Global Models of Atmospheric Composition - Atmospheric Chemistry - Lecture Slides, Slides of Chemistry

Download Global Models of Atmospheric Composition - Atmospheric Chemistry - Lecture Slides and more Slides Chemistry in PDF only on Docsity!

GLOBAL MODELS OF ATMOSPHERIC COMPOSITION

HOW TO MODEL ATMOSPHERIC COMPOSITION?

Solve continuity equation for chemical mixing ratios

C

(x i

,^

t)

Fires

Landbiosphere

Humanactivity

Lightning

Ocean

Volcanoes

Transport

Eulerian form:

i

i^

i^

i

C

C

P

L

t







 







U

Lagrangian form:

i

i^

i

dC

P

L

dt





U

= wind vector

P

i^

=

local sourceof chemical

i

L

i^

= local sink

Chemistry

Aerosol microphysics

docsity.com

OPERATOR SPLITTING IN EULERIAN MODELS

i^

i^

i

TRANSPORT

LOCAL

C

C

dC

t

t

dt

… and integrate each process separately over discrete time steps:

(Local)•(Transport)

i^

o

i^

o

C

t

t

C

t

Split the continuity equation into contributions from transport and local terms:

Transport

advection, convection:

Local

chemistry, emission, deposition, aerosol processes:

i

i

TRANSPORT

i

i

LOCAL

dC

C

dt

dC

P

dt

U

i

L

C

C

These operators can be split further: •

split transport into 1-D advective and turbulent transport for

x, y, z

(usually necessary)

split local into chemistry, emissions, deposition (usually not necessary)

Reduces dimensionality of problem

SPLITTING THE TRANSPORT OPERATOR

Wind velocity

U

has turbulent fluctuations over time step



t

:

( )

'( )

t

t





U

U

U

Time-averagedcomponent(resolved)

Fluctuating component(stochastic)

1

(

)

i^

i^

i

xx

C

C

C

u

K

t

x

x

x











 











Further split transport in

x, y, and z

to reduce dimensionality. In

x

direction:

u v w

U

Split transport into advection (mean wind) and turbulent components:

1

i

i^

i

C

C

C

t





 

 



 





U

K

air densityturbulent diffusion matrix

K

advection

turbulence (

st

-order closure)

advectionoperator

turbulentoperator

VERTICAL TURBULENT TRANSPORT (BUOYANCY)

Convective cloud(0.1-100 km)

Model grid scale

Modelverticallevels

updraft

entrainment

downdraft

detrainment

Wet convection issubgrid scale in globalmodels and must betreated as a verticalmass exchangeseparate from transportby grid-scale winds.Need info on convectivemass fluxes from themodel meteorologicaldriver.

generally dominates over mean vertical advection

K-diffusion OK for dry convection in boundary layer (small eddies)

Deeper (wet) convection requires non-local convective parameterization

LOCAL (CHEMISTRY) OPERATOR:

solves ODE system for

n

interacting species

i

n

1

i

i^

i^

n

dC

P

L

C

C

dt

C

C

C

System is typically “stiff” (lifetimes range over many orders of magnitude) →

implicit solution method is necessary.



Simplest method: backward Euler. Transform into system of

n

algebraic

equations with

n

unknowns

i^

o

i^

o

i^

o

i^

o

C

t^

t

C

t

P

t

t

L

t

t

i

n

t

C

C

o

t

t

C

Solve e.g., by Newton’s method. Backward Euler is stable, mass-conserving,flexible (can use other constraints such as steady-state, chemical familyclosure, etc… in lieu of

C



t

)

^

But it is expensive. Most 3-D models use

For each species higher-order implicit schemes such as the Gear method.

LAGRANGIAN APPROACH: TRACK TRANSPORT OF

POINTS IN MODEL DOMAIN (NO GRID)

U



t

U’



t

Transport large number of points with trajectories from input meteorological data base (U) + randomturbulent component (U’) over time steps



t

Points have mass but no volume

Determine local concentrations as the number of points within a given volume •

Nonlinear chemistry requires Eulerian mapping at every time step (semi-Lagrangian)

PROS over Eulerian models:

no Courant number restrictions

no numerical diffusion/dispersion

easily track air parcel histories

invertible with respect to time

CONS:

need very large # points for statistics

inhomogeneous representation of domain

convection is poorly represented

nonlinear chemistry is problematic

position

t

o

position t

o



t

LAGRANGIAN RECEPTOR-ORIENTED MODELING

Run Lagrangian model backward from receptor location,with points released at receptor location only

Efficient cost-effective quantification of source influence distribution on receptor (“footprint”) •

Enables inversion of source influences by the adjoint method (backward model is the adjoint ofthe Lagrangian forward model)

GEOS-Chem GLOBAL 3-D CHEMICAL TRANSPORT MODEL

Solves 3-D continuity equations on global Eulerian grid using NASA Goddard Earth Observing System (GEOS) assimilated meteorological data (1985-present)or GISS GCM output (paleo and future climate) •

Horizontal resolution 1

o

x

o

to 4

o

x

o

, 48-72 vertical layers

Used by ~30 groups around the world for wide range of atmospheric composition problems: aerosols, oxidants, carbon, mercury, isotopes…

Illustrate here with Harvard work on tropospheric ozone

OZONE: “GOOD UP HIGH, BAD NEARBY”

Nitrogen oxide radicals; NO

x

= NO + NO

2

Sources: combustion, soils, lightning Volatile organic compounds (VOCs)

Methane Sources: wetlands, livestock, natural gas… Non-methane VOCs (NMVOCs) Sources: vegetation, combustion

Carbon monoxide (CO) Sources: combustion, VOC oxidation

Tropospheric

ozone

precursors

Climatology

of

observed

ozone

at

400

hPa

in

July

from

ozonesondes

and

MOZAIC

aircraft

(circles)

and

corresponding

GEOS-

Chem

model

results

for

1997 (contours).

GEOS-Chem troposphericozone columns for July 1997

.

GLOBAL DISTRIBUTION OF TROPOSPHERIC OZONE

Li et al., JGR [2001]

COMPARISON TO TES SATELLITE OBSERVATIONS

IN MIDDLE TROPOSPHERE

Zhang et al. [2006]

(July 2005) averagingkernels

GEOS-Chem GLOBAL BUDGET OF TROPOSPHERIC OZONE

O

O

2

h



O

OH

HO

h



, H

2

O

Deposition

NO

H

2

O

2

CO, VOC

NO

h



STRATOSPHERETROPOSPHERE

8-18 km

Chem prod introposphere,Tg y

Chem loss introposphere,Tg y

Transport fromstratosphere,Tg y

Deposition,Tg y

Burden, Tg

Lifetime, days

Present-dayPreindustrial

docsity.com

IPCC RADIATIVE FORCING ESTIMATE FOR TROPOSPHERIC

OZONE (0.35 W m

) RELIES ON GLOBAL MODELS

Preindustrialozone models

}

Observations at mountainsites in Europe[Marenco et al., 1994]

…but these underestimate the observed rise in ozone over the 20

th

century