Land Surface Modeling

Helin Wei

Acknowledge: Mike Ek provides most of slides here

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• Role of Land Surface Models (LSMs)• Requirements and Noah LSM - atmospheric forcing, valid physics, land data

sets/parameters, initial land states, cycled land states

- Noah LSM• Recent upgrades of Noah in the NCEP GFS • Validation• Future upgrade

Outline

• Traditionally, from a coupled (atmosphere-ocean-land-ice) Numerical Weather Prediction (NWP) and climate modeling perspective, a land-surface model provides quantities to a parent atmospheric model:- Surface sensible heat flux,- Surface latent heat flux (evapotranspiration)- Upward longwave radiation

(or skin temperature and surface emissivity),- Upward (reflected) shortwave radiation

(or surface albedo, including snow effects),- Surface momentum exchange.

Role of Land Models

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…to close the surface energy budget, & provide surface boundary conditions to NWP and climate models.

seasonal storage

Atmospheric Energy Budget

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• Land models close the surface water budget, and provide surface boundary conditions to models.

Water Budget (Hydrological Cycle)

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LoCo: Local land-atmospheric modeling

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• NEAR-SURFACE LOCAL COUPLING METRIC: Evaporative fraction change with changing soil moisture for both bare soil & vegetated surface = function of near-surface turbulence, canopy control, soil hydraulics & soil thermodynamics,• Utilize GHP/CEOP reference site data sets (“clean” fluxnet),• Extend to coupling with atmos. boundary-layer and entrainment processes,• Link with approaches by Santanello et al.

From “GEWEX Imperatives: Plans for

2013 and Beyond”

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Betts et al(1996)

Diurnal time-scales

Seasonal

Century

Land-Atmosphere Interaction

History of Land Modeling (e.g. at NCEP)– 1960s (6-Layer PE model): land surface ignored• Aside from terrain height and surface friction effects– 1970s (LFM): land surface ignored– Late 1980s (NGM): first simple land model introduced (Tuccillo)• Single layer soil slab (“force-restore” model: Deardorff)• No explicit vegetation treatment• Temporally fixed surface wetness factor• Diurnal cycle is treated (as is PBL) with diurnal surface radiation• Surface albedo, skin temperature, surface energy balance• Snow cover (but not depth)– Early1990s (Global Model): OSU land model (Mahrt& Pan, 1984)• Multi-layer soil column (2-layers)• Explicit annual cycle of vegetation effects• Snow pack physics (snowdepth, SWE)– Mid-90s (Meso Model): OSU/Noah LSM replaces Force-Restore– Mid 2000s (Global Model): Noah replaces OSU (Ek et al 2003)– Mid 2000s (Meso Model: WRF): Unified Noah LSM with NCAR– 2000s-10s: Noah “MP” with explicit canopy, ground water,CO2

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• Role of Land Surface Models (LSMs)• Requirements and Noah LSM - atmospheric forcing, valid physics, land data

sets/parameters, initial land states, cycled land states

- Noah LSM• Recent upgrades of Noah in the NCEP GFS • Validation• Future upgrade

Outline

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• To provide proper boundary conditions, land model must have:- Necessary atmospheric forcing to drive the land

model,- Appropriate physics to represent land-surface

processes (for relevant time/spatial scales),- Corresponding land data sets and associated

parameters, e.g. land use/land cover (vegetation type), soil type, surface albedo, snow cover, surface roughness, etc., and

- Proper initial land states, analogous to initial atmospheric conditions, though land states may carry more “memory” (e.g. especially in deep soil moisture), similar to ocean SSTs.

Land Model Requirements

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Land modelingexample:

• Products and models are integrated & consistent throughout time & space, as well as across forecast application & domain.

Static vegetation, e.g. climatology

or realtime observations

Dynamic vegetation, e.g. plant

growth

Dynamic ecosystems,

e.g. changing land cover

Weather & Climate a “Seamless Suite”

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• To provide proper boundary conditions, land model must have:- Necessary atmospheric forcing to drive the land

model,- Appropriate physics to represent land-surface

processes (for relevant time/spatial scales),- Corresponding land data sets and associated

parameters, e.g. land use/land cover (vegetation type), soil type, surface albedo, snow cover, surface roughness, etc., and

- Proper initial land states, analogous to initial atmospheric conditions, though land states may carry more “memory” (e.g. especially in deep soil moisture), similar to ocean SSTs.

Land Model Requirements

• Four soil layers (10, 30, 60, 100 cm thick).

• Linearized (non-iterative) surface energy budget; numerically efficient.

• Soil hydraulics and parameters follow Cosby et al.

• Jarvis-Stewart “big-leaf” canopy cond.

• Direct soil evaporation.• Canopy interception.• Vegetation-reduced soil

thermal conductivity.• Patchy/fractional snow

cover effect on surface fluxes; coverage treated as function of snowdepth & veg type 13

Unified NCEP-NCAR Noah land model

• Freeze/thaw soil physics.• Snowpack density and snow water

equivalent.• Veg & soil classes parameters.

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Soil Moisture (Θ):• “Richard’s Equation”; DΘ (soil water diffusivity) and KΘ (hydraulic conductivity), are nonlinear functions of soil moisture and soil type (Cosby et al 1984); FΘ is a source/sink term for precipitation/evapotranspiration.Soil Temperature (T):• CT (thermal heat capacity) and KT (soil thermal conductivity; Johansen 1975), non-linear functions of soil/type; soil ice = fct(soil type/temp./moisture).

Canopy water (Cw):• P (precipitation) increases Cw, while Ec (canopy water evaporation) decreases Cw.

Prognostic Equations

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Surface Energy Budget

 

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Surface Water Budget

S = change in land-surface waterP = precipitationR = runoffE = evapotranspiration

P-R = infiltration of moisture into the soil• S includes changes in soil moisture, snowpack (cold season), and canopy water (dewfall/frostfall and intercepted precipitation, which are small).• Evapotranspiration is a function of surface, soil and vegetation characteristics: canopy water, snow cover/ depth, vegetation type/cover/density & rooting depth/ density, soil type, soil water & ice, surface roughness.• Noah model provides: S, R and E.

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Potential Evaporation

= slope of saturation vapor pressure curveRn-G = available energy

= air densitycp = specific heatCh = surface-layer turbulent exchange coefficientU = wind speede = atmos. vapor pressure deficit (humidity) = psychrometric constant, fct(pressure)

open water surface

(Penman)

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Surface Latent Heat Flux

• LEc is a function of canopy water % saturation.• LEt uses Jarvis (1976)-Stewart (1988) “big-leaf”

canopy conductance.• LEd is a function of near-surface soil % saturation.• LEc, LEt, and LEd are all a function of LEp.

soil

canopycanopy water

Transpiration(LEt)

Canopy WaterEvap. (LEc)

Bare SoilEvaporation (LEd)

(Evapotranspiration)

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Surface Latent Heat Flux (cont.)Canopy Water Evaporation (LEc):• Cw, Cs are canopy water & canopy water saturation, respectively, a function of veg. type; nc is a coeff.Transpiration (LEt):

• gc is canopy conductance, gcmax is maximum canopy conductance and gS, gT, ge, gΘ are solar, air temperature, humidity, and soil moisture availability factors, respectively, all functions of vegetation type.Bare Soil Evaporation (LEd):• Θd, Θs are dry (minimum) & saturated soil moisture contents, =fct(soil type); nd is a coefficient (nom.=2).

max s

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Latent Heat Flux over SnowLE (shallow snow) LE (deep snow)<

• LEns = “non-snow” evaporation (evapotranspiration terms).• 100% snowcover a function of vegetation type, i.e. shallower for grass & crops, deeper for forests.

soil

snowpack

Shallow/Patchy SnowSnowcover<1

Deep snowSnowcover=1

LEsnow = LEp

LEsnow = LEp

LEns = 0

Sublimation (LEsnow)

LEns < LEp

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Surface Sensible Heat Flux

, cp = air density, specific heatCh = surface-layer turbulent exchange coeff.U = wind speed

Tsfc-Tair = surface-air temperature difference• “effective” Tsfc for canopy, bare soil, snowpack.

soil

canopy snowpackbare soil

(from canopy/soilsnowpack surface)

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Ground Heat Flux

KT = soil thermal conductivity (function of soil type: larger for moister soil, larger for clay soil; reduced through canopy, reduced through snowpack)z = upper soil layer thicknessTsfc-Tsoil = surface-upper soil layer temp. difference

• “effective” Tsfc for canopy, bare soil, snowpack.

soil

canopy snowpackbare soil

(to canopy/soil/snowpack surface)

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Land Data Sets (e.g. GFS/CFS, GLDAS)

Soil Type(1-deg, Zobler)

Vegetation Type(1-deg, SIB)

Green Vegetation Fraction (monthly, 1/8-deg,

NESDIS/AVHRR)

Max.-Snow Albedo(1-deg, Robinson)

Snow-Free Albedo(seasonal, 1-deg,

Matthews)

July JulyJan Jan

NEMS/GFS Modeling Summer School 24

1: broadleaf-evergreen trees 2: broadleaf-deciduous trees 3: broadleaf and needleleaf trees4: needleleaf-evergreen trees 5: needleleaf-deciduous trees (larch) 6: broadleaf trees with groundcover 7: groundcover only (perennial) 8: broadleaf shrubs with perennial groundcover 9: broadleaf shrubs with bare soil 10: dwarf trees and shrubs with groundcover (tundra) 11: bare soil 12: cultivations (the same parameters as for type 7) 13: glacial ice

13-type SIB used in the OPS GFS (global 1-degree)

NEMS/GFS Modeling Summer School 25

9-type Zolber used in the OPS GFS (global 1-degree)

1: loamy sand 2: silty clay loam 3: light clay 4: sandy loam 5: sandy clay 6: clay loam7: sandy clay loam 8: loam 9: loamy sand

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Land surface model physics parameters (examples)

• Surface momentum roughness dependent on vegetation/land-use type.

• Stomatal control dependent on vegetation type, direct effect on transpiration.

• Depth of snow (snow water equivalent, or s.w.e.) for deep snow and assumption of maximum snow albedo is a function of vegetation type.

• Heat transfer through vegetation and into the soil a function of green vegetation fraction (coverage) and leaf area index (density).

• Soil thermal and hydraulic processes highly dependent on soil type (vary by orders of magnitude).

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• Valid land state initial conditions are necessary for NWP and climate models, & must be consistent with the land model used in a given weather or climate model, i.e. from same cycling land model.

• Land states spun up in a given NWP or climate model cannot be used directly to initialize another model without a rescaling procedure because of differing land model soil moisture climatologies.

May Soil Moisture Climatology from 30-year

NCEP Climate Forecast System Reanalysis (CFSR),

spun up from Noah land model coupled with CFS.

Initial Land States

Initial Land States (cont.)

Air Force Weather Agency snow cover & depth

• In addition to soil moisture: the land model provides surface skin temperature, soil temperature, soil ice, canopy water, and snow depth & snow water equivalent.

National Ice Center snow cover

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Initial Land States (cont.)• In seasonal (and longer) climate simulations,

land states are “cycled” so that there is an evolution in land states in response to atmospheric forcing and land model physics.

• Land data set quantities may be observed and/or simulated, e.g. green vegetation fraction & leaf area index, and even land-use type (evolving ecosystems).

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Uncoupled“NLDAS”(drought)

Air Quality

WRF NMM/ARWWorkstation WRF

WRF: ARW, NMMETA, RSM

Satellites99.9%

Regional NAMWRF NMM

(including NARR)

Hurricane GFDLHWRF

GlobalForecastSystem

Dispersion

ARL/HYSPLIT

Forecast

Severe Weather

Rapid Updatefor Aviation (ARW-based)

ClimateCFS

1.7B Obs/Day

Short-RangeEnsemble Forecast

Noah Land Model Connections in NOAA’s NWS Model Production Suite

MOM42-Way Coupled Oceans

HYCOM

WaveWatch III

NAM/CMAQ

Regional DataAssimilation

Global DataAssimilation

North American Ensemble Forecast System

GFS, Canadian Global Model

NOAH Land Surface Model

NCEP-NCAR unified

GLDAS

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• Surface energy (linearized) & water budgets; 4 soil layers.• Forcing: downward radiation, precip., temp., humidity, pressure, wind.• Land states: Tsfc, Tsoil*, soil water* and soil ice*, canopy water*, snow depth/density*. *prognostic• Land data sets: green vegetation frac., veg. type, soil type, snow-free albedo & maximum snow albedo.

NCEP-NCAR unified Noah land model

• Noah coupled with NCEP models: North American Mesoscale model (NAM; short-range), Global Forecast System (GFS; medium-range), Climate Forecast System (CFS; seasonal), and uncoupled NCEP modeling systems, i.e. NLDAS & GLDAS.

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• Role of Land Surface Models (LSMs)• Requirements and Noah LSM - atmospheric forcing, valid physics, land data

sets/parameters, initial land states, cycled land states

- Noah LSM• Recent upgrades of Noah in the NCEP GFS

• Validation• Future upgrade

Outline

GFS : Land Model UpgradeNoah LSM (new) versus OSU LSM (old):

• Noah LSM (vegetation, snow, ice)– 4 soil layers (10, 30, 60, 100 cm)– Frozen soil physics included– Add glacial ice treatment– Two snowpack states (SWE, density)– Surface fluxes weighted by snow cover fraction– Improved seasonal cycle of vegetation– Spatially varying root depth– Runoff and infiltration account for sub-grid

variability in precipitation & soil moisture– Improved thermal conduction in soil/snow– Higher canopy resistance– Improved evaporation treatment over bare

soil and snowpack

• OSU LSM– 2 soil layers (10, 190 cm)– No frozen soil physics– Only one snowpack state (SWE)– Surface fluxes not weighted by

snow fraction– Vegetation fraction never less than

50 percent– Spatially constant root depth– Runoff & infiltration do not account

for subgrid variability of precipitation & soil moisture

– Poor soil and snow thermal conductivity, especially for thin snowpack

Noah LSM replaced OSU LSM in operational NCEP medium-rangeGlobal Forecast System (GFS) in late May 2005

Pre-May 05 GFS: with OSU LSM

Post-May 05 GFS: with new Noah LSM

Mean GFS surface latent heat flux: 09-25 May 2005:Upgrade to Noah LSM significantly reduced the GFS surface latent heat flux

(especially in non-arid regions)

May 2011, the new thermal roughness scheme was implemented to deal with the daytime cold skin temp bias over semi-arid region during the warm season

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• Role of Land Surface Models (LSMs)• Requirements and Noah LSM - atmospheric forcing, valid physics, land data

sets/parameters, initial land states, cycled land states

- Noah LSM• Recent upgrades of Noah in the NCEP GFS • Validation• Future upgrade

Outline

grid2obs for 2m-T Rh, and 10-m wind from Fanglin Yanghttp://www.emc.ncep.noaa.gov/gmb/STATS_vsdb/g2o

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2m-T Rh, and 10-m wind comparisons between GFS and NAM

http://www.emc.ncep.noaa.gov/mmb/research/nearsfc/nearsfc.verf.html

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April, 2013Red: OBS Blue: GFS Green: NAM

SURFX (Surface Flux) NetworkNOAA/ATDD, Tilden Meyers et al

Compare monthly diurnal composites of modeloutput versus observations from flux sites to

assess systematic model biases. From Mike EK

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January

Ft. Peck,Montana

(grassland)

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Ft. Peck,Montana

(grassland) July

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SURFACE ENERGY BUDGET TERMS

January 2008monthly averages:

model vs obs

Ft. Peck, Montana(grassland)

Downward Solar

Downward LongwaveReflected Solar

Upward Longwave

Ground Heat FluxLatent Heat FluxSensible Heat Flux 43

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• Role of Land Surface Models (LSMs)• Requirements and Noah LSM - atmospheric forcing, valid physics, land data

sets/parameters, initial land states, cycled land states

- Noah LSM• Recent upgrades of Noah in the NCEP GFS • Validation• Future upgrade

Outline

Future improvements

More land surface data assimilation (soil moisture, snow, etc)

Replace land surface characteristic data by more recent and high-resolution one

Physics upgrades : -Noah MP: urbanization, dynamic vegetation, ground water, carbon cycle, multi-layer snow model)

-River routing

NEMS/GFS Modeling Summer School 45

1: broadleaf-evergreen trees!2: broadleaf-deciduous trees 3: broadleaf and needleleaf trees!4: needleleaf-evergreen trees5: needleleaf-deciduous trees (larch) 6: broadleaf trees with groundcover 7: groundcover only (perennial) 8: broadleaf shrubs with perennial groundcover 9: broadleaf shrubs with bare soil 10: dwarf trees and shrubs with groundcover (tundra) 11: bare soil 12: cultivations (the same parameters as for type 7) 13: glacial ice

13-type SIB used in the OPS GFS (global 1-degree)

20-type IGBP used in the test (global 1-km)1:Evergreen Needleleaf Forest2:Evergreen Broadleaf Forest3:Deciduous Needleleaf Forest4:Deciduous Broadleaf Forest5:Mixed Forests6:Closed Shrublands7:Open Shrublands8:Woody Savannas9:Savannas10:Grasslands11:Permanent wetlands12:Croplands13:Urban and Built-Up14:Cropland/natural vegetation mosaic15:Snow and Ice16:Barren or Sparsely Vegetated17:Water18:Wooded Tundra19:Mixed Tundra20:Bare Ground Tundra

1 loamy sand 2 silty clay loam 3 light clay 4 sandy loam 5 sandy clay 6 clay loam7 sandy clay loam 8 loam 9 loamy sand

9-type Zolber used in the OPS GFS (global 1-degree)

19-type STASGO used in the test (global 1-km)1: sand2: loamy sand3: sandy loam4: silt loam5: silt6:loam7:sandy clay loam8:silty clay loam9:clay loam10:sandy clay11: silty clay12: clay13: organic material14: water15: bedrock16: other (land-ice)17: playa18: lava19: white sand