Alpine Paleoclimatology
Understanding the cause-and-effect relationships for expected climate change is important to the community for three reasons: (1) to predict the character of the change; (2) to see if it can be prevented, or at least minimized, should it be perceived as threatening; and (3) to plan for the change if...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Book Part |
| Language: | unknown |
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MIT Press
1998
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.48350/155101 https://boris.unibe.ch/155101/ |
| Summary: | Understanding the cause-and-effect relationships for expected climate change is important to the community for three reasons: (1) to predict the character of the change; (2) to see if it can be prevented, or at least minimized, should it be perceived as threatening; and (3) to plan for the change if it cannot be avoided. lts cause, anthropogenic or natural, is a central issue. If the change were perceived, for example, to be a natural cooling (e.g., a drift toward another glacial stage), the management strategy might be changed to "Increase the atmospheric C02 contentl" This emphasizes the state of the climate as such is not of importance to man so much as the impact at ground zero (hydrology, vegetation, erosion, frequency and severity of extreme events, ice melting, sea-level change). In many cases proxy data are actually more closely related to the impacts than the climate; indeed, climate reconstructions from proxy data are commonly routed through the impacts. In this chapter we have presented a selection of the data types and methodologies currently used for Alpine climatic and impact reconstructions, their qualitative and quantitative advantages and limitations, and examples of the deliverable results. Table 3.4 provides an overview of the applicability of each and indicates the range of potential cross correlations between subsets. Large amounts of various kinds of proxy data from the Alpine region have already been published, much in the form of time series profiles with interpretations, but encompassing techniques for modeling proxy data are mostly still at the developmental stage. In particular, models must link observations with regional climatic scenarios correctly in space and time to realize the full potential of the proxy data. This goal can be attained only through an interdisciplinary approach involving regional climate simulations and reconstructions and should lead to innovative high-resolution modeling approaches in which both kinds of information guide the design of simulations. There is currently no interface in climate models for the direct input of climatic information based on proxy data. Each discipline essentially has different operational data requirements, methodologies, and spatial and temporal scales of approach and outputs. Based on full-scale physical process simulations, model outputs are in the nature of time-slice snapshots for large areas and exhibit only limited close-up detail. Continental proxy-data reconstructions use collections of documented or natural evidence to synthesize a local or regional scenario, usually without addressing the role of large-scale physics. Archive evidence commonly spans long time periods and has good local resolution, but particularly in the case of natural archives, limited temporal fine tuning (seasonal or langer). Archive evidence may be discontinuous from site to site, and climate signals mostly need to be teased out of local bulk environmental signatures. Topographie representation in both approaches are poor to very poor (improvement may require nested regional models). Comparisons can only be made between the spatial outputs from both disciplines if they have similar scales and sufficient detail. In such cases, validation checks of model outputs may result in arbitrary parameter adjustments to improve model performance. Proxy data also require calibration, and the output requires validation. Calibration and validation for the very recent past are based directly on meteorological and hydrological network instrumental data; for periods farther back in time, documentary records, multiproxy approaches and various statistical techniques (regression analysis, multivariate statistics, geostatistics) are employed. The strength of proxy- data archives lies in the length of time they cover, which permits identification and statistical analysis of climatic fluctuations of much lower frequency than would otherwise be possible. The record of tree ring cell densities calibrated using summer temperatures (figure 3.17) provides an elegant example of this. Indeed, the regional warming trend during the last hundred years appears less of an amen for the future, at least in terms of human causes, when viewed on the langer time scale (see, e.g., figure 2.4), in which a warming trend appears in the context of a recovery from the midnineteenth century cool period. lt has at times been argued that, for an area as small as the Alpine region, climate reconstructions based on proxy data are unlikely to be relevant for correlation with the output of larger-scale models. However, (1) a set of climatic and environmental conditions defined for the Alpine region has strong implications for conditions farther afield (e.g., Alpine glacier responses during the Little lce Age indicated a climatic condition affecting the entire continent), and (2) a reconstruction of climate in the Alpine region can be viewed as a single station in a network, much the same way as a single meteorological station is. The output from validated models may in turn be able to fill in the gaps in climate reconstructions and indicate potential critical sites for proxy-data investigations. As yet, the goal of defining the regional spatial response patterns associated with the decadal and century-length climatic perturbations observed in archived time series has eluded climate research. An intermediate linking approach may include several steps: 1. defining the modern spatial pattern 2. establishing how the topography of that pattern changes shape and amplitude in response to larger-scale forcing 3. identifying a minimum number of definitive-response sites keyed to the pattern 4. moving the pattern through time using the evidence provided by the set of response site records as a guide 5. employing limited-area models for selected time slices. The simultaneous response of local stations to regional climate forcing is well documented: For instance, irrespective of geographical location or altitude, both the short-term structure and the longer-term secular increase in surface air temperature in Switzerland have been similar over the last hundred years (figure 3.2); in addition, surface lake water temperatures show essentially the same signal as air temperatures (figure 3.20). Beniston et al. (1994) have linked decadal trends in Swiss meteorological parameters, including air temperature, via pressure field characteristics to the North Atlantic Oscillation · Index (i.e., to the difference in sea level pressures between the Azores and Iceland, also a measure of the strengths of the Westerlies over the North Atlantic: see also chapter 2) Thus proxy indicator charaderistics in a given Swiss lake that read to temperature (lacustrine thermal structure, primary produdivity, deep-water oxygen content, remobilization of ionic species, and the like) can exhibit a measurable response to synoptic-scale events. For example, oxygen isotope values in meteoric waters closely follow temperature trends (figure 3.32), so the detailed similarities the isotopic records from Gerzensee and from the Dye 3 ice core display (figure 3.34) would appear to signify responses to synoptic scenarios that have overridden local controls. Global climate research involves both diagnosis of the past state of the climate and estimation of its future evolution. Modelers aim to predict future climate scenarios accurately under the assumption of, for instance, a doubling of atmospheric carbon dioxide concentrations, but are still testing and refining their models. Proxy-data reconstrudions focus on the past to obtain insights into the frequencies, amplitudes, extents, and impads of climatic conditions both within a regime and between regimes, but the necessary tools are still being calibrated. That the current anthropogenic contribution to climate has no precedent is of concern to both approaches. The climate during the last interglacial (Eemian) has been suggested as one analogy for future climate because it was warmer than the present by up to 2° C, although this was clearly not due to anthropogenic causes. Indeed part of the problem, with resped to scientific precision, is that the expeded change will not be large in comparison to natural changes in the past. Despite this, its impad on civilization is likely to be severe, largely because operational structures have been constructed so precisely in accordance with the most recent prevailing climate state. Coastal lowlands, delta flats, port cities, and other shoreline infrastrudures, for example, have been developed under the tacit assumption of constant marine conditions. Resource and environmental management pradices (for example, in farming, forestry, and water resources) have developed under prevailing meteorological conditions and therefore function optimally under precisely these, and not future conditions. With the trend toward higher (mesoscale) spatial resolution in applying climate models and the trend toward more spatially coherent paleoclimate reconstrudions based on (regional) proxy data sets, the disciplines of modeling and paleoclimatology are now approaching one another. Moreover, these data sets will help define the regional effects of global climate shifts climate modeling predicts, an area of critical importance for future socioeconomic and ecological planning. Thus a strong interdisciplinary approach is desirable, involving the development of common goals in the fields of climate modeling and paleoclimatological reconstrudions based on proxy data, and optimum progress is likely to depend on a complementary approach. Figure 3.37 summarizes the current conceptual approach to interdisciplinary climate reconstrudion and simulation. The convergence of approaches combining observational evidence and modeling results should help further our understanding of the fundamental processes involved in determining Alpine climates. Ultimately, the results of this research should be useful not only to other rnernbers of the clirnate research cornmunity but also to those policyrnakers charged with coordinating the responses of society to any likely future change in clirnate, regardless of whether such a change is anthropogenic or natural in origin. |
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