Justin MinderYale Geology & GeophysicsDavid KingsmillNOAA-ESRL (HMT)

Mesoscale variations in Sierra Nevada snow lines: Climatology, case study, and mechanisms

Also: Gerard Roe, Dale Durran (UW)

What role to mesoscale processes play in modulating the rain-snow transition over mountains?

Mountain snow and climate change

The partitioning between rain & snow has big impacts on both hydrological resources & hazards

z

x

wind

ZS

Z0CδS

δδ0C

The mountainside snow line& mesoscale controls

ZS: Snow lineZ0C : Zero-degree line

ZBB: Bright band elevation

ZBB

Snowline observations: Case studies

Distance (km)

Altit

ude

(km

)

Lowering of ZBB & Z0C by up to 1km over:• N. Sierra Nevada• Oregon Cascades• Italian Alps

Marwitz (1987)

Medina et al. (2005)

N. Sierra: Isotherms (oC)

Italian Alps: Reflectivity(dBZe)

Z0C

ZBB

• Lowering of the snowline is a climatological feature• ΔZS ~100m’s, big enough for major impacts on snowpack and flooding

2005/6 -2007/8 storm-based climatology

ZBB drops

ZBB rises

Snowline observations: N. Sierra Climatology

What causes ΔZS (ΔZBB) and its variability?

~50km

Z 0C

Why does the snowline dip downwards towards the terrain?Possible mechanisms

Pseudo-adiabatic cooling from lifting

Z 0C

Cooling by melting of orographically enhanced snowfall

Z 0C

Z S

Increased melting distance for orographically enhanced snowfall

Z 0C

Along-barrier transport of cool/dry air

2-D semi-idealized numerical simulations

w-damping Layer (Klemp 2009)

stratosphere

tropospherehm

,a

RH = 20% N

d = 0.01 s-1

U

WRF-ARW (v3.0.1) Δx=2km 201 vertical eta-levels

(Δz=20-400m) Open BCs in x Periodic BCs in y Free slip bottom boundary Thompson et al. bulk microphysics

(6 phases, incl. Graupel) f-plane

( f = 10-4 s-1)

Initial conditions:Prescribe: T

s : temp. at z=0

Nm

: moist stability

RH : relative humidity U : cross-mountain windsTerrain:

cos4 ridge, with prescribed:h

m : height=1.5km

a

: half-width=40kmRun to steady state

RH = 95%N

m = 0.005 s-1

U = 15 m s-1

2D semi-idealized WRF simulations:

Mechanisms

Minder, JR, DR Durran, GH Roe, 2011: Mesoscale Controls on the Mountainside Snow-line. Journal of the Atmospheric Sciences, 68, 2107-2127.

wind

~20%

~45%

~30%

Minder et al. (2011)

Ts=7oCT

s=3oC

• Z0C

upwind rises 742 m with warming, ZS on the mountainside rises only 530 m.

• Mesoscale processes “buffer” effects of warming on the snow-line by ~30%.

2D semi-idealized WRF simulations:

Sensitivity to Temperature

2D semi-idealized WRF simulations:Sensitivity to microphysics

MicrophysicsMinder et al. (2011)

Feb 8-12, 2007

A case study of Northern Sierra Nevada snowline behavior

GOES IR (shading)&

Sea Level pressure (contours)

• Do idealized results carry-over?• Do 3D dynamics, PBL fluxes, radiation, etc. change the answer?

CFCATA

BBDBLU

SHS profiler & balloons

profilers sfc. met.

Mesoscale ObservationsNOAA HMT-West

White et al. (2002) algorithm for ZBB detection

• 72 hr simulation

Feb 8, 12 UTC – Feb 11, 12 UTC

• 4 nested domains

(27km; 9km ; 3km; 1km)

• IC’s and BC’s from NARR

Nudge doms. 1-2 towards NARR

• 118 vertical levels

Δz = 30 m from 1-3km

• Parameterizations:

WSM6 microphysics

Kain-Fritsch convection (d1-3)

MYJ boundary layer

Mesoscale Modeling

OLR (shading) Sea Level Pressure (contours)

Surface (Precip. & Temp.)

Observations WRF

T(°C

)Pr

ecip

(mm

)

Time (UTC; dd.hh) Time (UTC; dd.hh)

Obs. WRF

S-band Profiler (dBZe): CFC

Z0C

Z0C

ZBB

ZBB

Observations

WRF

ZBB & Z0C : upwind vs. mountain

ΔBB

= -110 m

ΔBB

= -140 m

ΔBB

= -70m

ΔBB

= -210 m

• Full drop in Z0C & ZS is more like 400-600m (underestimated by profilers)

WRF cross – section

Z0C

1hr rainfall (shading)500m winds (barbs)

wind

x(km)

y(km

) Frozen precip.mix. ratio (shading)

~20%Causes?• ~100 m melting distance

Trajectory diagnostics (1):Pseudo-adiabatic mechanisms

• Calculate 3-hr back-trajectories from model output, ending at Z0C on transect.

• Try to use simple pseudo-adiabatic parcel model to predict Z0C for each traj.

Total ΔZ0C

Pseu

do-

adia

batic

“oth

er”

~40%

• ~200 m pseudo-adiabatic (3D)

Trajectory diagnostics (2):Cooling by melting mechanism

Δ

7 18• Construct a θe budget for two representative trajectories

• Δθe is almost entirely due to cooling by melting snow

TotalCooling by melting

TotalCooling by melting

fhrfhr ~30%• ~150 m cooling from melting

~30%

~40%

~20%

Case study summary & further work

Still working on:• Sensitivity to microphysics• Sensitivity to temperature

Future plans:• Examine other cases

(low snowline w/ more blocking)• More climatological analysis with

HMT data• LES of melting layer turbulence• Examination of other settings

CONCLUSIONSA mesoscale lowering of the snowline over terrain appears to be a common feature of mid-latitude mountain climate

A range of pseudo-adiabatic, diabatic, & microphysical processes may explain this behavior

These processes may be simulated and diagnosed in mesoscale numerical models, which suggest important roles for several mechanisms

The dependence of these mechanisms on climate may result in modulations of large-scale climate impacts

Climate-connections are being further investigated using multi-year observations and regional climate models

z

zero-degree line

T

z

Z0C

0ºC

ZBB

ZS

Z0C

The atmospheric snowline

The elevation in the atmosphere where falling snow melts into rain

q s,g

z

Z0C

(q s,g

)o

(q s,g

)o/2

ZS

Melting layer

snow line

dbZ

z

Z0C

ZBB

Bright band

bright-band height

(δ)Dmelt

What physical processes determine ZS?

Role of: Melting Distance (Dmelt

)

(δ)Dmelt

= (Z0C

)mtn.

- (ZS)

mtn.

(δ)Dmelt

= 125 m

qc (shading), Isotherms ( contours every 1oC)

What physical processes determine ZS?

Role of: Latent Cooling from Melting (Qmelt

)

(δ)Qmelt

ZS and Z

0C from runs:

with Qmelt

(solid)

without Qmelt

(dashed)(δ)

Qmelt = (δ

0C) - (δ

0C)

no-Qmelt

(δ)Qmelt

= 61 m

Advection through melting layer is too fast for substantial Q

melt

qc (shading)

What physical processes determine ZS?

Role of: pseudo-adiabatic Cooling (Qad.

)

0°C T

Z ΓΓm

δ0C

Ts

dT/dz=Γ

Ts

T(z) Z0C

Γd

parcel

environment

Consider flow over a mountain that is:SteadyInviscidStably stratifiedPseudo-adiabatic

Moist thermodynamics following air parcel determines δ

0C

Captured by simple air parcel model (δ

0C)

parcel depends on: T

s, Γ (N

m), RH

(δ)Qad. = 81 m(δ

0C)

parcel = 107 m

c.f. WRF :

(δ0C

)no-Qmelt

= 81 m

What physical processes determine ZS?

Summary

Z0Cδ

x

z ZS

(δ)Qad.

(δ)Qmelt

(δ)Dmelt

δ = (δ)Dmelt

+ (δ)Qmelt

+ (δ)Qad.

267m = 125 m + 61 m + 81 m

…but how general is this result ?

S-band Profiler (dBZe): ATA