905 lines
63 KiB
ReStructuredText
905 lines
63 KiB
ReStructuredText
.. _rst_Surface Characterization, Vertical Discretization, and Model Input Requirements:
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Surface Characterization, Vertical Discretization, and Model Input Requirements
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===================================================================================
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.. _Surface Characterization:
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Surface Characterization
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-----------------------------
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.. _Surface Heterogeneity and Data Structure:
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Surface Heterogeneity and Data Structure
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Spatial land surface heterogeneity in CLM is represented as a nested
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subgrid hierarchy in which grid cells are composed of multiple land
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units, snow/soil columns, and PFTs (:numref:`Figure CLM subgrid hierarchy`).
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Each grid cell can have
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a different number of land units, each land unit can have a different
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number of columns, and each column can have multiple PFTs. The first
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subgrid level, the land unit, is intended to capture the broadest
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spatial patterns of subgrid heterogeneity. The current land units are
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glacier, lake, urban, vegetated, and crop (when the crop model option is
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turned on). The land unit level can be used to further delineate these
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patterns. For example, the urban land unit is divided into density
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classes representing the tall building district, high density, and
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medium density urban areas.
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The second subgrid level, the column, is intended to capture potential
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variability in the soil and snow state variables within a single land
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unit. For example, the vegetated land unit could contain several columns
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with independently evolving vertical profiles of soil water and
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temperature. Similarly, the managed vegetation land unit can be divided
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into two columns, irrigated and non-irrigated. The default snow/soil
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column is represented by 25 layers for ground (with up to 20 of these
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layers classified as soil layers and the remaining layers classified as
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bedrock layers) and up to 10 layers for snow, depending on snow
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depth. The central characteristic of the column subgrid level is that
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this is where the state variables for water and energy in the soil and
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snow are defined, as well as the fluxes of these components within the
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soil and snow. Regardless of the number and type of PFTs occupying space
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on the column, the column physics operates with a single set of upper
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boundary fluxes, as well as a single set of transpiration fluxes from
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multiple soil levels. These boundary fluxes are weighted averages over
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all PFTs. Currently, for lake and vegetated land units, a single column
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is assigned to each land unit. The crop land unit is split into
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irrigated and unirrigated columns with a single crop occupying each
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column. The urban land units have five columns (roof, sunlit walls and
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shaded walls, and pervious and impervious canyon floor) (Oleson et
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al. 2010b). The glacier land unit is separated into up to 10 elevation
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classes.
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.. _Figure CLM subgrid hierarchy:
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.. Figure:: image1.png
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Configuration of the CLM subgrid hierarchy. Box in upper right shows hypothetical subgrid distribution for a single grid cell. Note that the Crop land unit is only used when the model is run with the crop model active. Abbreviations: TBD – Tall Building District; HD – High Density; MD – Medium Density, G – Glacier, L – Lake, U – Urban, C – Crop, V – Vegetated, PFT – Plant Functional Type, Irr – Irrigated, UIrr – Unirrigated. Red arrows indicate allowed land unit transitions. Purple arrows indicate allowed patch-level transitions.
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The third subgrid level is referred to as the patch level. Patches can be PFTs or bare ground on the vegetated land unit
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and crop functional types (CFTs) on the crop land unit.
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The patch level is intended to capture the
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biogeophysical and biogeochemical differences between broad categories
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of plants in terms of their functional characteristics. On the vegetated
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land unit, up to 16 possible PFTs that differ in physiology and
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structure may coexist on a single column. All fluxes to and from the
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surface are defined at the PFT level, as are the vegetation state
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variables (e.g. vegetation temperature and canopy water storage). On the
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crop land unit, typically, different crop types can be represented on each
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crop land unit column (see Chapter :numref:`rst_Crops and Irrigation` for details).
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In addition to state and flux variable data structures for conserved
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components at each subgrid level (e.g., energy, water, carbon), each
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subgrid level also has a physical state data structure for handling
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quantities that are not involved in conservation checks (diagnostic
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variables). For example, the urban canopy air temperature and humidity
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are defined through physical state variables at the land unit level, the
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number of snow layers and the soil roughness lengths are defined as
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physical state variables at the column level, and the leaf area index
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and the fraction of canopy that is wet are defined as physical state
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variables at the PFT level.
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The standard configuration of the model subgrid hierarchy is illustrated
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in :numref:`Figure CLM subgrid hierarchy`. Here, only four PFTs are shown
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associated with the single
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column beneath the vegetated land unit but up to sixteen are possible.
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The crop land unit is present only when the crop model is active.
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Note that the biogeophysical processes related to soil and snow require
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PFT level properties to be aggregated to the column level. For example,
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the net heat flux into the ground is required as a boundary condition
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for the solution of snow/soil temperatures (Chapter :numref:`rst_Soil and Snow Temperatures`). This column
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level property must be determined by aggregating the net heat flux from
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all PFTs sharing the column. This is generally accomplished in the model
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by computing a weighted sum of the desired quantity over all PFTs whose
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weighting depends on the PFT area relative to all PFTs, unless otherwise
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noted in the text.
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.. _Vegetation Composition:
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Vegetation Composition
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Vegetated surfaces are comprised of up to 15 possible plant functional
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types (PFTs) plus bare ground (:numref:`Table Plant functional types`). An
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additional PFT is added if
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the irrigation model is active and six additional PFTs are added if the
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crop model is active (Chapter :numref:`rst_Crops and Irrigation`).
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In :numref:`Table Plant functional types`, IVT = 0,14 refers to the index of PCT_NAT_VEG
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on the surface dataset while IVT = 15,18 refers to the index of PCT_CFT on the surface dataset. These
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plant types differ in leaf and stem optical properties that determine reflection,
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transmittance, and absorption of solar radiation (:numref:`Table Plant functional type optical properties`), root
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distribution parameters that control the uptake of water from the soil
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(:numref:`Table Plant functional type root distribution parameters`), aerodynamic parameters that determine resistance to heat,
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moisture, and momentum transfer (:numref:`Table Plant functional type aerodynamic parameters`), and photosynthetic
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parameters that determine stomatal resistance, photosynthesis, and
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transpiration (:numref:`Table Plant functional type (PFT) stomatal conductance parameters`,
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:numref:`Table Temperature dependence parameters for C3 photosynthesis`). The composition and abundance of PFTs
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within a grid cell can either be prescribed as time-invariant fields
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(e.g., using the present day dataset described in section 21.3.3) or can
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evolve with time if the model is run in transient landcover mode
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(Chapter :numref:`rst_Transient Landcover Change`).
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.. _Table Plant functional types:
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.. table:: Plant functional types
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+-----+--------------------------------------------------------------+-------------------+
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| IVT | Plant functional type | Acronym |
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+=====+==============================================================+===================+
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| 0 | Bare Ground | NET Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 1 | Needleleaf evergreen tree – temperate | NET Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 2 | Needleleaf evergreen tree - boreal | NET Boreal |
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+-----+--------------------------------------------------------------+-------------------+
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| 3 | Needleleaf deciduous tree – boreal | NDT Boreal |
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+-----+--------------------------------------------------------------+-------------------+
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| 4 | Broadleaf evergreen tree – tropical | BET Tropical |
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+-----+--------------------------------------------------------------+-------------------+
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| 5 | Broadleaf evergreen tree – temperate | BET Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 6 | Broadleaf deciduous tree – tropical | BDT Tropical |
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+-----+--------------------------------------------------------------+-------------------+
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| 7 | Broadleaf deciduous tree – temperate | BDT Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 8 | Broadleaf deciduous tree – boreal | BDT Boreal |
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+-----+--------------------------------------------------------------+-------------------+
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| 9 | Broadleaf evergreen shrub - temperate | BES Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 10 | Broadleaf deciduous shrub – temperate | BDS Temperate |
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+-----+--------------------------------------------------------------+-------------------+
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| 11 | Broadleaf deciduous shrub – boreal | BDS Boreal |
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+-----+--------------------------------------------------------------+-------------------+
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| 12 | C\ :sub:`3` arctic grass | - |
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+-----+--------------------------------------------------------------+-------------------+
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| 13 | C\ :sub:`3` grass | - |
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+-----+--------------------------------------------------------------+-------------------+
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| 14 | C\ :sub:`4` grass | - |
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+-----+--------------------------------------------------------------+-------------------+
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| 15 | C\ :sub:`3` Unmanaged Rainfed Crop | UCrop UIrr |
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+-----+--------------------------------------------------------------+-------------------+
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| 16 | :sup:`1`\ C\ :sub:`3` Unmanaged Irrigated Crop | UCrop Irr |
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+-----+--------------------------------------------------------------+-------------------+
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| 17 | :sup:`2`\ Managed Rainfed Crop | Crop UIrr |
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+-----+--------------------------------------------------------------+-------------------+
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| 18 | :sup:`2`\ Managed Irrigated Crop | Crop Irr |
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+-----+--------------------------------------------------------------+-------------------+
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:sup:`1`\ Only used if irrigation is active (Chapter :numref:`rst_Crops and Irrigation`).
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:sup:`2`\ Only used if crop model is active (see Chapter :numref:`rst_Crops and Irrigation` for list of represented crops).
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.. _Vegetation Structure:
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Vegetation Structure
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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Vegetation structure is defined by leaf and stem area indices
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(:math:`L,\, S`) and canopy top and bottom heights (:math:`z_{top}`,\ :math:`z_{bot}` ).
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Separate leaf and
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stem area indices and canopy heights are prescribed or calculated for each PFT. Daily leaf
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and stem area indices are obtained from griddeddatasets of monthly values (section
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:numref:`Surface Data`). Canopy top and bottom heights for trees are from ICESat (:ref:`Simard et al. (2011) <Simardetal2011>`).
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Canopy top and bottom heights for short vegetation are obtained from gridded datasets but are invariant in space
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and time and were obtained from PFT-specific values (:ref:`Bonan et al. (2002a) <Bonanetal2002a>`) (:numref:`Table Plant functional type canopy top and bottom heights`).
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When the biogeochemistry model is active,
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vegetation state (LAI, SAI, canopy top and bottom heights) are calculated prognostically
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(see Chapter :numref:`rst_Vegetation Phenology and Turnover`).
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.. _Table Plant functional type canopy top and bottom heights:
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.. table:: Plant functional type canopy top and bottom heights
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+--------------------------------------------------------------+-------------------+-------------------+
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| Plant functional type | :math:`z_{top}` | :math:`z_{bot}` |
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+==============================================================+===================+===================+
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| BES Temperate | 0.5 | 0.1 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| BDS Temperate | 0.5 | 0.1 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| BDS Boreal | 0.5 | 0.1 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| C\ :sub:`3` arctic grass | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| C\ :sub:`3` grass | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| C\ :sub:`4` grass | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| UCrop UIrr | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| UCrop Irr | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| Crop UIrr | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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| Crop Irr | 0.5 | 0.01 |
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+--------------------------------------------------------------+-------------------+-------------------+
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.. _Phenology and vegetation burial by snow:
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Phenology and vegetation burial by snow
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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When the biogeochemistry model is inactive, leaf and stem area indices
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(m\ :sup:`2` leaf area m\ :sup:`-2` ground area) are updated
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daily by linearly interpolating between monthly values. Monthly PFT leaf
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area index values are developed from the 1-km MODIS-derived monthly grid
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cell average leaf area index of :ref:`Myneni et al. (2002) <Mynenietal2002>`,
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as described in :ref:`Lawrence and Chase (2007) <LawrenceChase2007>`. Stem area
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ndex is calculated from the monthly PFT leaf area index using the methods of
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:ref:`Zeng et al. (2002) <Zengetal2002>`. The leaf and stem area indices are
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adjusted for vertical burying by snow (:ref:`Wang and Zeng 2009 <WangZeng2009>`)
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as
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.. math::
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:label: 2.1
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A=A^{*} ( 1-f_{veg}^{sno} )
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where :math:`A^{\*}` is the leaf or stem area before adjustment for
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snow, :math:`A` is the remaining exposed leaf or stem area,
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:math:`f_{veg}^{sno}` is the vertical fraction of vegetation covered by snow
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.. math::
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:label: 2.2
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{f_{veg}^{sno} = \frac{z_{sno} -z_{bot} }{z_{top} -z_{bot} } \qquad {\rm for\; tree\; and\; shrub}} \\
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{f_{veg}^{sno} = \frac{\min \left(z_{sno} ,\, z_{c} \right)}{z_{c} } \qquad {\rm for\; grass\; and\; crop}}
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where :math:`z_{sno} -z_{bot} \ge 0,{\rm \; }0\le f_{veg}^{sno} \le 1`, :math:`z_{sno}` is the depth of snow (m)
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(Chapter :numref:`rst_Snow Hydrology`), and :math:`z_{c} = 0.2` is the snow depth when short vegetation is assumed to
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be completely buried by snow (m). For numerical reasons, exposed leaf and stem area are set to zero if less than
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0.05. If the sum of exposed leaf and stem area is zero, then the surface is treated as snow-covered ground.
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.. _Vertical Discretization:
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Vertical Discretization
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----------------------------
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..
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(this was taken from Initialization; is it still needed?
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Vegetated and glacier land units have fifteen vertical layers, while
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lakes have ten. For soil points, temperature calculations are done over
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all layers, :math:`N_{levgrnd} =15`, while hydrology calculations are
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done over the top ten layers, :math:`N_{levsoi} =10`, the bottom five
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layers being specified as bedrock.
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.. _Soil Layers:
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Soil Layers
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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The soil column can be discretized into an arbitrary number of layers. The default
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vertical discretization (:numref:`Table Soil layer structure`) uses
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:math:`N_{levgrnd} = 25` layers, of which :math:`N_{levsoi} = 20` are hydrologically and
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biogeochemically active. The deepest 5 layers are only included in the thermodynamical
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calculations (:ref:`Lawrence et al. 2008 <Lawrenceetal2008>`) described in Chapter
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:numref:`rst_Soil and Snow Temperatures`.
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The layer structure of the soil is described by the node depth, :math:`z_{i}`
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(m), the thickness of each layer, :math:`\Delta z_{i}` (m), and the depths
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at the layer interfaces :math:`z_{h,\, i}` (m).
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.. _Table Soil layer structure:
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.. table:: Soil layer structure
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+---------------+------------------+------------------------+------------------------+
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| Layer | :math:`z_{i}` | :math:`\Delta z_{i}` | :math:`z_{h,\, i}` |
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+===============+==================+========================+========================+
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| 1 | 0.010 | 0.020 | 0.020 |
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+---------------+------------------+------------------------+------------------------+
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| 2 | 0.040 | 0.040 | 0.060 |
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+---------------+------------------+------------------------+------------------------+
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| 3 | 0.090 | 0.060 | 0.120 |
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+---------------+------------------+------------------------+------------------------+
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| 4 | 0.160 | 0.080 | 0.200 |
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+---------------+------------------+------------------------+------------------------+
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| 5 | 0.260 | 0.120 | 0.320 |
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+---------------+------------------+------------------------+------------------------+
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| 6 | 0.400 | 0.160 | 0.480 |
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+---------------+------------------+------------------------+------------------------+
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| 7 | 0.580 | 0.200 | 0.680 |
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+---------------+------------------+------------------------+------------------------+
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| 8 | 0.800 | 0.240 | 0.920 |
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+---------------+------------------+------------------------+------------------------+
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| 9 | 1.060 | 0.280 | 1.200 |
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+---------------+------------------+------------------------+------------------------+
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| 10 | 1.360 | 0.320 | 1.520 |
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+---------------+------------------+------------------------+------------------------+
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| 11 | 1.700 | 0.360 | 1.880 |
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+---------------+------------------+------------------------+------------------------+
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| 12 | 2.080 | 0.400 | 2.280 |
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+---------------+------------------+------------------------+------------------------+
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| 13 | 2.500 | 0.440 | 2.720 |
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+---------------+------------------+------------------------+------------------------+
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| 14 | 2.990 | 0.540 | 3.260 |
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+---------------+------------------+------------------------+------------------------+
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| 15 | 3.580 | 0.640 | 3.900 |
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+---------------+------------------+------------------------+------------------------+
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| 16 | 4.270 | 0.740 | 4.640 |
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+---------------+------------------+------------------------+------------------------+
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| 17 | 5.060 | 0.840 | 5.480 |
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+---------------+------------------+------------------------+------------------------+
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| 18 | 5.950 | 0.940 | 6.420 |
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+---------------+------------------+------------------------+------------------------+
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| 19 | 6.940 | 1.040 | 7.460 |
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+---------------+------------------+------------------------+------------------------+
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| 20 | 8.030 | 1.140 | 8.600 |
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+---------------+------------------+------------------------+------------------------+
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| 21 | 9.795 | 2.390 | 10.990 |
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+---------------+------------------+------------------------+------------------------+
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| 22 | 13.328 | 4.676 | 15.666 |
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+---------------+------------------+------------------------+------------------------+
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| 23 | 19.483 | 7.635 | 23.301 |
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+---------------+------------------+------------------------+------------------------+
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| 24 | 28.871 | 11.140 | 34.441 |
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+---------------+------------------+------------------------+------------------------+
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| 25 | 41.998 | 15.115 | 49.556 |
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+---------------+------------------+------------------------+------------------------+
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Layer node depth (:math:`z_{i}` ), thickness (:math:`\Delta z_{i}` ), and depth at
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layer interface (:math:`z_{h,\, i}` ) for default soil column. All in meters.
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.. _Depth to Bedrock:
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Depth to Bedrock
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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The hydrologically and biogeochemically active portion of the soil column can be
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restricted to a thickness less than that of the maximum soil depth. By providing
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a depth-to-bedrock dataset, which may vary spatially, the number of layers used
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in the hydrologic and biogeochemical calculations, :math:`N_{bedrock}`, may be
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specified, subject to the constraint :math:`N_{bedrock} \le N_{levsoi}`.
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The default depth-to-bedrock values are from
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:ref:`Pelletier et al. [2016]<Pelletieretal2016>`.
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.. _Model Input Requirements:
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Model Input Requirements
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----------------------------
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.. _Atmospheric Coupling:
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Atmospheric Coupling
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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The current state of the atmosphere (:numref:`Table Atmospheric input to land model`)
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at a given time step is
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used to force the land model. This atmospheric state is provided by an
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atmospheric model in coupled mode or from an observed dataset in land-only
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mode (Chapter :numref:`rst_Land-Only Mode`). The land model then initiates a full set of
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calculations for surface energy, constituent, momentum, and radiative
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fluxes. The land model calculations are implemented in two steps. The
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land model proceeds with the calculation of surface energy, constituent,
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momentum, and radiative fluxes using the snow and soil hydrologic states
|
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from the previous time step. The land model then updates the soil and
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snow hydrology calculations based on these fluxes. These fields are
|
||
passed to the atmosphere (:numref:`Table Land model output to atmospheric model`). The albedos sent to the atmosphere
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||
are for the solar zenith angle at the next time step but with surface
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conditions from the current time step.
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.. _Table Atmospheric input to land model:
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.. table:: Atmospheric input to land model
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Field | variable name | units |
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+======================================================+================================================+=================================================+
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| :sup:`1`\ Reference height | :math:`z'_{atm}` | m |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Atmosphere model's surface height | :math:`z_{surf,atm}` | m |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Zonal wind at :math:`z_{atm}` | :math:`u_{atm}` | m s\ :sup:`-1` |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Meridional wind at :math:`z_{atm}` | :math:`v_{atm}` | m s\ :sup:`-1` |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Potential temperature | :math:`\overline{\theta _{atm} }` | K |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Specific humidity at :math:`z_{atm}` | :math:`q_{atm}` | kg kg\ :sup:`-1` |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Pressure at :math:`z_{atm}` | :math:`P_{atm}` | Pa |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Temperature at :math:`z_{atm}` | :math:`T_{atm}` | K |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
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| Incident longwave radiation | :math:`L_{atm} \, \downarrow` | W m\ :sup:`-2` |
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+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| :sup:`2`\ Liquid precipitation | :math:`q_{rain}` | mm s\ :sup:`-1` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| :sup:`2`\ Solid precipitation | :math:`q_{sno}` | mm s\ :sup:`-1` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| Incident direct beam visible solar radiation | :math:`S_{atm} \, \downarrow _{vis}^{\mu }` | W m\ :sup:`-2` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| Incident direct beam near-infrared solar radiation | :math:`S_{atm} \, \downarrow _{nir}^{\mu }` | W m\ :sup:`-2` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| Incident diffuse visible solar radiation | :math:`S_{atm} \, \downarrow _{vis}` | W m\ :sup:`-2` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| Incident diffuse near-infrared solar radiation | :math:`S_{atm} \, \downarrow _{nir}` | W m\ :sup:`-2` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| Carbon dioxide (CO\ :sub:`2`) concentration | :math:`c_{a}` | ppmv |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| :sup:`3`\ Aerosol deposition rate | :math:`D_{sp}` | kg m\ :sup:`-2` s\ :sup:`-1` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| :sup:`4`\ Nitrogen deposition rate | :math:`NF_{ndep\_ s{\it min}n}` | g (N) m\ :sup:`-2` yr\ :sup:`-1` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
| :sup:`5`\ Lightning frequency | :math:`I_{l}` | flash km\ :sup:`-2` hr\ :sup:`-1` |
|
||
+------------------------------------------------------+------------------------------------------------+-------------------------------------------------+
|
||
|
||
:sup:`1`\ The atmospheric reference height received from the
|
||
atmospheric model :math:`z'_{atm}` is assumed to be the height above
|
||
the surface as defined by the roughness length :math:`z_{0}` plus
|
||
displacement height :math:`d`. Thus, the reference height used for flux
|
||
computations (Chapter :numref:`rst_Momentum, Sensible Heat, and Latent Heat Fluxes`)
|
||
is :math:`z_{atm} =z'_{atm} +z_{0} +d`. The
|
||
reference heights for temperature, wind, and specific humidity
|
||
(:math:`z_{atm,\, h}` , :math:`z_{atm,\, {\it m}}` ,
|
||
:math:`z_{atm,\, w}` ) are required. These are set equal
|
||
to\ :math:`z_{atm}` .
|
||
|
||
:sup:`2`\ CAM provides convective and large-scale liquid
|
||
and solid precipitation, which are added to yield total liquid
|
||
precipitation :math:`q_{rain}` and solid precipitation
|
||
:math:`q_{sno}` .
|
||
However, in CLM5, the atmosphere's partitioning into liquid and solid
|
||
precipitation is ignored. Instead, CLM repartitions total precipitation
|
||
using a linear ramp. For most landunits, this ramp generates all snow
|
||
below :math:`0 ^{\circ} C`, all rain above :math:`2 ^{\circ} C`,
|
||
and a mix of rain and snow for intermediate temperatures. For glaciers,
|
||
the end points of the ramp are :math:`-2 ^{\circ} C` and :math:`0
|
||
^{\circ} C`, respectively. Changes to the phase of precipitation are
|
||
accompanied by a sensible heat flux (positive or negative) to conserve
|
||
energy.
|
||
|
||
:sup:`3`\ There are 14 aerosol deposition rates required depending
|
||
on species and affinity for bonding with water; 8 of these are dust
|
||
deposition rates (dry and wet rates for 4 dust size bins,
|
||
:math:`D_{dst,\, dry1} ,\, D_{dst,\, dry2} ,\, D_{dst,\, dry3} ,\, D_{dst,\, dry4}` ,
|
||
:math:`D_{dst,\, \, wet1} ,D_{dst,\, wet2} ,\, D_{dst,wet3} ,\, D_{dst,\, wet4}` ),
|
||
3 are black carbon deposition rates (dry and wet hydrophilic and dry
|
||
hydrophobic rates,
|
||
:math:`D_{bc,\, dryhphil} ,\, D_{bc,\, wethphil} ,\, D_{bc,\, dryhphob}` ),
|
||
and 3 are organic carbon deposition rates (dry and wet hydrophilic and
|
||
dry hydrophobic rates,
|
||
:math:`D_{oc,\, dryhphil} ,\, D_{oc,\, wethphil} ,\, D_{oc,\, dryhphob}` ).
|
||
These fluxes are computed interactively by the atmospheric model (when
|
||
prognostic aerosol representation is active) or are prescribed from a
|
||
time-varying (annual cycle or transient), globally-gridded deposition
|
||
file defined in the namelist (see the CLM4.5 User’s Guide). Aerosol
|
||
deposition rates were calculated in a transient 1850-2009 CAM simulation
|
||
(at a resolution of 1.9x2.5x26L) with interactive chemistry (troposphere
|
||
and stratosphere) driven by CCSM3 20\ :sup:`th` century
|
||
sea-surface temperatures and emissions (:ref:`Lamarque et al. 2010<Lamarqueetal2010>`) for
|
||
short-lived gases and aerosols; observed concentrations were specified
|
||
for methane, N\ :sub:`2`\ O, the ozone-depleting substances (CFCs)
|
||
,and CO\ :sub:`2`. The fluxes are used by the snow-related
|
||
parameterizations (Chapters :numref:`rst_Surface Albedos` and :numref:`rst_Snow Hydrology`).
|
||
|
||
:sup:`4`\ The nitrogen deposition rate is required by the
|
||
biogeochemistry model when active and represents the total deposition of
|
||
mineral nitrogen onto the land surface, combining deposition of
|
||
NO\ :sub:`y` and NH\ :sub:`x`. The rate is supplied either
|
||
as a time-invariant spatially-varying annual mean rate or time-varying
|
||
for a transient simulation. Nitrogen deposition rates were calculated
|
||
from the same CAM chemistry simulation that generated the aerosol
|
||
deposition rates.
|
||
|
||
:sup:`5`\ Climatological 3-hourly lightning frequency at
|
||
:math:`\sim`\ 1.8\ :sup:`o` resolution is provided, which was
|
||
calculated via bilinear interpolation from 1995-2011 NASA LIS/OTD grid
|
||
product v2.2 (http://ghrc.msfc.nasa.gov) 2-hourly, 2.5\ :sup:`o`
|
||
lightning frequency data. In future versions of the model, lightning
|
||
data may be obtained directly from the atmosphere model.
|
||
|
||
Density of air (:math:`\rho _{atm}` ) (kg m\ :sup:`-3`) is also
|
||
required but is calculated directly from
|
||
:math:`\rho _{atm} =\frac{P_{atm} -0.378e_{atm} }{R_{da} T_{atm} }`
|
||
where :math:`P_{atm}` is atmospheric pressure (Pa), :math:`e_{atm}` is
|
||
atmospheric vapor pressure (Pa), :math:`R_{da}` is the gas constant for
|
||
dry air (J kg\ :sup:`-1` K\ :sup:`-1`) (:numref:`Table Physical constants`), and
|
||
:math:`T_{atm}` is the atmospheric temperature (K). The atmospheric
|
||
vapor pressure :math:`e_{atm}` is derived from atmospheric specific
|
||
humidity :math:`q_{atm}` (kg kg\ :sup:`-1`) as
|
||
:math:`e_{atm} =\frac{q_{atm} P_{atm} }{0.622+0.378q_{atm} }` .
|
||
|
||
The O\ :sub:`2` partial pressure (Pa) is required but is
|
||
calculated from molar ratio and the atmospheric pressure
|
||
:math:`P_{atm}` as :math:`o_{i} =0.209P_{atm}` .
|
||
|
||
.. _Table Land model output to atmospheric model:
|
||
|
||
.. table:: Land model output to atmospheric model
|
||
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Field | Variable name | units |
|
||
+=======================================+================================================+==============================================================+
|
||
| :sup:`1`\ Latent heat flux | :math:`\lambda _{vap} E_{v} +\lambda E_{g}` | W m\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Sensible heat flux | :math:`H_{v} +H_{g}` | W m\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Water vapor flux | :math:`E_{v} +E_{g}` | mm s\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Zonal momentum flux | :math:`\tau _{x}` | kg m\ :sup:`-1` s\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Meridional momentum flux | :math:`\tau _{y}` | kg m\ :sup:`-1` s\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Emitted longwave radiation | :math:`L\, \uparrow` | W m\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Direct beam visible albedo | :math:`I\, \uparrow _{vis}^{\mu }` | - |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Direct beam near-infrared albedo | :math:`I\, \uparrow _{nir}^{\mu }` | - |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Diffuse visible albedo | :math:`I\, \uparrow _{vis}` | - |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Diffuse near-infrared albedo | :math:`I\, \uparrow _{nir}` | - |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Absorbed solar radiation | :math:`\vec{S}` | W m\ :sup:`-2` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Radiative temperature | :math:`T_{rad}` | K |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Temperature at 2 meter height | :math:`T_{2m}` | K |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Specific humidity at 2 meter height | :math:`q_{2m}` | kg kg\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Wind speed at 10 meter height | :math:`u_{10m}` | m s\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Snow water equivalent | :math:`W_{sno}` | m |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Aerodynamic resistance | :math:`r_{am}` | s m\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Friction velocity | :math:`u_{*}` | m s\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| :sup:`2`\ Dust flux | :math:`F_{j}` | kg m\ :sup:`-2` s\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
| Net ecosystem exchange | NEE | kgCO\ :sub:`2` m\ :sup:`-2` s\ :sup:`-1` |
|
||
+---------------------------------------+------------------------------------------------+--------------------------------------------------------------+
|
||
|
||
:sup:`1`\ :math:`\lambda _{vap}` is the latent heat of
|
||
vaporization (J kg\ :sup:`-1`) (:numref:`Table Physical constants`) and :math:`\lambda` is
|
||
either the latent heat of vaporization :math:`\lambda _{vap}` or latent
|
||
heat of sublimation :math:`\lambda _{sub}` (J kg\ :sup:`-1`)
|
||
(:numref:`Table Physical constants`) depending on the liquid water and ice content of the top
|
||
snow/soil layer (section 5.4).
|
||
|
||
:sup:`2`\ There are :math:`j=1,\ldots ,4` dust transport bins.
|
||
|
||
.. _Initialization:
|
||
|
||
Initialization
|
||
^^^^^^^^^^^^^^^^^^^^
|
||
|
||
Initialization of the land model (i.e., providing the model with initial
|
||
temperature and moisture states) depends on the type of run (startup or
|
||
restart) (see the CLM4.5 User’s Guide). A startup run starts the model
|
||
from either initial conditions that are set internally in the Fortran
|
||
code (referred to as arbitrary initial conditions) or from an initial
|
||
conditions dataset that enables the model to start from a spun up state
|
||
(i.e., where the land is in equilibrium with the simulated climate). In
|
||
restart runs, the model is continued from a previous simulation and
|
||
initialized from a restart file that ensures that the output is
|
||
bit-for-bit the same as if the previous simulation had not stopped. The
|
||
fields that are required from the restart or initial conditions files
|
||
can be obtained by examining the code. Arbitrary initial conditions are
|
||
specified as follows.
|
||
|
||
Soil points are initialized with
|
||
surface ground temperature :math:`T_{g}` and soil layer temperature
|
||
:math:`T_{i}` , for :math:`i=1,\ldots ,N_{levgrnd}` , of 274 K,
|
||
vegetation temperature :math:`T_{v}` of 283 K, no snow or canopy water
|
||
(:math:`W_{sno} =0`, :math:`W_{can} =0`), and volumetric soil water
|
||
content :math:`\theta _{i} =0.15` mm\ :sup:`3` mm\ :sup:`-3`
|
||
for layers :math:`i=1,\ldots ,N_{levsoi}` and :math:`\theta _{i} =0.0`
|
||
mm\ :sup:`3` mm\ :sup:`-3` for layers
|
||
:math:`i=N_{levsoi} +1,\ldots ,N_{levgrnd}` . placeLake temperatures
|
||
(:math:`T_{g}` and :math:`T_{i}` ) are initialized at 277 K and
|
||
:math:`W_{sno} =0`.
|
||
|
||
Glacier temperatures (:math:`T_{g} =T_{snl+1}` and :math:`T_{i}` for
|
||
:math:`i=snl+1,\ldots ,N_{levgrnd}` where :math:`snl` is the negative
|
||
of the number of snow layers, i.e., :math:`snl` ranges from –5 to 0) are
|
||
initialized to 250 K with a snow water equivalent :math:`W_{sno} =1000`
|
||
mm, snow depth :math:`z_{sno} =\frac{W_{sno} }{\rho _{sno} }` (m) where
|
||
:math:`\rho _{sno} =250` kg m\ :sup:`-3` is an initial estimate
|
||
for the bulk density of snow, and :math:`\theta _{i}` \ =1.0 for
|
||
:math:`i=1,\ldots ,N_{levgrnd}` . The snow layer structure (e.g., number
|
||
of snow layers :math:`snl` and layer thickness) is initialized based on
|
||
the snow depth (section 6.1). The snow liquid water and ice contents (kg
|
||
m\ :sup:`-2`) are initialized as :math:`w_{liq,\, i} =0` and
|
||
:math:`w_{ice,\, i} =\Delta z_{i} \rho _{sno}` , respectively, where
|
||
:math:`i=snl+1,\ldots ,0` are the snow layers, and :math:`\Delta z_{i}`
|
||
is the thickness of snow layer :math:`i` (m). The soil liquid water and
|
||
ice contents are initialized as :math:`w_{liq,\, i} =0` and
|
||
:math:`w_{ice,\, i} =\Delta z_{i} \rho _{ice} \theta _{i}` for
|
||
:math:`T_{i} \le T_{f}` , and
|
||
:math:`w_{liq,\, i} =\Delta z_{i} \rho _{liq} \theta _{i}` and
|
||
:math:`w_{ice,\, i} =0` for :math:`T_{i} >T_{f}` , where
|
||
:math:`\rho _{ice}` and :math:`\rho _{liq}` are the densities of ice
|
||
and liquid water (kg m\ :sup:`-3`) (:numref:`Table Physical constants`), and :math:`T_{f}`
|
||
is the freezing temperature of water (K) (:numref:`Table Physical constants`). All vegetated and
|
||
glacier land units are initialized with water stored in the unconfined
|
||
aquifer and unsaturated soil :math:`W_{a} =4000` mm and water table
|
||
depth :math:`z_{\nabla }` at five meters below the soil column.
|
||
|
||
.. _Surface Data:
|
||
|
||
Surface Data
|
||
^^^^^^^^^^^^^^^^^^
|
||
|
||
Required surface data for each land grid cell are listed in
|
||
:numref:`Table Surface data required for CLM and their base spatial resolution`
|
||
and include the glacier, lake, and urban fractions of the grid cell
|
||
(vegetated and crop occupy the remainder), the fractional cover of each
|
||
plant functional type (PFT), monthly leaf and stem area index and canopy
|
||
top and bottom heights for each PFT, soil color, soil texture, soil
|
||
organic matter density, maximum fractional saturated area, slope,
|
||
elevation, biogenic volatile organic compounds (BVOCs) emissions
|
||
factors, population density, gross domestic production, peat area
|
||
fraction, and peak month of agricultural burning. Optional surface data
|
||
include crop irrigation and managed crops. All fields are aggregated to
|
||
the model’s grid from high-resolution input datasets (
|
||
:numref:`Table Surface data required for CLM and their base spatial resolution`) that
|
||
are obtained from a variety of sources described below.
|
||
|
||
.. _Table Surface data required for CLM and their base spatial resolution:
|
||
|
||
.. table:: Surface data required for CLM and their base spatial resolution
|
||
|
||
+--------------------------------------------+---------------------------+
|
||
| Surface Field | Resolution |
|
||
+============================================+===========================+
|
||
| Percent glacier | 0.05\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Percent lake and lake depth | 0.05\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Percent urban | 0.05\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Percent plant functional types (PFTs) | 0.05\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Monthly leaf and stem area index | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Canopy height (top, bottom) | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Soil color | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Percent sand, percent clay | 0.083\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Soil organic matter density | 0.083\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Maximum fractional saturated area | 0.125\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Elevation | 1km |
|
||
+--------------------------------------------+---------------------------+
|
||
| Slope | 1km |
|
||
+--------------------------------------------+---------------------------+
|
||
| Biogenic Volatile Organic Compounds | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Crop Irrigation | 0.083\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Managed crops | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Population density | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Gross domestic production | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Peat area fraction | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
| Peak month of agricultural waste burning | 0.5\ :sup:`o` |
|
||
+--------------------------------------------+---------------------------+
|
||
|
||
At the base spatial resolution of 0.05\ :sup:`o`, the percentage of
|
||
each PFT is defined with respect to the vegetated portion of the grid
|
||
cell and the sum of the PFTs is 100%. The percent lake,
|
||
glacier, and urban at their base resolution are specified with respect
|
||
to the entire grid cell. The surface dataset creation routines re-adjust
|
||
the PFT percentages to ensure that the sum of all land cover types in
|
||
the grid cell sum to 100%. A minimum threshold of 0.1% of the grid cell
|
||
by area is required for urban areas.
|
||
|
||
The percentage glacier mask was derived from vector data of global
|
||
glacier and ice sheet spatial coverage. Vector data for glaciers (ice
|
||
caps, icefields and mountain glaciers) were taken from the first
|
||
globally complete glacier inventory, the Randolph Glacier Inventory
|
||
version 1.0 (RGIv1.0: :ref:`Arendt et al. 2012 <Arendtetal2012>`).
|
||
Vector data for the Greenland Ice Sheet were provided by Frank Paul and
|
||
Tobias Bolch (University of Zurich: :ref:`Rastner et al. 2012
|
||
<Rastneretal2012>`). Antarctic Ice Sheet data were provided by Andrew
|
||
Bliss (University of Alaska) and were extracted from the Scientific
|
||
Committee on Antarctic Research (SCAR) Antarctic Digital Database
|
||
version 5.0. Floating ice is only provided for the Antarctic and does
|
||
not include the small area of Arctic ice shelves. High spatial
|
||
resolution vector data were then processed to determine the area of
|
||
glacier, ice sheet and floating ice within 30-second grid cells
|
||
globally. The 30-second glacier, ice sheet and Antarctic ice shelf masks
|
||
were subsequently draped over equivalent-resolution GLOBE topography
|
||
(Global Land One-km Base Elevation Project, Hastings et al. 1999) to
|
||
extract approximate ice-covered elevations of ice-covered regions. Grid
|
||
cells flagged as land-ice in the mask but ocean in GLOBE (typically,
|
||
around ice sheets at high latitudes) were designated land-ice with an
|
||
elevation of 0 meters. Finally, the high-resolution mask/topography
|
||
datasets were aggregated and processed into three 3-minute datasets:
|
||
3-minute fractional areal land ice coverage (including both glaciers and
|
||
ice sheets); 3-minute distributions of areal glacier fractional coverage
|
||
by elevation and areal ice sheet fractional coverage by elevation. Ice
|
||
fractions were binned at 100 meter intervals, with bin edges defined
|
||
from 0 to 6000 meters (plus one top bin encompassing all remaining
|
||
high-elevation ice, primarily in the Himalaya). These distributions by
|
||
elevation are used to divide each glacier land unit into columns based
|
||
on elevation class.
|
||
|
||
When running with the CISM ice sheet model, CISM dictates glacier areas
|
||
and elevations in its domain, overriding the values specified by CLM's
|
||
datasets. In typical CLM5 configurations, this means that CISM dictates
|
||
glacier areas and elevations over Greenland.
|
||
|
||
Percent lake and lake depth are area-averaged from the 90-second
|
||
resolution data of :ref:`Kourzeneva (2009, 2010) <Kourzeneva2009>` to the 0.05\ :sup:`o`
|
||
resolution using the MODIS land-mask. Percent urban is derived from
|
||
LandScan 2004, a population density dataset derived from census data,
|
||
nighttime lights satellite observations, road proximity and slope
|
||
(:ref:`Dobson et al. 2000 <Dobsonetal2000>`) as described by
|
||
:ref:`Jackson et al. (2010) <Jacksonetal2010>` at 1km
|
||
resolution and aggregated to 0.05\ :sup:`o`. A number of urban
|
||
radiative, thermal, and morphological fields are also required and are
|
||
obtained from :ref:`Jackson et al. (2010) <Jacksonetal2010>`. Their description can be found in
|
||
Table 3 of the Community Land Model Urban (CLMU) technical note (:ref:`Oleson
|
||
et al. 2010b <Olesonetal2010b>`).
|
||
|
||
Percent PFTs are derived from MODIS satellite data as described in
|
||
:ref:`Lawrence and Chase (2007) <LawrenceChase2007>` (section 21.3.3).
|
||
Prescribed PFT leaf area index is derived from the MODIS satellite data of
|
||
:ref:`Myneni et al. (2002) <Mynenietal2002>` using the de-aggregation methods
|
||
described in :ref:`Lawrence and Chase (2007) <LawrenceChase2007>`
|
||
(section 2.2.3). Prescribed PFT stem area index is derived from PFT leaf
|
||
area index phenology combined with the methods of :ref:`Zeng et al. (2002) <Zengetal2002>`.
|
||
Prescribed canopy top and bottom heights are from :ref:`Bonan (1996) <Bonan1996>` as
|
||
described in :ref:`Bonan et al. (2002b) <Bonanetal2002b>`. If the biogeochemistry model is
|
||
active, it supplies the leaf and stem area index and canopy top and
|
||
bottom heights dynamically, and the prescribed values are ignored.
|
||
|
||
Soil color determines dry and saturated soil albedo (section :numref:`Ground Albedos`).
|
||
Soil colors are from :ref:`Lawrence and Chase (2007) <LawrenceChase2007>`.
|
||
|
||
The soil texture and organic matter content determine soil thermal and
|
||
hydrologic properties (sections 6.3 and 7.4.1). The International
|
||
Geosphere-Biosphere Programme (IGBP) soil dataset (Global Soil Data Task
|
||
2000) of 4931 soil mapping units and their sand and clay content for
|
||
each soil layer were used to create a mineral soil texture dataset
|
||
:ref:`(Bonan et al. 2002b) <Bonanetal2002b>`. Soil organic matter data is merged from two
|
||
sources. The majority of the globe is from ISRIC-WISE (:ref:`Batjes, 2006 <Batjes2006>`).
|
||
The high latitudes come from the 0.25\ :sup:`o` version of the
|
||
Northern Circumpolar Soil Carbon Database (:ref:`Hugelius et al. 2012 <Hugeliusetal2012>`). Both
|
||
datasets report carbon down to 1m depth. Carbon is partitioned across
|
||
the top seven CLM4 layers (:math:`\sim`\ 1m depth) as in
|
||
:ref:`Lawrence and Slater (2008) <LawrenceSlater2008>`.
|
||
|
||
The maximum fractional saturated area (:math:`f_{\max }` ) is used in
|
||
determining surface runoff and infiltration (section 7.3). Maximum
|
||
fractional saturated area at 0.125\ :sup:`o` resolution is
|
||
calculated from 1-km compound topographic indices (CTIs) based on the
|
||
USGS HYDRO1K dataset (:ref:`Verdin and Greenlee 1996 <VerdinGreenlee1996>`)
|
||
following the algorithm in :ref:`Niu et al. (2005) <Niuetal2005>`.
|
||
:math:`f_{\max }` is the ratio between the number
|
||
of 1-km pixels with CTIs equal to or larger than the mean CTI and the
|
||
total number of pixels in a 0.125\ :sup:`o` grid cell. See
|
||
section 7.3.1 and :ref:`Li et al. (2013b) <Lietal2013b>` for further details. Slope and
|
||
elevation are also obtained from the USGS HYDRO1K 1-km dataset
|
||
(:ref:`Verdin and Greenlee 1996 <VerdinGreenlee1996>`). Slope is used in the
|
||
surface water parameterization (section :numref:`Surface Water Storage`), and
|
||
elevation is used to calculate the grid cell standard deviation of
|
||
topography for the snow cover fraction parameterization (section :numref:`Snow Covered Area Fraction`).
|
||
|
||
Biogenic Volatile Organic Compounds emissions factors are from the Model
|
||
of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1;
|
||
:ref:`Guenther et al. 2012 <Guentheretal2012>`).
|
||
|
||
The default list of PFTs includes an unmanaged crop treated as a second
|
||
C3 grass (:numref:`Table Plant functional types`). The unmanaged crop has grid cell fractional cover
|
||
assigned from MODIS satellite data (:ref:`Lawrence and Chase (2007) <LawrenceChase2007>`). A managed
|
||
crop option uses grid cell fractional cover from the present-day crop
|
||
dataset of :ref:`Ramankutty and Foley (1998) <RamankuttyFoley1998>`
|
||
(CLM4CNcrop). Managed crops are assigned in the proportions given by
|
||
:ref:`Ramankutty and Foley (1998) <RamankuttyFoley1998>` without
|
||
exceeding the area previously assigned to the unmanaged crop. The
|
||
unmanaged crop continues to occupy any of its original area that remains
|
||
and continues to be handled just by the CN part of CLM4CNcrop. The
|
||
managed crop types (corn, soybean, and temperate cereals) were chosen
|
||
based on the availability of corresponding algorithms in AgroIBIS
|
||
(:ref:`Kucharik et al. 2000 <Kuchariketal2000>`;
|
||
:ref:`Kucharik and Brye 2003 <KucharikBrye2003>`). Temperate cereals
|
||
include wheat, barley, and rye here. All temperate cereals are treated
|
||
as summer crops (like spring wheat, for example) at this time. Winter
|
||
cereals (such as winter wheat) may be introduced in a future version of
|
||
the model.
|
||
|
||
To allow crops to coexist with natural vegetation in a grid cell and be
|
||
treated by separate models (i.e., CLM4.5BGCcrop versus the Dynamic
|
||
Vegetation version (CLM4.5BGCDV)), we separate the vegetated land unit
|
||
into a naturally vegetated land unit and a human managed land unit. PFTs
|
||
in the naturally vegetated land unit share one soil column and compete
|
||
for water (default CLM setting). PFTs in the human managed land unit do
|
||
not share soil columns and thus permit for differences in land
|
||
management between crops.
|
||
|
||
CLM includes the option to irrigate cropland areas that are equipped for
|
||
irrigation. The application of irrigation responds dynamically to climate
|
||
(see Chapter :numref:`rst_Crops and Irrigation`). In CLM, irrigation is
|
||
implemented for the C3 generic crop only. When irrigation is enabled, the
|
||
cropland area of each grid cell is divided into an irrigated and unirrigated
|
||
fraction according to a dataset of areas equipped for irrigation
|
||
(:ref:`Siebert et al. (2005) <Siebertetal2005>`). The area of irrigated
|
||
cropland in each grid cell is given by the
|
||
smaller of the grid cell’s total cropland area, according to the default
|
||
CLM4 dataset, and the grid cell’s area equipped for irrigation. The
|
||
remainder of the grid cell’s cropland area (if any) is then assigned to
|
||
unirrigated cropland. Irrigated and unirrigated crops are placed on
|
||
separate soil columns, so that irrigation is only applied to the soil
|
||
beneath irrigated crops.
|
||
|
||
Several input datasets are required for the fire model (:ref:`Li et al. 2013a <Lietal2013a>`)
|
||
including population density, gross domestic production, peat area
|
||
fraction, and peak month of agricultural waste burning. Population
|
||
density at 0.5\ :sup:`o` resolution for 1850-2100 combines 5-min
|
||
resolution decadal population density data for 1850–1980 from the
|
||
Database of the Global Environment version 3.1 (HYDEv3.1) with
|
||
0.5\ :sup:`o` resolution population density data for 1990, 1995,
|
||
2000, and 2005 from the Gridded Population of the World version 3
|
||
dataset (GPWv3) (CIESIN, 2005). Gross Domestic Production (GDP) per
|
||
capita in 2000 at 0.5\ :sup:`o` is from :ref:`Van Vuuren et al. (2006) <VanVuurenetal2006>`,
|
||
which is the base-year GDP data for IPCC-SRES and derived from
|
||
country-level World Bank’s World Development Indicators (WDI) measured
|
||
in constant 1995 US$ (:ref:`World Bank, 2004 <WorldBank2004>`) and the UN Statistics Database
|
||
(:ref:`UNSTAT, 2005 <UNSTAT2005>`). The peatland area fraction at 0.5\ :sup:`o`
|
||
resolution is derived from three vector datasets: peatland data in
|
||
Indonesia and Malaysian Borneo (:ref:`Olson et al. 2001 <Olsonetal2001>`); peatland data in
|
||
Canada (:ref:`Tarnocai et al. 2011 <Tarnocaietal2011>`); and bog, fen and mire data in boreal
|
||
regions (north of 45\ :sup:`o`\ N) outside Canada provided by the
|
||
Global Lakes and Wetlands Database (GLWD) (:ref:`Lehner and Döll, 2004 <LehnerDoll2004>`). The
|
||
climatological peak month for agricultural waste burning is from :ref:`van der
|
||
Werf et al. (2010) <vanderWerfetal2010>`.
|
||
|
||
.. _Adjustable Parameters and Physical Constants:
|
||
|
||
Adjustable Parameters and Physical Constants
|
||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||
|
||
Values of certain adjustable parameters inherent in the biogeophysical
|
||
or biogeochemical parameterizations have either been obtained from the
|
||
literature or calibrated based on comparisons with observations. These
|
||
are described in the text. Physical constants, generally shared by all
|
||
of the components in the coupled modeling system, are presented in
|
||
:numref:`Table Physical constants`.
|
||
|
||
|
||
.. _Table Physical constants:
|
||
|
||
.. csv-table:: Physical constants
|
||
:header: "description", "name", "value", "units"
|
||
:widths: 40, 20, 20, 20
|
||
|
||
"Pi", :math:`\pi`, 3.14159265358979323846, "\-"
|
||
"Acceleration of gravity", :math:`g`, 9.80616, m s\ :sup:`-2`
|
||
"Standard pressure", :math:`P_{std}`, 101325, "Pa"
|
||
"Stefan-Boltzmann constant", :math:`\sigma`, 5.67 :math:`\times 10^{-8}`, W m :sup:`-2` K :math:`{}^{-4}`
|
||
"Boltzmann constant", :math:`\kappa`, 1.38065 :math:`\times 10^{-23}`, J K :sup:`-1` molecule :sup:`-1`
|
||
"Avogadro’s number", :math:`N_{A}`, 6.02214 :math:`\times 10^{26}`, molecule kmol\ :sup:`-1`
|
||
"Universal gas constant", :math:`R_{gas}`, :math:`N_{A} \kappa`, J K :sup:`-1` kmol :sup:`-1`
|
||
"Molecular weight of dry air", :math:`MW_{da}`, 28.966, kg kmol :sup:`-1`
|
||
"Dry air gas constant", :math:`R_{da}`, :math:`{R_{gas} \mathord{\left/ {\vphantom {R_{gas} MW_{da} }} \right. \kern-\nulldelimiterspace} MW_{da} }`, J K :sup:`-1` kg :sup:`-1`
|
||
"Molecular weight of water vapor", :math:`MW_{wv}`, 18.016, kg kmol :sup:`-1`
|
||
"Water vapor gas constant", :math:`R_{wv}`, :math:`{R_{gas} \mathord{\left/ {\vphantom {R_{gas} MW_{wv} }} \right. \kern-\nulldelimiterspace} MW_{wv} }`, J K :sup:`-1` kg :sup:`-1`
|
||
"Von Karman constant", :math:`k`, 0.4, "\-"
|
||
"Freezing temperature of fresh water", :math:`T_{f}`, 273.15, K
|
||
"Density of liquid water", :math:`\rho _{liq}`, 1000, kg m :sup:`-3`
|
||
"Density of ice", :math:`\rho _{ice}`, 917, kg m :sup:`-3`
|
||
"Specific heat capacity of dry air", :math:`C_{p}`, 1.00464 :math:`\times 10^{3}`, J kg :sup:`-1` K :sup:`-1`
|
||
"Specific heat capacity of water", :math:`C_{liq}`, 4.188 :math:`\times 10^{3}`, J kg :sup:`-1` K :sup:`-1`
|
||
"Specific heat capacity of ice", :math:`C_{ice}`, 2.11727 :math:`\times 10^{3}`, J kg :sup:`-1` K :sup:`-1`
|
||
"Latent heat of vaporization", :math:`\lambda _{vap}`, 2.501 :math:`\times 10^{6}`, J kg :sup:`-1`
|
||
"Latent heat of fusion", :math:`L_{f}`, 3.337 :math:`\times 10^{5}`, J kg :sup:`-1`
|
||
"Latent heat of sublimation", :math:`\lambda _{sub}`, :math:`\lambda _{vap} +L_{f}`, J kg :sup:`-1`
|
||
:sup:`1` "Thermal conductivity of water", :math:`\lambda _{liq}`, 0.57, W m :sup:`-1` K :sup:`-1`
|
||
:sup:`1` "Thermal conductivity of ice", :math:`\lambda _{ice}`, 2.29, W m :sup:`-1` K :sup:`-1`
|
||
:sup:`1` "Thermal conductivity of air", :math:`\lambda _{air}`, 0.023 W m :sup:`-1` K :sup:`-1`
|
||
"Radius of the earth", :math:`R_{e}`, 6.37122, :math:`\times 10^{6}` m
|
||
|
||
:sup:`1`\ Not shared by other components of the coupled modeling system.
|
||
|