Effects of vegetation on surface climate and regional atmospheric structure.

David FitzjarraldJungle Research Group, Atmospheric Sciences Research CenterUniversity at Albany, SUNY

&Ricardo SakaiMatt Czikowsky

Alex Tsoyref

“Only boundary layer flux convergences alter surface climate.”

• Observations provide information for modelers in two ways:• time series gridded in time and/or space (our duty)

standard climatological studies:(e.g., “daily temperature range”)

• data analyzed to infer bulk or emergent properties(e.g., “tendency Bowen ratio, spring date,

streamflow recession”)

• Models should be confronted (in public) with observations, after which they either:

• are ‘validated’ OR

• fail to represent important features in the observations(and get improved)

“IF YOU CAN’T WIN, YOU CAN’T LOSE.”

How might land cover changes affect climate?

1. Albedo effects: are pastures cooler than forests? recent model findings……….

2. Scaling outward from Harvard Forest results spring as a land cover change experiment

synoptic composites inferring parameters that control streamflow

inferring a bulk property: canopy resistance

leaf emergence and spring climate: recent changes

boundary layer feedbacks on surface fluxes:forced cumulus clouds

evapotranspiration and streamflow changes

3. Suggestions for enhanced interaction among climate modelers and observers.

Can land cover changes really be so unimportant to climate change?

Baidya Roy et al., 2003

Bonan (“Frost follows the plow”)

found summer anomalies for the NE US,

comparing modern vegetation - natural:

Summer

Temperature: -0.6 °C

Precipitation: +0.3 mm/d

Net radiation: -4.7 W/ m2

Sensible heat flux: -5.9 W/m2

Latent heat flux: +1.9 W/m2

Bonan, Ecol. Applic. 9, 1999

Models show cooling owing tovegetation, or warming, sincethe time of undisturbed forests….

(pastures are cooler than forests..) Baidya Roy et al., 2003

From Myhre and Myhre (2003):

Albedo changes since preagriculture time, for

Eight different land cover interpretations.

Myhre and Myhre (2003):

Radiative forcing due to human-influence vegetation changes.

Eight different land cover interpretations.

Using different values of

Albedos with given land-use

Categories leads to forcing

From - 0.02 to + 0.28 Wm-2!

Pielke et al. 2002Argue that ‘regional climatechange potential’ should replaceequivalent radiative forcing

Changes in energy partition NOTjust changes in reflectance willdominate regional climate perturbations due to land use changes.

Longwave forcing due to CO2 removal through sequestration (nWm-2 ha-1 )

Global mean shortwave forcing due to albedo reduction (nWm-2 ha-1 )

Equivalent C emissions to give same effect as albedo reduction (tC ha -1 )

Net radiative forcing due to afforestation (nWm-2 ha-1 )-0.6 -0.4 -0.2 -0.1 -0.05 +0.05 -0.1 0.15 0.3

(on a stranger note, one of the larger land-use inducedchanges are large positive temperature anamolies in thePacific Ocean.) Teleconnections!

Tropical pasture changing from dry to wet season

Albedo effect, but also a switch in Bowen ratio

B = H / LE

Wet season Dry season

HLE LE

H

Energy partition toward increased H buffers part of the any heating owing to albedo decrease.

Daily course.

DRY WET

FCO2 Day Night

PAR

Q*

Qg

Annual course

Leaf emergence at Harvard Forest presents a shock to the lower boundary conditions…….

A bulk property, the canopy resistance rc to water vapor transfer. Carefully tracking leaf state for several years, one finds thatThe rc scales with LAI even as leaves emerge.

“c” shows results from conifer and “d” deciduous canopies reported by Kelliher et al. Different days from the calculations at HF are shown as are regressions from two different years. “X” is the averagegrowing season value (days 216-275). (Sakai et al., 1997).

Growing season averagerc

LAI

Conifers

Kelliher et al. deciduous

e-6 = 0.0025

Convective boundary layer at Harvard Forest

This layer accepts the surface fluxes and a small fraction of the energy converges there to alter state.

Observed median cloud base.

LCL of surface air

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Deepest mixed layers in the early spring--opposite of a ‘seasonal rectifier’

Leaf-out

Massachusetts

Rain forest at equator

S. American savannah

Thermodynamic diagram illustrates connectionsamong surface climate, cloud base and likelyboundary layer thickness in the afternoon.

Freedman et al. 2001

Lq (kJ/kg)

Cp T

Seasonal changes.

LCL

(cloud modulated climate)

Synoptic scale changes-- recovery following a cold front…..

Freedman & Fitzjarrald, 2001

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Open areas (like the sandy spot for the ASOS observations at Orange airport are most definitely hotter than the forest! Tendency over several days is that the clouds buffer the heating, moistening of the boundary layer. Heading toward RH,

LCL equil.

Synoptically based composites:

(don’t average over the phenomenon.)

Freedman and Fitzjarrald, 2001.

A simple slab model illustrates the sensitivity of the sequence to Bowen ratios characteristic of the pre-leaf spring and the foliated period.

Model must get the partition right.

FPAR > 0.5

Days frost-free

C uptake period

Canopy duration

White et al., 2001

Growing season length

Std. deviations

Length of the growing season makes a large difference to annual temperature changes--leaf emergence changes the energy partition, the albedo, and other parameters.

Growing season length

White et al., 2003

Frost-free days

Canopy period

Carbon uptake period

From gridded data sources (e.g., VEMAP)

Short time series only from the satelliterecord.

Thirteen years of albedo measurements at Harvard Forest.Did you really expect to go up with leaf out?

Sensitivity of ecosystem to albedo change is illustrated by the time series of Q*/Sdw.

In regions with effective ET, the surface radiation budget is buffered by changes in energyPartition and net long-wave radiative fluxes--cannot count on albedo effect alone….

Q*/Sdw

1 - L/Sdw

julian.day

mean

100 150 200 250 300

1.5

2.0

2.5

3.0

3.5

4.0

4.5

19991998

Onset of spring from the albedo measurements tested with direct observations…..

Divides roughly into Bush and Clinton administrations….

LAI at Harvard Forest (CCB data) 1998 & 1999

(from Harvard group…..)

Outlier 1998, fewer clouds April & May, cloudy June, July, August

JAN MAR MAY JULY SEP NOV

1998

Monthly boundary layer (forced) cumulus days, Orange MA

0 2 4 6 8 10 12 14 18

Rugosity (m)

16 %

8%

“Rugosity” determines albedo in forests.

Reflections in bumpy terrain: Implications of canopy surface variations for the radiation balance of vegetation”,

Ogunjemiyo, Parker, and Roberts, 2004.

Fitzjarrald et al. (2001)“Climatic consequences of leaf presence…”

B' ≡cp

∂θ∂t

h

L∂q∂t

h

B≡Ho

LEo

Returning to the link between sfc forcing and surface conditions….

Inferred estimates of spring date tested with the lilac network (Schwartz)

(and also with other measures. The simple methodworks well where there is overlap, gives some confidence in applying to long time series.)

New England

New England

Midwest, NJ

Spring T

Earlier spring should mean cooler spring temperatures……

Seeking the response of the watershed to the abrupt onset of ET.

Czikowsky and Fitzjarrald, 2004.

Recession time constant --- e-folding time to return to base flow after a rain event, shows the impact of deciduous leaf emergence.

Czikowsky and Fitzjarrald, 2004.

Comparing streamflow and Bowen ratio approaches….

1970/2000 – 1928/1958 1976/2000 – 1951/1975

Region Mean n Mean n

NE, NY -5.2 ± 0.9 85 -6.6 ± 0.6 236

PA, NJ 1.0 ± 1.6 36 1.6 ± 0.7 130

VA 4.8 ± 4.9 26 -5.0 ± 1.6 112

Czikowsky and Fitzjarrald, 2004.

The time constant for the watershed is proportional to the riparian area, and inversely proportional to the cross-sectional area of the drainage, and the

hydraulic conductivity.

dripwwAAKd=τInterpreting observations with simple models……

Czikowsky and Fitzjarrald, 2004.Time (dimensionless)

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• Data should be analyzed with a plan to testing models.

Must seek bulk and emergent properties.Don’t settle with just the delivery of averaged data to the modelers.

• Models should be designed with as many observable parameters as possible.

Don’t stop evaluating until you are right for the right reasons.More ‘confrontation’, less ‘validation’.

Dilemma

I want to be famous so I can be humble about being famous.

What good is my humility when I am stuck in this obscurity?

David Budbill