ALBERT

Description: We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores. We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins. These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts.

Description: We investigate the role of the tropics, the stratosphere, and atmosphere‐ocean coupling for seasonal forecasts of strong, potentially damaging, Northern Hemisphere extratropical winter wind storm frequencies. This is done by means of relaxation experiments with the European Centre for Medium‐Range Weather Forecasts model, which allow us to prescribe perfect forecasts for specific parts of the coupled atmosphere‐ocean system. We find that perfect predictions of the Northern Hemisphere stratosphere significantly enhance winter storm predictive skill between eastern Greenland and Northern Europe. Correct seasonal predictions of the occurrence of stratospheric sudden warmings play a decisive role. The importance of correctly predicting the tropics and of two‐way atmosphere‐ocean coupling, both for forecasting stratospheric sudden warming risk and, correspondingly, severe winter storm frequency, is noted.

Description: The spatial pattern of the first mode of interannual variability associated with the East Asian summer monsoon (EASM), obtained from a multivariate Empirical Orthogonal Functions (MV-EOF) analysis, corresponds to the Pacific–Japan (PJ) pattern and is referred to as the PJ-mode. The present study investigates the interannual variation of the PJ-mode from the perspective of the intraseasonal timescale. In particular, the impact of the Madden–Julian oscillation (MJO) on the interannual variation of the PJ-mode is investigated. The results show that the MJO has a significant influence on the interannual variation of the PJ-mode mainly in the lower troposphere (850 hPa) and that the former accounts for approximately 11% of the amplitude of the latter. The major part of the contribution comes from a change in frequency of the different phases of the MJO, especially that of MJO phase 6. This suggests that intraseasonal variation of the convection anomalies over the tropical eastern Indian and western Pacific Oceans plays an important role in the interannual variation of the PJ-mode. In addition, MJO phase 7 also contributes to the interannual variability of the PJ-mode, in this case induced by both the change in frequency and the change in circulation anomalies associated with MJO phase 7.

Description: Recent studies using reanalysis data and complex models suggest that the Tropics influence midlatitude blocking. Here, the influence of tropical precipitation anomalies is investigated further using a dry dynamical model driven by specified diabatic heating anomalies. The model uses a quasi‐realistic setup based on idealized orography and an idealized representation of the land‐ocean thermal contrast. Results concerning the El Niño Southern Oscillation and the Madden‐Julian Oscillation are mostly consistent with previous studies and emphasize the importance of tropical dynamics for driving the variability of blocking at midlatitudes. It is also shown that a common bias in models of the Coupled Model Intercomparison Project Phase 5 (CMIP5), namely, excessive tropical precipitation, leads to an underestimation of midlatitude blocking in our model, also a common bias in the CMIP5 models. The strongest blocking anomalies associated with the tropical precipitation bias are found over Europe, where the underestimation of blocking in CMIP5 models is also particularly strong.

Description: We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

Description: Beside its global effects, climate change is manifested in many regionally pronounced features mainly resulting from changes in the oceanic and atmospheric circulation. Here we investigate the influence of the North Atlantic SST on shaping the winter-time response to global warming. Our results are based on a long-term climate projection with the Max Planck Institute Earth System Model (MPI-ESM) to investigate the influence of North Atlantic sea surface temperature pattern changes on shaping the atmospheric climate change signal. In sensitivity experiments with the model’s atmospheric component we decompose the response into components controlled by the local SST structure and components controlled by global/remote changes. MPI-ESM simulates a global warming response in SST similar to other climate models: there is a warming minimum—or ”warming hole”—in the subpolar North Atlantic, and the sharp SST gradients associated with the Gulf Stream and the North Atlantic Current shift northward by a few a degrees. Over the warming hole, global warming causes a relatively weak increase in rainfall. Beyond this, our experiments show more localized effects, likely resulting from future SST gradient changes in the North Atlantic. This includes a significant precipitation decrease to the south of the Gulf Stream despite increased underlying SSTs. Since this region is characterised by a strong band of precipitation in the current climate, this is contrary to the usual case that wet regions become wetter and dry regions become drier in a warmer climate. A moisture budget analysis identifies a complex interplay of various processes in the region of modified SST gradients: reduced surface winds cause a decrease in evaporation; and thermodynamic, modified atmospheric eddy transports, and coastal processes cause a change in the moisture convergence. The changes in the the North Atlantic storm track are mainly controlled by the non-regional changes in the forcing. The impact of the local SST pattern changes on regions outside the North Atlantic is small in our setup.

Description: 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.

Description: The Bjerknes feedback is the dominant positive feedback in the equatorial ocean basins. To examine the seasonality, symmetry, and stationarity of the Pacific and Atlantic Bjerknes feedbacks we decompose them into three feedback elements that relate thermocline depth, sea surface temperature (SST), and western basin wind stress variability to each other. We partition feedback elements into composites associated with positive or negative anomalies. Using robust regression, we diagnose the strength of each composite. For the recent period 1993‐2012, composites of the Pacific Bjerknes feedback elements agree well with previous work. Positive composites are generally stronger than negative composites, and all feedback elements are weakest in late boreal spring. In the Atlantic, differences between positive and negative composites are less consistent across feedback elements. Specifically, wind variability seems to play a less important role in shaping atmosphere‐ocean coupling in the Atlantic when compared to the Pacific. However, a clear seasonality emerges: Feedback elements are generally strong in boreal summer and, for the negative composites, again in boreal winter. The Atlantic Bjerknes feedback is dominated by subsurface‐surface coupling. Applying our analysis to overlapping 25‐year periods for 1958‐2009 shows that the strengths of feedback elements in both ocean basins vary on decadal time scales. While the overall asymmetry of the Pacific Bjerknes feedback is robust, the strength and symmetry of Atlantic feedback elements vary considerably between decades. Our results indicate that the Atlantic Bjerknes feedback is non‐stationary on decadal time scales.

Description: Due to strong mean state‐biases most coupled models are unable to simulate equatorial Atlantic variability. Here, we use the Kiel Climate Model to assess the impact of bias reduction on the seasonal prediction of equatorial Atlantic sea surface temperature (SST). We compare a standard experiment (STD) with an experiment that employs surface heat flux correction to reduce the SST bias (FLX) and, in addition, apply a correction for initial errors in SST. Initial conditions for both experiments are generated in partially coupled mode, and seasonal hindcasts are initialized at the beginning of February, May, August and November for 1981–2012. Surface heat flux correction generally improves hindcast skill. Hindcasts initialized in February have the least skill, even though the model bias is not particularly strong at that time of year. In contrast, hindcasts initialized in May achieve the highest skill. We argue this is because of the emergence of a closed Bjerknes feedback loop in boreal summer in FLX that is a feature of observations but is missing in STD.