Concept and scientific plans
It is of vital importance to understand whether increasing human population and industrialization have already caused, or have the potential to induce significant changes in earth's climate. In order to properly address this question, one needs quantitative information regarding the amplitude and rapidity of natural variations of temperature in the ocean, over the continents, and in the cryosphere. The best way to ascertain the extent of past changes is through the inspection of historical time series of direct temperature measurements or documentation of such environmental observations.
Unfortunately, the type of direct temperature measurement records which would allow one to quantify climate changes on a global scale are too short, and they fall already within the period of strong human impact on natural conditions. Information regarding the pre-anthropogenic state of the system can be obtained either from proxies that record past climate and environmental conditions, or by simulating climate using comprehensive models of the climate system under appropriate external forcing changes. The paleoclimate record provides an excellent test of these models as it reveals climate variations that have actually occurred in the past.
In the field of "paleoclimate modeling" there is potential in bringing together Earth System Modeling, statistical analyses of historical and proxy data, as well as work with conceptual models. These directions of research are reflected by our research (link to articles). Presently, we are closely collaborating with people from the data side of the paleoclimate community in order to understand variations documented in corals and sediments with a high temporal resolution. Computer simulations and conceptual models contribute to a system-analytical understanding of the dynamics of the earth's climate system. One goal is to bring the specialists from the modeling and the archive communities together in order to create an interdisciplinary environment for paleoclimate research. In the following, the specifics of research activity are described.
1) Global Earth System Model for paleoclimatic applications
One motivation for paleoclimatic research is to validate state-of-the-art coupled climate models for paleoclimatic time slices and specific climate transitions during the Quaternary. Furthermore, analyzing paleoclimatic records and models in tandem allows for the evaluation of climate transitions and the analysis of forcing and feedback mechanisms of glacial-interglacial and future climate changes.
An Earth System Model is used for the study of climate dynamics on decadal to multi-millennial time-scales. The model provides a laboratory for the numerical simulation of climate transitions during the last glacial-interglacial cycles, as well as for the next millennium. The concept of pathways of external forcing into the climate response is used in order to introduce a novel view of the paleoclimatic record. Special attention is paid to the validation with terrestrial, marine and ice core data. In a long-term perspective, a three-dimensional climate model should explicitly resolve atmospheric dynamics and include climate components such as vegetation, the cryosphere, and the oceans. Furthermore, the model should be capable of simulating bio-geochemical cycles, including the carbon cycle and marine sediments, as well as isotopes in the climate components. To this end, well documented and tested model components should be used and adapted for paleoclimatic purposes. Simulations of transitions for the past and future climate will examine thresholds and feedbacks in the climate system. For this purpose, comprehensive models like ECHAM and models of reduced complexity (PUMA, LSG, etc.) are applied.
2) Statistical data analysis
One main focus involves the reconstruction of climate, based on observational, model and proxy data. The statistical analysis provides furthermore a synthesis, comparison and interpretation of paleo and simulated data. Climate reconstructions will be built by geostatistics, which is based on spatial correlations or composite maps. The combined use of paleoclimate reconstructions and model-simulated climate data will be undertaken, bringing together expertise and data from the paleoclimate and the climate modeling communities.
The comparison of paleo and model data can be carried out in a number of ways. The simplest approach is to subsample the model output fields, picking out data only from these locations and seasons for which the paleo reconstructions exist (Jones et al., 1998). Modeled signal-to noise-ratios may be used to evaluate locations where climate phenomena can be detected. Comparison can also be made with different simulations, in order to assess whether the additional forcings raise the levels of multi-decadal to centennial variability to a similar extent in both the simulated and reconstructed climates. Using the model work and instrumental data, teleconnections and their role for long-term climate variability are investigated. Model results are compared with recent reconstructions of the temperature record of the last millennium (Mann et al., 1999).
In addition to the paleo evidence being used to evaluate model performance, the model simulations will aid in the interpretation of the paleo data. The climate simulations enable a separation of the externally-forced climate signal from internal variability (to the extent that the signal is distinguishable from the noise), something that cannot be achieved using paleo data alone. The model signals will be used to interpret the paleoclimate reconstructions, in terms of the causes of the observed variations.
In order to get a physically consistent picture of the underlying large-scale processes, the statistical analysis is of central importance for paleoclimate research proposed in my concept. Typical circulation patterns are evaluated with the help of instrumental and historical data (e.g., Appenzeller et al., 1999; Rimbu et al., 2001). Historical and reanalysis data sets are used to find the associated atmospheric circulation and sea surface temperature patterns. One objective of such studies is to understand the teleconnections that control the low frequency variations in the proxy records. In the ideal case, the method provides for a reconstruction of climate modes beyond the instrumental record. It can also bring climate shifts, such as that observed in the 1970s, into a long-term context. The proxy data can provide estimates of natural climate variability in the pre-industrial era. This seems to be very important in terms of detection of the anthropogenic influence on climate change.
3) Theory and conceptual models
In addition to the proposed work with complex numerical models, it can be of great utility to reduce the system to low-order, box, and conceptual models. This complementary approach has been successfully applied to a number of questions regarding feedback mechanisms and the basic dynamical behavior (Lohmann et al., 1996b; Lohmann and Schneider, 1999; Timmermann and Lohmann, 2000). For the determination of first exit times between climate attractors, concepts of `Large deviation theory' (Freidlin, 1999) can be introduced into climate research. In some cases, e.g. the stochastic climate model of Hasselmann (1976), such models can provide a null hypothesis for the complex system.
The transition from highly complex equations to a low-order description of climate is an important topic of research. In his recent book 'Dynamical Paleoclimatology', Saltzman (2002) formulated a dynamical system approach in order to differentiate between fast-response and slow-response variables. In statistical mechanics, a similar approach is formulated by Mori-Zwanzig, in which the phase space is coarse grained in space and time (this formalism can also be applied to dissipative systems; Chorin et al., 2000). As an alternative to this method, one can try to derive a phenomenologically based climate theory. This can be based on fundamental and derived modes in climate theory for interannual to millennial timescales (Dima and Lohmann, 2004). This approach can be formulated in terms of superposition and selection of certain modes of climate variability. Interestingly, these modes can also be obtained in welldated proxy data from Cariaco basin and Greenland ice cores.