WP I.5: Convectively forced gravity waves and impact in the stratosphere

(1)

WP I.5: Convectively forced gravity waves and impact in the stratosphere

1)Motivation and Formalism 2)Results

3) Validation against observations

4)Summary, milestones, deliverables, ect..

EMBRACE GA, 2014

F. Lott, A. de la Camara, L. Guez, A. Hertzog, P. Maury, R. Plougonven Laboratoire de Météorologie Dynamique, Paris.

A.C Bushell, N. Butchart, S. H Derbyshire, G. J Shutts, S. B Vosper, S. Webster UK Met Office, Exeter

(2)

1) Motivation and formalism

Mesoscale GWs transport momentum from the lower atmosphere to the stratosphere and

mesosphere

GWs significantly contribute to driving the Brewer-Dobson

circulation, the QBO, etc.

GWs break and deposit momentum to the mean flow

- Density decrease with altitude - Critical levels

To incorporate these effects and have a realistic atmosphere, all ESMs and GCMs have GWD parameterizations:

None of the models in CMIP5 relate gravity waves parameterization to their Convective (or other) sources.

Today: GWs forcings do not change when the climate change

GWs forcings do not vary with tropospheric modes of variability like ENSO

(3)

Hertzog et al. 2012 JAS Dewan&Good 1986 JGR

Show intermittent GW fluxes

Hertzog et al. (2012).

Property used in global “spectral schemes”

Hines (1997), Warner&McIntyre (2001), Scinocca (2003)

70's-90's observations (vertical soundings) Recent balloon and satellite obs.

Long-term averages of vertical profiles show well- defined vertical wavenumber spectra

Van Zandt (1982), Fritts et al. (1988), Fritts&Lu (1993)

Property justifying stochastic schemes

Lott et al. (2012), Lott&Guez (2013)

Can these approach be reconciled?

1) Motivation and formalism

UK Met. Office uses the Warner and McIntyre

Spectral scheme IPSL uses a multiwave stochastic scheme

(4)

⃗F=

∑

_n^∞₌₁ ^Cn

2 ⃗F_n

∑

_n^∞₌₁ ^Cn

2=1

where

1) Motivation and formalism

Exemple of the stochastic multiwave scheme at IPSL where the Fourier series at the basis of the subgrid scale waves parameterization, are replaced by stochastic

series where the GWs momentum fluxes are written:

How convective sources can be represented in a gravity wave scheme? M 1.16

For the F_n we use the linear theory and treat each waves independently from the others.

⃗ k

_n

, ω

_n

Wavenumber and frequency chosen randomly:

Passage from one level to the next as in Lindzen (1981)

(each waves traval independently from the other, breaking and critical levels control the drag vertical distribution):

∆^{z, G}_uw^{, S}_c^{, k}^*^,µ: Tunable parameters

⃗F_nl=ρ_r k⃗_n

∣^k^⃗n∣

(

^G^b⁽¹⁻^cos⁸^{φ) +} ^G^uw^∣^k^⃗ⁿ^∣^N²^e^−m^Ωnⁿ²^Δ^z²

3

(

^ρ^{R L}r H c^W_p

)

²^P^r²

)

GWs due to convection:

P_r is the precipitation

Stochastic background flux to represent

GWs from fronts

Launched Fluxes:

G_b: Chosen out of a log-normal distribution

(5)

1) Motivation and formalism

Why should we take precipitation rather than other field to quantify the wave sources? We are guided here by the very high resolution

simulations

Momentum flux coarse grained to 440km grid

Momentum flux (Pa) 0200-0300Z on

01-Sep-2011

High resolution original grid

2.2km

In EMBRACE we proposed to use High Res. Simulations

to tune GWS schemes

(6)

1) Motivation and formalism

Why should we take precipitation rather than other field to quantify the wave sources? We are guided here by the very high resolution

simulations

Momentum flux coarse grained to 440km grid

0200-0300Z on 01-Sep-2011

High resolution original grid

2.2km

Empirical relation between precips and GWs momentum fluxes

In EMBRACE we proposed to use High Res. Simulations

to tune GWS schemes

(7)

Lott and Guez, JGR 2013 CGWs

Stress (1 week)

CGWs drag

Same zonal mean stress

Real precip. Stress amplitude (CI=2mPa) Uniformized precip. Stress amplitude (CI=2mPa)

Eq 30N 60N 90N

30S 60S

90S0 60E 120E 180E 60W 120W 0 60E 120E 180E 60W 120W

Real precip. du/dt *e(-z/2H), CI= 0.1 m/s/d Uniformized precip. du/dt *e(-z/2H), CI= 0.1 m/s/d

Eq 30N 60N 30S

60S 60S 30S Eq 30N 60N

More drag near and above stratopause Slightly less drag in the QBO region

50 60

40 30 20 10

50 60

40 30 20 10

0.15 0.25 0.35 0.45

0.05 0.05 0.15 0.25 0.35 0.45

2) Results

Benefit of having few large GWs rather than a large ensemble of small ones Exemple of the GWs due to convection:

(8)

2) Results

UK Met office, Structure of the launched GW momentum predicted interactively by the UKMO GCM

Spatial structure in January

Temporal structure: the zonal mean launched GWs flux now has an annual cycle that follows that of convection

(9)

LMDz version with 80 levels, dz<1km In the stratosphere

QBO of irregular period with mean around 26month, 20% too small amplitude

Westerly phase lacks of connection with the stratopause SAO

Lott and Guez, JGR13

a) LMDz with convective GWs LMDz+CGWs

b) MERRA

1000 100

10 20 1 0.1 1000 100

10 20 1 0.1

1990 1992 1994 1996 1998

2 4 6 8

2) Results

(10)

CONCORDIASI (2010)

Rabier et al. 2010 BAMS

19 super-pressure balloons launched from McMurdo, Antarctica, during Sep and Oct 2010.

The balloons were advected by the wind on a isopycnic surface at ~ 20 km height.

3) Validation against observations

Instruments on board sampled the interior of the stratospheric polar vortex every 30 s for an

averaged period of 2 months.

Dataset of GW momentum fluxes (as by Hertzog et al. 2008)

www.lmd.polytechnique.fr/VORCORE/Djournal2/Journal.htm

GWs from the scheme:

Offline runs using ERAI and GPCP data corresponding to the

Concordiasi period.

Important: Satellite (partial) observations in the tropics support what is shown next.

(11)

3) Validation against observations

The stochastic scheme parameters can be tuned to produce fluxes as intermittent as in balloon observations.

Intermittency of GW momentum flux

de la Cámara et al. 2014, Submitted.

Remember that intermittency is important because it produces GW breaking at lower altitudes (Lott&Guez 2013)

In order to parameterize GWs issued from fronts, we add a stochastic background flux with

log-normal distribution to the convective GWs:.

(12)

3) Validation against observations

Vertical spectra of GWs energy

Average of periodograms The observed “universal spectra” can be obtained with a “multiwave scheme” as a superposition of individual periodograms

of GW packets.

de la Cámara et al. 2014, Submitted Remember that

In order to parameterize GWs issued from fronts, we add a stochastic background flux with

log-normal distribution to the convective GWs.

(13)

3 ) Validation against observations

de la Cámara et al. 2014,Submitted

What cause the intermittency?

Sources, like P² for convection or ξ² for fronts have lognormal distributions (P precipitation, ξ relative vorticity)

For waves produced by PV see Lott et al.~(2012)

Results for intermittency suggest to relate the GWs to their sources

(14)

3 ) Validation against observations

Bushell et al.. 2014, in preparation

What cause the intermittency?

Here we show the globally spectral scheme at UKMO.

Results for intermittency suggest to relate the GWs to their sources

Constant source Mean O[1mPa]

Max ~ 1.7mPa

Convective source Mean O[1mPa]

Max > 25mPa

Height ASL

GW filtering creates

log-normal form ^Sea

(15)

Continuing work

3) Validation against observations

Pre-Concordiasi (2010)

3 balloons in the Tropics

Jewtoukoff et al 2013

Nested domains down to dx = 1 km

Case study of waves excited by a cyclone

Simulated gravity waves

Simulated cyclone

(radar reflectivity)

(16)

4) Summary et caetera

Milestones and deliverables

M1.16: Parameterizations of convectively forced gravity waves installed in IPSL and UKMO model.

Done, 2 papers published.

M1.18: CGW param available for testing in CMIP 5 coupled simulations. Ongoing at IPSL, but the main problem is to make the ESM OK to run with a high vertical resolution in the

stratosphere (to have a QBO).

D1.19: Report on the performance of the CGWs schemes compared to available observations and high resolution simulations: For obs. At least one Per review paper submitted.

D1.20: Report on the impact of CGWs on the simulated stratosphere, with a particular focus on the tropics and QBO. Done, at least one paper submitted (at IPSL). At UKMO, a GRL paper not related to EMBRACE shows that the model can produce a QBO with a CGWs scheme.

(17)

Not a milestone and not a deliverable but essential, nevertheless....

Interaction between resolved waves and parameterized waves

4) Summary et caetera

Equatorial waves:

Remember also that when you start to have positive zonal winds, the planetary scale Yanai wave is much improved

(the composite method is described in Lott et al. 2009)

Lott et al.~2013

ERAI 21, 11 cases

LMDz+CGWs 10 cases

LMDz withou CGWs 10 cases 20S

20N

Eq

20S 20N

Eq

20S 20N

Eq

80E 0

80W 40W 40E

80E 0

80W 40W 40E

80E 0

80W 40W 40E

Composite of Rossby-gravity waves at 50hPa (T and wind)

(18)

4) Summary et caetera

Symmetric precipitations : spectra (lines)

And

coherency with U850 (color) Increasing precipitation variability

Convectively coupled waves

A large variability in precipitations

spectra

With QBO Without QBO

Frequency (Cy/day)

0.1

0.01

Frequency (Cy/day)Frequency (Cy/day)Frequency (Cy/day)Frequency (Cy/day)

0.1

0.01

0.1

0.01

0.1

0.01

0.1

0.01

ERAI and GPCP MRI

MPI-MR MPI-LR

MPI-MR

CMCC IPSL5A

IPSL5B HadGEM2-MR

MIROC Can-ESM2

-10 -8 -6 -4 -2 2 4 6 8 10 -10 -8 -6 -4 -2 2 4 6 8 10

Some models have : CCEWs strong enough to affect the precipitation

Variablity

CCEWs but not strong enough to impact the PREC

spectra (only visible in the coherency) No CCEWs at all The PREC variability varies a lot from one model

to the other (as in CMIP3, see Straub Hertel Kiladis 2013)

Wavenumber Wavenumber

CMCC

Kelvin waves In troposphere

Lott et al. 2014

(19)

10 5 0 -5 -10

10 5 0 -5

Lag (days)Lag (days)Lag (days)Lag (days)Lag (days) -10v 10

5 0 -5 -10

10 5 0 -5 -10

10 5 0 -5 -120 -60 0 60 120 -10

Longitude (0 is arbitrary)

-120 -60 0 60 120 -120 -60 0 60 120

-120 -60 0 60 120

-120 -60 0 60 120 Longitude (0 is arbitrary)

Rossby Gravity wave composites at 50hPa

Hovmoller of V at equator

MRI ERAI

MPI-MR MPI-LR

CMCC IPL5A (High precip variability)

HadGEM2-MR

HadGEM2-MR IPL5B (Low precip variability)

MIROC Can-ESM2

Rossby Gravity waves in CMIP 5 Model

4) Summary et caetera

(20)

10 5 0 -5 -10

10 5 0 -5

5 0 -5 -10

10 5 0 -5 -10

10 5 0 -5 -120 -60 0 60 120 -10

-120 -60 0 60 120 -120 -60 0 60 120

-120 -60 0 60 120

MRI ERAI

MPI-MR MPI-LR

HadGEM2-MR

MIROC Can-ESM2

Eastward phase speed but

Westward group velocity as expected for RGWs.

In models without QBO, the RGWs packets stay at the same place, the eastward intrinsic group

speed balancing the westward advection.

This is not the case in Models with a QBO, and

where the RG waves packets travel over very large distances.

This long distance travel is particularly pronounced

in the UKMO model!

Rossby Gravity waves

4) Summary et caetera

(21)

10 5 0 -5 -10

10 5 0 -5

5 0 -5 -10

10 5 0 -5 -10

10 5 0 -5 -120 -60 0 60 120 -10

-120 -60 0 60 120 -120 -60 0 60 120

-120 -60 0 60 120

MRI ERAI

MPI-MR MPI-LR

HadGEM2-MR

MIROC Can-ESM2

in the UKMO model!

4) Summary et caetera

(22)

10 5 0 -5 -10

10 5 0 -5

5 0 -5 -10

10 5 0 -5 -10

10 5 0 -5 -120 -60 0 60 120 -10

-120 -60 0 60 120 -120 -60 0 60 120

-120 -60 0 60 120

MRI ERAI

MPI-MR MPI-LR

HadGEM2-MR

MIROC Can-ESM2

in the UKMO model!

4) Summary et caetera

(23)

Scientific points concerning the relations between the GWs and their sources It helps produce a realistic QBO in models

Evaluations of vertical spectra show that we can reconcile “multiwaves” and “globally spectral” parameterizations.

Validation against balloon shows that the observed intermittency result from:

(i) filtering by the background flow (as expected from past studies) (ii)Relation with the sources (precipitations and fronts)

Next work:

Relate the GWs to their frontal sources (e.g. ξ², see theory in Lott et al.~2010, 2012).

Evaluate further the impacts of parameterizations on the variability in the middle atmosphere (relation between QBO and ENSO, timing of SH final warmings, …)

And more on the use of high resolution simulations vs observations in the tropics