relaxation method, following the equation:
104	!! \latexonly
105	!! \input{season_lin_relax_eqn1.tex}
106	!! \endlatexonly
107	!! \n
108	!! The long-term variables are therefore updated on a daily basis. This method allows for
109	!! smooth temporal variation of the long-term variables which are used to calculate
110	!! vegetation dynamics (Krinner et al., 2005). \n
111	!! Sections 6 to 11 calculate the variables required for to determine leaf onset in
112	!! the module ::stomate_phenology.
113	!! These include :
114	!! - the dormance onset and time-length, when GPP is below a certain threshold \n
115	!! - the growing degree days (GDD), which is the sum of daily temperatures greater than
116	!! -5 degrees C, either since the onset of the dormancy period, or since midwinter \n
117	!! - the number of chilling days, which is the number of days with a daily temperature
118	!! lower than a PFT-dependent threshold since the beginning of the dormancy period \n
119	!! - the number of growing days, which is the the number of days with a temperature
120	!! greater than -5 degrees C since the onset of the dormancy period \n
121	!! - the time since the minimum moisture availability in the dormancy period. \n
122	!! These variables are used to determine the conditions needed for the start of the
123	!! leaf growing season. The specific models to which they correspond are given below. \n
124	!! Sections 15 to 20 are used to update the maximum/minimum or the sum of various
125	!! meteorological and biological variables during the year that are required for
126	!! calculating either leaf onset or longer-term vegetation dynamics the following year. \n
127	!! At the end of the year, these variables are updated from "thisyear" to "lastyear",
128	!! in Section 21 of this subroutine, for use the following year. \n
129	!! Finally the probably amount of herbivore consumption is calculated in Section 22,
130	!! following McNaughton et al. (1989).
131	!!
132	!! RECENT CHANGE(S): None
133	!!
134	!! MAIN OUTPUT VARIABLE(S): :: herbivores,
135	!! :: maxmoiavail_lastyear, :: maxmoiavail_thisyear,
136	!! :: minmoiavail_lastyear, :: minmoiavail_thisyear,
137	!! :: maxgppweek_lastyear, :: maxgppweek_thisyear,
138	!! :: gdd0_lastyear, :: gdd0_thisyear,
139	!! :: precip_lastyear, :: precip_thisyear,
140	!! :: lm_lastyearmax, :: lm_thisyearmax,
141	!! :: maxfpc_lastyear, :: maxfpc_thisyear,
142	!! :: moiavail_month, :: moiavail_week,
143	!! :: t2m_longterm, :: t2m_month, :: t2m_week,
144	!! :: tsoil_month, :: soilhum_month,
145	!! :: npp_longterm, :: turnover_longterm, :: gpp_week,
146	!! :: gdd_m5_dormance, :: gdd_midwinter,
147	!! :: ncd_dormance, :: ngd_minus5, :: time_lowgpp,
148	!! :: time_hum_min, :: hum_min_dormance
149	!!
150	!! REFERENCES :
151	!! - Krinner, G., N. Viovy, N. de Noblet-Ducoudre, J. Ogee, J. Polcher, P.
152	!! Friedlingstein, P. Ciais, S. Sitch and I.C. Prentice (2005), A dynamic global
153	!! vegetation model for studies of the coupled atmosphere-biosphere system, Global
154	!! Biogeochemical Cycles, 19, doi:10.1029/2003GB002199.
155	!! - McNaughton, S.J., M. Oesterheld, D.A. Frank and K.J. Williams (1989),
156	!! Ecosystem-level patterns of primary productivity and herbivory in terrestrial
157	!! habitats, Nature, 341, 142-144.
158	!!
159	!! FLOWCHART :
160	!! \latexonly
161	!! \includegraphics[scale = 1]{season_flowchart_part1.png}
162	!! \includegraphics[scale = 1]{season_flowchart_part2.png}
163	!! \includegraphics[scale = 1]{season_flowchart_part3.png}
164	!! \endlatexonly
165	!! \n
166	!_ =================================================================================================================================
167
168	SUBROUTINE season (npts, dt, veget_cov, veget_cov_max, &
169	moiavail_daily, t2m_daily, tsoil_daily, soilhum_daily, lalo, &
170	precip_daily, npp_daily, biomass, turnover_daily, gpp_daily, when_growthinit, &
171	maxmoiavail_lastyear, maxmoiavail_thisyear, &
172	minmoiavail_lastyear, minmoiavail_thisyear, &
173	maxgppweek_lastyear, maxgppweek_thisyear, &
174	gdd0_lastyear, gdd0_thisyear, &
175	precip_lastyear, precip_thisyear, &
176	lm_lastyearmax, lm_thisyearmax, &
177	maxfpc_lastyear, maxfpc_thisyear, &
178	moiavail_month, moiavail_week, t2m_longterm, tau_longterm, t2m_month, t2m_week, &
179	tsoil_month, soilhum_month, &
180	npp_longterm, turnover_longterm, gpp_week, &
181	gdd_m5_dormance, gdd_midwinter, ncd_dormance, ngd_minus5, &
182	time_hum_min, hum_min_dormance, gdd_init_date , &
183	gdd_from_growthinit, herbivores, &
184	Tseason, Tseason_length, Tseason_tmp, &
185	Tmin_spring_time, t2m_min_daily, begin_leaves, onset_date)
186
187	!
188	!! 0. Variable and parameter declaration
189	!
190
191	!
192	!! 0.1 Input variables
193	!
194	INTEGER(i_std), INTENT(in) :: npts !! Domain size - number of grid cells (unitless)
195	REAL(r_std), INTENT(in) :: dt !! time step in days (dt_days)
196	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: veget_cov !! coverage fraction of a PFT. Here: fraction of
197	!! total ground. (0-1, unitless)
198	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: veget_cov_max !! "maximal" coverage fraction of a PFT (for LAI ->
199	!! infinity) (0-1, unitless)Here: fraction of
200	!! total ground.
201	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: moiavail_daily !! Daily moisture availability (0-1, unitless)
202	REAL(r_std), DIMENSION(npts), INTENT(in) :: t2m_daily !! Daily 2 meter temperature (K)
203	REAL(r_std), DIMENSION(npts,nslm), INTENT(in) :: tsoil_daily !! Daily soil temperature (K)
204	REAL(r_std), DIMENSION(npts,nslm), INTENT(in) :: soilhum_daily !! Daily soil humidity (0-1, unitless)
205	REAL(r_std), DIMENSION(npts,2), INTENT(in) :: lalo !! array of lat/lon
206	REAL(r_std), DIMENSION(npts), INTENT(in) :: precip_daily !! Daily mean precipitation @tex ($mm day^{-1}$)
207	!! @endtex
208	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: npp_daily !! daily net primary productivity @tex ($gC m^{-2}
209	!! day^{-1}$) @endtex
210	REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(in) :: biomass !! biomass @tex ($gC m^{-2} of ground$) @endtex
211	REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(in) :: turnover_daily !! Turnover rates @tex ($gC m^{-2} day^{-1}$)
212	!! @endtex
213	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: gpp_daily !! daily gross primary productivity
214	!! (Here: @tex $gC m^{-2} of total ground
215	!! day^{-1}$) @endtex
216	REAL(r_std), DIMENSION(npts,nvm), INTENT(in) :: when_growthinit !! how many days ago was the beginning of the
217	!! growing season (days)
218	LOGICAL, DIMENSION(npts,nvm), INTENT(in) :: begin_leaves !! signal to start putting leaves on (true/false)
219	REAL(r_std), DIMENSION(npts), INTENT(in) :: t2m_min_daily !! Daily minimum 2-meter temperature (K)
220
221	!
222	!! 0.2 Output variables
223	! (diagnostic)
224	!
225	REAL(r_std), DIMENSION(npts,nvm), INTENT(out) :: herbivores !! time constant of probability of a leaf to be
226	!! eaten by a herbivore (days)
227
228	!
229	!! 0.3 Modified variables
230	!
231	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxmoiavail_lastyear !! last year's maximum moisture
232	!! availability (0-1, unitless)
233	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxmoiavail_thisyear !! this year's maximum moisture
234	!! availability (0-1, unitless)
235	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: minmoiavail_lastyear !! last year's minimum moisture
236	!! availability (0-1, unitless)
237	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: minmoiavail_thisyear !! this year's minimum moisture
238	!! availability (0-1, unitless)
239	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxgppweek_lastyear !! last year's maximum weekly GPP
240	!! @tex ($gC m^{-2} week^{-1}$) @endtex
241	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxgppweek_thisyear !! this year's maximum weekly GPP
242	!! @tex ($gC m^{-2} week^{-1}$) @endtex
243	REAL(r_std), DIMENSION(npts), INTENT(inout) :: gdd0_lastyear !! last year's annual GDD0 (C)
244	REAL(r_std), DIMENSION(npts), INTENT(inout) :: gdd0_thisyear !! this year's annual GDD0 (C)
245	REAL(r_std), DIMENSION(npts), INTENT(inout) :: precip_lastyear !! last year's annual precipitation
246	!! @tex ($mm year^{-1}$) @endtex
247	REAL(r_std), DIMENSION(npts), INTENT(inout) :: precip_thisyear !! this year's annual precipitation
248	!! @tex ($mm year^{-1}$) @endtex
249	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: lm_lastyearmax !! last year's maximum leaf mass, for each
250	!! PFT @tex ($gC m^{-2}$) @endtex
251	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: lm_thisyearmax !! this year's maximum leaf mass, for each
252	!! PFT @tex ($gC m^{-2}$) @endtex
253	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxfpc_lastyear !! last year's maximum fpc for each PFT, on
254	!! ground (0-1, unitless)
255	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: maxfpc_thisyear !! this year's maximum fpc for each PFT, on
256	!! ground (0-1, unitless)
257	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: moiavail_month !! "monthly" moisture availability
258	!! (0-1, unitless)
259	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: moiavail_week !! "weekly" moisture availability
260	!! (0-1, unitless)
261	REAL(r_std), DIMENSION(npts), INTENT(inout) :: t2m_longterm !! "long term" 2-meter temperatures (K)
262	REAL(r_std), INTENT(inout) :: tau_longterm
263	REAL(r_std), DIMENSION(npts), INTENT(inout) :: t2m_month !! "monthly" 2-meter temperatures (K)
264	REAL(r_std), DIMENSION(npts), INTENT(inout) :: t2m_week !! "weekly" 2-meter temperatures (K)
265	REAL(r_std), DIMENSION(npts), INTENT(inout) :: Tseason !! "seasonal" 2-meter temperatures (K),
266	!! used to constrain boreal treeline
267	REAL(r_std), DIMENSION(npts), INTENT(inout) :: Tseason_tmp !! temporary variable to calculate Tseason
268	REAL(r_std), DIMENSION(npts), INTENT(inout) :: Tseason_length !! temporary variable to calculate Tseason:
269	!! number of days when t2m_week is higher than 0 degree
270	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: Tmin_spring_time !! Number of days after begin_leaves (leaf onset)
271	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: onset_date !! Date in the year at when the leaves started to grow(begin_leaves)
272	REAL(r_std), DIMENSION(npts,nslm), INTENT(inout) :: tsoil_month !! "monthly" soil temperatures (K)
273	REAL(r_std), DIMENSION(npts,nslm), INTENT(inout) :: soilhum_month !! "monthly" soil humidity (0-1, unitless)
274	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: npp_longterm !! "long term" net primary productivity
275	!! @tex ($gC m^{-2} year^{-1}$) @endtex
276	REAL(r_std), DIMENSION(npts,nvm,nparts,nelements), INTENT(inout) :: turnover_longterm !! "long term" turnover rate
277	!! @tex ($gC m^{-2} year^{-1}$) @endtex
278	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: gpp_week !! "weekly" GPP @tex ($gC m^{-2} day^{-1}$)
279	!! @endtex
280	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: gdd_m5_dormance !! growing degree days above threshold -5
281	!! deg. C (C)
282	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: gdd_midwinter !! growing degree days since midwinter (C)
283	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: ncd_dormance !! number of chilling days since leaves
284	!! were lost (days)
285	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: ngd_minus5 !! number of growing days (days)
286	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: time_hum_min !! time elapsed since strongest moisture
287	!! availability (days)
288	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: hum_min_dormance !! minimum moisture during dormance
289	!! (0-1, unitless)
290	REAL(r_std), DIMENSION(npts,2), INTENT(inout) :: gdd_init_date !! inital date for gdd count
291	REAL(r_std), DIMENSION(npts,nvm), INTENT(inout) :: gdd_from_growthinit !! growing degree days, threshold 0 deg. C
292	!! since beginning of season
293
294	!
295	!! 0.4 Local variables
296	!
297	INTEGER(i_std) :: j !! indices (unitless)
298	REAL(r_std) :: ncd_max !! maximum ncd (to avoid floating point
299	!! underflows) (days)
300	REAL(r_std), DIMENSION(npts) :: sumfpc_nat !! sum of natural fpcs (0-1, unitless)
301	!! [DISPENSABLE]
302	REAL(r_std), DIMENSION(npts,nvm) :: weighttot !! weight of biomass @tex ($gC m^{-2}$)
303	!! @endtex
304	REAL(r_std), DIMENSION(npts,nvm) :: nlflong_nat !! natural long-term leaf NPP
305	!! @tex ($gC m^{-2} year^{-1}$) @endtex
306	REAL(r_std), DIMENSION(npts,nvm) :: green_age !! residence time of green tissue (years)
307	REAL(r_std), DIMENSION(npts) :: consumption !! herbivore consumption
308	!! @tex ($gC m^{-2} day^{-1}$) @endtex
309	REAL(r_std), DIMENSION(npts) :: fracnat !! fraction of each gridcell occupied by
310	!! natural vegetation (0-1, unitless)
311	REAL(r_std), DIMENSION(npts) :: solad !! maximal radation during current day
312	!! (clear sky condition)
313	REAL(r_std), DIMENSION(npts) :: solai !! maximal radation during current day
314	!! (clear sky condition)
315	REAL(r_std), DIMENSION(npts) :: cloud !! cloud fraction
316
317	!_ =================================================================================================================================
318
319	IF (printlev>=3) WRITE(numout,*) 'Entering season'
320
321	!
322	!! 1. Initializations
323	!! 1.1 Calculate ::ncd_max - the maximum possible NCD (number of chilling days) as:
324	!! \latexonly
325	!! \input{season_ncdmax_eqn2.tex}
326	!! \endlatexonly
327	!! \n
328	!! where one_year is 1 year in seconds (defined in ::constantes).
329	!
330	ncd_max = ncd_max_year * one_year
331
332	IF ( firstcall_season ) THEN
333
334	!
335	!! 1.2 first call - output message giving the setting of the ::gppfrac_dormance,
336	!! ::hvc1, ::hvc2 and ::leaf_frac (as a percentage) parameters which are
337	!! defined at the beginning of this subroutine. Also outputs the value of
338	!! ::ncd_max.
339	!
340
341	IF ( printlev>=2 ) THEN
342
343	WRITE(numout,*) 'season: '
344
345	WRITE(numout,) ' > maximum GPP/GGP_max ratio for dormance (::gppfrac_dormance) :',gppfrac_dormance !
346
347	WRITE(numout,) ' > maximum possible ncd(days) (::ncd_max) : ',ncd_max !
348
349	WRITE(numout,) ' > herbivore consumption C (gC/m2/d) as a function of NPP (gC/m2/d): (::hvc1) (::hvc2)' !
350	WRITE(numout,) ' C=',hvc1,' NPP^',hvc2
351	WRITE(numout,) ' > for herbivores, suppose that (::leaf_frac_hvc)',leaf_frac_hvc100., &
352	'% of NPP is allocated to leaves'
353
354	ENDIF
355
356	!
357	!! 1.3 Check whether longer-term meteorological and phenology-related variables are not initialized
358	!! to less than zero. If the following meteorological variables are less than ::min_stomate which is set
359	!! to 1.E-8 in ::grid, then they are set to the current daily value. If the phenology-
360	!! related variables are less than ::min_stomate, they are set to "undef".
361	!! Warning messages are output in each case, and are also output if "long-term" C fluxes GPP,
362	!! NPP and turnover are less than ::min_stomate.
363	!
364
365	!! 1.3.1 moisture availabilities (i.e. relative soil moisture, including the root soil profile):
366
367	!! 1.3.1.1 "monthly" (::moiavail_month)
368	IF ( ABS( SUM( moiavail_month(:,2:nvm) ) ) .LT. min_stomate ) THEN
369
370	! in this case, set them it today's moisture availability
371	WRITE(numout,*) 'Warning! We have to initialize the ''monthly'' moisture availabilities. '
372	moiavail_month(:,:) = moiavail_daily(:,:)
373
374	ENDIF
375
376	!! 1.3.1.2 "weekly" (::moiavail_week)
377
378	IF ( ABS( SUM( moiavail_week(:,2:nvm) ) ) .LT. min_stomate ) THEN
379
380	! in this case, set them it today's moisture availability
381	WRITE(numout,*) 'Warning! We have to initialize the ''weekly'' moisture availabilities. '
382	moiavail_week(:,:) = moiavail_daily(:,:)
383
384	ENDIF
385
386	!! 1.3.2 2-meter temperatures:
387
388	!! "monthly" (::t2m_month)
389	IF ( ABS( SUM( t2m_month(:) ) ) .LT. min_stomate ) THEN
390
391	! in this case, set them to today's temperature
392	WRITE(numout,*) 'Warning! We have to initialize the ''monthly'' 2m temperatures.'
393	t2m_month(:) = t2m_daily(:)
394
395	ENDIF
396
397	!! "weekly" (::2m_week)
398	IF ( ABS( SUM( t2m_week(:) ) ) .LT. min_stomate ) THEN
399
400	! in this case, set them to today's temperature
401	WRITE(numout,*) 'Warning! We have to initialize the ''weekly'' 2m temperatures.'
402	t2m_week(:) = t2m_daily(:)
403
404	ENDIF
405
406	!! 1.3.3 "monthly" soil temperatures (::tsoil_month):
407	!MM PAS PARALLELISE!!
408	IF ( ABS( SUM( tsoil_month(:,:) ) ) .LT. min_stomate ) THEN
409
410	! in this case, set them to today's temperature
411	WRITE(numout,*) 'Warning!'// &
412	' We have to initialize the ''monthly'' soil temperatures.'
413	tsoil_month(:,:) = tsoil_daily(:,:)
414
415	ENDIF
416
417	!! 1.3.4 "monthly" soil humidity (::soilhum_month):
418	IF ( ABS( SUM( soilhum_month(:,:) ) ) .LT. min_stomate ) THEN
419
420	! in this case, set them to today's humidity
421	WRITE(numout,*) 'Warning!'// &
422	' We have to initialize the ''monthly'' soil humidity.'
423	soilhum_month(:,:) = soilhum_daily(:,:)
424
425	ENDIF
426
427	!! 1.3.5 growing degree days, threshold -5 deg C (::gdd_m5_dormance):
428	IF ( ABS( SUM( gdd_m5_dormance(:,2:nvm) ) ) .LT. min_stomate ) THEN
429	WRITE(numout,*) 'Warning! Growing degree days (-5 deg) are initialized to ''undef''.'
430	gdd_m5_dormance(:,:) = undef
431	ENDIF
432
433	!! 1.3.6 growing degree days since midwinter (::gdd_midwinter):
434	IF ( ABS( SUM( gdd_midwinter(:,2:nvm) ) ) .LT. min_stomate ) THEN
435	WRITE(numout,*) 'Warning! Growing degree days since midwinter' // &
436	' are initialized to ''undef''.'
437	gdd_midwinter(:,:) = undef
438	ENDIF
439
440	!! 1.3.7 number of chilling days since leaves were lost (::ncd_dormance):
441	IF ( ABS( SUM( ncd_dormance(:,2:nvm) ) ) .LT. min_stomate ) THEN
442	WRITE(numout,*) 'Warning! Number of chilling days is initialized to ''undef''.'
443	ncd_dormance(:,:) = undef
444	ENDIF
445
446	!! 1.3.8 number of growing days, threshold -5 deg C (::ngd_minus5):
447	IF ( ABS( SUM( ngd_minus5(:,2:nvm) ) ) .LT. min_stomate ) THEN
448	WRITE(numout,*) 'Warning! Number of growing days (-5 deg) is initialized to 0.'
449	ENDIF
450
451	!! 1.3.9 "long term" npp (::npp_longterm):
452	IF ( ABS( SUM( npp_longterm(:,2:nvm) ) ) .LT. min_stomate ) THEN
453	WRITE(numout,*) 'Warning! Long term NPP is initialized to 0.'
454	ENDIF
455
456	!! 1.3.10 "long term" turnover (::turnover_longterm):
457	IF ( ABS( SUM( turnover_longterm(:,2:nvm,:,:) ) ) .LT. min_stomate ) THEN
458	WRITE(numout,*) 'Warning! Long term turnover is initialized to 0.'
459	ENDIF
460
461	!! 1.3.11 "weekly" GPP (::gpp_week):
462	IF ( ABS( SUM( gpp_week(:,2:nvm) ) ) .LT. min_stomate ) THEN
463	WRITE(numout,*) 'Warning! Weekly GPP is initialized to 0.'
464	ENDIF
465
466	!! 1.3.12 minimum moisture availabilities (::minmoiavail_thisyear)
467	!! In this case, if the minimum moisture
468	!! is less than ::min_stomate, the variable is set to ::large_value,
469	!! which is defined in ::stomate_constants as 1.E33_r_std:
470	IF ( ABS( SUM( minmoiavail_thisyear(:,2:nvm) ) ) .LT. min_stomate ) THEN
471
472	! in this case, set them to a very high value
473	WRITE(numout,*) 'Warning! We have to initialize this year''s minimum '// &
474	'moisture availabilities.'
475	minmoiavail_thisyear(:,:) = large_value
476
477	ENDIF
478
479	!
480	!! 1.4 reset firstcall_season flag
481	!
482
483	firstcall_season = .FALSE.
484
485	ENDIF
486
487	! determine min yearly clear sky radiation (solstice) as beginning for gdd count
488	cloud(:) = zero
489	CALL downward_solar_flux (npts, lalo(:,1),julian_diff,12.,cloud,1,solad,solai)
490
491	WHERE (solad(:) .LT. gdd_init_date(:,2))
492	gdd_init_date(:,1)= julian_diff
493	gdd_init_date(:,2)= solad(:)
494	ENDWHERE
495
496
497	!
498	!! NOTE: Sections 2. to 5. compute slowly-varying, "long-term" (i.e. weekly/monthly)
499	!! input variables using a linear relaxation method, following the equation:
500	!! \latexonly
501	!! \input{season_lin_relax_eqn1.tex}
502	!! \endlatexonly
503	!! \n
504	!! as described in the introduction to this subroutine (see Krinner et al., 2005).
505	!! The time constant in the above equation is given for each of the variables
506	!! described.
507	!
508
509	!
510	!! 2. Moisture availability (relative soil moisture, including the root profile) :
511	!! The time constants (as in the above equation) for these calculations are
512	!! given by the parameters ::tau_hum_month (for the monthly
513	!! calculation) or ::tau_hum_week (for the weekly),
514	!! which are set in ::stomate_data to be 20 and 7 days respectively.
515	!! If the moisture availability is less than zero, it is set to zero.
516	!! These variables are mostly used in the phenological leaf onset and senescence
517	!! models in the modules ::stomate_phenology and ::stomate_turnover,
518	!! respectively. They are used in models which require a moisture limitation
519	!! condition. These are the 'hum', 'moi', 'humgdd' and 'moigdd' onset models,
520	!! and the 'mixed' and 'dry' (weekly only) senescence models. In addition,
521	!! the weekly moisture availability is used to calculate the limitation
522	!! on the fraction of NPP allocated to different compartments in the module
523	!! ::stomate_alloc.
524	!
525
526	!
527	!! 2.1 "monthly" (::moiavail_month)
528	!
529
530	moiavail_month = ( moiavail_month * ( tau_hum_month - dt ) + &
531	moiavail_daily * dt ) / tau_hum_month
532
533	DO j = 2,nvm ! Loop over # PFTs
534	WHERE ( ABS(moiavail_month(:,j)) .LT. EPSILON(zero) )
535	moiavail_month(:,j) = zero
536	ENDWHERE
537	ENDDO
538
539	!
540	!! 2.2 "weekly" (::moiavail_week)
541	!
542
543	moiavail_week = ( moiavail_week * ( tau_hum_week - dt ) + &
544	moiavail_daily * dt ) / tau_hum_week
545
546	DO j = 2,nvm ! Loop over # PFTs
547	WHERE ( ABS(moiavail_week(:,j)) .LT. EPSILON(zero) )
548	moiavail_week(:,j) = zero
549	ENDWHERE
550	ENDDO
551
552	!
553	!! 3. 2-meter temperatures
554	!! The time constants for the "long-term", "monthly" and "weekly" 2-meter
555	!! temperatures are given by the parameters ::tau_longterm_max,
556	!! ::tau_t2m_month, and ::tau_t2m_week,
557	!! which are set in ::stomate_data to be 3 * one year (in seconds, as
558	!! described above) and 20 and 7 days respectively.
559	!! If the temperature is less than zero, it is set to zero.
560	!! In addition the "long term" temperature is written to the history file. \n
561	!! These variables are used in many different modules of STOMATE.
562	!! The longterm t2m is limied to the intervall [tlong_ref_min, tlong_ref_max]
563	!! using the equation:
564	!! \latexonly
565	!! \input{season_t2m_long_ref_eqn3.tex}
566	!! \endlatexonly
567	!! \n
568	!! The "monthly" and "weekly" temperature is used in the modules
569	!! ::stomate_phenology and ::stomate_turnover for the onset and senescence
570	!! phenological models which require a temperature condition. In addition
571	!! the "monthly" temperature is used in ::lpj_constraints to determine
572	!! the presence and regeneration of the vegetation and in the module
573	!! ::stomate_assimtemp to calculate photosynthesis temperatures.
574
575	! Update tau_longterm
576	tau_longterm = MIN(tau_longterm+dt,tau_longterm_max)
577
578	! Recalculate the reference temperature using the old reference temperature and the current temperature
579	t2m_longterm(:) = ( t2m_longterm(:) * ( tau_longterm - dt ) + &
580	t2m_daily(:) * dt ) / tau_longterm
581
582	! The longterm reference is not allowed to go outside the interval [tlong_ref_min, tlong_ref_max]
583	t2m_longterm(:) = MAX( tlong_ref_min, MIN( tlong_ref_max, t2m_longterm(:) ) )
584
585	CALL xios_orchidee_send_field("t2m_longterm",t2m_longterm)
586
587	CALL histwrite_p (hist_id_stomate, 'T2M_LONGTERM', itime, &
588	t2m_longterm, npts, hori_index)
589
590	!
591	!! 3.3 "monthly" (::t2m_month)
592	!
593
594	t2m_month = ( t2m_month * ( tau_t2m_month - dt ) + &
595	t2m_daily * dt ) / tau_t2m_month
596
597	WHERE ( ABS(t2m_month(:)) .LT. EPSILON(zero) )
598	t2m_month(:) = zero
599	ENDWHERE
600
601	! Store the day in onset_date when the leaves started grow. julian_diff is the day in the year [1-366].
602	WHERE ( begin_leaves(:,:) )
603	onset_date(:,:)=julian_diff
604	ELSEWHERE
605	onset_date(:,:)=0
606	ENDWHERE
607
608	! Calculate "seasonal" temperature
609	WHERE ( t2m_week (:) .GT. ZeroCelsius )
610	Tseason_tmp(:) = Tseason_tmp(:) + t2m_week(:)
611	Tseason_length(:)=Tseason_length(:) + dt
612	ENDWHERE
613
614	! calculate Tmin in spring (after onset)
615	DO j=1, nvm
616	IF (leaf_tab(j)==1 .AND. pheno_type(j)==2) THEN
617	! leaf_tab=broadleaf and pheno_typ=summergreen
618	! Only treat broadleag and summergreen pfts
619
620	WHERE ( Tmin_spring_time(:,j)>0 .AND. (Tmin_spring_time(:,j)<spring_days_max) )
621	Tmin_spring_time(:,j)=Tmin_spring_time(:,j)+1
622	ELSEWHERE
623	Tmin_spring_time(:,j)=0
624	ENDWHERE
625
626	WHERE ( begin_leaves(:,j) )
627	Tmin_spring_time(:,j)=1
628	ENDWHERE
629	END IF
630	END DO
631
632	!
633	!! 3.4 "weekly" (::t2m_week)
634	!
635
636	t2m_week = ( t2m_week * ( tau_t2m_week - dt ) + &
637	t2m_daily * dt ) / tau_t2m_week
638
639	WHERE ( ABS(t2m_week(:)) .LT. EPSILON(zero) )
640	t2m_week(:) = zero
641	ENDWHERE
642
643	!
644	!! 4. "monthly" soil temperatures (::tsoil_month)
645	!! The time constant is given by the parameter ::tau_tsoil_month,
646	!! which is set in ::stomate_data to be 20 days.
647	!! If the monthly soil temperature is less than zero, it is set to zero. \n
648	!! This variable is used in the ::stomate_allocation module.
649	!
650
651	tsoil_month = ( tsoil_month * ( tau_tsoil_month - dt ) + &
652	tsoil_daily(:,:) * dt ) / tau_tsoil_month
653
654	WHERE ( ABS(tsoil_month(:,:)) .LT. EPSILON(zero) )
655	tsoil_month(:,:) = zero
656	ENDWHERE
657
658	!
659	!! 5. ''monthly'' soil humidity (or relative soil moisture - ::soilhum_month)
660	!! The time constant is given by the parameter ::tau_soilhum_month,
661	!! which is set in ::stomate_data to be 20 days.
662	!! If the monthly soil humidity is less than zero, it is set to zero.
663	!
664
665	soilhum_month = ( soilhum_month * ( tau_soilhum_month - dt ) + &
666	soilhum_daily * dt ) / tau_soilhum_month
667
668	WHERE ( ABS(soilhum_month(:,:)) .LT. EPSILON(zero) )
669	soilhum_month(:,:) = zero
670	ENDWHERE
671
672	!
673	!! 6. Calculate the dormance time-length (::time_lowgpp).
674	!! The dormancy time-length is increased by the stomate time step when
675	!! the weekly GPP is below one of two thresholds,
676	!! OR if the growing season started more than 2 years ago AND the amount of biomass
677	!! in the carbohydrate reserve is 4 times as much as the leaf biomass.
678	!! i.e. the plant is declared dormant if it is accumulating carbohydrates but not
679	!! using them, so that the beginning of the growing season can be detected .
680	! This last condition was added by Nicolas Viovy.
681	!! - NV: special case (3rd condition)
682	!! Otherwise, set ::time_lowgpp to zero. \n
683	!! The weekly GPP must be below either the parameter ::min_gpp_allowed, which is set at
684	!! the beginning of this subroutine to be 0.3gC/m^2/year,
685	!! OR it must be less than last year's maximum weekly GPP multiplied by the
686	!! maximal ratio of GPP to maximum GPP (::gppfrac_dormance), which is set to 0.2 at the
687	!! beginning of this subroutine. \n
688	!! This variable is used in the ::stomate_phenology module to allow the detection of the
689	!! beginning of the vegetation growing season for different onset models.
690	!! Each PFT is looped over.
691	!
692	!NVMODIF
693	!!$ DO j = 2,nvm ! Loop over # PFTs
694	!!$ WHERE ( ( gpp_week(:,j) .LT. min_gpp_allowed ) .OR. &
695	!!$ ( gpp_week(:,j) .LT. gppfrac_dormance * maxgppweek_lastyear(:,j) ) .OR. &
696	!!$ ( ( when_growthinit(:,j) .GT. 2.*one_year ) .AND. &
697	!!$ ( biomass(:,j,icarbres,icarbon) .GT. biomass(:,j,ileaf,icarbon)*4. ) ) )
698	!!$ ! WHERE ( ( gpp_week(:,j) .EQ. zero ) .OR. &
699	!!$ ! ( gpp_week(:,j) .LT. gppfrac_dormance * maxgppweek_lastyear(:,j) ) .OR. &
700	!!$ ! ( ( when_growthinit(:,j) .GT. 2.*one_year ) .AND. &
701	!!$ ! ( biomass(:,j,icarbres,icarbon) .GT. biomass(:,j,ileaf,icarbon)*4. ) ) )
702	!!$
703	!!$ time_lowgpp(:,j) = time_lowgpp(:,j) + dt
704	!!$
705	!!$ ELSEWHERE
706	!!$
707	!!$ time_lowgpp(:,j) = zero
708	!!$
709	!!$ ENDWHERE
710	!!$ ENDDO
711
712	!
713	!! 7. Calculate the growing degree days (GDD - ::gdd_m5_dormance).
714	!! This variable is the GDD sum of the temperatures higher than -5 degrees C.
715	!! It is inititalised to 0 at the beginning of the dormancy period (i.e.
716	!! when ::time_lowgpp>0), and is set to "undef" when there is GPP
717	!! (::time_lowgpp=0), as it is not used during the growing season. \n
718	!! ::gdd_m5_dormance is further scaled by (::tau_gdd -dt / ::tau_gdd),
719	!! - ::tau_gdd is set to 40. in the module ::stomate_constants. \n
720	! Nicolas Viovy - not sure why this is...
721	!! This variable is used in the ::stomate_phenology module for the
722	!! 'humgdd' and 'moigdd' leaf onset models. \n
723	!! Each PFT is looped over but ::gdd_m5_dormance is only calculated for
724	!! those PFTs for which a critical GDD is defined, i.e. those which are
725	!! assigned to the 'humgdd' or 'moigdd' models. \n
726	!! Finally if GDD sum is less than zero, then it is set to zero.
727	!
728
729	DO j = 2,nvm ! Loop over # PFTs
730
731	IF (.NOT. natural(j)) THEN
732	! reset counter: start of the growing season
733	WHERE ((when_growthinit(:,j) .EQ. zero))
734	gdd_from_growthinit(:,j) = zero
735	ENDWHERE
736	! increase gdd counter
737	WHERE ( t2m_daily(:) .GT. (ZeroCelsius) )
738	gdd_from_growthinit(:,j) = gdd_from_growthinit(:,j) + &
739	dt * ( t2m_daily(:) - (ZeroCelsius) )
740	ENDWHERE
741	ELSE
742	gdd_from_growthinit(:,j) = undef
743	ENDIF
744
745	! only for PFTs for which critical gdd is defined
746	! gdd_m5_dormance is set to 0 at the end of the growing season. It is set to undef
747	! at the beginning of the growing season.
748
749	IF ( ALL(pheno_gdd_crit(j,:) .NE. undef) ) THEN
750
751	!
752	!! 7.1 set to zero if undefined and there is no GPP
753	!
754
755	WHERE (gdd_init_date(:,1) .EQ. julian_diff)
756
757	gdd_m5_dormance(:,j) = zero
758
759	ENDWHERE
760
761	!
762	!! 7.2 set to undef if there is GPP
763	!
764
765	WHERE ( when_growthinit(:,j) .EQ. zero )
766
767	gdd_m5_dormance(:,j) = undef
768
769	ENDWHERE
770
771	!
772	!! 7.3 normal update as described above where ::gdd_m5_dormance is defined (not set to "undef").
773	!
774
775	WHERE ( ( t2m_daily(:) .GT. ( ZeroCelsius - gdd_threshold ) ) .AND. &
776	( gdd_m5_dormance(:,j) .NE. undef ) )
777	gdd_m5_dormance(:,j) = gdd_m5_dormance(:,j) + &
778	dt * ( t2m_daily(:) - ( ZeroCelsius - gdd_threshold ) )
779	ENDWHERE
780
781	WHERE ( gdd_m5_dormance(:,j) .NE. undef )
782	gdd_m5_dormance(:,j) = gdd_m5_dormance(:,j) * &
783	( tau_gdd - dt ) / tau_gdd
784	ENDWHERE
785
786	ENDIF
787
788	ENDDO
789
790	!
791	!! 7.4 Set to zero if GDD is less than zero.
792
793	DO j = 2,nvm ! Loop over # PFTs
794	WHERE ( ABS(gdd_m5_dormance(:,j)) .LT. EPSILON(zero) )
795	gdd_m5_dormance(:,j) = zero
796	ENDWHERE
797	ENDDO
798
799	!
800	!! 8. Calculate the growing degree days (GDD) since midwinter (::gdd_midwinter)
801	!! This variable represents the GDD sum of temperatures higher than a PFT-dependent
802	!! threshold (::ncdgdd_temp), since midwinter.
803	!! Midwinter is detected if the monthly temperature (::t2m_month) is lower than the weekly
804	!! temperature (::t2m_week) AND if the monthly temperature is lower than the long-term
805	!! temperature (t2m_longterm). These variables were calculated earlier in this subroutine. \n
806	!! ::gdd_midwinter is initialised to 0.0 when midwinter is detected, and from then on
807	!! increased with each temperature greater than ::ncdgdd_temp, which is defined
808	!! in the module ::stomate_constants. \n
809	!! ::gdd_midwinter is set to "undef" when midsummer is detected, following the opposite
810	!! conditions to those used to define midwinter. \n
811	!! The variable is used in the ::stomate_phenology module for the leaf onset model 'ncdgdd'.
812	!! Each PFT is looped over but the ::gdd_midwinter is only calculated for those
813	!! PFTs for which a critical 'ncdgdd' temperature is defined, i.e. those which are
814	!! assigned to the 'ncdgdd' model. \n
815	!
816
817	DO j = 2,nvm ! Loop over # PFTs
818
819	! only for PFTs for which ncdgdd_crittemp is defined
820
821	IF ( ncdgdd_temp(j) .NE. undef ) THEN
822
823	!
824	!! 8.1 set to 0 if undef and if we detect "midwinter"
825	!
826
827	!!$ WHERE ( ( gdd_midwinter(:,j) .EQ. undef ) .AND. &
828	!!$ ( t2m_month(:) .LT. t2m_week(:) ) .AND. &
829	!!$ ( t2m_month(:) .LT. t2m_longterm(:) ) )
830	WHERE (gdd_init_date(:,1) .EQ. julian_diff)
831
832	gdd_midwinter(:,j) = zero
833
834	ENDWHERE
835
836	!
837	!! 8.2 set to undef if we detect "midsummer"
838	!
839
840	WHERE ( ( t2m_month(:) .GT. t2m_week(:) ) .AND. &
841	( t2m_month(:) .GT. t2m_longterm(:) ) )
842
843	gdd_midwinter(:,j) = undef
844
845	ENDWHERE
846
847	!
848	!! 8.3 normal update as described above
849	!
850
851	WHERE ( ( gdd_midwinter(:,j) .NE. undef ) .AND. &
852	( t2m_daily(:) .GT. ncdgdd_temp(j)+ZeroCelsius ) )
853
854	gdd_midwinter(:,j) = &
855	gdd_midwinter(:,j) + &
856	dt * ( t2m_daily(:) - ( ncdgdd_temp(j)+ZeroCelsius ) )
857
858	ENDWHERE
859
860	ENDIF
861
862	ENDDO
863
864	!
865	!! 9. Calculate the number of chilling days (NCD) since leaves were lost (::ncd_dormance).
866	!! This variable is initialised to 0 at the beginning of the dormancy period (::time_lowgpp>0)
867	!! and increased by the stomate time step when the daily temperature is lower than the
868	!! PFT-dependent threshold ::ncdgdd_temp, which is defined for each PFT
869	!! in a table (::ncdgdd_temp_tab) in the module ::stomate_data. \n
870	!! It is set to "undef" when there is GPP (::time_lowgpp=0) as it is not needed during
871	!! the growing season. \n
872	!! The variable is used in the ::stomate_phenology module for the leaf onset model 'ncdgdd'.
873	!! Each PFT is looped over but the ::ncd_dormance is only calculated for those
874	!! PFTs for which a critical 'ncdgdd' temperature is defined, i.e. those which are
875	!! assigned to the 'ncdgdd' model.
876	!
877
878	DO j = 2,nvm ! Loop over # PFTs
879
880	IF ( ncdgdd_temp(j) .NE. undef ) THEN
881
882	!
883	!! 9.1 set to zero if undefined and there is no GPP
884	!
885
886	WHERE (gdd_init_date(:,1) .EQ. julian_diff)
887
888	ncd_dormance(:,j) = zero
889
890	ENDWHERE
891
892	!
893	!! 9.2 set to undef if there is GPP
894	!
895
896	WHERE ( when_growthinit(:,j) .EQ. zero )
897
898	ncd_dormance(:,j) = undef
899
900	ENDWHERE
901
902	!
903	!! 9.3 normal update, as described above, where ::ncd_dormance is defined
904	!
905
906	WHERE ( ( ncd_dormance(:,j) .NE. undef ) .AND. &
907	( t2m_daily(:) .LE. ncdgdd_temp(j)+ZeroCelsius ) )
908
909	ncd_dormance(:,j) = MIN( ncd_dormance(:,j) + dt, ncd_max )
910
911	ENDWHERE
912
913	ENDIF
914
915	ENDDO
916
917	!
918	!! 10. Calculate the number of growing days (NGD) since leaves were lost (::ngd_minus5).
919	!! This variable is initialised to 0 at the beginning of the dormancy period (::time_lowgpp>0)
920	!! and increased by the stomate time step when the daily temperature is higher than the threshold
921	!! -5 degrees C. \n
922	!! ::ngd_minus5 is further scaled by (::tau_ngd -dt / ::tau_ngd),
923	!! - ::tau_ngd is set to 50. in the module ::stomate_constants. \n
924	! Nicolas Viovy - not sure why this is...
925	!! The variable is used in the ::stomate_phenology module for the leaf onset model 'ngd'.
926	!! Each PFT is looped over.
927	!! If the NGD is less than zero, it is set to zero.
928	!
929
930	DO j = 2,nvm ! Loop over # PFTs
931
932	!
933	!! 10.1 Where there is GPP (i.e. ::time_lowgpp=0), set NGD to 0.
934	!! This means that we only take into account NGDs when the leaves are off
935	!
936
937	WHERE (gdd_init_date(:,1) .EQ. julian_diff)
938	ngd_minus5(:,j) = zero
939	ENDWHERE
940
941	!
942	!! 10.2 normal update, as described above.
943	!
944
945	WHERE ( t2m_daily(:) .GT. (ZeroCelsius - gdd_threshold) )
946	ngd_minus5(:,j) = ngd_minus5(:,j) + dt
947	ENDWHERE
948
949	ngd_minus5(:,j) = ngd_minus5(:,j) * ( tau_ngd - dt ) / tau_ngd
950
951	ENDDO
952
953	DO j = 2,nvm ! Loop over # PFTs
954	WHERE ( ABS(ngd_minus5(:,j)) .LT. EPSILON(zero) )
955	ngd_minus5(:,j) = zero
956	ENDWHERE
957	ENDDO
958
959	!
960	!! 11. Calculate the minimum humidity/relative soil moisture since dormance began (::hum_min_dormance)
961	!! and the time elapsed since this minimum (::time_hum_min). \n
962	!! The minimum moisture availability occurs when the monthly moisture availability, which is updated
963	!! daily earlier in this subroutine as previously described, is at a minimum during the dormancy period.
964	!! Therefore the ::hum_min_dormance is initialised to the monthly moisture availability
965	!! at the beginning of the dormancy period (i.e. if it was previously set to undefined and the
966	!! ::time_lowgpp>0) AND then whenever the monthly moisture availability is less than it has previously
967	!! been. \n
968	!! Consequently, the time counter (::time_hum_min) is initialised to 0 at the beginning of the dormancy
969	!! period (i.e. if it was previously set to undefined and the ::time_lowgpp>0) AND when the minimum
970	!! moisture availability is reached, and is increased by the stomate time step every day throughout
971	!! the dormancy period. \n
972	!! ::time_hum_min is used in the ::stomate_phenology module for the leaf onset models 'moi' and 'moigdd'.
973	!! Each PFT is looped over but the two variables are only calculated for those
974	!! PFTs for which the critical parameter ::hum_min_time is defined, i.e.
975	!! those which are assigned to the 'moi' or 'moigdd' models.
976	!
977
978	DO j = 2,nvm ! Loop over # PFTs
979
980	IF ( hum_min_time(j) .NE. undef ) THEN
981
982	!
983	!! 11.1 initialize if undefined and there is no GPP
984	!
985
986	WHERE (when_growthinit(:,j) .EQ. zero)
987
988	time_hum_min(:,j) = zero
989	hum_min_dormance(:,j) = moiavail_month(:,j)
990
991	ENDWHERE
992
993	!
994	!! 11.3 normal update, as described above, where ::time_hum_min and ::hum_min_dormance are defined
995	!
996
997	!! 11.3.1 increase time counter by the stomate time step
998
999	WHERE ( hum_min_dormance(:,j) .NE. undef )
1000
1001	time_hum_min(:,j) = time_hum_min(:,j) + dt
1002
1003	ENDWHERE
1004
1005	!! 11.3.2 set time counter to zero if minimum is reached
1006
1007	WHERE (( hum_min_dormance(:,j) .NE. undef ) .AND. &
1008	( moiavail_month(:,j) .LE. hum_min_dormance(:,j) ) )
1009
1010	hum_min_dormance(:,j) = moiavail_month(:,j)
1011	time_hum_min(:,j) = zero
1012
1013	ENDWHERE
1014
1015	ENDIF
1016
1017	ENDDO
1018
1019	!
1020	!! NOTE: Sections 12. to 14. compute slowly-varying, "long-term" (i.e. weekly/monthly)
1021	!! C fluxes (NPP, turnover, GPP) using the same linear relaxation method as in
1022	!! Sections 2. and 5. and described in the introduction to this section, as given
1023	!! by the following equation:
1024	!! \latexonly
1025	!! \input{season_lin_relax_eqn1.tex}
1026	!! \endlatexonly
1027	!! \n
1028	!! The following variables are calculated using the above equation, and the time constant
1029	!! is given for each.
1030	!
1031
1032	!
1033	!! 12. Update the "long term" NPP. (::npp_daily in gC/m^2/day, ::npp_longterm in gC/m^2/year.)
1034	!! The time constant is given by the parameter ::tau_longterm,
1035	!! which is set in ::stomate_data to be 3 * one year (in seconds, as
1036	!! described above). If the ::npp_longterm is less than zero then set it to zero. \n
1037	!! ::npp_longterm is used in ::stomate_lpj in the calculation of long-term
1038	!! vegetation dynamics and in ::stomate_lcchange in the calculation of
1039	!! land cover change. It is also used to calculate diagnose the hebivory activity in
1040	!! Section 22 of this subroutine.
1041	!
1042
1043	npp_longterm = ( npp_longterm * ( tau_longterm - dt ) + &
1044	(npp_dailyone_year) dt ) / &
1045	tau_longterm
1046
1047	DO j = 2,nvm ! Loop over # PFTs
1048	WHERE ( ABS(npp_longterm(:,j)) .LT. EPSILON(zero) )
1049	npp_longterm(:,j) = zero
1050	ENDWHERE
1051	ENDDO
1052
1053	!
1054	!! 13. Update the "long term" turnover rates (in gC/m^2/year).
1055	!! The time constant is given by the parameter ::tau_longterm,
1056	!! which is set in ::stomate_data to be 3 * one year (in seconds, as
1057	!! described above). If the ::turnover_longterm is less than zero then set it to zero.\n
1058	!! ::turnover_longterm is used in ::stomate_lpj and :: lpg_gap in the calculation
1059	!! of long-term vegetation dynamics.
1060	!
1061
1062	turnover_longterm(:,:,:,:) = ( turnover_longterm(:,:,:,:) * ( tau_longterm - dt ) + &
1063	(turnover_daily(:,:,:,:)one_year) dt ) / &
1064	tau_longterm
1065
1066	DO j = 2,nvm ! Loop over # PFTs
1067	WHERE ( ABS(turnover_longterm(:,j,:,:)) .LT. EPSILON(zero) )
1068	turnover_longterm(:,j,:,:) = zero
1069	ENDWHERE
1070	ENDDO
1071
1072	!
1073	!! 14. Update the "weekly" GPP (where there is vegetation), otherwise set to zero.
1074	!! The time constant is given by the parameter ::tau_gpp_week,
1075	!! which is set in ::stomate_data to be 7 days. If the ::gpp_week is
1076	!! less than zero then set it to zero. \n
1077	!! ::gpp_week is used to update the annual maximum weekly GPP (::maxgppweek_thisyear)
1078	!! in Section 16 of this subroutine, which is then used to update the variable
1079	!! ::maxgppweek_lastyear in Section 21 of this subroutine. Both ::gpp_week and
1080	!! ::maxgppweek_lastyear are used in Section 6 of this subroutine to calculate
1081	!! the onset and time-length of the dormancy period.
1082	! Note: Used to be weekly GPP divided by veget_cov_max, i.e. per ground covered, but not anymore.
1083	!
1084
1085	WHERE ( veget_cov_max .GT. zero )
1086
1087	gpp_week = ( gpp_week * ( tau_gpp_week - dt ) + &
1088	gpp_daily * dt ) / tau_gpp_week
1089
1090	ELSEWHERE
1091
1092	gpp_week = zero
1093
1094	ENDWHERE
1095
1096	DO j = 2,nvm ! Loop over # PFTs
1097	WHERE ( ABS(gpp_week(:,j)) .LT. EPSILON(zero) )
1098	gpp_week(:,j) = zero
1099	ENDWHERE
1100	ENDDO
1101
1102	!
1103	!! 15. Update the maximum and minimum moisture availabilities (::maxmoiavail_thisyear
1104	!! and ::minmoiavail_thisyear). If the daily moisture availability, ::moiavail_daily,
1105	!! which was calculated earlier in this subroutine, is greater or less than the current
1106	!! value of the maximum or minimum moisture availability, then set the value for the maximum
1107	!! or minimum to the current daily value respectively. \n
1108	!! ::maxmoiavail_thisyear and ::minmoiavail_thisyear are used to update the variables
1109	!! ::maxmoiavail_lastyear and ::minmoiavail_lastyear in Section 21 of this subroutine,
1110	!! which are used in the module ::stomate_phenology for the leaf onset models 'hum' and
1111	!! 'humgdd', and in the module ::stomate_turnover for the leaf senescence models 'dry'
1112	!! and 'mixed'.
1113	!
1114
1115	WHERE ( moiavail_daily .GT. maxmoiavail_thisyear )
1116	maxmoiavail_thisyear = moiavail_daily
1117	ENDWHERE
1118
1119	WHERE ( moiavail_daily .LT. minmoiavail_thisyear )
1120	minmoiavail_thisyear = moiavail_daily
1121	ENDWHERE
1122
1123	!
1124	!! 16. Update the annual maximum weekly GPP (::maxgppweek_thisyear), if the weekly GPP
1125	!! is greater than the current value of the annual maximum weekly GPP.
1126	!! The use of this variable is described in Section 14.
1127	!
1128
1129	WHERE ( gpp_week .GT. maxgppweek_thisyear )
1130	maxgppweek_thisyear = gpp_week
1131	ENDWHERE
1132
1133	!
1134	!! 17. Update the annual GDD0 by adding the current daily 2-meter temperature
1135	!! (multiplied by the stomate time step, which is one day), if it is greater
1136	!! than zero degrees C. \n
1137	!! This variable is mostly used in the module ::lpj_establish.
1138	!
1139
1140	WHERE ( t2m_daily .GT. ZeroCelsius )
1141	gdd0_thisyear = gdd0_thisyear + dt * ( t2m_daily - ZeroCelsius )
1142	ENDWHERE
1143
1144	!
1145	!! 18. Update the annual precipitation by adding the current daily precipitation
1146	!! amount (multiplied by the stomate time step, which is usually one day). \n
1147	!
1148
1149	precip_thisyear = precip_thisyear + dt * precip_daily
1150
1151
1152	!
1153	!! 19. Update the annual maximum leaf mass for each PFT (::lm_thisyearmax) and the maximum fractional
1154	!! plant cover if the LPJ DGVM is activated.
1155	!
1156
1157	!
1158	!! 19.1 If the LPJ DGVM is activated first the fraction of natural vegetation (::fracnat), i.e. non-
1159	!! agricultural vegetation (PFTs 2-11) is calculated for each PFT. Each PFT is looped over.
1160	!
1161	IF(ok_dgvm ) THEN
1162
1163	fracnat(:) = un
1164	DO j = 2,nvm ! Loop over # PFTs
1165	IF ( .NOT. natural(j) ) THEN
1166	fracnat(:) = fracnat(:) - veget_cov_max(:,j)
1167	ENDIF
1168	ENDDO
1169
1170	ENDIF
1171
1172	!
1173	!! 19.2 If LPJ and STOMATE are activated, first the maximum fractional plant cover needs to be updated,
1174	!! and then this year's leaf biomass. Each PFT is looped over.
1175	!! Both are updated according to the linear relaxation method described above.
1176	!! \latexonly
1177	!! \input{season_lin_relax_eqn1.tex}
1178	!! \endlatexonly
1179	!! \n
1180	!! The time constant for this process is set as one year (in seconds) divided by the parameter
1181	!! ::leaflife_tab, which gives the leaf lifetime in years and is set for each PFT in the module
1182	!! ::stomate_constants. Each PFT is looped over. \n
1183	!
1184
1185	IF ( ok_stomate ) THEN
1186	IF(ok_dgvm ) THEN
1187	DO j=2,nvm ! Loop over # PFTs
1188
1189	!
1190	!! 19.2.1 Calculate maximum fractional plant cover (::maxfpc_lastyear).
1191	!! If natural vegetation is present in the grid cell, and the leaf
1192	!! biomass is greater than three-quarters of last year's leaf biomass, the maximum fractional plant
1193	!! cover for last year is updated. \n
1194	!! The short-term variable (Xs in the above equation) that is being used to update the long-term
1195	!! maximum fractional plant cover is the fractional cover of natural vegetation, specified as
1196	!! ::veget_cov/::fracnat. Last year's value is then set to be this year's value.
1197	!
1198
1199	IF ( natural(j) .AND. ok_dgvm ) THEN
1200
1201	WHERE ( fracnat(:) .GT. min_stomate .AND. biomass(:,j,ileaf,icarbon).GT. lm_lastyearmax(:,j)*0.75 )
1202	maxfpc_lastyear(:,j) = ( maxfpc_lastyear(:,j) * ( one_year/leaflife_tab(j)- dt ) + &
1203	veget_cov(:,j) / fracnat(:) * dt ) / (one_year/leaflife_tab(j))
1204	ENDWHERE
1205	maxfpc_thisyear(:,j) = maxfpc_lastyear(:,j) ! just to initialise value
1206
1207	ENDIF
1208
1209	!NV : correct initialization
1210	!!$ WHERE(biomass(:,j,ileaf,icarbon).GT. lm_lastyearmax(:,j)*0.75)
1211	!!$ lm_lastyearmax(:,j) = ( lm_lastyearmax(:,j) * ( one_year/leaflife_tab(j)- dt ) + &
1212	!!$ biomass(:,j,ileaf,icarbon) * dt ) / (one_year/leaflife_tab(j))
1213	!!$ ENDWHERE
1214	!!$ lm_thisyearmax(:,j)=lm_lastyearmax(:,j) ! just to initialise value
1215
1216
1217	!
1218	!! 19.2.2 Update this year's leaf biomass (::lm_thisyearmax).
1219	!! The short-term variable (Xs in the above equation) that is being used to update the long-term
1220	!! this year's leaf biomass is the leaf biomass pool (::biomass(i,j,ileaf).
1221	!
1222	WHERE (lm_thisyearmax(:,j) .GT. min_stomate)
1223	WHERE(biomass(:,j,ileaf,icarbon).GT. lm_thisyearmax(:,j)*0.75)
1224	lm_thisyearmax(:,j) = ( lm_thisyearmax(:,j) * ( one_year/leaflife_tab(j)- dt ) + &
1225	biomass(:,j,ileaf,icarbon) * dt ) / (one_year/leaflife_tab(j))
1226	ENDWHERE
1227	ELSEWHERE
1228	lm_thisyearmax(:,j) =biomass(:,j,ileaf,icarbon)
1229	ENDWHERE
1230
1231	ENDDO
1232
1233	ELSE
1234
1235	!
1236	!! 19.3 If LPJ DGVM is not activated but STOMATE is, the maximum leaf mass is set to be the same
1237	!! as the leaf biomass (::biomass(i,j,ileaf), without a change in the maximum fractional plant cover.
1238	!
1239	DO j = 2,nvm ! Loop over # PFTs
1240	WHERE ( biomass(:,j,ileaf,icarbon) .GT. lm_thisyearmax(:,j) )
1241	lm_thisyearmax(:,j) = biomass(:,j,ileaf,icarbon)
1242	ENDWHERE
1243	ENDDO
1244
1245	ENDIF !(ok_dgvm)
1246	ELSE
1247
1248	!
1249	!! 19.4 If STOMATE is not activated, the maximum leaf biomass is set to be the maximum possible
1250	!! LAI of the PFT.
1251	!
1252
1253	DO j = 2,nvm ! Loop over # PFTs
1254	lm_thisyearmax(:,j) = lai_max(j) / sla(j)
1255	ENDDO
1256
1257	ENDIF !(ok_stomate)
1258
1259	!
1260	!! 20. Update the annual maximum fractional plant cover for each PFT if the current fractional cover
1261	!! (::veget_cov), is larger than the current maximum value.
1262	!! ::veget_cov is defined as fraction of total ground. Therefore, maxfpc_thisyear has the same unit.
1263	!
1264
1265	WHERE ( veget_cov(:,:) .GT. maxfpc_thisyear(:,:) )
1266	maxfpc_thisyear(:,:) = veget_cov(:,:)
1267	ENDWHERE
1268
1269	!
1270	!! 21. At the end of the every year, last year's maximum and minimum moisture availability,
1271	!! annual GDD0, annual precipitation, annual max weekly GPP, and maximum leaf mass are
1272	!! updated with the value calculated for the current year, and then their value reset.
1273	!! Either to zero for the maximum variables, or to ::large_value (set to be 1.E33 in ::
1274	!! the module ::stomate_constants) for the minimum variable ::minmoiavail_thisyear.
1275	!
1276
1277	IF ( LastTsYear ) THEN
1278
1279	!
1280	!! 21.1 Update last year's values. \n
1281	!! The variables ::maxmoiavail_lastyear, ::minmoiavail_lastyear and ::maxgppweek_lastyear
1282	!! are updated using the relaxation method:
1283	!! \latexonly
1284	!! \input{season_lin_relax_eqn1.tex}
1285	!! \endlatexonly
1286	!! \n
1287	!! where Xs is this year's value, dt (Delta-t) is set to 1 (year), and the time constant (tau) !??
1288	!! is set by the parameter ::tau_climatology, which is set to 20 years at the beginning
1289	!! of this subroutine. \n
1290	!! The other variables (::gdd0_lastyear, ::precip_lastyear, ::lm_lastyearmax and
1291	!! ::maxfpc_lastyear) are just replaced with this year's value.
1292	!
1293	!NVMODIF
1294	maxmoiavail_lastyear(:,:) = (maxmoiavail_lastyear(:,:)*(tau_climatology-1)+ maxmoiavail_thisyear(:,:))/tau_climatology
1295	minmoiavail_lastyear(:,:) = (minmoiavail_lastyear(:,:)*(tau_climatology-1)+ minmoiavail_thisyear(:,:))/tau_climatology
1296	maxgppweek_lastyear(:,:) =( maxgppweek_lastyear(:,:)*(tau_climatology-1)+ maxgppweek_thisyear(:,:))/tau_climatology
1297	! maxmoiavail_lastyear(:,:) = maxmoiavail_thisyear(:,:)
1298	! minmoiavail_lastyear(:,:) = minmoiavail_thisyear(:,:)
1299	! maxgppweek_lastyear(:,:) = maxgppweek_thisyear(:,:)
1300
1301	gdd0_lastyear(:) = gdd0_thisyear(:)
1302
1303	precip_lastyear(:) = precip_thisyear(:)
1304
1305	lm_lastyearmax(:,:) = lm_thisyearmax(:,:)
1306
1307	maxfpc_lastyear(:,:) = maxfpc_thisyear(:,:)
1308
1309	! Calculate Tseason
1310	Tseason(:) = zero
1311	WHERE ( Tseason_length(:) .GT. min_sechiba )
1312	Tseason(:) = Tseason_tmp(:) / Tseason_length(:)
1313	ENDWHERE
1314
1315	!
1316	!! 21.2 Reset new values for the "this year" variables. \n
1317	!! The maximum variables are set to zero and the minimum variable ::minmoiavail_thisyear
1318	!! is set to ::large_value (set to be 1.E33 in the module ::stomate_constants).
1319	!
1320
1321	maxmoiavail_thisyear(:,:) = zero
1322	minmoiavail_thisyear(:,:) = large_value
1323
1324	maxgppweek_thisyear(:,:) = zero
1325
1326	gdd0_thisyear(:) = zero
1327
1328	precip_thisyear(:) = zero
1329
1330	lm_thisyearmax(:,:) = zero
1331
1332	maxfpc_thisyear(:,:) = zero
1333
1334	Tseason_tmp(:) = zero
1335	Tseason_length(:) =zero
1336	Tmin_spring_time(:,:)=zero
1337	onset_date(:,:)=zero
1338
1339	!
1340	! 21.3 Special treatment for maxfpc. !??
1341	!! 21.3 Set the maximum fractional plant cover for non-natural vegetation
1342	!! (i.e. agricultural C3 and C4 - PFT 12 and 13) vegetation for last year to be zero.
1343	!
1344
1345	!
1346	! 21.3.1 Only take into account natural PFTs
1347	!
1348
1349	DO j = 2,nvm ! Loop over # PFTs
1350	IF ( .NOT. natural(j) ) THEN
1351	maxfpc_lastyear(:,j) = zero
1352	ENDIF
1353	ENDDO
1354
1355	! 21.3.2 In Stomate, veget_cov is defined as a fraction of ground, not as a fraction
1356	! of total ground. maxfpc_lastyear will be compared to veget_cov in lpj_light.
1357	! Therefore, we have to transform maxfpc_lastyear.
1358
1359
1360	! 21.3.3 The sum of the maxfpc_lastyear for natural PFT must not exceed fpc_crit (=.95).
1361	! However, it can slightly exceed this value as not all PFTs reach their maximum
1362	! fpc at the same time. Therefore, if sum(maxfpc_lastyear) for the natural PFTs
1363	! exceeds fpc_crit, we scale the values of maxfpc_lastyear so that the sum is
1364	! fpc_crit.
1365
1366	!!$ ! calculate the sum of maxfpc_lastyear
1367	!!$ sumfpc_nat(:) = zero
1368	!!$ DO j = 2,nvm ! Loop over # PFTs
1369	!!$ sumfpc_nat(:) = sumfpc_nat(:) + maxfpc_lastyear(:,j)
1370	!!$ ENDDO
1371	!!$
1372	!!$ ! scale so that the new sum is fpc_crit
1373	!!$ DO j = 2,nvm ! Loop over # PFTs
1374	!!$ WHERE ( sumfpc_nat(:) .GT. fpc_crit )
1375	!!$ maxfpc_lastyear(:,j) = maxfpc_lastyear(:,j) * (fpc_crit/sumfpc_nat(:))
1376	!!$ ENDWHERE
1377	!!$ ENDDO
1378
1379	ENDIF ! LastTsYear
1380
1381	!
1382	!! 22. Diagnose herbivore activity (::herbivores), determined as probability for a leaf to be
1383	!! eaten in a day (follows McNaughton et al., 1989). \n
1384	!! The amount of herbivore activity is used in the modules ::lpj_establish
1385	!! and ::stomate_turnover.
1386	!
1387
1388	!
1389	!! 22.1 First calculate the mean long-term leaf NPP in grid box, mean residence
1390	!! time (years) of green tissue to give the biomass available for herbivore consumption.
1391	!! Each PFT is looped over, though the calculation is only made for
1392	!! natural vegetation (PFTs 2-11).
1393	!
1394
1395	nlflong_nat(:,:) = zero
1396	weighttot(:,:) = zero
1397	green_age(:,:) = zero
1398	!
1399	DO j = 2,nvm ! Loop over # PFTs
1400	!
1401	IF ( natural(j) ) THEN
1402	!
1403	!! 22.1.1 Calculate the total weight of the leaves (::weighttot) as last year's leaf biomass
1404	!
1405	weighttot(:,j) = lm_lastyearmax(:,j)
1406
1407	!
1408	!! 22.1.2 Calculate the mean long-term leaf NPP as the long-term NPP calculated in Section 12 of
1409	!! this subroutine weighted by the leaf fraction (::leaf_frac), which is defined to be 0.33
1410	!! at the beginning of this subroutine.
1411	!
1412	nlflong_nat(:,j) = npp_longterm(:,j) * leaf_frac_hvc
1413
1414	!
1415	!! 22.1.3 Calculate the mean residence time of the green tissue (::green_age)
1416	!! This is calculated as the sum of 6 months
1417	!! for natural seasonal vegetation (i.e. PFTs 3, 6, 8-11), and 2 years for evergreen
1418	!! (PFTs 2, 4, 5, 8), multiplied by last year's leaf biomass for each PFT, divided by the
1419	!! total weight of the leaves for all PFTs.
1420	! This is a crude approximation. !!?? By whom?
1421	!! The difference between seasonal and evergreen vegetation is determined by the parameter
1422	!! ::pheno_model, which specifies the onset model of the PFT.
1423
1424	!
1425	IF ( pheno_model(j) .EQ. 'none' ) THEN
1426	green_age(:,j) = green_age_ever * lm_lastyearmax(:,j)
1427	ELSE
1428	green_age(:,j) = green_age_dec * lm_lastyearmax(:,j)
1429	ENDIF
1430	!
1431	ENDIF
1432	!
1433	ENDDO
1434	!
1435	WHERE ( weighttot(:,:) .GT. min_sechiba )
1436	green_age(:,:) = green_age(:,:) / weighttot(:,:)
1437	ELSEWHERE
1438	green_age(:,:) = un
1439	ENDWHERE
1440
1441	!
1442	!! 22.2 McNaughton et al. (1989) give herbivore consumption as a function of mean, long-term leaf NPP.
1443	!! as it gives an estimate of the edible biomass. The consumption of biomass by herbivores and the
1444	!! resultant herbivore activity are calculated following the equations:
1445	!! \latexonly
1446	!! \input{season_consumption_eqn4.tex}
1447	!! \endlatexonly
1448	!! \n
1449	!! and
1450	!! \latexonly
1451	!! \input{season_herbivore_eqn5.tex}
1452	!! \endlatexonly
1453	!! \n
1454	!
1455
1456	DO j = 2,nvm ! Loop over # PFTs
1457	!
1458	IF ( natural(j) ) THEN
1459	!
1460	WHERE ( nlflong_nat(:,j) .GT. zero )
1461	consumption(:) = hvc1 * nlflong_nat(:,j) ** hvc2
1462	herbivores(:,j) = one_year * green_age(:,j) * nlflong_nat(:,j) / consumption(:)
1463	ELSEWHERE
1464	herbivores(:,j) = 100000.
1465	ENDWHERE
1466	!
1467	ELSE
1468	!
1469	herbivores(:,j) = 100000.
1470	!
1471	ENDIF
1472	!
1473	ENDDO
1474	herbivores(:,ibare_sechiba) = zero
1475
1476	IF (printlev>=4) WRITE(numout,*) 'Leaving season'
1477
1478	END SUBROUTINE season
1479
1480	END MODULE stomate_season

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