Reconstructing Climate Using Ensemble Kalman Fitting
Knowledge of the climate past is indispensable for a better understanding of current and future changes in the climate system. However, past climate information is often very sparse. Interpretations of spatial patterns or circulation changes are not possible directly. In recent years, new numerical techniques have been developed that make it possible to link sparse climate information from the past with climate model simulations. Such data assimilation methods provide optimal estimates of the spatio-temporal variability of the past climate, which are at the same time physically consistent and consistent with the assimilated climate information. In the REUSE project such a data set is being created.
The aim is a monthly, global, 3-dimensional reconstruction of the atmosphere back to 1600, combining climate information from measurements, historical documents and tree rings with 30 simulations of a climate model. The method is available, but needs to be adapted and refined in order to achieve a good reconstruction. The new method brings a significant improvement compared to conventional reconstruction methods; a global monthly climate reconstruction does not yet exist. On the basis of this data set, the transition from the climate of the "Little Ice Age" to the present climate will be examined more closely. A particular focus is on decadal fluctuations in climate and the large-scale atmospheric circulation.