Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods

Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system “Mittelfristige Klimaprognose” (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using the ensemble Kalman filter, the filtered anomaly initialization, and the initialization method by partially coupled spin‐up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter corrects each ensemble member with the ensemble mean during model integration. And the bred vectors perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low‐resolution configuration (Preop‐LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop‐LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the ensemble Kalman filter and filtered anomaly initialization show the most distinct improvements over Preop‐LR for surface temperatures and upper ocean heat content, followed by the bred vectors, the ensemble dispersion filter, and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin‐wide long‐term mean and variability and with respect to the temporal evolution at the 26° N latitude

Initialization and ensemble generation for decadal climate predictions: A comparison of different methods

Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system "Mittelfristige Klimaprognose" (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using the ensemble Kalman filter (EnKF), the filtered anomaly initialization (FAI) and the initialization method by partially coupled spin‐up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter (EDF) corrects each ensemble member with the ensemble mean during model integration. And the bred vectors (BV) perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low‐resolution configuration (Preop‐LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop‐LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the EnKF and FAI show the most distinct improvements over Preop‐LR for surface temperatures and upper ocean heat content, followed by the BV, the EDF and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin‐wide long‐term mean and variability, and with respect to the temporal evolution at the 26° N latitude

Stabilität des Klimasystems und extreme Klimate in Modellexperimenten

The present thesis examines the ocean and atmospheric dynamics of present-day climate and LGM through Ocean and Atmosphere General Circulation models. Simulating the glacial climate different LGM reconstructions of sea surface temperatures and sea-ice margins are used as forcing fields for the models: CLIMAP (1981), a modification of CLIMAP (1981), with additional cooling in the tropics, and reconstructions as produced from Weinelt et al. (1996) and GLAMAP 2000, which show seasonally ice free conditions in the Nordic seas. The stability of the thermohaline circulations under different reconstructions is investigated together with the corresponding atmospheric dynamics. The stability analysis, by means of freshwater flux hysteresis maps reveals mono-stability for each glacial background state, which appears to be a robust feature of the glacial ocean. The impact of the changed orography in North America together with the ice-albedo feedback due to the largely expanded Laurentide Ice Sheet and the reduction of the CO2 concentration are assessed. The results show a strong dependence of the glacial Northern Hemisphere circulation pattern to the changed orography. The Laurentide Ice Sheet forces a deflection of the westerlies, their enhancement and a southward displacement. The oceanic heating contributes only 20-40% to the North Atlantic cooling. Motivated by the extreme climates in the Earth´s history, namely the full earth glaciation in the Neoproterozoic era, known as "snowball" Earth, the atmospheric model is forced with extreme boundary and initial conditions. The impact of land albedo, oceanic heat transport, CO2, initial temperature conditions on the extreme climates are examined. Changing only one boundary or initial condition, the model produces open ice free tropical oceans. Using a proper combination of the varied forcing parameters a full ´Earth glaciation´ results. Oceanic heat transport and orography have only a minor influence on the climate instability

Skill assessment of different ensemble generation schemes for retrospective predictions of surface freshwater fluxes on inter and multi-annual timescales

The long term variability and its predictability of the monthly mean oceanic surface net freshwater fluxes is compared in a set of retrospective predictions. All are using the same model setup, and only differ in the implemented ocean initialisation method and ensemble generation method. The basic aim is to deduce the differences between the initialization/ensemble generation methods in view of the uncertainty of the verifying observational data sets. The analysis will give an approximation of the uncertainties of the net freshwater fluxes, which up to now appear to be one of the most uncertain products in observational data and model outputs. All ensemble generation methods are implemented into the MPI-ESM earth system model in the framework of the ongoing MiKlip project (www.fona-miklip.de). Hindcast experiments are initialised annually between 2000–2004, and from each start year 8 ensemble members are run for 10 years forward. Four different ensemble generation methods are compared: (i) a method based on the Anomaly Transform method in which the initial oceanic perturbations represent orthogonal and balanced anomaly structures in space and time and between the variables taken from a control run, (ii) one-day-lagged ocean states from the MPI-ESM-LR Baseline 1 system, (iii) one-day-lagged ocean and atmospheric states with preceding full-field nudging to re-analysis in the atmospheric and anomaly nudging in the oceanic component of the system – the Baseline MPI-ESM-LR system, (iv) an Ensemble Kalman Filter (EnKF) implemented into oceanic part of MPI-ESM, assimilating monthly subsurface oceanic temperature and salinity using the Parallel Data Assimilation Framework and full-field nudging in the atmosphere. The hindcasts are evaluated probabilistically using freshwater flux data set from NCEP-R2. On the global scale the physically motivated methods (i) and (iv) provide probabilistic hindcasts to some extent higher correlation and reliability than the lagged initialization methods (ii)/(iii) despite the large uncertainties in the verifying observations and in the simulations. We suggest similar approaches for further evaluations of other variables of decadal hindcasts systems

Klimawandelbedingte Ertragsveränderungen und Flächennutzung (KlimErtrag)

We provide an overview of the state of knowledge on the climate change impacts on German crop production and generate model-based, quantitative and spatially differentiated simulations of the yield changes of the most important German arable crops, up to the middle of the century. To simulate yields, we use several agro-ecosystem models and provide a meta-analysis of the related scientific literature. In addition, we consider the effects of specific weather conditions such as heat and drought periods on yields in the past. In order to assess the future development, we use the data of different climate projections . On average, with regional differences, the simulations show no decline in yields until the middle of the century and no increase in yield variability. We observe a decrease in the effectiveness of the CO2 fertilization effect for yield increases of winter wheat over time. The yields of silage maize benefit the least from CO2 fertilization. For the past, we identify yield losses due to extreme summer and spring drought for almost all crops as well as due to heat events for winter wheat and partly for oilseed rape. Heat-related yield losses increase for winter wheat with increasing CO2 concentrations. However, we cannot identify an unambiguous increase in yield losses due to extreme drought or waterlogging in the future. Uncertainties in the results exist, amongst other reasons, due to a wide range of future precipitation development in the underlying climate models, in particular with regard to the reliability of the precipitation projection in spring. The simulations do not consider adaptation of production to climate change as well as negative yield effects due to potential increase in storms, hail storms, heavy rain or harmful organisms

Quality Management Framework for Climate Datasets

Data from a variety of research programmes are increasingly used by policy makers, researchers, and private sectors to make data-driven decisions related to climate change and variability. Climate services are emerging as the link to narrow the gap between climate science and downstream users. The Global Framework for Climate Services (GFCS) of the World Meteorological Organization (WMO) offers an umbrella for the development of climate services and has identified the quality assessment, along with its use in user guidance, as a key aspect of the service provision. This offers an extra stimulus for discussing what type of quality information to focus on and how to present it to downstream users. Quality has become an important keyword for those working on data in both the private and public sectors and significant resources are now devoted to quality management of processes and products. Quality management guarantees reliability and usability of the product served, it is a key element to build trust between consumers and suppliers. Untrustworthy data could lead to a negative economic impact at best and a safety hazard at worst. In a progressive commitment to establish this relation of trust, as well as providing sufficient guidance for users, the Copernicus Climate Change Service (C3S) has made significant investments in the development of an Evaluation and Quality Control (EQC) function. This function offers a homogeneous user-driven service for the quality of the C3S Climate Data Store (CDS). Here we focus on the EQC component targeting the assessment of the CDS datasets, which include satellite and in-situ observations, reanalysis, climate projections, and seasonal forecasts. The EQC function is characterised by a two-tier review system designed to guarantee the quality of the dataset information. While the need of assessing the quality of climate data is well recognised, the methodologies, the metrics, the evaluation framework, and how to present all this information to the users have never been developed before in an operational service, encompassing all the main climate dataset categories. Building the underlying technical solutions poses unprecedented challenges and makes the C3S EQC approach unique. This paper describes the development and the implementation of the operational EQC function providing an overarching quality management service for the whole CDS data