The ability to project climate change is fundamental to society. Currently, large uncertainties in the projections exist due to complex interactions between climate and other components of the Earth System. The goal of ClimVal is to quantify strengths and weaknesses as well as uncertainty of the MiKlip model system through a comprehensive model evaluation with observations. The model evaluation will focus on the representation of the climatological mean state, variability, trends, extreme events, as well as spatial and temporal patterns in selected Essential Climate Variables (ECVs) that are important for decadal predictions.
Except for sea ice, access to validated long-time series of observational data to be used in the model evaluation within ClimVal will be provided or supported by other partners and the coordinators of Module E. Datasets for (1) Arctic sea ice area and extent from 1978 to date from several combined passive microwave sensors, and (2) thickness of thin Arctic sea ice from 2002 to date from additional optical and microwave L-band sensors will be developed. We will contribute to climate monitoring by extending and continuously updating the sea ice observational time series.
We will make optimal use of observational data by systematically confronting them with model outputs. ClimVal will perform a rigorous model skill assessment with the help of diagnostics and observationally-based performance metrics which will feed back to the MiKlip consortium so that an improved MiKlip model system with demonstrably enhanced prediction skills on the decadal time scale can be developed.
The main goal of the ClimVal project is to quantify strengths and weaknesses as well as uncertainty of the MiKlip model system, with a focus on the representation of selected Essential Climate Variables (ECVs) that are important for decadal predictions. This goal will be achieved through a comprehensive evaluation with observational data. In particular, ClimVal aims at the data focused validation of fundamental climatological fields of the whole climate system by employing a wide range of satellite based observations. For this purpose, performance metrics and scores for the evaluation of the complex system will be developed. In addition, ClimVal will provide a long homogeneous data set of sea ice extent and thickness. The main contributions of ClimVal to MiKlip in the various development stages (DS) are:
Institut für Physik der Atmosphäre DLR Oberpfaffenhofen
PD. Dr. habil. Veronika Eyring
Insitute of Environmental Physics, Universität Bremen
Dr. Georg Heygster
Huntemann, M. | G. Heygster, L. Kaleschke, T. Krumpen, M. Mäkynen, and M. Drusch´