Influence of the Multidecadal Atlantic Meridional Overturning Circulation Variability on European Climate

The influence of the natural multidecadal variability of the Atlantic meridional overturning circulation (MOC) on European climate is investigated using a simulation with the coupled atmosphere–ocean general circulation model ECHAM5/Max Planck Institute Ocean Model (MPI-OM). The results show that Atlantic MOC fluctuations, which go along with changes in the northward heat transport, in turn affect European climate. Additionally, ensemble predictability experiments with ECHAM5/MPI-OM show that the probability density functions of surface air temperatures in the North Atlantic/European region are affected by the multidecadal variability of the large-scale oceanic circulation. Thus, some useful decadal predictability may exist in the Atlantic/European sector

Unraveling causes for the changing behavior of the Tropical Indian Ocean in the past few decades

AbstractObservations show that decadal (10?20 yr) to interdecadal (>20 yr) variability of the tropical Indian Ocean (TIO) sea surface temperature (SST) closely follows that of the Pacific until the 1960s. Since then, the TIO SST exhibits a persistent warming trend, whereas the Pacific SST shows large-amplitude fluctuations associated with the interdecadal Pacific oscillation (IPO), and the decadal variability of the TIO SST is out of phase with that of the Pacific after around 1980. Here causes for the changing behavior of the TIO SST are explored, by analyzing multiple observational datasets and the recently available large-ensemble simulations from two climate models. It is found that on interdecadal time scales, the persistent TIO warming trend is caused by emergence of anthropogenic warming overcoming internal variability, while the time of emergence occurs much later in the Pacific. On decadal time scales, two major tropical volcanic eruptions occurred in the 1980s and 1990s causing decadal SST cooling over the TIO during which the IPO was in warm phase, yielding the out-of-phase relation. The more evident fingerprints of external forcing in the TIO compared to the Pacific result from the much weaker TIO internal decadal?interdecadal variability, making the TIO prone to the external forcing. These results imply that the ongoing warming and natural external forcing may make the Indian Ocean more active, playing an increasingly important role in affecting regional and global climate

Monitoring and quantifying future climate projections of dryness and wetness extremes: SPI bias

The adequacy of the gamma distribution (GD) for monthly precipitation totals is reconsidered. The motivation for this study is the observation that the GD fails to represent precipitation in considerable areas of global observed and simulated data. This misrepresentation may lead to erroneous estimates of the Standardised Precipitation Index (SPI), evaluations of models, and assessments of climate change. In this study, the GD is compared to the Weibull (WD), Burr Type III (BD), exponentiated Weibull (EWD) and generalised gamma (GGD) distribution. These distributions extend the GD in terms of possible shapes (skewness and kurtosis) and the behaviour for large arguments. The comparison is based on the Akaike information criterion, which maximises information entropy and reveals a trade-off between deviation and the numbers of parameters used. We use monthly sums of observed and simulated precipitation for 12 calendar months of the year. Assessing observed and simulated data, (i) the Weibull type distributions give distinctly improved fits compared to the GD and (ii) the SPI resulting from the GD overestimates (underestimates) extreme dryness (wetness). © 2012 Author(s). CC Attribution 3.0 License

Numerical Investigation into Dynamic Loading of Rubber Compound

The present paper analyses the heat generation build(up in silicone rubber samples when subjected to dynamic cyclic loading. Material properties of the rubber were determined through thermal and mechanical experimental testing. These properties are necessary to set up the computational model. The model includes a fully coupled transient nonlinear thermo(mechanical finite element analysis. In order to validate this approach, numerical results are compared with those gathered experimentally. The numerical model developed and validated could be used to simulate various industrial applications, involving rubber parts, for efficient and sustainable desig

Recent progress in understanding and predicting Atlantic decadal climate variability

Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems

Initialization shock in decadal hindcasts due to errors in wind stress over the tropical Pacific

Low prediction skill in the tropical Pacific is a common problem in decadal prediction systems, especially for lead years 2–5 which, in many systems, is lower than in uninitialized experiments. On the other hand, the tropical Pacific is of almost worldwide climate relevance through its teleconnections with other tropical and extratropical regions and also of importance for global mean temperature. Understanding the causes of the reduced prediction skill is thus of major interest for decadal climate predictions. We look into the problem of reduced prediction skill by analyzing the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcasts for the fifth phase of the Climate Model Intercomparison Project and performing a sensitivity experiment in which hindcasts are initialized from a model run forced only by surface wind stress. In both systems, sea surface temperature variability in the tropical Pacific is successfully initialized, but most skill is lost at lead years 2–5. Utilizing the sensitivity experiment enables us to pin down the reason for the reduced prediction skill in MPI-ESM to errors in wind stress used for the initialization. A spurious trend in the wind stress forcing displaces the equatorial thermocline in MPI-ESM unrealistically. When the climate model is then switched into its forecast mode, the recovery process triggers artificial El Niño and La Niña events at the surface. Our results demonstrate the importance of realistic wind stress products for the initialization of decadal prediction

Extreme event return times in long-term memory processes near 1/<i>f</i>

The distribution of extreme event return times and their correlations are analyzed in observed and simulated long-term memory (LTM) time series with 1/<i>f</i> power spectra. The analysis is based on tropical temperature and mixing ratio (specific humidity) time series from TOGA COARE with 1 min resolution and an approximate 1/<i>f</i> power spectrum. Extreme events are determined by Peak-Over-Threshold (POT) crossing. The Weibull distribution represents a reasonable fit to the return time distributions while the power-law predicted by the stretched exponential for 1/<i>f</i> deviates considerably. <br><br> For a comparison and an analysis of the return time predictability, a very long simulated time series with an approximate 1/<i>f</i> spectrum is produced by a fractionally differenced (FD) process. This simulated data confirms the Weibull distribution (a power law can be excluded). The return time sequences show distinctly weaker long-term correlations than the original time series (correlation exponent <span style="text-decoration:overline">&gamma;</span>&asymp;0.56)

Extreme event return times in long-term memory processes near 1/f

The distribution of extreme event return times and their correlations are analyzed in observed and simulated long-term memory (LTM) time series with 1/f power spectra. The analysis is based on tropical temperature and mixing ratio (specific humidity) time series from TOGA COARE with 1 min resolution and an approximate 1/f power spectrum. Extreme events are determined by PeakOver-Threshold (POT) crossing. The Weibull distribution represents a reasonable fit to the return time distributions while the power-law predicted by the stretched exponential for 1/f deviates considerably. For a comparison and an analysis of the return time predictability, a very long simulated time series with an approximate 1/f spectrum is produced by a fractionally differenced (FD) process. This simulated data confirms the Weibull distribution (a power law can be excluded). The return time sequences show distinctly weaker long-term correlations than the original time series (correlation exponent (gamma) over bar approximate to 0.56)