Implementation of Noah land surface model advances in the
National Centers for Environmental Prediction operational
日夜操劳mesoscale Eta model
M.B.Ek,1K.E.Mitchell,1Y.Lin,1E.Rogers,1P.Grunmann,1V.Koren,2G.Gayno,3
and J.D.Tarpley4
Received6December2002;revid1August2003;accepted6October2003;published29November2003.
[1]We prent the impact tests that preceded the most recent operational upgrades to the
land surface model ud in the National Centers for Environmental Prediction(NCEP)
mesoscale Eta model,who operational domain includes North America.The
improvements consist of changes to the‘‘Noah’’land surface model(LSM)physics,most
notable in the area of cold ason process.Results indicate improved performance in
forecasting low-level temperature and humidity,with improvements to(or without
affecting)the overall performance of the Eta model quantitative precipitation scores and
upper air verification statistics.Remaining issues that directly affect the Noah LSM
performance in the Eta model include physical parameterizations of radiation and clouds,
which affect the amount of available energy at the surface,and stable boundary layer and
surface layer process,which affect surface turbulent heat fluxes and ultimately the
surface energy budget.I NDEX T ERMS:3322Meteorology and Atmospheric Dynamics:Land/
atmosphere interactions;3329Meteorology and Atmospheric Dynamics:Mesoscale meteorology;
K EYWORDS:coupled modeling,Eta model,land surface model
主持人台词大全
Citation:Ek,M.B.,K.E.Mitchell,Y.Lin,E.Rogers,P.Grunmann,V.Koren,G.Gayno,and J.D.Tarpley,Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model,J.Geophys. Res.,108(D22),8851,doi:10.
1029/2002JD003296,2003.
1.Introduction
[2]During the past two decades,a number of advances in land surface models(LSMs)have been made in simulating surface energy and water fluxes and the surface energy and water budgets in respon to near-surface atmospheric forcing.The companion evolution of soil moisture,soil temperature,and snowpack are important to the surface energy and water budgets on ,daily)to ,asonal to annual)timescales,and they in turn depend on surface conditions(such as vegetation state and soil texture).Increasingly then,the parameterizations of land surface process have become more physically bad becau of heightened multidisciplinary cooperation and incread knowledge in the fields of meteorology,hydrol-ogy,and plant and soil physics.
[3]Surface fluxes provide the necessary lower boundary conditions for numerical weather prediction(NWP)and climate models.The weather and climate models are computationally intensive and as such the LSMs utilized must be efficient in their reprentation of land surface process.At the ont of the1990s,the National Centers for Environmental Prediction(NCEP)started
testing the efficient LSM developed for u in NWP at Oregon State University(OSU)beginning in the middle1980s[Mahrt and Pan,1984;Pan and Mahrt,1987].The original OSU LSM consisted of two soil layers with thermal conduction equations for soil temperature and a form of Richardson’s equation for soil moisture.The effect of stomatal control by plants was reprented via a constant‘‘plant coefficient’’(fractional,0to1)to account for atmospheric influences, multiplied by the soil moisture availability(fractional,0to1) to account for the soil moisture influence,finally multiplied by the potential evaporation[Mahrt and Ek,1984].Later,a variable plant coefficient that accounted for stomatal control was related to a canopy conductance formulation using the common‘‘big leaf’’approach[Jarvis,1976;Noilhan and Planton,1989],reported by Holtslag and Ek [1996],where canopy conductance is modeled as a function of soil moisture availability and atmospheric conditions (solar insolation,temperature,and humidity).
[4]During the1990s,NCEP greatly expanded its land surface modeling collaborations via veral components of the Global Energy and Water Cycle Experiment(GEWEX), most notably,the GEWEX Continental-Scale International Project(GCIP)and the Project for Intercomparison of Land-
JOURNAL OF GEOPHYSICAL RESEARCH,VOL.108,NO.D22,8851,doi:10.1029/2002JD003296,2003 1Environmental Modeling Ce
nter,National Centers for Environmental
Prediction,Suitland,Maryland,USA.
2Office of Hydrologic Development,National Weather Service,Silver
Spring,Maryland,USA.
3Air Force Weather Agency,Offutt Air Force Ba,Nebraska,USA.
4Office of Rearch and Applications,National Environmental Satellite
Data and Information Service,Suitland,Maryland,USA.
Copyright2003by the American Geophysical Union.
0148-0227/03/2002JD003296$09.00
GCP12-1
surface Parameterization Schemes(PILPS).The collabo-rations included the Office of Hydrological
Development (OHD)of the National Weather Service,National Environ-mental Satellite Data and Information Service(NESDIS), NASA,National Center for Atmospheric Rearch (NCAR),the U.S.Air Force,and OSU and other university partners.As an outgrowth of the collaborations and their broad scope of LSM testing in both uncoupled and coupled mode over a wide range of space scales and timescales(e citations below),NCEP substantially enhanced the OSU LSM,now renamed the Noah LSM in recognition of the broad partnership above.
[5]The mesoscale model forecast suite at NCEP is the Eta model[Janjic´,1990,1994;Black,1994;Mesinger, 2000]and its Eta Data Assimilation System(EDAS) [Rogers et al.,1996],now run operationally at12-km resolution with60layers.NCEP generally first implements the Noah LSM enhancements in the Eta-EDAS suite, followed later by implementation in the NCEP Global Forecast System(GFS).Before introducing the latest Noah LSM enhancements and tests that are the subject of this paper,we first briefly review the highlights of the earlier Noah LSM upgrades that have taken place in the Eta-EDAS suite at NCEP over the past ven years.The included an increa from two to four soil layers,modifications to the canopy conductance formulation[Chen et al.,1996],bare soil evaporation and vegetation phenology[Betts et al., 1997],surface runoff and infiltration[Schaake et al., 1996],and thermal roughness length treatment in the surface layer exchan
ge coefficients[F.Chen et al.,1997].A key companion advance was the implementation of fully con-tinuous lf-cycling of soil moisture and temperature in the EDAS(without soil moisture nudging)in June1998.Since then the Eta model initial soil moisture and temperature are sole products of the EDAS(namely,the coupled Noah-Eta model and the land surface forcing internal to the EDAS) without undue drift in soil moisture and temperatures. [6]The above forerunner Noah LSM advances have yielded improved model performance,both in an offline mode(that is,atmospheric-forced LSM-only runs for spe-cific sites or in two-dimensional horizontal land surface domains),as well as coupled in the fully three-dimensional operational mesoscale Eta analysis and forecast system. Offline testing of the Noah LSM has involved veral PILPS and related or similar ,Chen et al., 1996;T.H.Chen et al.,1997;Qu et al.,1998;Wood et al., 1998;Chen and Mitchell,1999;Koren et al.,1999; Schlosr et al.,2000;Slater et al.,2001;Boone et al., 2001;Bowling et al.,2003].Coupled evaluation has addresd performance of the Noah LSM in an NWP tting with focus on land surface process from local to conti-nental ,Berbery et al.,1996,1999,2003;F.Chen et al.,1997;Betts et al.,1997;Yucel et al.,1998;Hinkelman et al.,1999;Angevine and Mitchell,2001;Berbery,2001; Marshall et al.,2003].
[7]Given the significant role GCIP has played in sup-porting land surface model development at NCE
P,it is appropriate to review the Noah LSM in this special GCIP issue.In describing the various model advances and when they occurred(e Table1),this paper reviews upgrades to the physical parameterizations and land surface fields ud in and by the Noah LSM along with the companion impact tests in the coupled Noah/Eta-EDAS suite,for the cold ason(ction2)and the warm ason(ction3).This latest pha of Noah LSM advances described here embodies a‘‘generational’’Noah LSM upgrade including
Table1.Timeline of Noah Land Surface Model(LSM)Evolution,With References to Relevant Model Physics and/or Land Surface Fields Implemented in the NCEP Operational Mesoscale Eta Model
Date Description Reference(s)
Original OSU LSM(Prior to NCEP Era)
potential evaporation Mahrt and Ek[1984]
surface fluxes,soil hydraulics,Mahrt and Pan[1984]
and soil thermodynamics and Pan and Mahrt[1987]
Noah LSM Implementation in Eta Model at NCEP
UCAV31Jan.1996OSU LSM introduced into Eta model Chen et al.[1996]
(GFS initial soil moisture and temperature)
surface runoff and infiltration Schaake et al.[1996] 24July1996ISLSCP vegetation greenness changes
18Feb.1997NESDIS vegetation greenness Gutman and Ignatov[1998]
随手笔记bare soil evaporation changes Betts et al.[1997]a
snow melt changes Betts et al.[1997]a
thermal roughness length changes F.Chen et al.[1997]a 9Feb.1998increa from2to4soil layers
3June1998lf-cycling Eta-EDAS soil moisture and temp.
NESDIS daily snow cover and a ice analysis Ramsay[1998]
Noah LSM Upgrades(With Asssment in Eta Model)Described in This Study
石膏线电视墙21July2001frozen soil physics Koren et al.[1999]
snowpack physics upgrade Koren et al.[1999]
maximum snow albedo climatology Robinson and Kukla[1985]
shallow snow thermal conductivity Lunardini[1981]
bare soil evaporation refinement
bare soil thermal conductivity changes Peters-Lidard et al.[1998]
vegetation-reduced soil thermal conductivity Peters-Lidard et al.[1997]
transpiration refinements
26Feb.2002patchy shallow snow thermal conductivity
a Assd in an Eta model study.
GCP12-2EK ET AL.:UPGRADED NOAH LAND SURFACE MODEL
the addition of frozen soil physics and major advances in snowpack-related physics[Koren et al.,199
9],significant improvements to bare soil evaporation,soil heat flux enhancements for bare soil,snow-covered and vegetated conditions,and some modest changes to canopy conduc-tance.The Noah LSM upgrades address Eta model forecast bias in near-surface air temperature and relative humidity thought to be due in part to deficiencies in Noah LSM physics evident in uncoupled testing(described above).
[8]This paper prents the follow-on testing to confirm in coupled mode the improvement anticipated from our uncoupled(offline)testing.The model testing and asss-ment includes regional verification of realtime parallel executions in winter,early spring,and summer,as well as individual ca studies(under conditions of minimal large-scale forcing)in order to demonstrate model bias reduc-tions.The most recent Noah LSM upgrades were tested in the NCEP mesoscale Eta model and then implemented in the Eta-EDAS suite operationally in July2001,with an additional change in February2002.We summarize our findings and suggest further Noah LSM improvements and future direction in ction4.
2.Cold Season Process
[9]Cold ason process are important in the evolution of the land surface for a large fraction of the
earth during many cold ason months.In the prence of snow cover, albedo increas,surface roughness is often reduced,and
the exchange of heat and moisture between land surface and atmosphere is diminished,while subsurface freezing reduces the movement of heat and moisture within the soil. All of the process affect the surface energy budget and thus the surface fluxes,so it is necessary to include the effects in LSMs ud in weather and climate models.The process are included in the Noah LSM upgrades demon-strated herein,as well as other land surface , Viterbo et al.,1999;Smirnova et al.,2000;Boone et al., 2000;Boone and Etchevers,2001].The improvements to the Noah LSM in the area of cold ason process were first made and tested in an offline mode by Koren et al. [1999]and during the PILPS2d exerci[Schlosr et al., 2000;Slater et al.,2001],and then in a coupled mode within the NCEP mesoscale Eta model as prented here.
2.1.Patchy Snow Cover and Frozen Soil
[10]The cold ason process that have been added or improved are described by Koren et al.[1999]and include the effect of latent heat relea during soil water freezing in winter,which ameliorates the typical underestimation(when frozen soil process are ignored)of soil temperature(
and thus surface and air temperatures)during soil freezing periods,and overestimation of temperatures during thawing periods.The frozen soil moisture content depends on the soil temperature,volumetric soil moisture,and character-istics dependent on soil texture.Additionally,a treatment of patchy(fractional)snow cover is introduced,which allows the surface temperature to exceed freezing.The previous formulation in the Noah LSM ud all incoming energy to melt and sublimate the snowpack(which was considered uniform across a gridbox)until complete ablation.This bounded the surface skin temperature at0°C(in the solution of the single surface energy budget),resulting in the daytime low-level air temperature holding near freezing. The new Noah LSM formulation allows for patchy snow cover if the snow depth is below some threshold,and hence allows expod ground,a lower albedo,more energy absorption,and the aggregate(gridbox)surface skin tem-perature(still corresponding to a single surface energy budget)to ri above0°C.As such the surface nsible heat flux increas with a corresponding increa in low-level air temperature.The subgrid patchiness is related to the depth of the snow and surface characteristics;for example,for a‘‘smoother’’surface such as a grassland,a smaller snow depth threshold is required for100%snow cover compared to a forest(Figure1).
[11]Moreover,the evolution of the snowpack density is added as a new snowpack state,and is govern
ed via a time-dependent snow compaction algorithm,which includes the effect of new snowfall.Previously the snow depth was assumed to have a‘‘typical’’5:1ratio,usually too low for new snowfall,but perhaps too high for an older snowpack. The snow density then affects the thermal conductivity through snow(previously assumed to be constant),which is important in determining the exchange of heat between the land surface and atmosphere.Also,in the prence of frozen soil moisture,the moisture ,of snowmelt water and precipitation)is reduced.The param-eterizations have been adopted in the current version of the Noah LSM with some modifications;for example,the computational efficiency of snow density formulation and frozen soil numerics have been greatly差不多拼音
improved.
Figure1.Snow cover fraction(s s)as a function of snow water equivalent(SWE,and snow depth assuming a snow density ratio of5:1)for the previous Noah LSM formulation (thin line,s s=0for SWE=0,and s s=1for SWE>0),and for the new Noah LSM formulation for forest(thick solid line)and grassland(thick dashed line)vegetation class.
EK ET AL.:UPGRADED NOAH LAND SURFACE MODEL GCP12-3
[12]Below,we describe our further extensions to the Noah LSM in terms of cold ason process beyond tho prented by Koren et al.[1999].
2.2.Soil Heat Flux Under Snow
[13]As the snowpack becomes very thin,it is difficult to estimate the large near-surface temperature gradients in the snow and upper soil layer,which sometimes leads to unrealistic spikes in the modeled values of the soil heat flux (G )through the snow and upper soil layer (e.g.,as en in the study by Hinkelman et al.[1999]).The original formulation for G in the Noah LSM assumed a constant value for the snow thermal conductivity (0.35W m À1K À1)with heat flux through the soil and snow determined as
G ¼K s ðT s ÀT s 1Þ=ÁZ s
ð1Þ
where K s is the snow thermal conductivity,T s and T s 1are the surface (snow)skin and upper soil layer (midpoint)temperatures,respectively (with the restriction that T s 273.15),and ÁZ s is the snow depth,assumed to be 10ÂSWE,where SWE is the snow water equivalent (so a snow density ratio of 10:1).The solution for G was then bounded by ±100W m À2for numerical stability becau with a vanishing snowpack (ÁZ s !0),G could spike with large positive or negative values,depending on the gradient of T s -T s 1(Figure 2).
[14]Therefore the soil heat flux formulation in the Noah LSM has been modified to include the effect of heat flow through thin patchy snow cover.This is done by considering the thermal conductivity of a snowpack-plus-upper-soil-layer following a method described by Lunardini [1981],where heat flow can be in parallel,in ries,or intermediate between the two.Here parallel heat flow through the snowpack-plus-upper-soil-layer is assumed,which yields a larger thermal conductivity (than say,ries),implicitly accounting for the nonuniform nature of snowpack cover.The effective thermal conductivity for the surface is then determined via a linear weighting between the snow-covered and non-snow-covered fractions (of a model gridbox),where
K T ¼ÁZ s K s þÁZ s 1K s 1ð2ÞK eff ¼s s K T þð1Às s ÞK s 1
ð3Þ
where K s 1,K T ,K eff are the thermal conductivities of the upper soil layer,snow-plus-upper-soil-layer,and patchy snow-covered surface (Figure 3),respectively,ÁZ s 1is the upper soil layer depth,and s s is the snow cover fraction (0 s s 1).The soil heat flux through the patchy snow-covered surface is then formulated as
G ¼
K eff ðT s ÀT s 1ÞÁZ s þÁZ s 1
ð4Þ
In this formulation the thermal conductivity remains robustly defined even in the extremes of vanishing snow cover (ÁZ s =0,s s =0,K eff =K s 1),or for a very
deep
Figure 2.Soil heat flux (G )through patchy snow cover as a function of snow depth for the previous Noah LSM formulation (thin line),and the new Noah LSM formulation for forest (thick solid line)and grassland (thick dashed line)vegetation class.Here we have assumed a temperature gradient of 3K (old formulation:equation (1);new formulation:equation (4)),and,for the new formulation,an upper soil layer volumetric soil moisture content of 0.29(yields soil thermal conductivity of 1.0W m À1K À1f
or Noah LSM soil texture class No.2,silty clay loam)and snow density ratio of 5:1(yields snow thermal conductivity of 0.108W m À1K À1
).
Figure 3.Thermal conductivity (K eff )through patchy snow cover versus snow water equivalent (SWE)for the previous Noah LSM formulation (thin line,K eff =K s =const.=0.35W m À1K À1),and new Noah LSM formulation for forest (thick solid line)and grassland (thick dashed line)vegetation cla
ss,with the same patchiness corresponding to Figure 1,and soil and snow conditions as in Figure 2.
GCP 12-4
EK ET AL.:UPGRADED NOAH LAND SURFACE MODEL
snowpack (ÁZ s )ÁZ s 1,s s =1,K eff !K s ),which is quite important for numerical stability.Chang et al.[1999]describe a similar thermal conductivity formulation (derived independently)adopted in another version of the OSU LSM,which accounts for a vanishing snowpack depth,although they did not account for patchy snow cover (equivalent to tting K eff =K T ).Patchy snow cover must be accounted for since it increas the heat flux between the surface and atmosphere (especially at smaller snow cover fractions)becau of the typically larger thermal conduc-tivity of soil compared to snow.
2.3.Albedo Over Snow
[15]In the prence of snow cover,the surface albedo may be markedly incread becau of the high albedo of snow (depending on vegetation cover).However,in con-ditions of shallow snowpack w
hen snow first accumulates at the start of snowfall or diminishes becau of snow subli-mation or snow melt,there will be patchy areas that are not snow ,in a model gridbox.To account for this patchiness effect,we formulate the surface albedo as a composite of a snow-covered and non-snow-covered sur-face as
a ¼a 0þð1Às f Þs s ða s Àa 0Þ
ð5Þ
where a ,a 0,and a s are the actual,snow-free,and maximum snow surface albedo,respectively,s f is the green vegetation fraction (0 s f 1),and s s is the snow cover
fraction (defined earlier),as illustrated in Figure 4.As snow depth becomes zero,the albedo becomes the snow-free albedo (a =a 0).When the snow depth exceeds a threshold value (dependent on land surface ,vegeta-tion type),snow cover is complete (s s =1)and a =a s ,the maximum snow albedo (described below).
[16]Over deep snow,the albedo of the surface is higher and in LSMs is often t to some uniformly large ,0.55previously in the Eta model.However,this can vary greatly depending on the surf
糖被
学生怎么画ace character.For example,a conifer forest may have a lower albedo becau of darker treetops sticking through a brighter (deep)snowpack,com-pared with a higher albedo for a completely snow-covered grassland.However,rather than u a maximum snow albedo simply as a function of the vegetation class or surface type (e.g.,as in the ECMWF land surface model [van den Hurk et al.,2000]),we u an annual maximum snow albedo climatology data t that extends the work of Robinson and Kukla [1985].Their original data t covered the area north of 25°N at 1°Â1°resolution,so for each 1°Â1°cell,the maximum snow albedo implicitly includes the effect of variable vegetation density (subgrid variability)within the same vegetation class.Note the differences between the North American boreal forests with lower maximum snow albedos due to more shading of the snowpack under the canopy,compared to the Great Plains grasslands with higher maximum snow albedos due to more open ground and expod snow cover (Figure
5).
Figure 4.Surface albedo contours as a function of snow cover fraction versus green vegetation fracti
on with ‘‘typical’’forest (grassland)values for snow-free albedo,a 0=0.15(a 0=0.20)and maximum snow albedo,a s =0.60(a s =0.70).
EK ET AL.:UPGRADED NOAH LAND SURFACE MODEL
GCP 12-5
[17]To populate a global1°Â1°databa,the maximum snow albedos from the original databa were correlated with the SiB vegetation class[Dorman and Sellers,1989] over this region to determine any pattern by‘‘binning’’the maximum snow albedo for a given vegetation class,then averaging and noting ranges.Indeed,the analysis showed a lower maximum snow albedo over forests than over short ,grasslands,tundra).The average maximum snow albedo for a given vegetation class was then applied to the region south of25°N,hence the more homogeneous ‘‘look’’of the databa in this‘‘filled’’region.Since there were no maximum snow albedo values for the tropical forest regions in the original databa,the maximum snow albedo for this vegetation type was nominally t to the Matthews[1983]snow-free albedo for the vegetation type in the regions.
2.4.Snowpack Initialization
[18]Before showing model impact studies,we review how the snowpack is initialized in the Eta model since snow cover and snow depth are important initial conditions for LSMs during winter months in many regions.Previously, only the daily47-km U.S.Air Force snow depth and a-ice analysis was ud in initializing snow and a-ice in Eta model forecasts.While not an upgrade in the context of the study here,a23-km northern hemisphere snow and ice chart (Figure6)prepared operationally on a daily basis year-round by the Satellite Analysis Branch of the Satellite Services Division of NESDIS[Ramsay,1998]is being ud operationally for the Noah LSM in the Eta-EDAS forecast system.This product provides superior information on the areal coverage of the snow and ice using visible imagery of the polar and geostationary(GOES)orbiting satellites as the primary tools for the analysis of this snow and ice cover, and relies on the human-interactive scrutiny of a trained satellite imagery analyst.Low-resolution visible data are ud,augmented whenever possible by the visible high-resolution imagery and visible GOES,GMS,and Meteosat data.In addition,ground weather obrvations and various DMSP microwave products are incorporated into this daily snow and ice chart.
[19]The Eta model initialization interpolates the most recent47-km U.S.Air Force(USAF)global snow depth analysis[Kopp and Kiess,1996]and the NESDIS
snow Figure5.Maximum snow albedo bad on Robinson and Kukla
[1985].
Figure 6.Snow cover over North America bad on
NESDIS snow cover analysis for4January2002.
GCP12-6EK ET AL.:UPGRADED NOAH LAND SURFACE MODEL
