Cotton W.R., Pielke R.A. Human Impacts on Weather and Climate

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Regional vegetation feedbacks 139

01224

Time (h)

Clearing

Forest

(b)

Wind speed (m

–1

)

Figure 6.27 Mean hourly wind speed at clearing and forest sites in the Amazon

for the period 12 October to 10 December 1990. From Bastable et al. (1993).

shows these effects on maximum and minimum temperature, rainfall, and above-

ground biomass growth, during a growing season averaged over the central Great

Plains. For example, the effect of enhanced atmospheric concentrations of carbon

dioxide on plant growth on a seasonal timescale is shown to be much more

important than the radiative effect of enhanced atmospheric carbon dioxide for

this region.

The nonlinear effect of vegetation–atmospheric feedback on this scale also

results in a complex spatial and temporal pattern of response. Not only is there

a teleconnection of atmospheric conditions to locations distant from where the

land feedback occurs, but the landscape at distant locations itself is influenced by

the altered weather. In manipulative vegetation experiments where carbon diox-

ide concentrations are arbitrarily increased, for example, this nonlinear feedback

between the atmosphere and land surface is missed since there is no feedback to

the regional weather (with greater vegetation cover resulting in greater summer

rainfall and cooler maximum temperatures).

The biogeochemical effect of enhanced carbon dioxide and trace gas concen-

tration, and of aerosol deposition (such as nitrogen; Raddatz, 2003; Galloway

et al., 2004; Holland, 2005) on landscape dynamics has also not been adequately

considered. For example, Jenkinson et al. (1991) demonstrated a significant

positive carbon dioxide radiative feedback where soils released carbon to the atmo-

sphere under warming conditions. Lenton (2000), using a simple box model, and

140 Other land-use/land-cover changes

01224

Time (h)

Clearing

Forest

(a)

Air temperature (

°C)

01224

Time (h)

Clearing

Forest

(b)

Air temperature (

°C)

Figure 6.28 Mean hourly air temperature at screen height at the clearing and

forest sites in the Amazon for (a) the dry period from 12 to 21 October 1990 and

(b) the wet period from 1 to 10 December 1990. From Bastable et al. (1993).

Cox et al. (2000) using general circulation model (GCM) sensitivity experiments,

showed that biogeochemical feedbacks in conjunction with an increased carbon

dioxide radiative warming produced an amplified regional and global temperature

increase. These results are in contrast to those of Eastman et al. (2001a) where a

cooler daytime and warmer nighttime in the central Great Plains was simulated in

Regional vegetation feedbacks 141

01224

Time (h)

Clearing

Forest

(a)

Specific humidity deficit (g kg

–1

)

Time (h)

Clearing

Forest

(b)

Specific humidity deficit (g kg

–1

)

Figure 6.29 Mean hourly specific humidity deficit at screen height at the

clearing and forest sites in the Amazon for (a) the dry period from 12 to 21

October 1990, and (b) the wet period from 1 to 10 December 1990. From

Bastable et al. (1993).

response to greater plant growth in a doubled carbon dioxide atmosphere. Zeng et al.

(2004) showed that abrupt transitions can occur in semi-arid regions associated with

the dynamical interactions of soil water and vegetation which further illustrates the

complexity of the nonlinear interactions between vegetation and the atmosphere.

142 Other land-use/land-cover changes

CLEAR DAY MAY 17, 1984

CLOUDY DAY MAY 18, 1984

IN THE OPEN

003 06 09 12 15 18 21 24

UNDER FOREST

TIME OF THE DAY (HR)

At 1cm depth

At 50

cm depth

Air temperature

1m height

SOIL TEMPERATURE (

Figure 6.30 Diurnal fluctuations in soil and air temperature under forest and

on cleared land in southern Nigeria. From Ghuman and Lal (1986).

Niyogi and Xue (2006) used a coupled process-based model to show that the

carbon assimilation potential for each of the GCM land-use categories (compris-

ing both C3 and C4 photosynthesis pathways) is sensitive to the soil moisture

availability. Niyogi et al. (2004) and Gu et al. (2003) have shown that atmo-

spheric aerosols, through their increase of the fraction of diffuse sunlight, enhance

photosynthesis. Nemani et al. (2002) demonstrated how increased precipitation

and humidity over the United States, particularly during the period from 1950

to 1993 increased the growth of natural vegetation more than increased carbon

dioxide and warmer temperatures did. Ozone pollution in China has been shown

to affect crop yields which will necessarily affect transpiration in the region

(Chameides et al., 1999).

The presence of drought and hydrological feedbacks associated with land-

use change locally or through teleconnections, therefore, have a direct impact

on the source/sink capabilities of the terrestrial ecosystem. These studies illus-

trate the significant role that biogeochemistry has within the climate system.

This feedback, along with other climate forcings and feedbacks (Pielke, 2001b),

make climate prediction on timescales of years and longer a particularly difficult

problem.

Regional vegetation feedbacks 143

Contributions to maximum

daily temperature (

°C)

–1.191

0.0141

–0.747

–1.2

–1

–0.8

–0.6

–0.4

–0.2

0.2

Contribution (

°C)

f 1

f 2

f 3

Contributions to minimum

daily temperature (

°C)

–0.017

0.097

0.261

–0.1

0.1

0.2

0.3

Contribution (

°C)

f 1

f 2

f 3

Contributions to daily

precipitation (mm)

–0.035

0.0078

–0.05

–0.04

–0.03

–0.02

–0.01

0.01

Contribution (mm)

f 1

f 2

f 3

Contributions to LAI

0.198

0.001

0.578

–0.1

0.1

0.2

0.3

0.4

0.5

0.6

Contribution (m

–2

)

f 1

f 2

f 3

–0.046

Figure 6.31 RAMS/GEMTM nonlinear coupled model results – the seasonal

domain-averaged (central Great Plains) for 210 days during the growing sea-

son, contributions to maximum daily temperature, minimum daily temperature,

precipitation, and leaf area index (LAI) due to: f 1 = natural vegetation, f 2 =

2 × CO

radiation, and f3 = 2 × CO

biology. From Rial et al. (2004) with kind

permission of Springer Science and Business Media.

Land-use/land-cover change

Grass/cropland Irrigation Forest

Shallow root

depth

High surface

albedo

Low surface

albedo

High seasonal

LAI

Deeper root

depth

Low seasonal

LAI

Depressed Bowen

ratio (LHF/SHF)

Depressed soil

moisture recycling

Gound water

pumping

Enhanced soil

moisture recycling

Enhanced Bowen

ratio (LHF/SHF)

Shallow moist

PBL

Deep dry PBL

Low CAPE

High CAPE

Local/regional climate

Moist convection process, mesoscale circulation (sea/land–land breeze)

Moisture/carbon/nitrogen allocation in soil

Figure 6.32 Hypotheses of the influence of land-use/land-cover change on

regional climate. From Pielke et al. (2006a).

144 Other land-use/land-cover changes

Increased anthropogenic CO

emission – its biological effect

Biogeophysics

Minutes–daily scale

Depressed

stomatal

conductance

Enhanced Bowen ratio

(LHF/SHF)

Deeper drier

PBL

Modify Bowen

ratio (LFH/SHF)

Modify

PBL

Modify

surface albedo

and emissivity

Biogeochemistry

Daily–seasonal scale

Biogeography

Year–decadal scale

Modify photosynthetic

carbon assimilation

Allocate LAI

Allocate root

Modify CAPE

Root-zone

moisture uptake

Modify soil

moisture recycling

Plant species

competition

Modify soil

organic matter

Soil texture

Soil albedo

Local/regional climate

Moist convection process, mesoscale circulation (sea/land–land breeze)

Moisture/carbon/nitrogen allocation in soil

Figure 6.33 Increased carbon dioxide on biological activity as it influences

weather. From Pielke et al. (2006a).

6.7 Conclusion

Figures 6.32 and 6.33 illustrates the pathways that land-use/land-cover change

and vegetation dynamics in response to increased concentration of carbon dioxide

act as climate forcings and feedbacks. Table 6.2 provides a summary list of

additional examples of papers which document the role of these climate forcings

and feedbacks in the climate system.

Table 6.2 Regional land-use/land-cover assessments: effect on weather and

climate

Geographic region Reference

Africa Brovkin et al. (1998, 2004), Claussen (1997), Claussen and

Gayler (1997), Claussen et al. (1999, 2002, 2003), Eltahir

(1996), Eltahir and Gong (1996), Gong and Eltahir (1996),

Irizarry-Ortiz et al. (2003), Kiang and Eltahir (1999), Kim and

Eltahir (2004), Maynard and Royer (2004), Pinty et al. (2000),

Polcher and Laval (1994a,b), Snyder et al. (2004a), Wang and

Eltahir (2000a,b,c,d,e, 2002), Wang et al. (2004), Xue et al.

(1990, 2004a), Zhang et al. (2001), Zheng and Eltahir (1997,

1998), Zheng et al. (1999)

Alaska, USA Mölders and Olson (2004)

Amazon Baidya Roy and Avissar (2002)

, Chagnon and Bras (2005),

Chagnonetal. (2004),Chenetal. (2001),Costaand Foley(2000),

Conclusion 145

Dickinson and Kennedy (1992), Dirmeyer and Shukla (1994),

Dolman et al. (1999), Durieux et al. (2003)

, Eltahir and

Bras (1993a, 1994a,b), Eltahir et al. (2004), Gash and

Nobre (1997)

, Gedney and Valdes (2000), Hahmann and

Dickinson (1997), Henderson-Sellers and Gornitz (1984),

Henderson-Sellers et al. (1993), Kleidon and Heimann (1999,

2000), Kleidon and Lorenz (2001), Lean and Rowntree (1997),

Lean and Warrilow (1989), Mylne and Rowntree (1992), Negri

et al. (2004)

, Nobre et al. (1991), Oyama and Nobre (2003,

2004), Polcher and Laval (1994a,b), Shukla et al. (1990), Silva

Dias et al. (2002), Wang et al. (2000), Werth and Avissar

(2002), Zeng (1998), Zeng et al. (1996), Zhang et al. (1996a,

2001)

Atlanta, Georgia, USA Shepherd et al. (2004)

Australia Eberbach (2003)

, Gero et al. (2006), Gordon et al. (2003)

Huang et al. (1995a,b), Lyons (2002), Lyons et al. (1996),

Miller et al. (2005), Narisma and Pitman (2003, 2004, 2006),

Narisma et al. (2003), Peel et al. (2005), Pitman and Narisma

(2005), Pitman et al. (2004), Ray et al. (2003), Timbal et al.

(2002)

, Timbal and Arblaster (2006)

Boreal Forest Betts (2000), Bonan et al. (1992), Brovkin et al. (2003),

Steyaert et al. (1997), Vidale et al. (1997)

Brazil Oyama and Nobre (2004)

Canadian Prairie Hanesiak et al. (2004), Raddatz (1998, 1999, 2000

, 2003,

2005), Raddatz and Cummine (2003)

Central Africa Eltahir et al. (2004), Mylne and Rowntree (1992), Werth and

Avissar (2005)

Central America Ray et al. (2006)

China Gao et al. (2003), Ming and Xinmin (2002)

, Sen et al. (2004a,

b), Simmonds et al. (1999)

, Suh and Lee (2004)

, Wang et al.

(2003), Wang et al. (2004), Wei and Fu (1998), Xue (1996),

Xuejie et al. (2003)

, Zhao and Pitman (2005), Zheng et al.

(2002)

Colorado, USA Borys et al. (2003), Chase et al. (1999)

, Hanamean et al.

(2003)

, Pielke and Zeng (1989)

, Segal et al. (1988, 1989)

Stohlgren et al. (1998)

Costa Rica Lawton et al. (2001), Nair et al. (2003)

East Asia Suh and Lee (2004)

East of 100



, USA Bonan (1999)

Eurasian Boreal Forest Betts (2000), Douville and Royer (1997)

Europe Dolman et al. (2004), Gaertner et al. (2001), Gates and Liess

(2001), Heck et al. (1999, 2001)

Florida, USA Marshall et al. (2003, 2004a,b), Pielke et al. (1999b)

Germany Mölders (1998, 1999a, 2000a,b), Mölders and Rühaak (2002)

Great Plains, USA Adegoke et al. (2006) Cheng and Cotton (2004), Eastman et al.

(2001a,b), Grossman et al. (2005), Holt et al. (2006) Mahmood

and Hubbard (2002, 2003)

, Mahmood et al. (2004

, 2006)

Muhs and Holliday (1995), Niyogi et al. (2006), Segal et al.

(1995)

, Strack et al. (2004)

146 Other land-use/land-cover changes

Table 6.2 (cont.)

Geographic region Reference

Houston, Texas, USA Jin et al. (2005), Shepherd and Burian (2003)

India Bosilovich and Schubert (2002)

, Douglas et al. (2006),

Niyogi et al. (2003)

Indonesia Polcher and Laval (1994a)

Israel (southern) De Ridder and Gallée (1998)

, Otterman et al. (1990)

Japan Ichinose (2003), Suh and Lee (2004)

Kansas, USA Clark and Arritt (1995)

Korea Suh and Lee (2004)

Mexico Asner and Heidebrecht (2005)

Middle Europe Millán et al. (2005), Mölders (1999b)

Midlatitudes Mahfouf et al. (1987)

, Segal et al. (1988)

, Seth and

Giorgi (1996)

Midwest, USA Bonan (2001), Carleton et al. (2001)

, Changnon et al.

(2003)

, Diffenbaugh (2005), Georgescu et al. (2003),

Rozoff et al. (2003), Weaver and Avissar (2001, 2002)

Mississippi River Basin, USA Twine et al. (2004)

Nebraska, USA Adegoke et al. (2003)

New York, USA Jin et al. (2005)

North Africa Cathcart and Badescu (2004), Xue (1997)

North America Bosilovich and Schubert (2002)

, Segal et al. (1998)

Skinner and Majorowicz (1999)

Oklahoma, USA Basara and Crawford (2002)

, McPherson et al. (2004)

Oklahoma and Kansas, USA Weaver and Avissar (2001)

Phoenix, Arizona, USA Diem and Brown (2003)

Puerto Rico van der Molen et al. (2005)

Regional paleo-studies Rivers and Lynch (2004)

Sahel Charney (1975), Clark et al. (2001, 2004), Claussen and

Gayler (1997), De Ridder (1998), Dolman et al. (2004),

Hutjes et al. (2003), Nicholson (2000), Nicholson et al.

(1998), Taylor et al. (2002), Wang and Eltahir (2000a),

Wang et al. (2004), Xue (1997), Xue and Shukla (1993),

Xue et al. (2004b), Zeng et al. (1999)

Sonoran Desert, Mexico Balling (1988)

Southeast Asia Henderson-Sellers et al. (1993), Kanae et al. (2001), Sen

et al. (2004a), Zhang et al. (2001)

South America Beltran, (2005), Cook and Vizy (2006), Eltahir and

Bras (1993a,b, 1994a,b), Eltahir and Humphries (1998);

Eltahir and Pal (1996), Oyama and Nobre (2003), Vizy

and Cook (2005), Wang et al. (1998, 2000)

Spain Hasler et al. (2005), Miao et al. (2003)

Tennessee, USA Banta and White (2003)

Texas, USA Barnston and Schickedanz (1984)

, Beebe (1974)

Moore and Rojstaczer (2002), Shepherd et al. (2002)

Tropical Savannas Hoffmann et al. (2002)

United States Alig et al. (2004), Baidya Roy et al (2003)

Bonan (1997, 1999), Christy et al. (2006), Civerolo

et al. (2000)

, Copeland et al. (1996), Givati and

Additional reading 147

Rosenfeld (2004), Hale et al. (2006), Kalnay and Cai (2003),

Kalnayetal.(2006), Limetal.(2005), Panetal.(2004), Shepherd

et al. (2002), Xue et al. (1996, 2001)

West Africa Cathcart and Badescu (2004), Mohr et al. (2003)

, Xue and

Shukla (1993), Zeng et al. (2002), Zheng and Eltahir (1997,

1998

)

Other studies of

mesoscale effects

Avissar and Chen (1993), Avissar and Liu (1996), Chase et al.

(1999), Chen and Avissar (1994a), Goutorbe et al. (1994),

Lynn et al. (1995a), Mahfouf et al. (1987), Mahrt et al. (1994),

Ookouchi et al. (1984), Pielke et al. (1991b), Segal and Arritt

(1992), Segal et al. (1988), Stohlgren et al. (1998), Taylor

et al. (1998), Wang et al. (1997, 1998), Weaver and Avissar

(2001)

Information was provided by Dr. Rick Raddatz.

Additional reading

There are several useful texts that are available to provide additional in-depth

information on the material in this chapter. These include:

Arora, V., 2002. Modeling vegetation as a dynamic component in

soil–vegetation–atmosphere transfer schemes and hydrologic models. Revs.

Geophys., 40, 1006, doi:10.1029/2001RG 000103.

Bonan, G. B., 2002. Ecological Climatology: Concepts and Applications. New York:

Cambridge University Press.

Dolman, A. J., A. Verhagen, and C. A. Rovers, 2003. Global Environmental Change and

Land Use. Dordrecht, The Netherlands: Kluwer.

iLEAPS, 2004. Integrated Land Ecosystem-Atmosphere Processes Study (iLEAPS): The

IGBP – Land-Atmosphere Project. Science Plan and Implementation Strategy.

Available online at: www.atm.helsinki.fi/ILEAPS/index.php?page=draft

Lambin, E. F., H. J. Geist, and E. Lepers, 2003. Dynamics of land-use and land-cover

change in tropical regions. Ann. Rev. Environ. Resources, 28, 205–241.

Lee, T. J., R. A. Pielke, and P. W. Mielke Jr., 1995: Modeling the clear-sky surface

energy budget during FIFE87. J. Geophys. Res., 100, 25585–25593.

Lepers, E., E. F. Lambin, A.C. Jenetos, et al., 2005. A synthesis of information on rapid

land-cover change for the period 1981–2000. BioScience, 55, 115–124.

McCumber, M. C., and R. A. Pielke, 1981. Simulation of the effects of surface fluxes of

heat and moisture in a mesoscale numerical model. I. Soil layer. J. Geophys. Res.,

86, 9929–9938.

Northern Eurasia Earth Science Partnership Initiative (NEESPI), 2004. NEESPI Science

Plan, P. Y. Groisman and S. A. Bartalev, eds. Available online at NEESPI.gsfc.

nasa.gov/

Orme, A. R. (ed.), 2002. Physical Geography of North America. Oxford, UK: Oxford

University Press.

Pitman, A. J., 2003. Review: The evolution of, and revolution in, land surface schemes

designed for climate models. Int. J. Climatol., 23, 479–510.

Waring, R. H., and S. W. Running, 1998: Forest Ecosystems: Analysis at Multiple

Scales, 2nd edn. San Diego, CA: Academic Press.

Concluding remarks regarding deliberate and

inadvertent human impacts on regional weather and

climate

We have seen that there is considerable evidence suggesting that anthropogenic

activity, either in the form of constructing major urban areas, changing natural

landscape to agricultural and grazing areas, or emission of particles and gases,

has contributed to changes in weather and climate on the regional scale. There

is a diversity of views on the demonstration of this evidence, however, with a

distinction between deliberate and inadvertent weather and climate changes. It

is curious, for example, that the scientific community has accepted the rainfall

change results obtained in studies such as METROMEX as being valid, yet has

questioned the validity of cloud-seeding-induced changes in rainfall inferred from

well-designed, randomized cloud seeding experiments.

The answer to this paradox lies in human psychology. As an example, Dr. Stan

Changnon described a conversation he had with Dr. John Tukey, one of the

world’s leading statisticians, following a meeting of the Weather Modification

Advisory Board in the 1990s. Stan asked John why the statisticians had been very

critical of attempts to prove planned weather modification of clouds and rainfall

was successful, yet were not so critical of inadvertent weather modification (i.e.,

the cities are not randomized). John looked up at Stan and said, “Well, Stan, in the

end it is just a lot more believable that a big city can cause clouds, rain, and hail

than it is that a small amount of seeding material can.” In other words, no matter

how objective we attempt to be, a certain amount of subjectivity is involved in

accepting the results of any scientific study.

In summary, while there is considerable evidence supporting the hypothesis that

human activity is inadvertently modifying weather and climate on the regional

scale, much more research is required to pinpoint the causes of inferred human-

related weather anomalies and to strengthen the statistical inferences and physical

understanding.

Unfortunately, United States federal funding of inadvertent weather modifica-

tion fell sharply in the 1980s along with that of deliberate weather modification.

148