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

Evaluation of the MiKlip decadal prediction system using satellite based cloud products

The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip) project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1) provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) and from the International Satellite Cloud Climatology Project (ISCCP). The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA), analysis rank histograms (ARH) and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0) emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP). By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP) region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only moderate positive correlations with the CLARA-A1 satellite retrieval for the TWP region which are hardly statistical significant. Evidence for predictability of the 2–5 lead year averaged total cloud cover is found for parts of the equatorial to mid-latitudinal North Atlantic

Revealing skill of the MiKlip decadal prediction system by three-dimensional probabilistic evaluation

Decadal climate predictions and their verification are part of ongoing research. This article studies different methods applied to decadal hindcasts of three-dimensional atmospheric variables to evaluate the MiKlip (Mittelfristige Klimaprognosen) prediction system. Variables such as upper air temperature are tight to the core of the prediction system and hence help to reveal its power and deficiencies. The verification uses both, necessary and sufficient probabilistic measures. We analyze annual and multi-year averages of air temperature and geopotential height and the parametrized quantity net water flux at the ocean surface, the so-called freshwater flux, also known as E‑P (evaporation minus precipitation), as an important variable for atmosphere-ocean coupling. The model data stem from various versions of the MiKlip prediction system and constitute different sets of ensemble hindcasts covering 1979–2012. The results reveal that the freshwater flux is far more sensitive to model deficiencies than the basic dynamical variables and the predictability decays much earlier with prediction lead time. Initializing the atmospheric component is more important for the predictability than the difference in resolution between two model versions. The combined initialization of atmosphere and ocean has the effect of increasing the predictability in the inner tropics from 1 to 2 years compared to the ocean only initialization. For prediction year 7–10, the hindcasts are still closer to each other than to the uninitialized historical runs indicating that the prediction system is still influenced by the initial conditions. The skill for prediction year 7–10 is, however, only marginally larger than the skill of the uninitialized ensemble. The three-dimensional skill analysis reveals a clear indication of a mid-tropospheric temperature error developing in the tropical Pacific area