2.1
Atmosphere/Hydrosphere/Biosphere Linkages
2.2
Modeling the Systems and their Linkages
2.3 Summary
A general form of the surface energy balance can be represented:
Rn = H + LE + G
where Rn is the net radiation at the surface, and H, LE, and G are the sensible, latent, and soil heat fluxes, respectively, into or away from the surface.
A general form of the surface water balance can be represented:
P = R + S + E
where P is the precipitation, R is the runoff, S is the soil water storage, and E is the water lost or gained through phase change at the surface.
While these relationships appear simple, they are actually quite complex. They form the framework within which important components of atmospheric, hydrospheric, and biospheric processes must be studied. Embodied within each of these terms are variables which are very difficult to measure over large areas. Nevertheless, the challenge confronting modelers of all environmental sciences is how best to formulate the various fluxes in numerical simulations. CASES aims to provide state-of-the-art answers to these questions.
The following sections discuss the scientific basis for CASES in more detail.
2.1 Linkages Between the Atmosphere, Hydrosphere, and Terrestrial Biosphere
Understanding the three-way interactions between the atmosphere, hydrosphere and terrestrial biosphere through land surface-atmosphere exchange processes is critical to understanding regional and local scale weather, climate and water basin hydrology. Terrestrial ecosystem-hydrologic-atmospheric interactions refer to exchanges of heat, moisture, momentum, trace gases and aerosols between land surfaces and the overlying air. These exchanges represent a dynamically coupled system which evolves as a result of interactions among its components. Terrestrial biospheric processes, hydrological partitioning, and terrain heterogeneity control fluxes of water, energy, and radiatively active trace gases (e.g., CO2, CO, CH4, NOx, N2O) and these fluxes perform important roles in determining mesoscale weather and climate by modifying energy gradients, circulation patterns, atmospheric chemistry, and cloud formation. The weather, in turn, influences biospheric and hydrospheric processes.
The importance of these interactions between the terrestrial biosphere, the hydrosphere and the atmosphere is now well accepted (Bolle et al. 1985, Dickinson 1986, Bolin and Cook 1983, Crutzen and Andreae 1985, Crutzen 1988, Matson and Ojima 1990). However, it has been largely in the last decade that the magnitudes of atmospheric and/or land cover impacts have become generally accepted, due mainly to concern about the effects of greenhouse gases and aerosols (Charlson and Wigley, 1994; IPCC 1992) and an increasing awareness of more localized land cover effects on regional climate (Dirmeyer, 1994; Loveland et al., 1991; Pielke, 1995). Additional evidence comes from Beljaars et al. (1994) and others, who have demonstrated that variations in soil water content can significantly impact model simulations of weather and climate.
Climate, in turn, affects terrestrial ecosystem dynamics and hydrological inputs and outputs at the land surface. Changing climate and land surface properties affect this three-way interaction and modify the terrestrial biosphere. The manner in which changes in terrestrial ecosystems affect these interactions through changes in ecological processes is not well understood.
The vertical structure of the daytime atmospheric boundary layer is critically dependent on the partitioning of net radiation into sensible and latent turbulent heat flux, and ground heat conduction (for a summary of these feedbacks, see e.g., Pielke, 1995). A deeper boundary layer results when more of this radiative energy is realized as sensible heat flux. When vegetation is present, the response of leaf conductance to atmospheric conditions represents a rapid feedback between the biosphere and the atmosphere. The passage of a cloud during daylight, for example, will significantly reduce net radiation with stoma apertures responding within minutes. The removal and emission of chemicals at the surface are regulated by many of the same processes that affect heat and moisture flux, although the chemical and physical properties of the chemicals must also be considered (Hicks and Matt, 1988; Wesely, 1989: Foken et al., 1995).
The drying of the near surface soil and the depletion of deeper soil moisture as a result of transpiration represent other, slower feedbacks with the atmosphere, varying over days to a few weeks. When vegetation becomes water stressed, for instance, stoma will close to conserve the remaining water, so that a larger fraction of the net radiation is realized as sensible heat flux. Precipitation represents a short-term feedback that can quickly replenish the soil moisture, as well as provide shallow liquid water layers on the vegetation. The water available for short-term reinsertion into the atmosphere also depends on surface and subsurface runoffs which are also dependent on precipitation rate, soil water content, precipitation type, etc.
Seasonal interactions include feedbacks between increases in biomass during the growth season which will modify the partitioning of latent and sensible heat fluxes. Nutrient limitations can also constrain biomass growth, particularly in moist environments (Schimel et al. 1994; Parton et al. 1993). It has been shown that the increase of mean temperature in the spring in the eastern United States is interrupted as vegetation leafs out. Also, drought conditions over the eastern United States are apparently perpetuated by the reduced transpiration from the water-stressed vegetation. Clearly there is a two-way feedback in which ecosystem development responds to the microclimate, and the ecosystem characteristics in turn affect the surface fluxes of heat, moisture, and trace gases.
Another important influence of the land surface on the atmosphere occurs through modification of the surface albedo. For example, desertification of the Sahel region of Africa may have resulted from excessive grazing by domesticated goats of the darker vegetation such that a larger fraction of the solar radiation is reflected back into space. It has been suggested that the Rajastan Desert in India has resulted from the same mechanism.
Recently, there have been several field programs designed in part to explore short-term (out to seasonal scale) atmosphere-terrestrial ecosystem interactions. These include the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in eastern Kansas (Sellers et al. 1992a; Betts and Beljaars 1993), the Hydrologic Atmospheric Pilot Experiment and Modelisation du Bilan Hydrique (HAPEX-MOBILHY) in southwest France (Andre et al. 1989b; Noilhan et al. 1991), the HAPEX-Sahel in Niger in central Africa (Gash et al. 1991), the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in the Amazon region of Brazil (Shuttleworth 1985; Wright et al. 1992; Gash and Shuttleworth 1991), and the Boreal Ecosystem-Atmosphere Study (BOREAS) in Manitoba and Saskatchewan in Canada (Sellers et al. 1996). A goal of the programs is to explore atmospheric-terrestrial ecological interactions for different major biomes.
CASES will complement these efforts by permitting both short and long-term measurements with a focus on the interactions. Among the linkages understood the least are interactions between the biosphere and atmosphere. Currently, land surface characteristics are specified for use in meteorological and hydrologic models, while ecological models use prescribed climate data. The CASES site in the Walnut watershed will permit fundamental studies of these interactions on a spectrum of time and spatial scales.
To close the land branch of the hydrologic cycle, four components must be considered: (a) precipitation, (b) the time rate of change of surface and subsurface water storage, (c) evaporation, and (d) the divergence of horizontal water transport in the surface and subsurface layers. The largest component of the hydrologic cycle over land is precipitation. As time scales become shorter than one week, the spatial and temporal distribution of precipitation becomes increasingly important.
The National Weather Service is about to complete the deployment of a national Doppler radar network - NEXRAD (WSR-88D). These radars have enhanced capabilities to estimate precipitation compared to radars used for the last 35 years. Nevertheless, performance evaluation to date suggests there is still room for improvement in the WSR-88D precipitation algorithms. Questions have surfaced about range biases, the generality of the radar-rainfall relationship, and the radar's ability to detect and quantify freezing rain, sleet, snow and hail events (Smith and Krajewski 1995).
Continuing efforts are needed to improve satellite derived precipitation estimates which have suffered from a lack of well defined in-situ areal precipitation measurements. Algorithms to derive precipitation from satellite data have been developed (Janowiak 1992; Richards and Arkin 1981) but estimates fall short of desired performance levels. Optimizing techniques for estimating precipitation will require an integration of satellite, radar, and gage observations. The distribution of soil water content is another hydrologic variable which could benefit from improved satellite algorithms. Of particular interest is the linkage between soil water content at the surface and its subsurface profile as a function of time during the growing season and in days following precipitation events. A well instrumented site is needed to provide ground truth for satellite and airborne sensors.
CASES will provide an excellent opportunity for integrating satellite, radar, and gage information and optimizing the performance of the NEXRAD network. The location of CASES places its center under the umbrella of four different WSR-88D radars at ranges varying from 50 to 210 km and in a climatic region which experiences a broad spectrum of precipitation events. With a deployment of supplemental rain gages, the CASES facility will provide an unprecedented data set for fine tuning the new radar system's capability to measure precipitation. Toward this end, exploratory polarimetric measurements have shown promise and can also be tested here. In addition, the measurement of streamflow at a number of nested gaging stations in the area will enable the observed runoff to be compared with the areal precipitation, providing an independent check of WSR-88D derived precipitation fields.
Closely connected to the occurrence of precipitation are the response characteristics of the watershed on which the precipitation is falling. Improved warnings of flash floods require that better rainfall observations and predictions be coupled with hydrologic models of runoff production on the basin scale. Once precipitation has reached the earth's surface, surficial processes such as infiltration, soil moisture flow, evaporation, transpiration, and runoff become primary players in subsequent redistribution of the water substance. One of the main obstacles in understanding surficial processes is the high spatial variability of surface features and hydrological factors. Integrating and linking these variables across the spectrum of relevant scales remains an outstanding challenge. Current parameterizations representing the hydrological processes of runoff, infiltration, soil moisture distributions, and evaporation/transpiration from bare and vegetated surfaces, have been developed from hillslope and small basin data. It is unknown whether these parameterizations are scale invariant and applicable to much larger river basins.
The Walnut Watershed, which comprises the CASES site, represents a unique set of conditions that will enable researchers to better understand hydrologic processes. The size of the Walnut Watershed (4800 sq. km.) is particularly useful as it approaches the grid size used in many weather and climate models. This represents a scale in which there has not been sufficient observations for valid model parameterizations. In addition, the Walnut River basin of the CASES site is similar in terrain and vegetation to the intensively studied Little Washita River watershed in Oklahoma, but is an order of magnitude larger, thereby providing opportunities for scaling inter-comparisons.
Climate and atmospheric deposition of nutrients affect ecosystem processes such as primary production and decomposition. These, in turn, feed directly back into climate and atmospheric systems by modifying fluxes of water and "greenhouse" gases such as CO2, CO, CH4, NOx and N2O. This class of interactions that result in immediate changes in hydrological and climatic properties can be referred to as "direct feedback effects". Examples of these processes include: (1) net C fluxes via plant production and decomposition; (2) biogenic trace gas exchange controlled by nutrient cycling processes such as denitrification, nitrification, leaching, methanogenesis, and biomass combustion; and (3) water and energy fluxes via evaporation, transpiration, run-off, and run-on. These processes are sensitive to changes in the environment and have relatively fast response times (days to years, Schimel et al. 1991, Ojima et al. 1991).
Ecological processes operating over longer time frames determine community structure, disturbance regimes, and other biotic interactions which indirectly affect biogeochemical and ecophysiological fluxes to the atmosphere and the hydrosphere. These interactions constitute the "indirect feedback effects" between natural ecosystems and the hydrological and climatic systems. Although less understood, they may just as important as shorter term processes in their influence on atmospheric and hydrological dynamics and subsequent changes in ecosystem properties. These effects result from changes in processes affecting ecosystem development which alter ecosystem structure (Ojima et al. 1991).
Modifications of biophysical characteristics of the land surface caused by a shift from forest to savanna-woodlands or grasslands or a shift from C4 tallgrass prairie to C3 wheat croplands are examples of changes of indirect ecological feedback to the atmosphere and the hydrosphere (Salati 1986, Eagleson 1986). Changes in the structure of vegetation alters the roughness and albedo of the land surface and can potentially modify local, regional, and global scale climate through changes in albedo, humidity, soil moisture, evaporation, transpiration, and ground-level wind patterns (Dickinson 1986, Sellers 1986, Pielke and Avissar, 1990).
At the CASES site, land use changes have resulted in the interesting juxtaposition of two major land cover classes, 1) intensive agriculture dominated by wheat and pasture fields and 2) rangelands which still retain characteristics of native prairie. The effect of this ecosystem conversion by agriculture produces a CASES site which has a natural grassland ecosystem dominated by C4 species and a derived system dominated by C3 species in a system of very low diversity (i.e., wheat). These two photosynthetic systems are of special interest and importance in the Great Plains (see Tieszen, 1994) because their distributions are largely climatically controlled in natural systems (Tieszen et al., 1979) and because they respond differently to various environmental factors (see Ehleringer and Monson, 1993) including CO2 concentrations, temperature, nitrogen availability, and water stress. These ecological interactions modifying fluxes of water and carbon also are important feedbacks to atmospheric phenomena, including mesoscale weather patterns and the evolution of climate patterns.
The replacement of C4 grassland by wheat, a C3 species, over large spatial areas results in substantially different phenological patterns of NDVI (Normalized Differential Vegetation Index, a surrogate for green biomass) with significantly earlier onsets of greenness in wheat and C3 pastures (see Reed et al., 1994, for phenology interpretations from NDVI and Tieszen et al., 1995, for grassland interpretations). Schwartz (1994) suggests that the onset of greenness is significantly related to the increase in atmospheric humidity and nighttime warming. The causal relationship which is implied, suggests that vegetation conversions which affect phenology (C4 to C3) should have marked effects on regional weather and climate via changes in the transfer of latent and sensible energy.
The linkages between weather/climate and land use, the alteration of natural phenological patterns, and changes in the magnitudes of leaf area index and greenness need to be understood to assess coevolution of weather/climate-ecosystem patterns in the Great Plains. CASES will facilitate such studies by providing the necessary detailed data sets to examine, verify, and parameterize these linkages.
2.2 Modeling the Systems and Their Linkages
Numerical weather prediction (NWP) models, used for either short- or long-term predictions, have neither the temporal nor spatial resolution required to adequately describe the interaction between the troposphere and the earth's surface. This interaction occurs within the planetary boundary layer (PBL), which is quite variable in depth, ranging from a few hundred meters to a few kilometers in depth, responding to the diurnal cycle of solar heating as well as to larger-scale dynamics and forcing (Stull, 1995a). Beljaars (1995) has noted, based on his work with the European Centre for Medium Range Weather Forecasts (ECMWF) model, that "The impact of the boundary layer in models is particularly felt after a few days of integration when accumulated surface fluxes contribute substantially to the heat, moisture and momentum balances of the atmosphere."
Atmospheric boundary layer (ABL) simulation has been shown to exhibit a strong degree of sensitivity to soil moisture conditions as well as to parameterization of soil hydraulic properties (Ek and Cuenca, 1994; Cuenca et al., 1996). The variety of ABL and GCM simulation models tested in the PILPS program yielded a wide scatter of results for annual latent and sensible heat fluxes, monthly soil moisture content, and runoff. Variations in predicted soil moisture content and runoff were apparently caused by differences in calculating water balance and soil water transport. With regard to the role of soil moisture in surface resistance parameterizations (Dickinson et al., 1993; Sellers et al., 1986; Pan and Mahrt, 1987), variations in soil moisture also caused differences in partitioning available energy into latent and sensible heat fluxes, thereby affecting the computed annual evapotranspiration.
The characterization of surface fluxes in atmospheric models has been limited to simple representations where most aspects of the soil and vegetation are prescribed. Stomatal conductance responds to atmospheric inputs of solar radiation, temperature, relative humidity, precipitation, carbon dioxide concentration, and to soil inputs of temperature and moisture. Such models are discussed in Avissar and Verstraete (1990), Andre et al. (1989a, Beljaars and Holstlag (1991), Clark and Arritt (1995), Bonan et al. (1993), Chen and Avissar (1994), Collins and Avissar (1994), Manqian and Jinjun (1993), Pitman (1994), Schadler et al. (1990), and Segal and Arritt (1992). These soil-vegetation parameterizations include BATS (Biosphere-Atmosphere-Transfer Scheme; Dickinson et al. 1986), SiB (Simple Biosphere scheme; Sellers et al. 1992a), SiB2 (Sellers et al. 1996) and LEAF (Land-Ecosystem-Atmosphere Feedback scheme; Lee et al. 1993).
An illustration of the form in which these modeling components are used in atmospheric models is shown in Figure 1 (45 kB).
These soil-vegetation schemes have been most extensively used in general circulation and mesoscale models. In most cases, only one vegetation and soil characterization is used for each horizontal model grid interval. Such a representation, based on averaged conditions, is presumed to represent the net effect of the landscape within that grid cell. Some newly considered approaches attempt to represent the landscape variability that may exist within a grid cell. One of these approaches includes the use of a mosaic of patches where subregions within a model grid are evaluated separately and the resultant grid-averaged heat, moisture, and momentum fluxes obtained by a fractional weighting
of the subregion fluxes (e.g., Miller 1994, Koster and Suarez 1992, Bonan et al. 1993, Pleim and Xiu 1995, Pitman 1994, Avissar and Pielke 1989, Collins and Avissar 1994, Li and Avissar 1994). Another approach uses a statistical-dynamical formulation in which the response to surface properties is assumed to vary with a specified statistical distribution (Avissar 1992).
The inability to formulate coupled land-surface/atmospheric boundary-layer processes that occur on scales smaller than those resolved by numerical weather prediction models can significantly degrade overall model performance. Subgrid scale processes, such as transport of heat and moisture between the land-surface and the atmosphere, must be parameterized from model-resolved variables. Furthermore, recent studies show that errors in such parameterizations may be even larger than earlier expected (e.g. Smith et al, 1992; Kubota and Sugita, 1994; Sun and Mahrt, 1995a,b; Godfrey and Beljaars, 1991; Stull, 1994; Ek and Cuenca, 1994; Beljaars, 1995; Cuenca et al, 1996; and others). Equally important, boundary-layer clouds are inferred from grid-averaged values (e.g. Slingo, 1980, 1987; Ek and Mahrt, 1991; and others), but failure to predict the subgrid fraction of boundary-layer cloud cover leads to major errors in the surface energy budget and fluxes to the atmosphere, which has important implications for large-scale modeling (Garratt et al, 1993; Garratt, 1994; Browning, 1994).
The generation of fluxes by unresolved subgrid mesoscale motions must also be considered (e.g. Bougeault et al, 1991; Mahfouf et al, 1987; Segal et al, 1988; Pinty et al, 1989). Numerical simulations suggest that heterogeneous landscape patterns, such as irrigated and non-irrigated land, snow and snowfree ground, etc., can produce atmospheric circulations that are as strong as sea breezes (e.g., Anthes, 1984; Zeng and Pielke, 1995). The resultant fluxes of energy and trace gases due to these mesoscale circulations has yet to be adequately considered in larger-scale models.
Garratt (1992) emphasized two aspects that are central to improve modeling of the PBL. These are i) the presence of clouds within the PBL and ii) the nature of the underlying surface. The emphasis is on the acquisition of long data records to provide quantitative evaluations of turbulent fluxes of sensible and latent heat at the surface, which represent an important source of moist available energy for atmospheric circulation and momentum diffusion. As Garratt notes in the concluding paragraph of his book, "The most promising strategy for improving a given parameterization scheme is to study carefully the performance of that scheme in a particular GCM and to compare simulations both with observations and with results from small-scale PBL models." This theme applies to all numerical model studies.
The establishment of the CASES site directs attention to the observational needs which must be met to provide the guidance and verification data required for the development of physically sound parameterization schemes that will have positive influences on NWP model performance.
Operational models in hydrology include those that cover the unsaturated zone from the soil surface to the water table, groundwater aquifer models, surface runoff models and open channel hydraulic models. Physically based models for components of the hydrologic cycle include parameterizations for canopy interception, infiltration, evapo-transpiration, snowmelt, interflow, overland flow, channel flow, unsaturated subsurface flow and saturated flow in groundwater aquifers. The model scenarios important for flood forecasting and potential control include single-event rainfall-runoff models, continuous stream-flow simulation models and flood hydraulics models.
The HEC-1 (Hydrologic Engineering Center) rainfall-runoff model is a standardized model which has been developed by the U.S. Army Corps of Engineers (Feldman, 1981). The program develops discharge hydrographs in response to historical or simulated rainfall events over the basin. Calibration can be made for unit hydrograph and loss rate parameters as well as channel routing parameters. The primary objective of the HEC-1 model is generation of the flood hydrograph. Longer term processes such as evaporation, transpiration, and soil moisture are not modeled. Basins can be divided into subbasins using HEC-1 and flow routing used to simulate the overall basin response. Model results include generation of hypothetical storm runoff, snowmelt runoff, dam safety applications and flood damage analysis (DeVries and Hromadka, 1992).
The National Weather Service FLDWAV program simulates unsteady flow for flood wave simulation based on solution of the one-dimensional St. Venant equations (Fread and Lewis, 1988). It is capable of simulation of unsteady flow conditions in dendritic (tree-shaped) waterways subject to backwater effects including flood forecasting, dam breach analysis by overtoppping or piping failure, inundation mapping, and representation of flow structures such as levees and gates (DeVries and Hromadka, 1992).
The hydrologic response unit (HRU) concept has been used to scale segments of a watershed with similar soil texture, topography, land use, vegetation and geological features (e.g. soil depth). The use of a GIS framework is particularly useful in delineating watershed and HRU boundaries. Physically-based hydrologic process models are applied to each HRU to simulate the response of the land surface to precipitation and atmospheric forcing through evaporation and transpiration (Leavesley et al., 1983).
Continuous streamflow simulation models are more complex than the HEC-1 model in that they must simulate watershed behavior between storm events and the processes of soil moisture depletion, evaporation, transpiration, and subsurface saturated and unsaturated flow must also be modeled. Lumped parameter models such as the Modular Modeling System (MMS), which divides the basin into hydrologic response units (HRUs), and distributed parameter models such as the Systeme Hydrologique European (SHE), which divides the watershed into rectangular grid points, fall into this class (Leavesley et al., 1983, 1995; Abbott et al., 1986a, 1986b).
MMS provides a framework for incorporation of various process models as well as model calibration and verification (Leavesley et al., 1995). MMS is a dynamic modeling platform which allows for development and addition of new hydrologic process models within a structured framework which is required for communication between the various process modules. The additional hydrologic processes simulated by such models require supplemental input data including atmospheric forcing, stomatal response functions, and soil hydraulic parameters. Models of this type can be applied to a wide range of hydrologic problems such as water resources planning, impacts of changes in land-use, groundwater transport and contamination, and erosion and sediment transport.
Both distributed and lumped parameter hydrologic models can make use of topography, surface and subsurface conditions described in geographic information system (GIS) data bases. Different data sets are co-located through the application of GIS and each data set is represented by an overlay. The information contained in a GIS can be used to separate regions for application of different types of hydrologic simulation models and for retrieval of physical conditions or properties over the region of interest. The information contained on multiple overlays can be used to determine relationships between various parameters within a basin or study area and can also be used to set initial or boundary conditions for hydrologic and atmospheric simulation models (Lee et al., 1993; Maidment, 1993).
Current operational flash flood guidance models do not accurately represent the spatial and temporal variability of predicted or observed precipitation. Operational models, usually run every 6 hours, take 6 hr precipitation forecasts and partition the rainfall equally over time and space into the basin being forecast. Observed precipitation is accounted for similarly although the models can be run more frequently in "flood" situations. Improvements can be made in modeling when and where the precipitation is falling. This is particularly important in convective situations where large amounts of rain can fall over small areas in short time intervals.
Operational runoff predictions are usually based on gaging curves which have been derived from historical data for each river, with land-surface characteristics and conditions included only implicitly. There is a need to incorporate high resolution depictions of land-surface characteristics, which have become available in recent years, into operational models.
Next generation hydrologic models are now being developed to use NEXRAD rainfall estimates in real time with high resolution depictions of land-surface characteristics. By providing detailed data sets, including high resolution gage and NEXRAD rainfall estimates, CASES will help resolve the appropriate temporal resolution needed for flash flood modeling based on precipitation characteristics and the spatial scale of the flash flood forecast. The nested basins within the Walnut watershed will provide an important testbed to refine and calibrate the modeling of distributed runoff and the conversion of runoff to streamflow by various routing methods.
The modeling of terrestrial ecosystems involves short-term responses of vegetation and soils to atmospheric effects, and longer-term evolution of species composition, biome dynamics, and nutrient cycling associated with landscape and soil structure changes (Ojima et al. 1991; Schimel et al. 1991). The assimilation of carbon from vegetation growth, and its subsequent release during decay has been a focus of these models (Schimel et al. 1990; Parton et al. 1993). However, the manner in which land use properties influence biospheric fluxes of CO2 remains an outstanding problem (Schimel, 1995).
The modeling framework of these simulation tools have generally involved empirically-based logic statements, which, while frequently based on fundamental biophysical concepts, are not expressed as differential equations. The spatial scales of these simulations have ranges from patch sizes to biome scales. These models, particularly when applied on the smaller spatial scales, include a stochastic component to represent unpredictable random inputs from the atmosphere and interactions within the vegetation such as a falling tree. An illustration of the framework of terrestrial-ecosystem models is shown in Figure 2 (9 kB).
These models require atmospheric inputs such as temperature, relative humidity, net radiation, and precipitation, to integrate their formulations forward in time. Output from nearby climatological stations have been used as the needed boundary conditions for these models when applied on the patch up to the regional scale. However, mean annual changes in regional precipitation and temperature patterns have little relevance to plant productivity and decomposition rates, when these changes take place unevenly throughout the annual cycle or geographical region. Ecosystem development is more sensitive to events as first frost occurrence, duration of wet or dry seasons, timing of thaw out, and beginning of the wet season, which are not well represented in average values of climatic parameters. These characteristics are crucial cues or constraints on processes such as germination, growth initiation, senescence, and mortality. Climate or weather patterns need to be expressed in daily, weekly, or at most, monthly time frames to capture and help predict these biotic processes.
On the global scale, output from general circulation models have been used to estimate potential changes of biome type in response to hypothesized climate change scenarios using, for example, the concept of a Holdridge diagram. More recent representations of equilibrium vegetation distributions are also available (Nielson, 1993).
Ojima et al. (1991) evaluated ecosystem sensitivity to the temporal and regional resolution of climate change (changes in annual mean climate vs. seasonally varying changes) by driving a regional ecosystem model with general circulation model (GCM) climate output. Using a grassland model developed for the North American Central Grasslands region (CENTURY, Parton et al. 1987), simulations of aboveground net primary productivity and soil organic carbon for 72 sites across the region were made. Climate change was applied in two ways: (1) monthly basis, where monthly changes in temperature (T) and precipitation (PPT) were based on monthly GCM output, and (2) annual basis, where annual changes in T and PPT from GCM output were applied uniformly across the year. The growing season climates that resulted from applying climate change at these two temporal resolutions differed substantially.
The complexity of the interactions between weather, climate, and biotic systems is tremendous. Understanding their linkages is an enormous challenge which has been hampered by both technological limitations and the lack of sufficient and spatially explicit data sets of carbon flux. The CASES research facility can provide a comprehensive set of carbon flux data and isotopic information to examine the fluxes and budgets for carbon in selected well-defined land cover classes within a thoroughly instrumented watershed of the Great Plains. This will improve our understanding and modeling of the terrestrial biosphere and its linkages to the atmosphere and hydrosphere.
The atmosphere, hydrosphere, and biosphere are coupled, interactive systems. It is no longer sufficient for one component to be studied using prescribed inputs from the other two. They must be studied together over extended time periods. The CASES site will enable scientists to pursue a broad range of interdisciplinary research including for example:
CASES represents a unique opportunity for scientists and students of the environmental sciences.
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