PMIP 2 Land-Surface and Vegetation Variables


 

Coordinator(s) Updated
Nathalie de Noblet / LSCE 03/10/2005

 

Note: the list of required variables is not stable yet. You will find in the tables below the variables that are likely to be found in the database, and the variables that were suggested as useful but did not make it to the final list.

 

Required variables

Name(s) Units Description Axes Frequency DB
DA MO SE AN
Required variables
[vcarcont]
[vegetation...
..._carbon_content]
kg m-2 Total vegetation carbon (above ground & roots) XYT     O O G
[vcarcontpft]
[vegetation...
..._carbon_content]
kg m-2 Total vegetation carbon (above ground & roots) by PFT XYVT     Vn Vn G
[scarcont]
[soil...
..._carbon_content]
kg m-2 Soil carbon content XYT     O O G
[pftfrac]
[pft_fraction]
1 PFT fractions XYVT     Vn Vn  
[npp]
[net_primary...
..._productivity...
.._of_carbon]
kg m-2 s-1 NPP of vegetation XYT   O O   G
[npppft]
[net_primary...
..._productivity...
.._of_carbon]
kg m-2 s-1 NPP of vegetation by PFT XYVT   Vn Vn   G
[laipft]
[leaf_area_index]
1 Leaf Area Index by PFT XYVT   Vn Vn    
[bioburnt]
[biomass_burnt]
kg m-2 s-1 Total biomass burnt XYT   O O    
[lcarcont]
[litter_carbon]
kg m-2 Litter carbon XYT     O O  
[lcarcontpft]
[litter_carbon]
kg m-2 Litter carbon by PFT XYVT     Vn Vn  
[hresp]
[heterotrophic...
..._respiration...
..._carbon_flux]
kg m-2 s-1 Heterotrophic respiration (I.e. respiration from the soil but not including root respiration) XYT   O O O G
[cheight]
[canopy_height]
m Canopy height XYT     O O  
[cheightpft]
[canopy_height]
m Canopy height by PFT XYT     O O  
[gpp]
[gross_primary...
..._productivity...
..._of_carbon]
kg m-2 s-1 Total gross primary production (GPP) XYT   O O   G
[gpppft]
[gross_primary...
..._productivity...
..._of_carbon]
kg m-2 s-1 Gross primary production (GPP) by PFT XYVT   Vn Vn   G
mrso
soil...
..._moisture_content
kg m-2 Soil moisture (integrated over soil column) XYT   O O   A1a5
mrros
surface...
..._runoff_flux
kg m-2 s-1 Surface runoff rate XYT     O   A1a21
mrro
runoff_flux
kg m-2 s-1 Total runoff rate (including drainage) XYT     O   A1a22
[dis]
[river...
..._discharge]
m3 s-1 Simulated River Discharge XYT     O   G
[tsoil]
[soil...
..._temperature]
K Average layer soil temperature XYST     Sn   G
evspsblveg
water...
..._evaporation...
..._flux...
..._from_canopy
kg m-2 s-1 Total canopy evaporation XYT     O   A1f2
[trans]
[transpiration...
..._flux]
kg m-2 s-1 Total plant transpiration XYT     O   G
[transpft]
[transpiration...
..._flux]
kg m-2 s-1 Plant transpiration by PFT XYVT     Vn   G
[esoil]
[water...
..._evaporation...
..._flux...
..._from_soil]
kg m-2 s-1 Bare soil evaporation XYT     O   G
[potevap]
[potential...
..._evaporation]
kg m-2 s-1 Potential evaporation XYT   O     G
[potevappft]
[potential...
..._evaporation]
kg m-2 s-1 Potential evaporation by PFT XYVT     Vn   G
Number of variables: 26
Estimated database size
MO: 6    MO-3D-20: 3     2475.0 Mb / 100 year(s)
SE: 16    SE-3D-20: 8    SE-3D-5: 1     67.9 Mb
AN: 6    AN-3D-20: 3     206.2 Mb / 100 year(s)
DB STORAGE REQUIRED = 2.7 Gb
 

High frequency surface processes variables required by the Dust Model

Please check Sandy Harrison's note to get full details about the dust model variables! The following table lists the variables that either are not required at all at DAily frequency in the PMIP 2 database, or are not required at a high enough frequency (sub-DAily) for the dust model.

Name(s) Units Description Axes Frequency DB
DA MO SE AN
mrso kg m-2 Soil moisture (in the top meter? at root depth?) XYT O       A
Number of variables: 1
Estimated database size
DA: 1     562.5 Mb / 50 year(s)
DB STORAGE REQUIRED = 0.5 Gb
 

Rejected variables

Name(s) Units Description Axes Frequency DB
DA MO SE AN
Variables moved to the Atmosphere Variables' list
orog m Orography XY         A
ts K Ground surface temperature (surface skin temperature?) XYT         A
tas K 2m air temperature XYT         A
pr kg m-2 s-1 Total precipitation XYT         A
huss kg kg-1 Surface specific humidity (2m) XYT         A
hurs 100 Surface relative humidity (2m) XYT         P
clt 100 Total cloud cover XYT         P
snc 100 Snow cover XYT         A
snd m Snow depth XYT         A
ps Pa Surface pressure XYT         A
uas m s-1 Surface (10m) eastward wind XYT         A
vas m s-1 Surface (10m) northward wind XYT         A
hfss W m-2 Heat flux sensible surface XYT         A
albs 100 Surface albedo XYT         A2
rss W m-2 SW radiation net surface XYT         A
rlus W m-2 LW radiation upward surface XYT         A
rls W m-2 LW radiation net surface XYT         A
Number of variables: 17
Other rejected variables
SAlbedo - Snow albedo XYT         G
Ecanop kg m-2 s-1 Interception evaporation XYZ         G
EvapSnow kg m-2 s-1 Snow Evaporation XYZ         G
SubSurf kg m-2 s-1 Sublimation of the snow free area XYT         G
Ewater kg m-2 s-1 Open water evaporation XYT         G
Qg W m-2 Ground heat flux (note: hf into the ground) XYT         G
mrfso
soil_frozen...
..._water_content
kg m-2 Total soil frozen water content XYT         A1a20
Qrec kg m-2 s-1 Recharge (note: recharge from river to the flood plain) XYT         G
SoilMoist kg m-2 Average layer soil moisture XYVT         G
SMLiqFrac   Average layer fraction of liquid moisture XYVT         G
SoilWet kg m-2 Total soil wetness XYVT         G
CanopInt kg m-2 Total canopy water storage XYVT         G
DelSurfStor kg m-2 Change in surface water storage XYT         G
SurfStor kg m-2 Surface water storage XYT         G
WaterTableD m Water table depth XYT         G
prsn kg m-2 s-1 Snowfall rate (water equivalent) XYT         A
Qa W m-2 Advective energy XYT         G
Qf W m-2 Energy of fusion XYT         G
Qtau N m-2 Momentum flux XYT         G
Qv W m-2 Energy of sublimation XYT         G
sic % Sea-ice concentration XYT         A
RainfSnowFrac   Fraction of rainfall on snow XYT         G
SnowfSnowFrac   Fraction of snowfall on snow XYT         G
SliqFrac   Snow liquid fraction XYT         G
snm kg m-2 s-1 Snow melt XYT         A1
snw kg m-2 Snow depth (water equivalent) XYT         A
SWEVeg kg m-2 SWE intercepted by the vegetation XYT         G
Qfz kg m-2 s-1 Re-freezing of water in the snow XYT         G
Qst kg m-2 s-1 Snow throughfall (note: Liquid water flowing out of the snow pack) XYT         G
SnowT K Snow surface temperature XYT         G
SnowTProf K Temperature profile in the snow XYZ         G
BaresoilT K Temperature of bare soil XYT         G
RadT K Surface Radiative Temperature XYT         G
VegT K Vegetation canopy temperature XYVT         G
NEE kg m-2 s-2 Net ecosystem exchange XYVT         G
Autoresp kg m-2 s-2 Autotrophic respiration XYVT         G
  ??? Leaf turnover rate XYVT          
Resp kg m-2 s-2 Total respiration on PFTs XYVT          
  kg m-2 s-2 Soil respiration XYT          
  ? Land snow melt heat flux XYT          
  ? Total moisture delivered to the boundary layer XYT          
RootMoist kg m-2 Soil water content in root zone XYVT         G
fdepth m Frozen soil depth XYT         G
tdepth m Depth to soil thaw XYT         G
SMFrozFrac ? Soil frozen fraction in first layer (or in root zone) XYVT         G
rlength m Roughness length XYT          
gs m s-1 Canopy conductance XYVT          
SubSnow kg m-2 s-1 Snow sublimation XYT         G
evap kg m-2 s-1 Total evapotranspiration (includes transpiration) XYT         G
ACond m s-1 Aerodynamic conductance XYT          
Qsb kg m-2 s-1 Subsurface runoff XYT         G
  ? Canopy throughfall XYT          
  kg m-2 Total soil water content (vertically integrated) XYT          
Number of variables: 53

Notes

Michel Crucifix

One difficulty arising from the various variable lists is that much information is redundant. Part of the problem could be solved by creating a separate list, called 'land surface processes', which, basically, would consider the diagnostics and prognostics of the land surface scheme.

Another difficulty is the very large number of variables. The number of variables to be centrally held and managed should not exceed 20 per module and per model, 5 to 10 of which only being compulsary. A more restrictive list presents both advantages of reducing our data storage requirements and improve the intrinsic quality of each variable (better control, quality check, better definition etc.) If a particular model seems to show a response specifically different from the others, it is always time to look at some very specific varibles, with the support of the expert on that model.

Can we make clear what we mean by soil wetness, soil moisture, and soil water content?


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