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OCR for page 59
J
TERRESTRIAL HYDROLOGY
AND VEGETATION FEEDBACKS
SUMMARY
Feedback processes over land are critically important to understanding
the climate response over land and its effect on humans. The responses of
the hydrologic and energy cycles over land play a critical role in determining
the impacts of climate change on water resources, carbon stocks, and
agriculture, yet these responses vary widely among different climate models.
Unfortunately, basic climate processes such as the response of the land-
atmosphere system to diurnal variations of insolation are poorly simulated in
current climate models. Snow and ice melting and their associated
hydrologic and radiative consequences tend to be poorly simulated, and
dynamic vegetation modeling is in its very early stages.
We recommend an integrated analysis of the diurnal and annual cycles
of the energy, water (in all its phases), and carbon budgets at the land-
surface and through the atmospheric boundary layer for different ecosystems
and climatic regimes, including managed ecosystems like irrigated cropland.
This analysis aimed at improving theoretical understanding and model
parameterizations needs to fully integrate land and atmosphere processes
and use carefully designed observational metrics to test modeled processes,
which must be robust in the face of time-varying land surface properties.
Sustained multiyear observations of terrestrial ecosystems, their functioning,
and their role in the climate system should be encouraged, to contribute to
the development and improvement of process-oriented vegetation models for
use with climate models.
59
OCR for page 60
60
UNDERSTANDING CLIME TE CHANGE FEEDBACKS
TERRESTRIAL HYDROLOGY
The global, annual-mean surface temperature is the most widely used
first-order measure of climate change. However, in assessing the impact of
climate change the water balance over land is at least as important.
Terrestrial surface hydrologic changes are important for human requirements
such as drinking water, sanitation, agriculture, transportation, and energy
supply. These changes are also important for the response of natural
ecosystems on land to human-induced climate change. The variables used to
measure changes in the surface water balance are precipitation, evaporation,
and runoff rates, as well as soil and surface water storage. These quantities
are related to temperature, wind, cloudiness, vegetation characteristics, and
other climate system variables.
For this report the primary interest in terrestrial hydrology is its role in
climate change feedbacks. In the tropics, interactions among land hydrology,
vegetation, and surface energy balance can foster feedback mechanisms that
may cause expansion or contraction of deserts, for example. In middle
latitudes interactions between winter snowfall, spring snowmelt, and
summertime convection can lead to potential changes in water availability
during the growing season that may pose a substantial threat to agriculture.
Earlier snowmelt can lead to more rapid drying, reduced summertime
precipitation, and increased surface temperature over land. These feedbacks
and the response of mid-latitude land hydrology to climate change and
global warming are highly uncertain. Better characterized or reduced
uncertainty in projections of the response of land hydrology to global
warming would have important implications for the development of
mitigation and adaptation strategies.
The feedbacks between soil water, evaporation, precipitation, and runoff
are an integral part of the hydrological cycle over land, as are the interaction
of vegetation and the frozen hydrology (ground and snow) at high latitudes,
with their impacts on albedo and the availability of water for evaporation.
Climate change, driven globally by the global rise of greenhouse gases, will
have regional impacts on this hydrological cycle, differing across latitude
and across continents. Currently our confidence in regional projections is
limited by our lack of understanding of the processes and feedbacks
controlling the precipitation-evaporation difference, both over land (where it
is fundamental to the long-term drift of the hydrological cycle) and over the
ocean (where it is one key component impacting the surface energy budget
and changes in the thermohaline circulation). Improving confidence in
regional temperature and freshwater resource projections is also intimately
OCR for page 61
TERRESTRIAL HYDROLOGYAND BEGETS TION FEEDBACKS
61
linked to a better understanding of the coupling between surface processes
and the atmospheric boundary layer.
In addition to the above concerns, recent estimates are that over 30
percent of the discharge of the world's rivers is actively managed. This has
occurred through the construction of some 40,000 major dams and diversion
structures, which have been capable of changing the hydrologic regimes of
the world's major rivers and potentially the global water cycle. The
feedbacks between the managed portion of the terrestrial water cycle and
other components have received virtually no attention, but are potentially
important because the effects of water management on natural hydrographs
are far larger than those projected to be caused by climate change. These
changes in the discharge regimes of large rivers are known to have changed
ocean circulation in the vicinity of river mouth estuaries, and perhaps at
larger scales. Furthermore, changes in vegetation, many of which are related
to water management, are known to have caused changes in the local cycling
of moisture in the land-atmosphere system (e.g., Stohlgren et al., 1998), and
anthropogenic changes in land cover due to management have been shown
to have affects at global scales (Chase et al., 1996, 2000~.
Reducing model uncertainty can be achieved in part through improved
understanding and projections of the regional long-term drift of the
hydrologic cycle over land. These improvements are fundamental to
projecting ecosystem dynamics on decadal timescales. At present, coupled
global models differ widely in their regional forecasts for future trends in the
hydrologic cycle. The U.S. Water Cycle Initiative (USGCRP, 2001) has
outlined several important science goals that need to be addressed to
improve our ability to model the global and regional water cycle. A focused
research effort is required to improve these models.
From a scientific perspective this area of research is ripe for progress.
Indeed, in the past five years considerable progress has been made in
understanding soil water feedback, in making soil water measurements, and
in the development of land surface data assimilation systems that indirectly
provide soil water fields on continental to global scales. The challenge ahead
is synthesis, because the water cycle plays such a central role and it interacts
directly with much of the climate system, and in particular over land with
the energy and carbon cycles.
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62
Soil Water Feedbacks
UNDERSTANDING CLIMATE CHANGE FEEDBACKS
Overview of Terrestrial Hydrology Feedbacks
The land-surface reservoirs of available soil water are small compared
to the ocean reservoir, typically of order 0.1-0.6 m of water. However, their
role is crucial to the surface climate over land because evaporation from the
near surface soil layer and transpiration of water extracted by vegetation
from their root zone is a major component of the surface energy balance.
Over wet soils the daily mean Bowen ratio (the ratio of the sensible to latent
heat flux) may be of order 0.5, while over dry soils when the vegetation
experiences water stress, the Bowen ratio may exceed 1. In turn the
increased evaporation over wet soils can lower maximum surface
temperature by several degrees.
A feedback arises because increased surface evaporation over large land
areas gives rise to increased precipitation (e.g., Beljaars et al., 1996), which
maintains soil water levels. This is primarily a feature of the warm season,
and wet regions of the tropics. Over the continents as a whole, precipitation
minus evaporation (P-E) is positive, which contributes the runoff of fresh
water to the oceans. Correspondingly E-P is positive over the oceans.
However, the balance between P and E varies widely, both spatially and
temporally. The monsoon circulations concentrate the flux of moisture from
ocean to continents. Over large regions of land in summer (remote from the
summer monsoon) P is more closely in balance with E. There is also a large
seasonal cycle in which winter precipitation adds to soil water reservoirs in
mid-latitudes and to snow accumulation at high latitudes, and this is drawn
down in spring and summer by both runoff and evaporation. The diurnal
cycle of precipitation and cloud is also involved, because transpiration
depends on daytime solar radiation (and thus involves critically the
shortwave cloud feedback), while the equilibrium temperature of the land-
surface (which determines outgoing longwave radiation) is sensitive as well
to the impact of clouds on the long wave balance, especially at night.
Although it seems clear that warming will accelerate the hydrological
cycle, the net change of P-E and runoff over land, particularly in the warm
season for specific regions, remains uncertain. At high latitudes it is possible
that the likely increase in winter precipitation will lead to increased
snowpack and spring runoff, but the impact on summer soil water,
evaporation, and precipitation remains uncertain.
The complex couplings among precipitation, evaporation, soil water,
runoff, the cloud fields, net radiation balance, and the vegetation on the
diurnal timescale have not yet been modeled satisfactorily for the present
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TERRESTRIA L HYDR OL OG Y AND VEGE TA TION FEEDBA CKS
63
climate. Typically this leads to fundamental errors in the diurnal cycle of
precipitation (Bests and Jakob, 2002~. The diurnal time scale, together with
the continental scale circulation dynamics and the seasonal cycle, must be
accurately modeled so that confidence can be assigned to projections of land
hydrology changes associated with global warming.
Snow-Albedo Feedback
One of the most important climatic characteristics of snow is its albedo.
Fresh snow on a fully covered surface has an albedo of approximately 0.8.
Aging of the snow will reduce this to about 0.4. Snow in tree-covered
landscapes has an albedo of about 0.2 to 0.4 depending on the vegetation
cover type.
In the fundamental snow-albedo feedback a decrease in snow extent
decreases the surface albedo which tends to increase surface temperature.
,
These changes can affect large-scale circulation and planetary albedo which
in turn, can affect subsequent snow precipitation and melt rates. There are
many confounding factors to this picture, including the effects of vegetation
and snow age.
Trees and other vegetation can protrude over snow and mask its high
albedo. As a result treeless areas have a higher albedo when snow is on the
ground than do forests. Numerous climate model studies have found that the
presence of the boreal forest warms climate compared to tundra (Bonan et
al., 1992; Douville and Royer, 1996~. Forest and tundra ecosystems also
differ in how they partition net radiation into sensible and latent heat fluxes.
For example, albedo differences in snow-covered and adjacent snow-free
forests can result in local energy circulations with advection of energy to the
forests (e.g., Taylor et al., 1998)
At the regional scale the removal of snow cover may affect the thermal
and dynamical structure of the atmosphere, but the temporal persistence of
these effects is uncertain (Yeh et al., 1983~. To date, one of the strongest
pieces of evidence of a snow cover and weather feedback is the connection
between springtime air temperature biases (5-10°C low in ECMWF weather
predictions due to specified high-latitude snow albedo, which was biased
high (by approximately 0.4) in the model (Viterbo and Betts, 1999~. This
result demonstrates the effect of large-scale snow cover on near surface air
temperature, with the correction of the albedo bias correcting the air
temperature bias.
In general the existence of a feedback mechanism between snow cover
extent and continental- to global-scale weather and climate requires that
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64
UNDERSTANDING CLIA~1TE CHANGE FEEDBACKS
snow processes affect atmospheric circulations at these scales. There are
model results that suggest such an effect. For example, the interannual
variations of the Asian summer monsoon rainfall have been significantly
correlated with the tropical sea surface temperature and the Eurasian snow
cover anomalies (Bamzai and Shukla, 1999, Corti et al., 2000~.
In general, current models represent mean global snow cover fairly well
but are less accurate in representing interannual snow cover variability. In
general even off line terrestrial hydrologic models, forced with observed
meteorology and radiation, tend to underestimate the observed variability in
the record. The biggest difference in the predictions among models occurs in
snow transition regions. Models do fairly well in the snow accumulation
season but differ greatly from observations in the melt season, resulting in
different predicted time of end-of-melt that varies by two to three weeks.
This can affect the subsequent prediction of the onset of vegetation activity.
The largest modeling challenge related to snow melt is representing sub-
grid snow cover at GCM grid scales. Accurately estimating the albedo of
retreating snow cover involves accounting for factors such as snow
patchiness and snow age. The modeling of these effects is well understood,
but has mostly been carried out over idealized domains where the contrasts
may not represent the variability observed in natural landscapes. The
modeling of natural domains requires high-resolution modeling and the
· ~ .
accompanying torc~ngs.
In validating model predictions against observations a significant
problem is the observational bias that results from the placement of
instrumentation in clearings and the rather different snow dynamics of
forested and cleared areas.
At the other end of the scale spectrum global modeling assessments of
the snow-climate feedback have been rather limited and the results show
discontinuous areas having correlations between snow extent and the Indian
monsoon rainfall. The scope of these studies should be expanded to
rigorously diagnose large-scale effects of snow cover on circulation and the
planetary albedo. An important part of this work is the boundary layer
coupling between the snow-covered surface and overlying atmosphere.
Modeling the melting of snow in springtime is important to correctly
simulating the role of snow in climate feedbacks over land. Key issues in
snow melt modeling include
· improving space-time distribution of snow. During the snow
accumulation period most model prediction problems are largely attributable
to precipitation and temperature surface forcing, while during snow ablation
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TERRESTRIAL HYDROLOGYAND VEGETATION FEEDBACKS
65
periods poor snow model predictions are more closely related to the model
parameterizations related to surface energy transfer.
· evaluating errors in space-time extent. There is a need to evaluate and
improve the quality of data; use this data for error diagnostic studies with a
focus on transient zones at regional and continental scales; and better utilize
offline evaluation methods.
· developing better global databases for model parameters (e.g.,
surface roughness, vegetation solar radiation extinction, canopy closure,
snow patchiness functions).
· developing point or small area datasets for offline model evaluation
across a range of snow climatologies and vegetation types, and for the
evaluation of new model parameterizations.
VEGETATION FEEDBACKS
The traditional view of terrestrial vegetation is that community
composition and ecosystem structure are determined by climate. However,
this is only part of the interaction of ecosystems with climate. Terrestrial
ecosystems affect climate through exchanges of energy, water, momentum,
CO2, and other radiatively important atmospheric gases. Changes in
community composition and ecosystem structure alter albedo, surface
roughness, stomata! physiology, leaf area, rooting depth, and nutrient
availability and in doing so alter surface energy fluxes, the hydrologic cycle,
and biogeochemical cycles. As a result, changes in ecosystem structure and
function and the replacement of one ecosystem with another in response to
climate change feed back to influence climate. The IPCC TAR has identified
changes in land cover as a potentially important climate feedback.
Most studies of vegetation feedbacks have focused on biogeophysical
processes related to energy, moisture, and momentum exchange with the
atmosphere. Biogeochemical feedbacks are only now being included in
climate models (Cox et al., 2000; Friedlingstein et al., 2001~. This review
focuses on biogeophysical feedbacks, considering a continuum of processes
and time scales from physiological (minutes) to phonological (seasons) to
vegetation dynamics (decades to hundreds of years).
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66
Stomata Feedback
UNDERSTANDING CLIMATE CHANGE FEEDBACKS
Overview of Vegetation Feedbacks
The partitioning of net radiation into sensible and latent heat fluxes by
vegetation is regulated in part by canopy conductance. Studies of the
physiological response of plants to short-term exposure to enhanced CO2
concentrations routinely find reduced stomata! conductance and greater
photosynthesis. Climate model simulations in which stomata! conductance
decreases with a doubling of atmospheric CO2 routinely show decreased
latent heat flux, increased sensible heat, and surface warming over large
vegetated regions in summer (e.g., Sellers et al., 1996~. In general, the
physiological effects of doubled CO2 amplify the warming associated with
the radiative effects of doubled CO2.
Previous climate model studies highlight the potential for physiological
feedbacks from vegetation (e.g., Sellers et al., 1996~. It is quite likely that
changing atmospheric CO2 concentration will alter the physiology of plants
and through this affect climate. However, we cannot yet quantify this
feedback with certainty and rank it relative to other climate feedbacks.
Uncertainty in its magnitude and importance arise for several reasons. First,
physiological processes operating at the scale of an individual leaf need to
be scaled to a canopy of leaves and then to a landscape of thousands of
plants. There are few observations to guide this scaling, as most studies of
stomata! conductance and its response to CO2 are obtained from leaf
measurements. Second, most studies examine the short-term response of
plants to CO2. Long-term acclimation to high CO2 may alter the short-term
reduction in stomata! conductance. Third, the reduction in stomata!
conductance observed in the laboratory may not be realized in the field,
where many other environmental factors (e.g., dry soil, low nutrient
availability) also limit photosynthesis. Finally, atmospheric CO2 is also
known to alter the allocation of carbon to the growth of foliage, stem, and
root biomass and the chemical quality of plant material. This is likely to
affect climate by changing, for example, the amount of leaf area from which
heat and moisture can be exchanged with the atmosphere or by changing the
amount of carbon stored in the soil.
Leaf Area Feedback
The seasonal emergence and senescence of leaves on deciduous trees
alters albedo and sensible and latent heat fluxes and in doing so alters
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T E R R E S T R I A L H Y D R O L O G Y ~ N D V E G E T A T I O N F E E D B A C K S
67
surface climate, including temperature and transpiration (Fitzjarrald et al.,
2001; Schwartz, 1999~. In the eastern United States, springtime air
temperatures are distinctly different after leaves emerge (Schwartz, 1992,
1996; Schwartz and Karl, 1990~. This temperature discontinuity over a
period of less than a few weeks is related to increased transpiration upon leaf
emergence that cools and moistens air. A similar distinct seasonal pattern to
air temperature coinciding with the absence or presence of leaves on
deciduous trees is seen in west central Canada (Hog" et al., 2000~.
Because of the importance of foliage in regulating surface climate,
improved representation of leaf area and its phonology are being
implemented in climate models. In general, higher leaf area increases
evaporation over vegetated regions in summer provided there is sufficient
soil water (e.g., Buermann et al., 2001~. As a result surface temperature
cools and precipitation increases. Prognostic models of leaf area in which
the amount of foliage depends on temperature, precipitation, and plant
productivity are being included in the land models used with climate models.
One study with interactive leaves found increased air temperature and
reduced evaporation and precipitation over extratropical regions of the
Northern Hemisphere in summer as result of lower leaf area (Dickinson et
al., 1998~.
As with stomata, leaf area must be considered a "known unknown" in its
magnitude and importance as a climate feedback. Observations of
temperature and leaf phonology demonstrate a change in temperature with
leaf emergence, but prognostic leaf phonology is a new process for land-
surface models. There is not a long history of climate model experiments to
demonstrate the robustness of this feedback among climate models or to
determine the key ecological processes regulating leaf area in a coupled
climate-vegetation model.
Biogeography Feedback
Vegetation changes naturally over time in response to recurring
disturbances and also in response to climate change. Fires, insect outbreaks,
and windstorms that kill large tracts of trees initiate a process of revegetation
and ecosystem recovery known as plant succession. A forest, for example,
may undergo successive transformation from bare ground to herbaceous
species to shrubs to young forest to mature forest following fire. Climate
change that may, for example, convert a forest to grassland is superimposed
on this successional development. This vegetation dynamics and change
from one vegetation type to another alters numerous surface properties such
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UNDERSTANDING CLIAL4TE CHANGE FEEDBACKS
as albedo, roughness, stomata! physiology, leaf area, and rooting depth and
in doing so can alter climate.
The impact of vegetation dynamics on climate is seen regionally in the
Sahel of North Africa and along the boreal forest-tundra ecotone.
Precipitation limits the northward advancement of grasses and shrubs into
the Sahara Desert. Temperature limits the northern extent of trees into
tundra. In both these regions climate model simulations show amplification
by vegetation of the climate response to changes in precipitation or
temperature. Expansion of grasses and shrubs into desert in response to
enhanced summer precipitation results in more precipitation (Claussen et al.,
1999; de Noblet-Ducoudre et al., 2000; Kutzbach et al., 1996~. The boreal
forest warms climate compared to tundra as a result of the lower winter
albedo of forest (Bonan et al., 1992; Foley et al., 1994~.
Global vegetation models have been developed to allow interactive
coupling of climate and vegetation. One approach, known as asynchronous
equilibrium coupling, takes advantage of the relationships between climate
and biogeography to interactively change vegetation cover (Claussen, 1994~.
Climate is simulated with an initial vegetation cover. This climate is used in
a biogeography model to simulate the geographic distribution of vegetation.
This map is then input to the climate model to obtain a new climate. Climate
is iterated in this manner several times until a stable solution is obtained.
Another type of model, known as a dynamic global vegetation model,
explicitly simulates transient vegetation dynamics (Foley et al., 1998, 2000~.
Coupled climate-vegetation models show that vegetation feedback
amplifies the climate response to solar radiation or atmospheric CO2. For
example, the colder climate as a result of reduced solar radiation and lower
atmospheric CO2 some 115,000 years ago is not in itself enough to initiate
an ice age. However, the associated reduction in the geographic extent of the
boreal forest and the expansion of tundra due to the cold climate produces
additional cooling that is sufficient to initiate an ice age (de Noblet et al.,
1996~. Coupled climate-vegetation models highlight the importance of the
beeline in reinforcing the cold high-latitude climate of the last glacial
maximum 21,000 years ago and the high-latitude warming 6,000 years ago
(Kubatzki and Claussen, 1998; Levis et al., 1999; Texier et al., 1997~. Other
studies show that changes in the geographic extent of vegetation enhance the
orbitally induced summer monsoon 6000 years ago in North Africa (de
Noblet-Ducoudre et al., 2000; Doherty et al., 2000; Texier et al., 1997~. The
doubling of atmospheric CO2 from pre-industrial levels is likely to result in
changes in ecosystem structure and function in response to altered
temperature, precipitation, and CO2 fertilization. Climate simulations with
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TERRESTRIAL HYDROLOGYAND VEGETA TION FEEDBACKS
69
coupled climate-vegetation models show large changes in climate as a result
of vegetation changes (Bests et al., 1997, 2000; Levis et al., 2000~.
As with stomata and leaf area, the inclusion of interactive vegetation in
climate models is relatively new. Initial work with these models has
demonstrated the potential for large feedbacks with climate. Future work
must demonstrate the robustness of these feedbacks and reduce the
uncertainty in these simulations.
Key aspects of the required research strategy are discussed below.
DEVELOPING A SCIENTIFIC STRATEGY
As described in the previous sections, several potential feedbacks exist
between vegetation and climate, including radiative (albedo), physiological
(stomata), micrometeorological (sensible and latent heat), hydrological
(snow, soil water), biogeochemical (carbon and other greenhouse gases), and
ecological (leaf area, biogeography). These are often viewed as separate
areas of research. In particular, our understanding of fundamental vegetation
processes and their inclusion in climate models suffers from the broad
multidisciplinary scope of the potential interactions. There is not a
coordinated research agenda to understand and model their potential
feedbacks.
We still lack the simplified theoretical models needed to generalize our
understanding of the feedbacks between the coupled energy and water cycles
across different climatic regimes. Theoretical work on the diurnal cycle of
the coupled land-surface-convective boundary layer system for different
ecosystems and seasons would lead to improved understanding of this basic
climatic control on cloud, radiation, and water cycle feedbacks over land. In
addition, more work on the coupling of soil water, resistance to evaporation,
lifting condensation level, and cloud base (observable Tom the ground by
lidar ceilometers) would deepen our understanding of the land-surface and
soil water controls on atmospheric subsaturation, cloudiness, and
precipitation. Theoretical work on feedbacks and other interactions between
ecosystems, biogeochemistry, and hydroclimatic processes at a very wide
range of time and space scales also requires further development.
Progress in understanding terrestrial feedbacks depends critically on
both systematic analysis of data generated by advanced, integrated
observational datasets, and on careful testing and improvement of coupled
modeling systems. Advancements in understanding of the processes
responsible for terrestrial hydrology and vegetation feedbacks could be
greatly facilitated by a program of integrated observations and analysis of
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UNDERSTANDING CLIME TE CHANGE FEEDBACKS
the diurnal and seasonal cycles of the energy, water, and carbon budgets at
the land-surface and through the atmospheric boundary layer. In addition,
longer-term measurements and analyses of interannual ecosystem and
hydrologic variability are important.
An important focus of research on terrestrial feedbacks should be on
improving the parameterization of dynamic vegetation in climate models.
This work must treat energy, water, carbon, and nutrients as a single system
rather than as disciplinary components. Observations must be made to better
understand the natural processes, improve the parameterizations, and test
those parameterizations in coupled models. By focusing systematically on
this joint observational and modeling problem, the various scientific
communities that monitor, study, and model terrestrial vegetation may be
spurred toward better integration in much the same way that coupled
atmosphere-ocean models led to integration of atmospheric and oceanic
sciences.
As discussed below, a global network of surface flux tower sites exists
(Baldocchi et al., 2001), but many analyses have a narrow focus on, for
example, the carbon balance at the site rather than the full energy, water, and
carbon balance and their coupling to the boundary layer, and its cloud field.
It is rare for example that sites measure boundary layer height, structure,
cloud base and cloud cover (even though this can be done remotely) or the
soil water profile. Yet the photosynthetic processes are tightly linked both to
the soil hydrology, the surface energy balance (which depends on the clouds
and the radiation field, whether direct or diffuse), as well as the coupling to
the boundary layer over the diurnal cycle. Our ability both to measure (the
fluxes) and to model the nighttime stable boundary layer is still
unsatisfactory, and progress probably requires a careful study of the coupled
water, energy, and CO2 budgets.
Therefore, an integrated analysis should evaluate and improve model
representation of physical processes known to affect the diurnal, seasonal,
and interannual cycles, using detailed field site data, as well as routine
observations and simplified models.
Observations
Perhaps the most fundamental problem regarding the understanding of
vegetation feedbacks is a lack of global datasets with which to evaluate
existing land-surface processes in climate models. In addition to being
critical for understanding terrestrial climate feedbacks, observations of
essential ecosystem variables, such as blame type, net primary production,
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TERRESTRIAL HYDROLOGY AND VEGETA TION FEEDBACKS
71
and carbon stores, are integrators of climate and therefore valuable
diagnostic measures of models' overall ability to simulate surface climate.
Unfortunately the existing observational efforts fall short of what is needed.
Field programs such as FIFE (First International Satellite Land Surface
Climatology Project Field Experiment), BOREAS (Boreal Ecosystem-
Atmosphere Study), and LBA (Large-Scale Biosphere-Atmosphere
Experiment in Amazonia) provide tower flux data (e.g., sensible heat, latent
heat, CO2) but only for particular locales. The inclusion of interactive
vegetation provides additional ecological data, such as net primary
production, carbon storage, leaf area, and biogeography, with which to test
climate models.
The AmeriFlux network of permanent towers allows for sustained
multiyear observation of particular ecosystems (Wofsy and Hollinger, 1998~.
It is part of a global network known as FLUXNET (Baldocchi et al., 2001~.
However, without the broad multidisciplinary focus of FIFE, BOREAS, or
LEA many of these tower sites lack the suite of ancillary hydrological and
ecological data needed to understand and model the observed fluxes. Most
tower sites do not include measurements and analysis of the full energy,
water, and carbon balance and their coupling to the boundary layer, and its
cloud field. We recommend that these sites expand their focus to include
such interactions, which are important for climate models on the boundary
layer scale.
The National Science Foundation's Long Term Ecological Research
(LTER) program allows the longest (in some cases multi decadal) sustained
observation of particular ecosystems. These sites have been chosen to span
the range of global biomes (e.g., tundra, boreal forest, grassland, desert). The
focus of research is decidedly ecological, emphasizing community
composition, ecosystem structure, and their response to environmental
change. Some sites (e.g., Harvard Forest) have towers.
Observations of terrestrial ecosystems, their functioning, and their role
in the climate system must be sustained over multiyear periods if they are to
be of greatest use in the development and improvement of process-oriented
vegetation models for use with climate models. A network of such
observation sites spanning the range of global biomes is desirable. This
suggests that coordination between the AmeriFlux and LTER programs is
important to help ensure that a diverse set of blames is observed.
Measurements using aircraft, such as the recent CRYSTAL and
COBRA studies, should also be used to help diagnose the ability of global
models to simulate the budgets of water, energy, and carbon for river basins
and major ecosystems up to the continental scale. This work should involve
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UNDERSTANDING CLIMATE CHANGE FEEDBACKS
a tight integration of land and atmospheric measurements and data
assimilation with climate modeling.
To develop the observational basis to improve and test models, both the
modeling and remote-sensing communities must work together to better
define the vegetation parameters that are observable by satellite and that are
critical to modeling vegetation feedback in the climate system. Some of the
parameters that are emerging from a dialogue between these communities
are leaf area and its phonology. Multiyear leaf area index datasets have been
and are being developed for use with climate models (e.g., Buermann et al.,
2001~. These data products can be used as prescribed leaf area or as a
validation of prognostic leaf area (Dickinson et al., 1998, Buermann et al.,
2001~. Another key emerging data product is fractional tree cover, which can
also be used as an input to and validation of models (Bonan et al., 2002~.
Sustained monitoring of these parameters and extension of these records in
the past should be encouraged to allow the modeling community to quantify
the vegetation forcing of climate. At the global scale key satellite-derived
data products, such as leaf area index, must have at least monthly temporal
resolution to be of greatest use in improving and testing climate simulations.
In addition, the data products should continue to expand the record to help
better account for interannual variability in leaf area.
Much of the global evaluation of the surface climate is still based on 2-
m air temperature, humidity, pressure, wind, and precipitation interpolated
from station observations. However, many important components of the
surface water and energy budget are not routinely measured, and some that
are measured at selected experimental sites may not be freely available in
the public domain. The shortwave and longwave radiation balances are only
recorded at relatively few baseline radiation measurement sites, although
satellite-based estimates of the surface short-wave balance have achieved a
fair degree of accuracy. The surface fluxes of sensible and latent heat
(together with some components of the radiation balance) are measured on
flux towers at some 50 or more sites globally, although not all these data are
freely accessible. Up-scaling these measurements over carefully selected
stands of vegetation to give regional averages (of, say, evaporation) is not
straightforward. Estimates of regional evaporation can be made using river
basin hydrologic models from observations of precipitation and river runoff.
However, regional estimates of precipitation can only be derived from point
rain gages and calibrated radars, where available, or from satellite retrievals.
Consequently precipitation estimates also have considerable uncertainty and
may be biased low when precipitation is frozen.
Important subsurface variables, such as soil temperature and soil water,
are also not routinely measured, although they are now being measured in a
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TERRESTRIAL HYDROLOGYAND VEGETATION FEEDBACKS
73
few important networks, such as the Oklahoma Mesonet and some
AmeriElux sites. The measurement of the freeze-thaw of the surface soil
layer is now possible from satellite microwave sensors, but this product is
not yet routinely available. Satellites can measure snow cover, but the
important measurement of snow water equivalent still presents problems. All
satellite measurements of the soil and surface layers have difficulties under
forest canopies
A promising approach for developing global soil water fields is the
extension of the land data assimilation system (LDAS) pioneered at the
National Centers for Environmental Prediction (NCEP) for the regional Eta
model. At present, two groups (one in the United States and one in Europe)
are developing a global LDAS, using a mix of satellite and surface data to
provide the surface radiation budget and precipitation needed to force offline
a land-surface-vegetation-hydrology model, which will give subsurface
fields of temperature and moisture. Global cooperation is here essential since
not all the necessary data has been freely shared in real time in the past. The
future availability from satellite of global maps of near-surface soil wetness
will provide further useful input.
Modeling
Because many of the key variables, especially below the surface, are not
measured globally, the surface temperature, soil water, and surface energy
balance in data assimilation systems is largely a product of a fully coupled
land-surface-vegetation-atmosphere model, often constrained by the
observed atmospheric diurnal cycle of temperature and humidity near the
surface. In forecast and climate models the computed land-surface boundary
condition depends on a large number of parameterized submodels, all of
which are highly coupled and tend to exhibit considerable differences
between each other and with observations. The relationships among the
variables in these models is complex, and thus lack of knowledge in one area
can have cascading effects. For example, the surface radiation budget
depends on the model parameterizations for the cloud fields (which are not
explicitly resolved in a global model), while the cloud fields depend on the
dynamics, and the moisture field which in turn depends on moisture
transports and the surface evapotranspiration. Soil water depends not only on
model precipitation and evaporation (coupled to photosynthesis) but also on
the subsurface hydrology, which is strongly dependent on the lateral
heterogeneity.
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74
UNDERSTANDING CLIMA TE CHANGE FEEDBACKS
The fundamental links between land-surface hydrologic processes,
clouds, and precipitation depend in global models on the parametric
representation of sub-grid scale boundary layer and cumulus convection. No
completely satisfactory parameterization exists for convective clouds, which
typically have organization on unresolved scales of 50 km and below.
Boundary layer parameterizations are typically quite separate (with different
formal closures) and poorly coupled to convective parameterizations in
large-scale numerical models, when in nature there is a smooth continuum
over the diurnal cycle. Over land in the tropics, for example, as the boundary
layer grows after sunrise shallow clouds quickly form, deepen into cumulus
congestus, and then organize into precipitating cloud bands, producing a
wide range of mid- and high-level clouds, all of which impact the diurnal
cycle of the surface radiation budget at the same time as they impact the
surface hydrologic budget. From a climate perspective this diurnal cycle of
convection plays an important role in the shortwave and longwave cloud
feedbacks discussed in Chapter 3. Cloud resolving models are proposed in
Chapter 3 as one tool with which to address some of these fundamental
unresolved issues of the interaction between different time and space scales,
although it is not yet possible to resolve simultaneously both boundary layer
clouds and deep convection. To comprehensively characterize and possibly
reduce uncertainty in the hydrological cycle of our climate models requires a
major ongoing effort both in synthesis and in rigorous diagnostics that cuts
across all modeling, theoretical, and observational communities.
Many areas of dynamic vegetation modeling, which are vitally
important for simulating long-term feedbacks between the biota and climate,
are still in stages of rapid development. It will be important to test the newly
emerging prognostic ecosystem and leaf phonology algorithms in coupled
climate-vegetation-land-surface models using both existing data and the new
data sources outlined in the previous sections.
Many of the feedbacks associated with vegetation occur at longer time
scales (centuries) than can be observed with existing observing systems.
Paleoclimate research is an important activity to understand vegetation
feedbacks on climate. The last glacial maximum and 6,000 years before
present have emerged as key periods of focused research demonstrating that
inclusion of interactive vegetation improves the simulated climate.
Paleoclimate research must be integrated with and indeed is critical to the
implementation, testing, and improvement of dynamic vegetation in climate
models. The community should work to define standard paleoclimate
experiments (e.g., last glacial maximum, 6000 B.P.) that are used to evaluate
the coupled climate-vegetation model and highlight the importance of
particular vegetation feedbacks (e.g., forest-tundra ecotone, green Sahara).
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TERREST~AL HYDROLOGYAND VEGETATION FEEDBACKS
Evaluating Progress
75
A clear metric for progress in the coming decade would be the accuracy
with which our earth system models can reproduce, for example, the
observed diurnal and seasonal variations of the hydrological cycle over land.
The short-term modes of variability, like the diurnal, are well represented in
even a few annual cycles, while interannual variability requires a longer
statistical period. Reanalysis of the past 40 to 50 years of atmospheric data is
now available (with new reanalyses in progress). The hydrological records
of the past few decades are also being synthesized for global use. Flux site
data records are approaching a decade in length. An accuracy of perhaps 5
percent in the key terms in the surface hydrology budget (precipitation and
evaporation) would be a realistic target for the coming decade.
The ability of climate models to successful reproduce the terrestrial
carbon cycle provides a clear metric to evaluate progress in vegetation
models. The carbon cycle integrates across temperature, precipitation,
energy fluxes, and the hydrologic cycle and the influence of these on various
ecological processes. Tower flux data, ancillary ecological data, satellite-
derived data products, and measurements of atmospheric carbon dioxide
provide a wealth of critical data with which to constrain and evaluate the
simulated carbon cycle.
Representative terms from entire chapter:
soil water
