© Crown copyright Met Office Diurnal cycle Land-Atmosphere Coupling Experiment (DICE) GLASS / GASS...

© Crown copyright Met Office

Diurnal cycle Land-Atmosphere Coupling Experiment(DICE)

GLASS / GASS joint project

Martin Best and Adrian Lock


Outline of the 3 stages of DICE

LSM and SCM stand-alone performance against observations

What is the impact of coupling?

How sensitive are different LSM and SCM to variations in forcing?


CASES-99 case study23-26 October 1999

• Field experiment in Kansas, USA

• We follow Steeneveld et al (2006)

• 3 day simulation from 2pm local time on 23rd October 1999

• Recall GABLS II ran for from 2pm on 22nd for 2.5 days

• Clear skies throughout

• Gives 3 nights of varying character

• intermittent turbulence

• continuous turbulence

• very stable, almost no turbulent fluxes


Experimental protocol

• LSM

• Soil spin-up:

• 9 years from saturated using WATCH forcing data

• 10th year forcing data from local site

• Two stage 1a experiments with forcing from 2m and 55m

• Stage 3a LSM experiments forced with stage 1b SCM data interpolated to 20m

• SCM

• Large-scale forcing:

• Time-varying geostrophic wind (uniform with height)

• Large-scale horizontal advective tendencies for T, q, u, v estimated from a simple budget analysis of the sondes

• Subsidence for T, q

• No relaxation

• Radiation switched on in all simulations

• SCM in stage 1b use observed sensible and latent heat fluxes and u* (either directly or via cD)

• Stage 3b SCM experiments forced with stage 1a LSM surface fluxes


Participating ModelsModel Contact Institute Levels Sensitivity tests

Arome & Arpege (NWP) Eric Bazile Meteo France 60/70 Resolution, soil

Arpege (CMIP5) Isabelle Beau Meteo France

ECEARTH Reinder Ronda, Bert Holtslag Wageningen University 91

GDPS3.0 Ayrton Zadra CMC 79 Surface properties

GFDL Sergey Malyshev, Kirsten Findell Princeton/GFDL 24

GISS_E2 Ann Fridlind, Andy Ackerman GISS 40

WRF (IAP) Bingcheng Wan IAP 119

IFS/HTESSEL Irina Sandu, Gianpaolo Balsamo ECMWF 137 LAI

LMDZ, ORCHIDEE Sonia Ait-Mesbah, Marie-Pierre Lefebvre, Frederique Cheruy LMD 70

MESO_NH Maria Jimenez, Patrick LeMoigne, Joan Cuxart IMEDEA, Meteo France, UIB 85 Bare soil

UM/JULES Adrian Lock, Martin Best Met Office 70 Vegetation

NCEP Weizhong Zheng,

Mike Ek

NOAA 65 z0

WRF-NOAH Wenyan Huang, Xinyong Shen, Weiguo Wang

NUIST 60 Many

WRF Wayne Angevine NOAA 119 PBL scheme

CAM5, CLM4 David Lawrence, Ben Sanderson NCAR 26


• A challenging surface?

• October grass was largely dead

• Rain in September left soil moist

• Excessive evaporation a feature of the first round of DICE

Google streetview

Courtesy of Joan Cuxart


Stage 1aSurface fluxes from 55m-forced LSMs

Round 1 data

Round 2 data

Remember these will be the SCM surface fluxes in Stage 3b

Not all LSM provided u*(not compulsory under ALMA convention)


SCM grids• Solid lines = control model

• Dotted/dashed lines = experiment

• Lowest grid-levels range from 1.5m to 85m


Stage 1bSCM forced by observed surface fluxes


Stage 1b summary (from October workshop)

• Simulations successfully completed

• SCM can be forced by observed fluxes and stresses

• Overall doing a reasonable job

• Stable 3rd night not stable enough

• Lots to look at

• SCM forcing issues:

• I‘m not happy with the wind forcing

• Can geostrophic wind be set better?

• simply use 1-3km average instead of below 3km?

• Remove fine-scale structure in wind ICs and forcing?

• Subsidence slightly too weak?

• Check cirrus on 26th (is it spurious?)

• Check SW TOA between models

• Check temperature budgets for all models

• What should be happening with near surface night-time moisture (LHF~0)?

Tending to ignore 26th

Improved since round 1See entrainment budgets later

Still ?

No change to forcing


Stage 1b near surface evolution SCM driven by observed surface fluxes

20m 55m


Stage 1b to 2Impact of coupling to surface


Stage 1b vs 2Bulk PBL sensitivity (variables at 55m)

• More spread between coupled models in stage 2 than stand-alone SCM in stage 1b

• More degrees of freedom• Moisture more sensitive than temperature?

θ55m

q55m

Stage 2

θ55m

q55m

Stage 1b


Stage 1b vs 2Bulk PBL depth sensitivity

• Some suggestion that PBL depth is less sensitive when coupled (especially in the evening)

Stage 1b

Stage 2

PBL depth calculated as whereRiB=0.25


Stage 1a (55m)

Impact of coupling on winds


SBL sensitivity in stage 2

• Models with stronger evening cooling in T2m have• Weaker sensible heat flux• Stronger soil heat flux

• Consistent with stronger T gradients

• GABLS3 (Bosveld et al, 2014) sensitivity tests suggest implies similar soil conductivity?


Stage 3b variabilityPerspective from the atmosphere1) Daytime


Stage 3b daytime sensitivities

• All models have more variability in the PBL moisture than temperature

• But (by 25th)) SCM differ more for theta than q

• How strongly is this driven by the surface fluxes?

24th and 25th 24th and 25th

Flavours of WRF


Stage 3b temperature sensitivity to SHF

Typically weak correlation between daytime PBL temperature and surface sensible heat flux


Stage 3b moisture sensitivity to LHF

Much stronger correlation between daytime PBL moisture and surface latent heat flux


Controls on daytime PBL

• Why should q correlate more with LHF?

• or T less with SHF?

• SHF dominates deepening of PBL through entrainment

• Stronger SHF implies greater PBL warming but also entrainment and PBL deepening

• but that implies further enhanced warming so still ought to correlate

• Look further at differences in PBL growth…


Daytime sensitivity: θ profiles (1400 CDT 25th)

NUIST warm outlier


Daytime sensitivity: q profiles (1400 CDT 25th)


Stage 3b sensitivities

• Some models have much greater sensitivity in PBL depth than others

• Diagnosed consistently using RiB=0.25

24th and 25th


Does PBL depth depend on EF?

Not really!


Does PBL depth depend on surface buoyancy flux?

In most models, yes


Entrainment sensitivity

• Estimate entrainment fluxes from PBL θv budget

Integrate over the boundary layer:

Rearranging gives:v

i Sz

ww

t i

surfv

zv

vθ

θθθ+

−−=

∂∂ ''''

vS

z

w

tvv

θθθ

+∂

∂−=

∂∂ ''

1''''

''−⎟⎟⎠

⎞⎜⎜⎝

⎛−

∂∂

=−=v

i Stw

z

w

wA v

surfv

i

sfv

zv

ent θ

θθθ

θ

Horizontal advection and radiation (~small)• I’m ignoring vertical advection (small in PBL)


Variability in entrainment buoyancy flux

• Note Aent<0 implies PBL warming less than expected from surface heating+forcing

• Could imply surface heating distributed above hpbl

• Hence sensitive to definition of hpbl

“Expected value” ~ 0.2

sfv

zv

entw

wA i

''

''

θ

θ−=

Generic hpbl (RiB) Models’ internal hpbl



• Note Aent<0 implies PBL warming less than expected from surface heating+forcing

• Could imply surface heating distributed above hpbl

• Hence sensitive to definition of hpbl


sfv

zv

entw

wA i

''

''

θ

θ−=


Take SCMs 3 and 10 on 25th as examples


Examples: GISS and NUIST (Exp2=MYNN level 3)

• Models’ hpbl are significantly higher than RiB predicts

• Using the higher level adds warming within the inversion to the mixed layer budget and gives a larger Aent

Generic hpbl (RiB)Models’ internal hpbl

1''''

''−⎟⎟⎠

⎞⎜⎜⎝

⎛−

∂∂

=−=v

i Stw

z

w

wA v

surfv

i

sfv

zv

ent θ

θ

θθ

θ



• Met Office SCM has Aent=0.2 with very little variability

• Slight odd because the code sets Aent=0.23 and also includes a contribution from u*


sfv

zv

entw

wA i

''

''

θ

θ−=



Entrainment sensitivity to u*

Sensitivity to u* goes the wrong way!


Variability in moisture entrainment

• Entrainment flux of moisture depends on PBL to free-troposphere moisture difference

• Most models (not NUIST) have mixed out dry slot above inversion on 24th

• Hence moist air is entrained and Aentq > 0

• On 25th free-atmosphere is robustly drier and Aentq is more similar (<0)

sfv

zv

entqqw

qwA i

''

''−=

Use models’ internal hpbl


Stage 3bStable boundary layers


Stable boundary layer

• As in daytime, more spread in moisture than temperature

• SCM fairly consistent, particularly for moisture

23rd, 24th and 25th 23rd, 24th and 25th



• More negative SHF generally implies colder 50m temperature

• Heat lost to surface



• Larger u* implies warmer 50m temperature on 24th (+)

• More turbulent SBL with more mixing of heat downwards


Remaining data issues

• Some stage 3b files do not have correct u* forcing

• Were given observed u* by (my) mistake

• Can anyone face rerunning stage 3b again?

• Could all groups provide u* and Tskin from LSMs?

• Notes for future intercomparisons

• Decide on grid indexing from surface or TOA

• Height as height above surface (not sea-level)

• Make sign convention clear


Potential discussion points

• Stage 1a: should be straightforward to understand reasons for excessive u* in some LSMs

• Simply excessive z0? If so why (eg canopy height, LAI)?

• Stage 1a: u* distributions very different (fall into 2 groups)

• Could all groups provide u* from LSMs

• Stage 1a: some LSMs have different daytime fluxes forced by 2m and 55m

• Similarity theory not holding?

• Stage 2 coupling: some positive some negative feedbacks on surface fluxes (cf stage 1a)

• Stage 2 coupling: net LW enhanced by day (increased upward LW) with less SHF

Change in near surface T gradients?

• Interesting soil heat flux “hysteresis” between day and night in some models

• Why this difference and what is the impact?

• Stage 1b,3b: why do some SCM mix out the inversion?

• Dependent on parametrization structure (eg non-local vs EDMF vs higher order)?

• Does it matter? Affects PBL budget so can effects be seen in going from stage 1a


Next steps

• Further iteration (eg corrected u* in stage 3b)?

• Ensure everyone has submitted all data (eg u* and Tskin, 2m and 55m forcing datasets)

• Start on writing intercomparison papers

• Overview paper on intercomparison stages

• 2nd paper on detailed LSM analysis and coupling?

• 3rd paper on SCM sensitivities (eg entrainment, SBL)?

• Special issue for DICE related studies?

• Make intercomparison model data (and CASES 99 obs) available for others to do more analysis

• Clean up datasets first?

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