Surface energy balance evaluators#

Evaluators used to solve the fluxes to and from the atmosphere and between layers of the surface. Typically in ATS these calculate evapotranspiration.

Area Fractions#

Frequently, the surface of a grid cell is split across at least two “subgrid components,” for instance snow covered and bare ground. This “subgrid” model allows smooth transitions between fully snow-covered and fully bare ground.

These area fractions often get included as area-weights in calculating full-cell quantities.

Two-component model#

A subgrid model for determining the area fraction of snow vs not snow within a grid cell.

Uses a simple linear transition to vary between liquid and bare ground, and another linear transition to vary between snow-covered and not-snow-covered.

Ordering of the area fractions calculated are: [bare ground/water, snow].

“evaluator type” = “area fractions, two components”

area-fractions-twocomponent-evaluator-spec:

“minimum fractional area [-]” [double] 1.e-5
Mimimum area fraction allowed, less than this is rebalanced as zero.

DEPENDENCIES:

“snow depth” [string]

Three-component model#

A subgrid model for determining the area fraction of land, water, and snow within a grid cell.

Uses a simple linear transition to vary between liquid and bare ground, and another linear transition to vary between snow-covered and not-snow-covered.

Ordering of the area fractions calculated are: [bare ground, water, snow].

“evaluator type” = “area fractions, three components”

area-fractions-threecomponent-evaluator-spec:

“minimum fractional area [-]” [double] 1.e-5
Mimimum area fraction allowed, less than this is rebalanced as zero.

DEPENDENCIES:

“snow depth” DOMAIN_SNOW-depth
“ponded depth” DOMAIN-ponded_depth

Three-component model, with microtopography#

A subgrid model for determining the area fraction of land, open water, and snow within a grid cell.

Uses the subgrid equation from Jan et al WRR 2018 for volumetric or effective ponded depth to determine the area of water, then heuristically places snow on top of that surface.

“evaluator type” = “area fractions, three components with microtopography”

area-fractions-threecomponent-microtopography-evaluator-spec

“snow transitional height [m]” [double] 0.02 Minimum thickness for specifying the snow gradient.
“minimum fractional area [-]” [double] 1.e-5 Mimimum area fraction allowed, less than this is rebalanced as zero.
“snow domain name” [string] DOMAIN_SNOW A default is guessed at by replacing “surface” with “snow” in the this’s domain.

KEYS:

“microtopographic relief” DOMAIN-microtopographic_relief The name of del_max, the max microtopography value.
“excluded volume” DOMAIN-excluded_volume The name of del_excluded, the integral of the microtopography.
“ponded depth” DOMAIN-pressure The name of the surface water ponded depth.
“snow depth” DOMAIN_SNOW-depth The name of the snow depth.
“volumetric snow depth” DOMAIN_SNOW-volumetric_depth The name of the snow depth.

NOTE: this evaluator simplifies the situation by assuming constant density. This make it so that ice and water see the same geometry per unit pressure, which isn’t quite true thanks to density differences. However, we hypothesize that these differences, on the surface (unlike in the subsurface) really don’t matter much. –etc

Potential Evapotranspiration#

Models of potential evapotranspiration approximate the difference in vapor pressure between the atmosphere and the soil as a function of available energy, allowing the calculation of the max flux of ET that the atmosphere could accept. This can then be limited based on water availability, etc.

Priestley-Taylor Potential Evapotranspiration#

Evaluates potential evapotranpiration (PET) using Priestley & Taylor formulation.

This implementation is based on models provided in the PRMS-IV, Version 4, see pages 90-93, Equations 1-57 to 1-60

Requires the following dependencies:

pet-priestley-taylor-evaluator-spec:

“include limiter” [bool] false If true, multiply potential ET by a limiter to get an actual ET.
“limiter number of dofs” [int] 1 Area fractions are often used as limiters, and these have multiple dofs. This provides how many.
“limiter dof” [int] 0 Area fractions are often used as limiters, and these have multiple dofs. This provides which one to use.
“include 1 - limiter” [bool] false If true, multiply potential ET by 1 - a limiter (e.g. a limiter that partitions between two pools) to get actual ET.
“1 - limiter number of dofs” [int] 1 Area fractions are often used as limiters, and these have multiple dofs. This provides how many.
“1 - limiter dof” [int] 0 Area fractions are often used as limiters, and these have multiple dofs. This provides which one to use.
“sublimate snow” [bool] false If true, use latent heat of
vaporization of snow, not water.

KEYS:

“air temperature” DOMAIN-air_temperature Air temp, in [K]
“surface temperature” DOMAIN-temperature Ground or leaf temp, in [K]. Note this may be the
same as air temperature.
“elevation” DOMAIN-elevation Elevation [m]
“net radiation” DOMAIN-net_radiation [W m^-2] Net radiation balance, positive to the ground.
“limiter” [-] See “include limiter” above.
“1 - limiter” [-] See “include 1 - limiter” above.

Downregulation and limiters#

Given a potential, the actual ET is often limited by available water (or nutrients or other quantities). These evaluators are used to limit, downregulate, distribute, or otherwise move a potential to an actual ET.

Transpiration Distribution#

Distributes and downregulates potential transpiration to the rooting zone.

The transpiration distribution evaluator looks to take a potential evapotranspiration and distribute it across the vertical column based on water availability and rooting depths. It also potentially limits the transpiration to avoid taking water where it is not available (thereby crashing the code).

This model is based off of versions from both CLM 4.5 and PRMS. It requires:

A root distribution profile.
A plant wilting factor (e.g. how water stressed is the plant?)
A potential transpiration, typically calculated from data or a potential difference based on a latent heat calculation.

Note this also requires columnar meshes – meaning that the subsurface mesh must have “build columns from set” provided.

A normalized fraction of water is calculated through multiplying the water factor by the root distribution factor, integrating across the column, and dividing by the integral. This gives a factor which sums to 1 and can be used to distribute the potential ET throughout the soil column.

Then, this potential ET is down-regulated and multiplied by the plant wilting factor. If there is no water locally, it cannot be taken. Note that almost always, if there is no water, this did not contribute (much) to the integral and so is already small. But if the entire root zone is dried out, this might have been a bunch of small numbers which then got normalized to 1, meaning they are all now significant.

Finally, transpiration may be turned off for winter – relative to time zero, parameters “leaf on doy” and “leaf off doy” are used to control when ET is zero. By default these are set to 0 and 366 days, ensuring that transpiration is never turned off and the potential ET must include this factor. This is the right choice for, e.g. ELM output, or eddy covariance flux tower data (where leaf on and off are already included in the potential calculation). It is the wrong choice for, e.g. Priestly-Taylor or Penmann-Montief models, which are happy to predict transpiration all winter long. Good choices for those models depend upon the local climate, but may be something like Julian day 101 for leaf on and Julian day 254 for leaf off (PRMS defaults for US temperate forests).

Note that “leaf on doy” and “leaf off doy” are relative to the simulation’s zero time, not the start time. Typically these are Julian day of the year, but this assumes that the 0 time of the simulation (not the “start time”, but time 0!) is Jan 1. This leaf on/off cycle is modulo the “year duration” (typically 1 noleap). Note if “leaf off doy” < “leaf on time” is ok too – this is the case if simulation time zero is mid-summer. These parameters come from the LandCover type.

transpiration-distribution-evaluator-spec * “year duration” [double] 1 * “year duration units” [string] noleap

“water limiter function” [function-spec] optional If provided, limit the total water sink as a function of the integral of the water potential * rooting fraction.

KEYS:

“plant wilting factor” DOMAIN-plant_wilting_factor
“rooting depth fraction” DOMAIN-rooting_depth_fraction
“potential transpiration” DOMAIN_SURF-potential_transpiration
“cell volume” DOMAIN-cell_volume
“surface cell volume” DOMAIN_SURF-cell_volume

Rooting Depth Fraction#

Provides a depth-based profile of root density.

Sets the (discrete) root fraction as a function of depth. The rooting density is given by:

This function is such that the integral over depth = [0,inf) is 1. Then, computing this over the vertical corridor is done by integrating this function between the depth of the face above and below for each grid cell, with the bottom-most grid cell integrating to infinity.

Note that the two parameters, \(\alpha\) and \(\beta\) are provided in the Land Cover class as “rooting profile alpha” and “rooting profile beta” respectively.

rooting-depth-fraction-evaluator-spec

“surface domain name” [string] SURFACE_DOMAIN Sane default provided for most domain names.

KEYS:

“cell volume” DOMAIN-cell_volume
“surface area” SURFACE_DOMAIN-cell_volume

Plant Wilting Point#

Plant wilting factor provides a moisture availability-based limiter on transpiration.

Also known as Beta, or the water availability factor, or the plant wilting factor, or the transpiration reduction function.

\[Beta = (p_closed - p) / (p_closed - p_open)\]

where p is the capillary pressure or water potential, and closed and open indicate the values at which stomates are fully open or fully closed (the wilting point).

Note this makes use of LandCover objects for water potential of fully open and fully closed stomata.

Note the challenges of using this model with arbitrary van Genuchten WRMs. See Verhoef & Egea, Ag. & Forest Meteorology, 2014 https://doi.org/10.1016/j.agrformet.2014.02.009

plant-wilting-factor-evaluator-spec

KEYS:

“capillary pressure” DOMAIN-capillary_pressure_gas_liq

Soil Resistance#

Downregulates evaporation through a dessicated zone via soil resistance. Currently support two soil resistance methods: Sakagucki-Zeng and Sellers. This will call soil resistance evaluator.

Radiation Balance Terms#

Often a balance of incoming and outgoing short and longwave radiations are required to determine the energy available to go into latent heat, and therefore potential evapotranspiration.

Note that incoming shortwave radiation is typically a user-provided meterological forcing dataset.

Radiation Balance#

Evaluates a net radiation balance for ground and canopy.

Here the net radiation is positive for energy inputs to the layer. Note that ground is based on the two-channel (land + snow) while canopy is assumed to be a simple, single layer.

This evaluator requires that the surface temperature, snow temperature, and canopy temperature are known, or at least being solved for.

Requires the use of LandCover types, for albedo and Beer’s law coefficients.

This is combination of CLM v4.5 Tech Note and Beer’s law for attenuation of radiation absorption. In particular, long-wave is exactly as Figure 4.1c in CLM 4.5 Tech Note. The main difference comes in how absorptivity (which is equal to emissivity, epsilon in that document) is defined. Here we use Beer’s law which is an exponential decay with LAI.

Unlike CLM 4.5, here we do not split shortwave into direct and diffuse light.

Computes:

“surface radiation balance” – Net radiation seen by the bare soil/ponded water, this includes radiation transmitted to the surface through the canopy, longwave emitted by the canopy, and less the longwave emitted by the surface itself. [W m^-2] of actual area – this does NOT include the surface area fraction factor which would be required to compute a total energy flux in W.
“snow radiation balance” – Net radiation seen by the snow. See surface above – all are the same except using snow properties. [W m^-2]
“canopy radiation balance” – this is a compute computation of the net radiation experienced by the canopy. It includes the portion of shortwave and longwave from the atmosphere that are absorbed via Beer’s law, minus the outgoing longwave emitted from the canopy, plus upward longwave radiation emitted by the snow and surface. It also does not include any secondary bounces (e.g. reflected atmosphere->canopy->cloud->back to canopy, or transmitted by the canopy, reflected by snow/surface.

Requires the use of LandCover types, for canopy albedo and Beer’s law coefficients.

“evaluator type” = “radiation balance, surface and canopy”

radiation-balance-evaluator-spec

KEYS: - “surface albedos” SURFACE_DOMAIN-albedos - “surface emissivities” SURFACE_DOMAIN-emissivities - “incoming shortwave radiation” SURFACE_DOMAIN-incoming_shortwave_radiation - “incoming longwave radiation” SURFACE_DOMAIN-incoming_longwave_radiation - “surface temperature” SURFACE_DOMAIN-temperature - “snow temperature” SNOW_DOMAIN-temperature - “canopy temperature” CANOPY_DOMAIN-temperature - “leaf area index” CANOPY_DOMAIN-leaf_area_index - “area fractions” SURFACE_DOMAIN-area_fractions

Note that this is a superset of the physics in the “canopy radiation evaluator,” and is therefore mutually exclusive with that model.

Canopy Radiation Balance#

Evaluates the canopy radiation balance, providing canopy net and radiation to the snow/surface.

Computes and sums the downward radiation terms, determining the total radiation sent down to the surface from the canopy and above.

Requires the use of LandCover types, for albedo and emissivity of the canopy itself, along with Beer’s law coefficients.

Computes:

canopy-downward_shortwave_radiation – transmitted shortwave. Note that incoming shortwave is attenuated by Beer’s law, and partially transmitted without attenuation when there are gaps (e.g. LAI < 1) in the canopy.
canopy-downward_longwave_radiation – transmitted longwave (see above, noting that Beer’s law coefficients should be used that absorb most if not all the longwave radiation), along with longwave emitted by the canopy computed using a canopy leaf temperature and a Bolzmann equation.
canopy-downward_net_radiation – this is a partial computation of the net radiation experienced by the canopy. It includes the portion of shortwave and longwave from the atmosphere that are absorbed via Beer’s law, minus the outgoing longwave emitted from the canopy (see downward above). It does NOT include upward longwave radiation emitted by the snow or surface. It also does not include any secondary bounces (e.g. reflected atmosphere->canopy->cloud->back to canopy, or transmitted by the canopy, reflected by snow).

Here the net radiation is positive for energy added to the canopy, while the other two are positive for energy sent to the layer below.

In the canopy-downward_net_radiation, we cannot include the upward terms YET, because these are a function of snow and surface temperature, which in turn depend upon the downward radiation computed here. So we choose to break the loop here, by computing downard terms first, then iterating to compute snow temperature, then compute upward terms. The alternative would be to have a formal snow energy PK that computed snow temperature, at which point we would solve all of these balances to convergence simultaneously.

“evaluator type” = “canopy radiation balance from above”

canopy-radiation-evaluator-spec

KEYS: - “incoming shortwave radiation” SURFACE_DOMAIN-incoming_shortwave_radiation - “incoming longwave radiation” SURFACE_DOMAIN-incoming_longwave_radiation - “canopy temperature” CANOPY_DOMAIN-temperature - “leaf area index” CANOPY_DOMAIN-leaf_area_index

Note that this is a subset of the physics in the “radiation balance evaluator,” and is therefore mutually exclusive with that model.

Surface Albedo#

Note that albedo is also a multiple subgrid component model, like surface balance.

Evaluates albedos and emissivities in a two-component subgrid model.

Evaluates the albedo and emissivity as an interpolation on the surface properties and cover. This allows for two components – snow and not snow (water/ice/land). Note this internally calculates albedo of snow based upon snow density.

Components are indexed by: 0 = land/ice/water, 1 = snow.

Requires the use of LandCover types, for ground albedo and emissivity.

albedo-evaluator-spec

“albedo ice [-]” [double] 0.44

“albedo water [-]” [double] 0.1168

“emissivity ice [-]” [double] 0.98

“emissivity water [-]” [double] 0.995

“emissivity snow [-]” [double] 0.98

KEYS:

“subgrid albedos” DOMAIN-subgrid_albedos

“subgrid emissivities” DOMAIN-subgrid_emissivities

DEPENDENCIES:

“snow density” SNOW_DOMAIN-density

“ponded depth” DOMAIN-ponded_depth

“unfrozen fraction” DOMAIN-unfrozen_fraction

Evaluates albedos and emissivities in a three-component subgrid model.

Evaluates the albedo and emissivity as an interpolation on the surface properties and cover. This allows for three components – water/ice, land, and snow. Note this internally calculates albedo of snow based upon snow density.

Components are: 0 = land, 1 = ice/water, 2 = snow.

Requires the use of LandCover types, for ground albedo and emissivity.

albedo-evaluator-subgrid-spec

“albedo ice [-]” [double] 0.44
“albedo water [-]” [double] 0.1168
“emissivity ice [-]” [double] 0.98
“emissivity water [-]” [double] 0.995
“emissivity snow [-]” [double] 0.98

KEYS:

“subgrid albedos” DOMAIN-subgrid_albedos
“subgrid emissivities” DOMAIN-subgrid_emissivities

DEPENDENCIES:

“snow density” SNOW_DOMAIN-density
“unfrozen fraction” DOMAIN-unfrozen_fraction

Incident Shortwave Radiation#

Evaluates the radiation incident on a non-flat surface.

Aspect modified shortwave radiation is determined by a factor which is multiplied by the ‘incoming radiation incident on a flat surface’ to determine the ‘incoming radiation incident on a sloping surface of a given aspect’ as a function of slope and aspect, Julian day of the year, and time of day. The latitude and Julian day of the year are used to modify this with both time of day and seasonal changes of the planet.

Note that some careful checking and experimentation has found that, in general, the daily average incoming radiation times the 12-noon aspect modifier correlates reasonably well with the daily average of the product of the hourly incoming radiation and the hourly aspect modifier. It is notably better than the daily average radiation times the daily average aspect modifier.

This implementation is derived from LandLab code, which is released under the MIT license.

incident_shortwave_radiation_evaluator-spec

“incident shortwave radiation parameters” [incident_shortwave_radiation_model-spec]

KEYS: - “slope” DOMAIN-slope_magnitude - “aspect” DOMAIN-aspect - “incoming shortwave radiation” DOMAIN-incoming_shortwave_radiation

Evaluates shortwave as a function of slope/aspect/etc.

incident_shortwave_radiation_model-spec

“latitude [degrees]” [double] Latitude of the site. A single typical value is fine for most domains, even relatively large ones (e.g. HUC4).
“daily averaged” [bool] true Compute a daily averaged radiation, as opposed to a time-specific, diurnal-cycle-resolving value.
“day of year at time 0 [Julian days]” [int] 0 (Jan 1). ATS has no notion of absolute time, so to do things that depend upon planetary dynamics we must know what the day of the year is. Typically this is set by your meteorological data – set this to be equal to the day of year of met data’s time 0.

Longwave Radiation#

Evaluates incoming longwave radiation from vapor pressure and air temperature.

longwave_evaluator-spec

DEPENDENCIES:

“air temperature key” [string] DOMAIN-air_temperature
“vapor pressure air key” [string] DOMAIN-vapor_pressure_air

Full Surface Energy Balance Models#

Finally, in addition to the potential-based models above, a few full-physics model are available. These are often based on older, monolithic models.

Bare Soil Surface Energy Balance#

Calculates source terms for surface fluxes to and from the atmosphere and a ground surface.

The ground is assumed to consist of two potential area-fraction components – snow and no-snow. In the case of snow on the ground, this solves for a snow temperature, given a skin temperature, that satisfies a energy balance equation. In the case of no-snow, this calculates a conductive heat flux to the ground from the atmosphere.

“evaluator type” = “surface energy balance, two components”

seb-twocomponent-evaluator-spec

“wind speed reference height [m]” [double] 2.0 Reference height at which wind speed is measured.
“minimum wind speed [m s^-1]” [double] 1.0 Sets a floor on wind speed for potential wierd data. Models have trouble with no wind.
“save diagnostic data” [bool] false Saves a suite of diagnostic variables to vis.
“surface domain name” [string] DEFAULT Default set by parameterlist name.
“subsurface domain name” [string] DEFAULT Default set relative to surface domain name.
“snow domain name” [string] DEFAULT Default set relative to surface domain name.

KEYS:

“surface water source” DOMAIN-water_source [m s^-1]
“surface energy source” DOMAIN-total_energy_source [MW m^-2]
“subsurface water source” DOMAIN-water_source [mol s^-1]
“subsurface energy source” DOMAIN-total_energy_source [MW m^-3]
“snow mass source - sink” DOMAIN-source_sink [m_SWE s^-1]
“new snow source” DOMAIN-source [m_SWE s^-1]
“albedo” DOMAIN-albedo [-] A single variate diagnostic of the final albedo.
“snowmelt” DOMAIN_SNOW-melt [m_SWE s^-1]
“evaporation” DOMAIN-evaporative_flux [m s^-1]
“snow temperature” DOMAIN_SNOW-temperature [K]
“sensible heat flux” DOMAIN-qE_sensible_heat [W m^-2]
“latent heat of evaporation” DOMAIN-qE_latent_heat [W m^-2]
“latent heat of snowmelt” DOMAIN-qE_snowmelt [W m^-2]
“outgoing longwave radiation” DOMAIN-qE_lw_out [W m^-2]
“conducted energy flux” DOMAIN-qE_conducted [W m^-2]

DEPENDENCIES:

“incoming shortwave radiation” DOMAIN-incoming_shortwave_radiation [W m^-2]
“incoming longwave radiation” DOMAIN-incoming_longwave_radiation [W m^-2]
“air temperature” DOMAIN-air_temperature [K]
“vapor pressure air” DOMAIN-vapor_pressure_air [Pa]
“wind speed” DOMAIN-wind_speed [m s^-1]
“precipitation rain” DOMAIN-precipitation_rain [m s^-1]
“precipitation snow” DOMAIN_SNOW-precipitation [m_SWE s^-1]
“snow depth” DOMAIN_SNOW-depth [m]
“snow density” DOMAIN_SNOW-density [kg m^-3]
“snow death rate” DOMAIN_SNOW-death_rate [m s^-1] Snow “death” refers to the last bit of snowmelt that we want to remove discretely.
“ponded depth” DOMAIN-ponded_depth [m]
“unfrozen fraction” DOMAIN-unfrozen_fraction [-] 1 –> all surface water, 0 –> all surface ice
“subgrid albedos” DOMAIN-albedos [-] Dimension 2 field of (no-snow, snow) albedos.
“subgrid emissivity” DOMAIN-emissivities [-] Dimension 2 field of (no-snow, snow) emissivities.
“area fractions” DOMAIN-fractional_areas Dimension 2 field of (no-snow, snow) area fractions (sum to 1).
“temperature” DOMAIN-temperature [K] surface skin temperature.
“pressure” DOMAIN-pressure [Pa] surface skin pressure.
“rsoil” DOMAIN-rsoil [s/m] soil resistance of top cells.
“subsurface pressure” DOMAIN_SS-pressure [Pa]
“molar density liquid” DOMAIN-molar_density_liquid [mol m^-3]
“mass density liquid” DOMAIN-mass_density_liquid [kg m^-3]

Calculates source terms for surface fluxes to and from the atmosphere and a ground surface characterized by three components – snow, water-covered ground, and vegetated/bare soil.

The surface energy balance on these area weighted patches are individually calculated then averaged to form the total quantities. All down- and up-scaling of relevant quantities are done through the area weighting, which is calculated by a minimum threshold in snow and a depression depth/geometry-based approach for water. All snow is assumed to first cover water (likely ice), then cover land, as both water and snow prefer low-lying depressions due to gravity- and wind-driven redistributions, respectively.

“evaluator type” = “surface energy balance, two components”

seb-threecomponent-evaluator-spec

“wind speed reference height [m]” [double] 2.0 Reference height at which wind speed is measured.
“minimum wind speed [m s^-1]” [double] 1.0 Sets a floor on wind speed for potential wierd data. Models have trouble with no wind.
“save diagnostic data” [bool] false Saves a suite of diagnostic variables to vis.
“surface domain name” [string] DEFAULT Default set by parameterlist name.
“subsurface domain name” [string] DEFAULT Default set relative to surface domain name.
“snow domain name” [string] DEFAULT Default set relative to surface domain name.

KEYS:

“surface water source” DOMAIN-water_source [m s^-1]
“surface energy source” DOMAIN-total_energy_source [MW m^-2]
“subsurface water source” DOMAIN-water_source [mol s^-1]
“subsurface energy source” DOMAIN-total_energy_source [MW m^-3]
“snow mass source - sink” DOMAIN-source_sink [m_SWE s^-1]
“new snow source” DOMAIN-source [m_SWE s^-1]
“albedo” DOMAIN-albedo [-] A single variate diagnostic of the final albedo.
“snowmelt” DOMAIN_SNOW-melt [m_SWE s^-1]
“evaporation” DOMAIN-evaporative_flux [m s^-1]
“snow temperature” DOMAIN_SNOW-temperature [K]
“sensible heat flux” DOMAIN-qE_sensible_heat [W m^-2]
“latent heat of evaporation” DOMAIN-qE_latent_heat [W m^-2]
“latent heat of snowmelt” DOMAIN-qE_snowmelt [W m^-2]
“outgoing longwave radiation” DOMAIN-qE_lw_out [W m^-2]
“conducted energy flux” DOMAIN-qE_conducted [W m^-2]

DEPENDENCIES:

“incoming shortwave radiation” DOMAIN-incoming_shortwave_radiation [W m^-2]
“incoming longwave radiation” DOMAIN-incoming_longwave_radiation [W m^-2]
“air temperature” DOMAIN-air_temperature [K]
“vapor pressure air” DOMAIN-vapor_pressure_air [Pa]
“wind speed” DOMAIN-wind_speed [m s^-1]
“precipitation rain” DOMAIN-precipitation_rain [m s^-1]
“precipitation snow” DOMAIN_SNOW-precipitation [m_SWE s^-1]
“snow depth” DOMAIN_SNOW-depth [m]
“snow density” DOMAIN_SNOW-density [kg m^-3]
“snow death rate” DOMAIN_SNOW-death_rate [m s^-1] Snow “death” refers to the last bit of snowmelt that we want to remove discretely.
“ponded depth” DOMAIN-ponded_depth [m]
“unfrozen fraction” DOMAIN-unfrozen_fraction [-] 1 –> all surface water, 0 –> all surface ice
“subgrid albedos” DOMAIN-albedos [-] Dimension 2 field of (no-snow, snow) albedos.
“subgrid emissivity” DOMAIN-emissivities [-] Dimension 2 field of (no-snow, snow) emissivities.
“area fractions” DOMAIN-fractional_areas Dimension 2 field of (no-snow, snow) area fractions (sum to 1).
“temperature” DOMAIN-temperature [K] surface skin temperature.
“pressure” DOMAIN-pressure [Pa] surface skin pressure.
“rsoil” DOMAIN-rsoil [s/m] soil resistance of top cells.
“subsurface pressure” DOMAIN_SS-pressure [Pa]
“molar density liquid” DOMAIN-molar_density_liquid [mol m^-3]
“mass density liquid” DOMAIN-mass_density_liquid [kg m^-3]